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Huang Y, Li X, Niu L, Zhang H, Zhang C, Feng Y, Wang Z, Zhang F, Luo X. CT venography combined with ultrasound-guided minimally invasive treatment for recurrent varicose veins: a pilot paired-design clinical trial. Clin Radiol 2024; 79:363-370. [PMID: 38290939 DOI: 10.1016/j.crad.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 09/26/2023] [Accepted: 12/24/2023] [Indexed: 02/01/2024]
Abstract
AIM To compare 1-year outcomes of computed tomography venography (CTV) combined with ultrasound-guided minimally invasive treatment with ascending phlebography and ultrasound-guided treatment for recurrent varicose veins. MATERIALS AND METHODS Consecutive patients with unilateral recurrent varicose veins were matched by gender, age, C classification, and degree of obesity, and randomised in a 1:1 ratio to receive either CTV (CTV group) or ascending phlebography (control group) combined with ultrasound-guided minimally invasive treatment. Patients were followed up by clinical and ultrasound examination. Follow-up was scheduled at 1 week, and 3, 6, and 12 months. The primary outcome measure was the Venous Clinical Severity Score (VCSS) at 12 months. Measures of secondary outcome included Chronic Insufficiency Venous International Questionnaire-20 (CIVIQ-20) score, recurrence of varicose vein or ulcer during 12 months, ulcer healing time, detection and location of treated veins. RESULTS Eighty patients were enrolled. Median VCSS in the CTV group was lower than it in the control group (p=0.04) and the CIVIQ-20 score was higher than the control group (p=0.02). By 12 months, no symptomatically recurrent varicose veins or ulcers had occurred. The ulcer healing time in CTV group was shorter (p<0.01). A greater number of patients had treated veins detected using CTV than by ascending venography (p=0.01), especially among patients with recurrence reflux veins in the groin, perineum, and vulva (p<0.01). CONCLUSION CTV combined with ultrasound may be more helpful than ascending phlebography combined with ultrasound to improve treatment efficacy for recurrent varices. These results should be verified by an future study with more patients and long-term follow-up.
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Affiliation(s)
- Y Huang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - X Li
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - L Niu
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - H Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - C Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Y Feng
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Z Wang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - F Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - X Luo
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
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Gou M, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Luo X, Li CSR, Zhang P, Huang J, Tian L, Hong LE, Tan Y. Correlation of Immune-Inflammatory Response System (IRS)/Compensatory Immune-Regulatory Reflex System (CIRS) with White Matter Integrity in First-Episode Patients with Schizophrenia. Mol Neurobiol 2024; 61:2754-2763. [PMID: 37932545 DOI: 10.1007/s12035-023-03694-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/04/2023] [Indexed: 11/08/2023]
Abstract
Several studies have reported compromised white matter integrity, and that some inflammatory mediators may underlie this functional dysconnectivity in the brain of patients with schizophrenia. The immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) are novel biomarkers for exploring the role of immune imbalance in the pathophysiological mechanism of schizophrenia. This study aimed to explore the little-known area regarding the composite score of peripheral cytokines, the IRS/CIRS, and its correlation with white matter integrity and the specific microstructures most affected in schizophrenia. First-episode patients with schizophrenia (FEPS, n = 94) and age- and sex-matched healthy controls (HCs, n = 50) were enrolled in this study. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay (ELISA), and psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). The whole brain white matter integrity was measured by fractional anisotropy (FA) from diffusion tensor imaging (DTI) using a 3-T Prisma MRI scanner. The IRS/CIRS in FEPS was significantly higher than that in HCs (p = 1.5 × 10-5) and Cohen's d effect size was d = 0.74. FEPS had a significantly lower whole-brain white matter average FA (p = 0.032), which was negatively associated with IRS/CIRS (p = 0.029, adjusting for age, sex, years of education, BMI, and total intracranial volume), but not in the HCs (p > 0.05). Among the white matter microstructures, only the cortico-spinal tract was significantly correlated with IRS/CIRS in FEPS (r = - 0.543, p = 0.0009). Therefore, elevated IRS/CIRS may affect the white matter in FEPS.
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Affiliation(s)
- Mengzhuang Gou
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Li
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Jinghui Tong
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yanfang Zhou
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ting Xie
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ting Yu
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Feng
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Baopeng Tian
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Shujuan Pan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ping Zhang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Li Tian
- Department of Physiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia.
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China.
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Luo X, Xue C, Chen J, Xue Y, Feng SM. [Comparison of the clinical efficacy of all-inside arthroscopic lateral ligament augmentation procedure and Broström procedure for the treatment of chronic lateral rotational ankle instability]. Zhonghua Wai Ke Za Zhi 2024; 62:581-590. [PMID: 38682630 DOI: 10.3760/cma.j.cn112139-20240105-00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
Objective: To compare the clinical efficacy of patients with chronic lateral rotational ankle instability(CLRAI) after all-inside arthroscopic lateral ligament augmentation procedure and Broström procedure. Methods: This is a retrospective cohort study. The clinical and imaging data of 106 CLRAI patients were collected at the Xuzhou Central Hospital from January 2021 to December 2022. The patients included 55 males and 51 females with an age of (32.6±8.2) years (range: 16 to 50 years). All patients were treated under all-inside arthroscopic, and were divided into Broström-Gould surgery group (n=54) and Broström surgery group (n=52) according to different ligament repair methods. At 3, 6, and 12 months after surgery, ankle inversion stress tests and anterior drawer tests were used to examine the stability of the ankle joint and observe gait. The American Orthopedic Foot and Ankle Society ankle hindfoot scale (AOFAS-AH) and Karlsson ankle function score (KAFS) were used to assess ankle function; Tegner score was used to assess the patient's level of exercise; the foot and ankle outcome score(FAOS)(including score of symptoms,pain,function, daily living,function, sports and recreational activities (sport); quality of life (QOL)) was used to assess the patient's daily activity ability. Comparisons of data were made using independent sample t test, repeated measures analysis of variance, LSD multiple comparison method, χ2 test or Mann-Whitney U test. Results: All operations were successfully accomplished. All incisions healed by first intention, without evidence of postoperative complications of implant rejection, ligation reaction, and nerve and vessel injury. All patients were followed up at 3, 6, and 12 months after surgery. Ankle varus stress test and anterior drawer test were negative. No evidence supporting lateral ankle instability was obtained. All patients eventually regained normal gait. No patients underwent revision surgery. Repeated measurement analysis of variance showed that AOFAS-AH, Tegner, KAFS and FAOS scores in the Brostrom-Gould group and the Brostrom group were significantly higher than those before surgery (P<0.01). The change trends of Tegner score and FAOS-sport score were significantly different between the two groups (F=18.839, P<0.01; F=8.169, P=0.005). Multiple comparisons revealed that at 3-, 6-and 12-month follow-up, the Tegner scores ((3 months: 3.7±0.5 vs. 3.3±0.5, t=-3.980, P<0.01; 6 months: 4.4±0.6 vs. 3.8±0.7, t=-4.792,P<0.01;12 months: 5.8±0.9 vs. 5.1±1.0, t=-3.889,P<0.01)), sport scores ((3 months: 82.5±3.7 vs. 79.3±3.8, LSD-t=-4.316, P<0.01; 6 months: 88.5±4.9 vs. 85.7±3.8, LSD-t=-3.312,P=0.001;12 months: 90.1±4.3 vs. 88.2±5.1, LSD-t=-2.112,P=0.037)) in the Broström-Gould surgery group were higher than those in the Broström surgery group, with statistical significances. Conclusions: Both Broström-Gould and Broström procedures under all-inside arthroscopic can make ankle stability and improve ankle function in the treatment of CLRAI. However, the former maybe shorten the time to return to exercise and achieve higher motor function.
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Affiliation(s)
- X Luo
- Department of Orthopedics, the Xuzhou Clinical College of Xuzhou Medical University,Xuzhou Central Hospital, Xuzhou 221009, China
| | - C Xue
- Department of Orthopedics, the Xuzhou Clinical College of Xuzhou Medical University,Xuzhou Central Hospital, Xuzhou 221009, China
| | - J Chen
- Department of Orthopedics, the Xuzhou Clinical College of Xuzhou Medical University,Xuzhou Central Hospital, Xuzhou 221009, China
| | - Y Xue
- Department of Orthopedics, the Xuzhou Clinical College of Xuzhou Medical University,Xuzhou Central Hospital, Xuzhou 221009, China
| | - S M Feng
- Department of Orthopedics, the Xuzhou Clinical College of Xuzhou Medical University,Xuzhou Central Hospital, Xuzhou 221009, China
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Wang F, Li H, Yi K, Wu Y, Bian Q, Guo B, Luo X, Kang Y, Wu Q, Ma Q. Long-term second-generation antipsychotics decreases bone formation and resorption in male patients with schizophrenia. Psychopharmacology (Berl) 2024:10.1007/s00213-024-06592-y. [PMID: 38647696 DOI: 10.1007/s00213-024-06592-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 04/15/2024] [Indexed: 04/25/2024]
Abstract
RATIONALE Patients with schizophrenia with second-generation antipsychotics (SGAs) treatment have shown an increased risk of bone fragility and susceptibility to fracture; however, it is still unclear whether this risk is derived from the effect of antipsychotics on balance of bone metabolism. OBJECTIVES We investigated the changes of two bone turnover biomarkers (BTMs) concentrations in people with schizophrenia receiving SGAs: procollagen type I aminoterminal propeptide (PINP) and C-terminal telopeptide of type I collagen (CTX-1) as BTMs of osteogenesis and bone resorption, respectively, to explore how antipsychotics contribute to bone fragility. METHODS We recruited 59 Chinese male patients with schizophrenia (32 drug-naïve first-episode (DNFE) patients and 27 chronic patients) to undergo 8 weeks SGAs treatment. Fasting peripheral blood samples of pre- and posttreatment were collected, plasma levels of PINP and CTX-1 were measured. RESULTS The interaction effects of group and time on PINP and CTX-1 concentrations were found (P = .016 and P = .008). There was a significant decrease for both BTMs concentrations of the posttreatment compared to the pretreatment (P<.001 and P = .003). Chronic patients had significantly higher changes of BTMs concentrations compared to DNFE patients (P = .048 and P = .024). There was a positive correlation of the two BTMs of pretreatment with disease course in DNFE group (r = .37, P = .039;r = .38, P = .035) and a negative correlation of PINP of pretreatment with age in the chronic group (r=-.40, P = .039). CONCLUSION Long-term SGAs medication inhibited osteogenesis in a dose- and time-dependent manner and damaged the balance of bone formation and bone resorption.
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Affiliation(s)
- Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China.
- Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, 830063, China.
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China.
| | - Hui Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, 100871, China
| | - Kaijun Yi
- Department of Orthopedics, Xiangyang No. 1 People's Hospital Affiliated to Hubei University of Medicine, Xiangyang, 441000, Hubei, China
| | - Yan Wu
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
| | - Qingtao Bian
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
| | - Baoyan Guo
- Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, 830063, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Yimin Kang
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China
| | - Qi Wu
- Fenyang College, Shanxi Medical University, Lvliang, 032200, China
- Department of Psychiatry, Changzhou Peace Hospital, The 102nd Hospital of The Chinese People's Liberation Army, Changzhou, 213003, China
| | - Qinghe Ma
- Department of Psychiatry, Changzhou Peace Hospital, The 102nd Hospital of The Chinese People's Liberation Army, Changzhou, 213003, China
- Department of Internal Medicine, The 904th Hospital of The Chinese People's Liberation Army, Wuxi, 214004, China
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Luo X, Lu LG, Mao YM. [Clinical status and challenges of new drugs for metabolic dysfunction-associated fatty liver disease]. Zhonghua Gan Zang Bing Za Zhi 2024; 32:300-302. [PMID: 38733182 DOI: 10.3760/cma.j.cn501113-20240226-00096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/13/2024]
Abstract
Metabolic dysfunction-associated fatty liver disease (MASLD) is a major public health problem that seriously affects human health. At present, some good progress has been made in the research and development of new drugs for MASLD, but there is still great space for exploration. This paper summarizes and analyzes the reasons in the current clinical status and challenges for the research and development of new drugs for MASLD.
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Affiliation(s)
- X Luo
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - L G Lu
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - Y M Mao
- Department of Gastroenterology, Shanghai Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200001, China
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6
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Li Y, Wang L, Huang J, Zhang P, Zhou Y, Tong J, Chen W, Gou M, Tian B, Li W, Luo X, Tian L, Hong LE, Li CSR, Tan Y. Serum neuroactive metabolites of the tryptophan pathway in patients with acute phase of affective disorders. Front Psychiatry 2024; 15:1357293. [PMID: 38680780 PMCID: PMC11046465 DOI: 10.3389/fpsyt.2024.1357293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/25/2024] [Indexed: 05/01/2024] Open
Abstract
Background Many studies showed disrupted tryptophan metabolism in patients with affective disorders. The aims of this study were to explore the differences in the metabolites of tryptophan pathway (TP) and the relationships between TP metabolites and clinical symptoms, therapeutic effect in patients with bipolar disorder with acute manic episode (BD-M), depressive episode (BD-D) and major depressive disorder (MDD). Methods Patients with BD-M (n=52) and BD-D (n=39), MDD (n=48) and healthy controls (HCs, n=49) were enrolled. The serum neuroactive metabolites levels of the TP were measured by liquid chromatography-tandem mass spectrometry. Hamilton Depression Scale-17 item (HAMD-17) and Young Mania Rating Scale (YMRS) were used to evaluate depressive and manic symptoms at baseline and after 8 weeks of antidepressants, mood stabilizers, some also received antipsychotic medication. Results The levels of tryptophan (TRP) and kynurenic acid (KYNA) were significantly lower and the ratios of tryptophan/kynurenine (TRP/KYN), 5-hydroxytryptamine/tryptophan (5-HT/TRP), quinolinic acid/kynurenic acid (QUIN/KYNA) were higher in BD-M, BD-D, MDD vs. HC. The levels of QUIN and the ratios of QUIN/KYNA were higher in BD-M than in BD-D, MDD, and HCs. The 5-hydroxyindoleacetic acid (5-HIAA) levels of patients with MDD were significantly higher than those in BD-M and BD-D. Binary logistic regression analysis showed the lower peripheral KYNA, the higher the QUIN level, and the higher the risk of BD-M; the lower peripheral KYNA and the higher KYN/TRP and 5-HT/TRP, the higher the risk of BD-D; and the lower the peripheral KYNA level and the higher the KYN/TRP and 5-HT/TRP, the higher the risk of MDD. Correlation analysis, showing a significant association between tryptophan metabolites and improvement of clinical symptoms, especially depression symptoms. Conclusions Patients with affective disorders had abnormal tryptophan metabolism, which involved in 5-HT and kynurenine pathway (KP) sub-pathway. Tryptophan metabolites might be potential biomarkers for affective disorders and some metabolites have been associated with remission of depressive symptoms.
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Affiliation(s)
- Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Leilei Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - L. Elliot Hong
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan, Hospital, Beijing, China
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Cao Y, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE. Phys Rev Lett 2024; 132:151801. [PMID: 38683006 DOI: 10.1103/physrevlett.132.151801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 01/04/2024] [Accepted: 03/13/2024] [Indexed: 05/01/2024]
Abstract
We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41} cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois, 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois, 60637, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- University of Chicago, Chicago, Illinois, 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois, 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois, 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | | | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois, 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois, 60637, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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8
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Zhou Y, Wang L, Yang K, Huang J, Li Y, Li W, Zhang P, Fan F, Yin Y, Yu T, Chen S, Luo X, Tan S, Wang Z, Feng W, Tian B, Tian L, Li CSR, Tan Y. Correlation of allostatic load and perceived stress with clinical features in first-episode schizophrenia. J Psychiatr Res 2024; 172:156-163. [PMID: 38382239 DOI: 10.1016/j.jpsychires.2024.02.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 02/03/2024] [Accepted: 02/07/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Stress plays an important role in the etiology of schizophrenia. However, the mechanisms by which chronic physiological stress and perceived stress relate to the clinical features of schizophrenia may differ. We aimed to elucidate the relationships among chronic physiological stress indexed by allostatic load (AL), perceived stress, and clinical symptoms in individuals with first-episode schizophrenia (FES). METHODS Individuals with FES (n = 90, mean age = 28.26years old, 49%female) and healthy controls (111, 28.88, 51%) were recruited. We collected data of 13 biological indicators to calculate the AL index, assessed subjective stress with the Perceived Stress Scale-14 (PSS-14), and compared AL and perceived stress between groups. Patients with FES were also evaluated with the Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale for Schizophrenia (CDSS). RESULTS Individuals with FES had higher AL and PSS score than healthy controls. There were no significant correlations between AL and PSS score in either patients or controls. Among individuals with FES, the AL index was associated with the severity of positive symptoms, while the PSS score was positively associated with CDSS score. Both elevated AL and PSS were correlated with the occurrence of schizophrenia. CONCLUSIONS Physiological stress, as reflected by AL, may be more related to positive symptoms, while perceived stress appear to be associated with depressive symptoms in individuals with FES. Longitudinal studies are necessary to explore the relationships between interventions for different stressor types and specific clinical outcomes in FES.
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Affiliation(s)
- Yanfang Zhou
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Leilei Wang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Kebing Yang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China.
| | - Junchao Huang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yanli Li
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Li
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ping Zhang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Fengmei Fan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Yi Yin
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Ting Yu
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Song Chen
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Shuping Tan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Zhiren Wang
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Wei Feng
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Baopeng Tian
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, China
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9
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Chao WH, Luo X, Liang GX, Zhang H, Yuan T, Wu QW, Shi ZH, Yang QT. [Application of image-based artificial intelligence in rhinology]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:277-283. [PMID: 38561271 DOI: 10.3760/cma.j.cn115330-20231025-00169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- W H Chao
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China Department of Clinical Data Center, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - G X Liang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - H Zhang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - T Yuan
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q W Wu
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
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Shen G, Wu Y, Wang K, Niculescu M, Liu Y, Kang Y, Luo X, Wang W, Chen YH, Liu Y, Wang F, Chen L. Impulsivity and aggression in alcohol withdrawal syndrome is modulated by the interaction of ZNF804A and mTOR polymorphism. Pharmacol Biochem Behav 2024; 236:173708. [PMID: 38216065 DOI: 10.1016/j.pbb.2024.173708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/19/2023] [Accepted: 01/05/2024] [Indexed: 01/14/2024]
Abstract
Alcohol withdrawal syndrome (AWS) is a poorly studied phenotype of alcohol use disorder. Understanding the relationship between allelic interactions and AWS-related impulsivity and aggression could have significant implications. This study aimed to investigate the main and interacting effects of ZNF804A and mTOR on impulsivity and aggression during alcohol withdrawal. 446 Chinese Han adult males with alcohol dependence were included in the study. Impulsivity and aggression were assessed, and genomic DNA was genotyped. Single gene analysis showed that ZNF804A rs1344706 (A allele/CC homozygote) and mTOR rs1057079 (C allele/TT homozygote) were strongly associated with AWS-related impulsivity and aggression. In the allelic group, MANOVA revealed a significant gene x gene interaction, suggesting that risk varied systematically depending on both ZNF804A and mTOR alleles. Additionally, a significant interactive effect of ZNF804A rs1344706 and mTOR rs7525957 was found on motor impulsivity and physical aggression, and the ZNF804A rs1344706 gene variant had significant effects on motor impulsivity and physical aggression only in mTOR rs7525957 TT homozygous carriers. The study showed that specific allelic combinations of ZNF804A and mTOR may have protective or risk-enhancing effects on AWS-related impulsivity and aggression.
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Affiliation(s)
- Guanghui Shen
- Wenzhou Seventh People's Hospital, Wenzhou 325006, China; School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China
| | - Yuyu Wu
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China
| | - Kexin Wang
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China
| | | | - Yuqing Liu
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China
| | - Yimin Kang
- Psychosomatic Medicine Research Division, Inner Mongolia Medical University, Hohhot, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Wei Wang
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China
| | - Yu-Hsin Chen
- Zhejiang Provincial Clinical Research Center for Mental Disorders, The Affiliated Wenzhou Kangning Hospital, Wenzhou Medical University, Wenzhou, China
| | - Yanlong Liu
- School of Mental Health, Wenzhou Medical University, Wenzhou 325035, China.
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, China.
| | - Li Chen
- Zhejiang Provincial Clinical Research Center for Mental Disorders, The Affiliated Wenzhou Kangning Hospital, Wenzhou Medical University, Wenzhou, China.
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11
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Chen W, Bai Y, Fang P, Chen J, Wang X, Li Y, Luo X, Xiao Z, Iyer R, Shan F, Yuan T, Wu M, Huang X, Fang D, Yang Q, Zhang Y. Body mass index's effect on CRSwNP extends to pathological endotype and recurrence. Rhinology 2024; 0:3161. [PMID: 38416065 DOI: 10.4193/rhin23.402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
BACKGROUND Elevated body mass index (BMI) has been recognized as an important contributor to corticosteroid insensitivity in chronic rhinosinusitis with nasal polyps (CRSwNP). We aimed to delineate the effects of elevated BMI on immunological endotype and recurrence in CRSwNP individuals. METHODOLOGY A total of 325 patients with CRSwNP undergoing FESS were recruited and stratified by BMI. H&E staining was employed for histological evaluation. Characteristics of inflammatory patterns were identified by immunohistochemical staining. The predictive factors for recurrence were determined and evaluated by multivariable logistic regression analysis and the receiver operating characteristic (ROC) curves across all subjects and by weight group. RESULTS In all patients with CRSwNP, 26.15% subjects were classified as overweight/obese group across BMI categories and exhibited a higher symptom burden. The upregulated eosinophil/neutrophil-dominant cellular endotype and amplified type 2/ type 3 coexisting inflammation was present in overweight/obese compared to underweight/normal weight controls. Additionally, a higher recurrent proportion was shown in overweight/obese patients than that in underweight/normal weight cohorts. Multivariable logistic regression analysis identified BMI as an independent predictor for recurrence. The predictive capacity of each conventional parameter (tissue eosinophil and CLCs count, and blood eosinophil percentage) alone or in combination was poor in overweight/obese subjects. CONCLUSIONS Overweight/obese CRSwNP stands for a unique phenotype and endotype. Conventional parameters predicting recurrence are compromised in overweight/obese CRSwNP, and there is an urgent need for novel biomarkers that predict recurrence for these patients.
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Affiliation(s)
- W Chen
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Bai
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - P Fang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - J Chen
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Wang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Li
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Luo
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Z Xiao
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - R Iyer
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - F Shan
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - T Yuan
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - M Wu
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Huang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - D Fang
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Q Yang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Zhang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Diabetology, Guangzhou Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Jiao Q, Dong Y, Ma X, Ji SS, Liu X, Zhang J, Sun X, Li D, Luo X, Zhang Y. Does Baseline Cognitive Function Predict the Reduction Rate in HDRS-17 Total Scores in First-Episode, Drug-Naïve Patients with Major Depressive Disorder? Neuropsychiatr Dis Treat 2024; 20:353-361. [PMID: 38415074 PMCID: PMC10898600 DOI: 10.2147/ndt.s453447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/06/2024] [Indexed: 02/29/2024] Open
Abstract
Purpose Major depressive disorder (MDD) is associated with worse cognitive functioning. We aim to examine the association between baseline cognitive functioning and the reduction rate in HDRS-17 total scores and to highlight the predictors of the reduction rate in HDRS-17 total scores in MDD with first-episode, drug-naïve (FED) patients. Patients and Methods Ninety FED patients were recruited consecutively and evaluated using the 17-item Hamilton Depression Rating Scale (HDRS-17), the 14-item Hamilton Anxiety Scale (HAMA-14), the Functioning Assessment Short Test (FAST) and the MATRICS Consensus Cognitive Battery (MCCB) at baseline and again at week 8. Results Eighty-four FED patients completed the study. Comparison showed that response group had significantly higher T scores in TMT-A, BACS-SC, WMS-III, BVMT-R, MSCEI and CPT-IP, but showed significantly lower scores in FAST total scores including autonomy, occupational functioning, cognitive functioning, interpersonal relationship than non- response group (all p's< 0.05). Partial correlation analysis also found that the reduction rate in HDRS-17 total scores could be negatively associated with autonomy, cognitive functioning and interpersonal relationship domains as well as total FAST scores, also was further positively associated with T-scores of BACS-SC, CPT-IP and MSCEI in MCCB, even when accounting for potential confounders. Furthermore, the levels of cognitive function domain, autonomy domain in FAST, and BACS-SC, CPT-IP in MCCB may predict the reduction rate in HDRS-17 total scores in FED patients (all p's< 0.05). Conclusion Our findings underscore significant correlations between baseline functioning and the reduction rate in HDRS-17 total scores in FED patients. Moreover, better baseline cognitive function, autonomy, speed of processing and attention/vigilance are more likely to predict patients' response to antidepressant treatment, indicating pre-treatment better cognitive functioning may be predictors to treatment response in FED.
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Affiliation(s)
- Qingyan Jiao
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
| | - Yeqing Dong
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, People’s Republic of China
| | - Xiaojuan Ma
- Tianjin Medical College, Tianjin, 300222, People’s Republic of China
| | - Shiyi Suzy Ji
- Teachers College, Columbia University, New York, NY, USA
| | - Xinyu Liu
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
| | - Jian Zhang
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
| | - Xia Sun
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
| | - Dazhi Li
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06511, USA
| | - Yong Zhang
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, 300222, People’s Republic of China
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Wang F, Li H, Kong T, Shan L, Guo J, Wu Y, Luo X, Satyanarayanan SK, Su K, Liu Y. Association of cigarette smoking with cerebrospinal fluid biomarkers of insulin sensitivity and neurodegeneration. Brain Behav 2024; 14:e3432. [PMID: 38361318 PMCID: PMC10869886 DOI: 10.1002/brb3.3432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/25/2024] [Accepted: 01/27/2024] [Indexed: 02/17/2024] Open
Abstract
INTRODUCTION Cigarette smoking increases both the risk for insulin resistance and amyloid-β (Aβ) aggregation, and impaired brain insulin/insulin-like growth factor 1 (IGF1) signaling might increase risk factors for Alzheimer's disease (AD). We aimed to investigate the association among cerebrospinal fluid (CSF) insulin sensitivity/IGF1, glucose/lactate, and Aβ42 and further explore whether insulin sensitivity contributed to the risk for AD in active smokers. METHODS In this cross-sectional study, levels of insulin, IGF1, and lactate/glucose of 75 active smokers and 78 nonsmokers in CSF were measured. Three polymorphisms regulating IGF1 were genotyped. Analysis of variance was used to compare differences of variables between groups. Partial correlation was performed to test the relationship between CSF biomarkers and smoking status. General linear models were applied to test the interaction of the effect of single nucleotide polymorphisms and cigarette smoking on CSF IGF1 levels. RESULTS In the CSF from active smokers, IGF1 and lactate levels were significantly lower (p = .016 and p = .010, respectively), whereas Aβ42 (derived from our earlier research) and insulin levels were significantly higher (p < .001 and p = .022, respectively) as compared to the CSF from nonsmokers. The AG + GG genotype of rs6218 in active smokers had a significant effect on lower CSF IGF1 levels (p = .004) and lower CSF insulin levels in nonsmokers (p = .016). CONCLUSIONS Cigarette smoking as the "at-risk" factor for AD might be due to lower cerebral insulin sensitivity in CSF, and the subjects with rs6218G allele seem to be more susceptible to the neurodegenerative risks for cigarette smoking.
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Grants
- QML20212003 "Qingmiao" program of Beijing Municipal Hospital Management Center
- LY202106 Youth Scientific Research Foundation of Beijing Huilongguan Hospital
- 2017Q007 Tianshan Youth Project-Outstanding Youth Science and Technology Talents of Xinjiang
- 2022J0112 Natural Science Foundation of Fujian Province
- ANHRF109-31 The 10th Inner Mongolia Autonomous Region 'Prairie excellence' Project, the An Nan Hospital, China Medical University, Tainan, Taiwan
- 110-13 The 10th Inner Mongolia Autonomous Region 'Prairie excellence' Project, the An Nan Hospital, China Medical University, Tainan, Taiwan
- 110-26 The 10th Inner Mongolia Autonomous Region 'Prairie excellence' Project, the An Nan Hospital, China Medical University, Tainan, Taiwan
- 2017E0267 The technology support project of xinjiang
- 7152074 Beijing Natural Science Foundation
- 2017D01C245 Natural Science Foundation of Xinjiang Province
- 2018D01C228 Natural Science Foundation of Xinjiang Province
- 2019D01C229 Natural Science Foundation of Xinjiang Province
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Affiliation(s)
- Fan Wang
- Beijing Huilongguan HospitalPeking UniversityBeijingChina
| | - Hui Li
- Department of Biomedical EngineeringCollege of Future TechnologyPeking UniversityBeijingChina
| | - Tiantian Kong
- Xinjiang Key Laboratory of Neurological Disorder Researchthe Second Affiliated Hospital of Xinjiang Medical UniversityUrumqiChina
| | - Ligang Shan
- Department of Anesthesiologythe Second Affiliated Hospital of Xiamen Medical CollegeXiamenChina
| | - Jiajia Guo
- Medical SectionThe Third Hospital of BaoGang GroupBaotouChina
- The Affiliated Hospital of Inner Mongolia Medical UniversityHuhhotChina
| | - Yan Wu
- Beijing Huilongguan HospitalPeking UniversityBeijingChina
| | - Xingguang Luo
- Department of PsychiatryYale University School of MedicineNew HavenUSA
| | - Senthil Kumaran Satyanarayanan
- Department of Psychiatry & Mind‐Body Interface Laboratory (MBI‐Lab)China Medical University HospitalTaichungTaiwan
- College of MedicineChina Medical UniversityTaichungTaiwan
| | - Kuan‐Pin Su
- Department of Psychiatry & Mind‐Body Interface Laboratory (MBI‐Lab)China Medical University HospitalTaichungTaiwan
- College of MedicineChina Medical UniversityTaichungTaiwan
- An‐Nan HospitalChina Medical UniversityTainanTaiwan
| | - Yanlong Liu
- Zhejiang Provincial Clinical Research Center for Mental Disorders, The Affiliated Wenzhou Kangning HospitalWenzhou Medical UniversityWenzhouChina
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14
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Abratenko P, Alterkait O, Andrade Aldana D, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow D, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Brunetti MB, Camilleri L, Cao Y, Caratelli D, Cavanna F, Cerati G, Chappell A, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Cross R, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Franco D, Furmanski AP, Gao F, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Gramellini E, Green P, Greenlee H, Gu L, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Ismail M, James C, Ji X, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Liu H, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Martynenko S, Mastbaum A, Mawby I, McConkey N, Meddage V, Micallef J, Miller K, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Moudgalya MM, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Pophale I, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Safa I, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector. Phys Rev Lett 2024; 132:041801. [PMID: 38335355 DOI: 10.1103/physrevlett.132.041801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 11/30/2023] [Indexed: 02/12/2024]
Abstract
We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150 MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245 MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - D Barrow
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Michigan State University, East Lansing, Michigan 48824, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- University of Chicago, Chicago, Illinois 60637, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - M B Brunetti
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Chappell
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | | | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - R Cross
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois 60637, USA
| | - D Franco
- University of Chicago, Chicago, Illinois 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - F Gao
- University of California, Santa Barbara, California 93106, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - E Gramellini
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Green
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Gu
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - M Ismail
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Nankai University, Nankai District, Tianjin 300071, China
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - H Liu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - S Martynenko
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - I Mawby
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N McConkey
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Micallef
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M M Moudgalya
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - I Safa
- Columbia University, New York, New York 10027, USA
| | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois 60637, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - W Wu
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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15
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Gou M, Chen W, Li Y, Chen S, Feng W, Pan S, Luo X, Tan S, Tian B, Li W, Tong J, Zhou Y, Li H, Yu T, Wang Z, Zhang P, Huang J, Kochunov P, Tian L, Li CSR, Hong LE, Tan Y. Immune-Inflammatory Response And Compensatory Immune-Regulatory Reflex Systems And White Matter Integrity in Schizophrenia. Schizophr Bull 2024; 50:199-209. [PMID: 37540273 PMCID: PMC10754202 DOI: 10.1093/schbul/sbad114] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Low-grade neural and peripheral inflammation are among the proposed pathophysiological mechanisms of schizophrenia. White matter impairment is one of the more consistent findings in schizophrenia but the underlying mechanism remains obscure. Many cerebral white matter components are sensitive to neuroinflammatory conditions that can result in demyelination, altered oligodendrocyte differentiation, and other changes. We tested the hypothesis that altered immune-inflammatory response system (IRS) and compensatory immune-regulatory reflex system (IRS/CIRS) dynamics are associated with reduced white matter integrity in patients with schizophrenia. STUDY DESIGN Patients with schizophrenia (SCZ, 70M/50F, age = 40.76 ± 13.10) and healthy controls (HCs, 38M/27F, age = 37.48 ± 12.31) underwent neuroimaging and plasma collection. A panel of cytokines were assessed using enzyme-linked immunosorbent assay. White matter integrity was measured by fractional anisotropy (FA) from diffusion tensor imaging using a 3-T Prisma MRI scanner. The cytokines were used to generate 3 composite scores: IRS, CIRS, and IRS/CIRS ratio. STUDY RESULTS The IRS/CIRS ratio in SCZ was significantly higher than that in HCs (P = .009). SCZ had a significantly lower whole-brain white matter average FA (P < .001), and genu of corpus callosum (GCC) was the most affected white matter tract and its FA was significantly associated with IRS/CIRS (r = 0.29, P = .002). FA of GCC was negatively associated with negative symptom scores in SCZ (r = -0.23, P = .016). There was no mediation effect taking FA of GCC as mediator, for that IRS/CIRS was not associated with negative symptom score significantly (P = .217) in SCZ. CONCLUSIONS Elevated IRS/CIRS might partly account for the severity of negative symptoms through targeting the integrity of GCC.
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Affiliation(s)
- Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Hongna Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
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16
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Liang H, Wang C, Zhu PF, Zeng QL, Huang XB, Pan YF, Pan YJ, Hu QY, Luo X, Chen H, Yu ZJ, Lu FM, Lyu J. [A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:1297-1305. [PMID: 38253074 DOI: 10.3760/cma.j.cn501113-20230505-00206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Objective: To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to pegylated interferon-α add-on therapy in patients with chronic hepatitis B. Methods: Patients with chronic hepatitis B who visited the First Affiliated Hospital of Zhengzhou University from 2018~2019 were prospectively enrolled. HBsAg≤ 1500 IU/mL, hepatitis B e antigen-negative, HBV DNA undetectable, received antiviral treatment with nucleos(t)ide analogues for at least one year, and pegylated interferon-α add-on therapy for 48 weeks were included. The primary endpoint of study was to determine the proportion of HBsAg clearance at 72 weeks. Concurrently, the predictive factors for HBsAg clearance were analyzed. Quantitative and qualitative data were analyzed using a t-test or non-parametric test and a Fisher's exact test. Results: A total of 38 cases were included in this study, of which 13 cases obtained HBsAg clearance at 48 weeks of therapy and another six cases obtained HBsAg clearance throughout the extended treatment period of 72 weeks, accounting for 50.00% of all enrolled patients. There was a significant difference in HBsAg dynamics between the HBsAg clearance group and the non-clearance group (P < 0.05). Univariate logistic regression analysis showed that patients' age, baseline, 12-and 24-week HBsAg levels, and early HBsAg reduction were predictive factors for HBsAg clearance at 72 weeks of treatment. Multivariate logistic regression analysis showed that age (OR = 1.311; P = 0.016; 95% confidence interval: 1.051~1.635) and HBsAg levels at 24 weeks of treatment (OR = 4.481; P = 0.004; 95% confidence interval: 1.634~12.290) were independent predictors for HBsAg clearance. Conclusion: Hepatitis B e antigen-negative, nucleos(t)ide analogue treated, HBsAg ≤ 1500 IU/mL, and HBV DNA undetectable, peg-IFNα add-on treatment for 48 weeks could promote HBsAg clearance in patients with chronic hepatitis B. Six of the sixteen cases (37.50%) who did not obtain HBsAg clearance at week 48 did so with the course of therapy extended to week 72. Hence, the optimal individualized treatment strategy should be customized according to the predictors rather than the fixed 48-week course. Age (≤ 38), baseline HBsAg level (≤2.86 log(10)IU/ml), HBsAg level at 24 weeks (≤ 0.92 log(10)IU/ml), and 12-week HBsAg decrease from baseline (≥ 0.67 log(10)IU/ml) indicate that patients are highly likely to obtain HBsAg clearance at the 72 weeks of combination therapy, in which the combined indicator based on HBsAg level ≤0.92 log(10)IU/ml at 24 weeks will identify 85.0% to 100.0% of patients with HBsAg clearance.
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Affiliation(s)
- H Liang
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - C Wang
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - P F Zhu
- Department of Clinical Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Q L Zeng
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - X B Huang
- Department of Clinical Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Y F Pan
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Y J Pan
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Q Y Hu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - X Luo
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - H Chen
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Z J Yu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - F M Lu
- Department of Microbiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - J Lyu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
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17
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Yang K, Du R, Yang Q, Zhao R, Fan F, Chen S, Luo X, Tan S, Wang Z, Yu T, Tian B, Le TM, Li CSR, Tan Y. Cortical thickness of the inferior parietal lobule as a potential predictor of relapse in men with alcohol dependence. Brain Imaging Behav 2023:10.1007/s11682-023-00838-7. [PMID: 38078981 DOI: 10.1007/s11682-023-00838-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/01/2023] [Indexed: 12/26/2023]
Abstract
Alcohol dependence is a disorder with a high recurrence rate that leads to a considerable public health burden. The risk of relapse appears to be related to a complex interplay of multiple factors. Herein, we aimed to explore the potential neural predictors of relapse in Chinese male patients with alcohol dependence. This study enrolled 58 male patients with alcohol dependence who had undergone acute detoxification. General demographic information and clinical features were collected. Magnetic resonance imaging data were used to measure cortical thickness across 34 regions of the brain. Patients were followed up at six months, and 51 patients completed the follow-up visit. These patients were divided into a relapser and an abstainer group. A binary logistic regression analysis was performed to investigate the potential risk factors of relapse. Compared to abstainers, relapsers showed higher inattention and non-planning impulsivity on the 11th version of the Barratt Impulsive Scale. The cortical thicknesses of the inferior-parietal lobules were significantly higher in abstainers compared with those in relapsers. Furthermore, binary logistic regression analysis showed that the thickness of the inferior parietal lobule predicted relapse, and lower non-planning impulse was a protective factor against relapse. Relapsers show poorer impulse control than abstainers, and structural magnetic resonance imaging revealed a decreased thickness of the inferior parietal lobule in relapsers. Our results indicate the thickness of the inferior parietal lobule as a potential relapse predictor in male patients with alcohol dependence.
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Affiliation(s)
- Kebing Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Ruonan Du
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Qingyan Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Rongjiang Zhao
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Thang M Le
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China.
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18
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Zhang H, Zhou M, Zhou QL, Luo X, Zheng R, Su J, Xiong GW, Cheng Y, Li YT, Zhang PP, Zhang K, Dai M, Huang XK, Zhang YN, Shi ZH, Tao J, Zhou YQ, Feng PY, Chen ZG, Yang QT. [Preliminary insights into the practice of hypoallergenic home visiting program]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1957-1963. [PMID: 38186142 DOI: 10.3760/cma.j.cn112150-20230903-00151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Allergic diseases affect about 40% of the world's population. Environmental factors are important in the occurrence and development of allergic diseases. Dust mites are one of the most important allergens in the indoor environment. The World Health Organization proposes the "four-in-one, combination of prevention and treatment" treatment principle for allergic diseases, in which environmental control to avoid or reduce allergens is the first choice for treatment. Modern people spend much more time at home (including sleeping) than outdoors, and the control of the home environment is particularly critical. This practice introduces the hypoallergenic home visit program, which including home environment assessment, environmental and behavioral intervention guidance, and common household hypoallergenic supplies and service guidance for the patient's home environment. The real-time semi-quantitative testing of dust mite allergens, qualitative assessments of other indoor allergens, record of patients' household items and lifestyle, and precise, individualized patient prevention and control education will be conducted. The hypoallergenic home visit program improves the doctors' diagnosis and treatment data dimension, and becomes a patient management tool for doctors outside the hospital. It also helps patients continue to scientifically avoid allergens and irritants in the environment, effectively build a hypoallergenic home environment, reduce exposure to allergens in the home environment, and achieve the goal of combining the prevention and treatment of allergic diseases.
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Affiliation(s)
- H Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q L Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - R Zheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - J Su
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - G W Xiong
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Cheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y T Li
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P P Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - K Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Dai
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X K Huang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y N Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - J Tao
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Q Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Respiratory and Intensive Care, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P Y Feng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Dermatology and Cosmetic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z G Chen
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
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19
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Mao Q, Luo J, Luo X, Zhu X, Wang K, Zuo L, Zhang Y, Luo X. RNA m 6A methylation in psychiatric disorders. EC Psychol Psychiatr 2023; 12:01127. [PMID: 38145106 PMCID: PMC10745284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
This comprehensive review introduces the features of m6A modification and its role in neuropsychiatric disorders. The research findings suggest that m6A modifications and their regulators play a critical role in the occurrence and development of major psychiatric disorders, especially Alzheimer's disease, affecting synaptic protein synthesis, subtype classification, immune infiltration, pathogenesis, and inflammatory infiltration. These findings highlight m6A regulators as potential new diagnostic and therapeutic targets, with m6A methyltransferase METTL3 being the best-characterized regulator in these diseases. The review concludes that m6A modification is a promising target for the prevention and treatment of major psychiatric disorders.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People’s Hospital of Deyang City, Deyang, Sichuan 618000, China
| | - Jessica Luo
- Northeastern University Khoury College of Computer Sciences, Boston, MA 02115, USA
| | - Xinqun Luo
- Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian 350004, China
| | - Xiaoyu Zhu
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV, USA
| | - Lingjun Zuo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin 300222, China
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
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20
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Huang YX, Zou XP, Zhang ZL, Ning K, Luo X, Xiong LB, Peng YL, Zhou ZH, Dong P, Guo SJ, Han H, Zhou FJ. [Relation factor analysis for the short-term preservation of ipsilateral renal function after partial nephrectomy]. Zhonghua Wai Ke Za Zhi 2023; 61:1099-1103. [PMID: 37932147 DOI: 10.3760/cma.j.cn112139-20230228-00086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Objectives: To analyze the factors relative to the short-term preservation of ipsilateral renal function after partial nephrectomy. Methods: The clinical data of 83 patients who were treated with partial nephrectomy from December 2014 to December 2019 in the Department of Urology, Sun Yat-sen University Cancer Center were retrospectively analyzed. There were 54 males and 29 females, aging (M (IQR)) 49 (17) years (range: 27 to 74 years). The ischemia time in operation was 25 (18) minutes (range: 10 to 67 minutes). Emission computed tomography scan and CT scan were performed before (within 1 month) and after (3 to 12 months) surgery. The volume of the ipsilateral and contralateral kidney was measured on the basis of preoperative and postoperative CT scans. The glomerular filtration rate (GFR) specifically in each kidney was estimated by emission computed tomography. Recovery from ischemia is determined by the formula: GFR preservation/volume saved×100%. Linear regression was used to explore the factors ralative to the short-term preservation of ipsilateral renal function after partial nephrectomy. Results: The GFR preservation of the ipsilateral kidney was 80.9 (25.2) % (range: 31.0% to 109.4%). The volume loss of the kidney resulted in a decrease of 12.0% (5.8 ml/(min×1.96 m2)) of GFR, while the ischemic injury resulted in a decrease of 6.5% (2.5 ml/(min×1.96 m2)) of GFR. The volume saved from the ipsilateral kidney was 87.1 (12.9) % (range: 27.0% to 131.7%). Recovery from ischemia was 93.5 (17.5) % (range:44.3% to 178.3%). In multivariate analysis, GFR preservation of the ipsilateral kidney was significantly correlated with the volume saved of the ipsilateral kidney (β=0.383, 95%CI: 0.144 to 0.622, P=0.002). It was not related to the ischemia time (β=0.046, 95%CI:-0.383 to 0.475, P=0.831). Conclusion: In the condition of limited ischemic time, in the short term ipsilateral renal function after partial nephrectomy is mainly determined by the loss of kidney volume, while ischemic injury only plays a minor role.
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Affiliation(s)
- Y X Huang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X P Zou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - L B Xiong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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21
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Gao S, Wang J, Wu X, Luo X, Li Q, Chen D, Liu X, Li W. [Molecular detection and subtyping of Blastocystis sp. in pigs in Anhui Province]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:508-512. [PMID: 38148541 DOI: 10.16250/j.32.1374.2023082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
OBJECTIVE To investigate the prevalence and subtype distribution of Blastocystis sp. in pigs in Anhui Province. METHODS A total of 500 stool samples were collected from large-scale pig farms in Bozhou, Anqing, Chuzhou, Hefei, Fuyang, and Lu'an cities in Anhui Province from October to December 2015. Blastocystis was detected in pig stool samples using a PCR assay based on the small subunit ribosomal RNA (SSU rRNA) gene, and positive samples were subjected to sequencing and sequence analysis. Blastocystis subtypes were characterized in the online PubMLST database, and verified using phylogenetic tree created with the neighbor-joining algorithm in the Meta software. RESULTS The prevalence of Blastocystis infection was 43.2% (216/500) in pigs in 6 cities of Anhui Province, and all pig farms were tested positive for Blastocystis. There was a region-specific prevalence rate of Blastocystis (17.2% to 50.0%) (χ2 = 26.084, P < 0.01), and there was a significant difference in the prevalence of Blastocystis sp. among nursery pigs (39.6%), preweaned pigs (19.1%), and growing pigs (62.3%) (χ2 = 74.951, P < 0.01). Both online inquiry and phylogenetic analysis revealed ST1, ST3, and ST5 subtypes in pigs, with ST5 as the predominant subtype. CONCLUSIONS The prevalence of Blastocystis sp. is high in pigs in Anhui Province, with three zoonotic subtypes identified, including ST1, ST3, and ST5.
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Affiliation(s)
- S Gao
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - J Wang
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Wu
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Luo
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - Q Li
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - D Chen
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Liu
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - W Li
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
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Lu Y, Liu H, Ye SG, Zhou LL, Luo X, Dang XY, Yuan XG, Qian WB, Liang AB, Li P. [Efficacy and safety analysis of the zanubrutinib-based bridging regimen in chimeric antigen receptor T-cell therapy for relapsed/refractory diffuse large B-cell lymphoma]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:813-819. [PMID: 38049332 PMCID: PMC10694070 DOI: 10.3760/cma.j.issn.0253-2727.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Indexed: 12/06/2023]
Abstract
Objective: To further elucidate the clinical efficacy and safety of a combination regimen based on the BTK inhibitor zebutanil bridging CD19 Chimeric antigen receptor T cells (CAR-T cells) in the treatment of relapsed/refractory diffuse large B-cell lymphoma (r/r DLBCL) . Methods: Twenty-one patients with high-risk r/r DLBCL were treated with a zanubrutinib-based regimen bridging CAR-T between June 2020 and June 2023 at the Department of Hematology, Tongji Hospital, Tongji University and the Second Affiliated Hospital of Zhejiang University, and the efficacy and safety were retrospectively analyzed. Results: All 21 patients were enrolled, and the median age was 57 years (range: 38-76). Fourteen patients (66.7%) had an eastern cooperative oncology group performance status score (ECOG score) of ≥2. Eighteen patients (85.7%) had an international prognostic index (IPI) score of ≥3. Three patients (14.3%) had an IPI score of 2 but had extranodal infiltration. Fourteen patients (66.7%) had double-expression of DLBCL and seven (33.3%) had TP53 mutations. With a median follow-up of 24.8 (95% CI 17.0-31.6) months, the objective response rate was 81.0%, and 11 patients (52.4%) achieved complete remission. The median progression-free survival (PFS) was 12.8 months, and the median overall survival (OS) was not reached. The 1-year PFS rate was 52.4% (95% CI 29.8% -74.3%), and the 1-year OS rate was 80.1% (95% CI 58.1% -94.6%). Moreover, 18 patients (85.7%) had grade 1-2 cytokine-release syndrome, and two patients (9.5%) had grade 1 immune effector cell-associated neurotoxicity syndrome. Conclusion: Zanubrutinib-based combination bridging regimen of CAR-T therapy for r/r DLBCL has high efficacy and demonstrated a good safety profile.
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Affiliation(s)
- Y Lu
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - H Liu
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - S G Ye
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - L L Zhou
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X Luo
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X Y Dang
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X G Yuan
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - W B Qian
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - A B Liang
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - P Li
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
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Ping J, Wan J, Huang C, Yu J, Luo J, Xing Z, Luo X, Du B, Jiang T, Zhang J. DNMT1 SNPs (rs2114724 and rs2228611) associated with positive symptoms in Chinese patients with schizophrenia. Ann Gen Psychiatry 2023; 22:40. [PMID: 37833704 PMCID: PMC10576382 DOI: 10.1186/s12991-023-00466-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
OBJECTIVE Schizophrenia is a serious mental disorder with complex clinical manifestations, while its pathophysiological mechanism is not fully understood. Accumulated evidence suggested the alteration in epigenetic pathway was associated with clinical features and brain dysfunctions in schizophrenia. DNA methyltransferases (DNMTs), a key enzyme for DNA methylation, are related to the development of schizophrenia, whereas the current research evidence is not sufficient. The aim of study was to explore the effects of gene polymorphisms of DNMTs on the susceptibility and symptoms of schizophrenia. METHODS The study was case-control study that designed and employed the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) as the diagnostic standard. 134 hospitalized patients with schizophrenia in the Third People's Hospital of Zhongshan City from January 2018 to April 2020 (Case group) as well as 64 healthy controls (Control group) from the same region were involved. Single nucleotide polymorphisms (SNPs) of DNMT1 genes (r s2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) were determined with massARRAY. Linkage disequilibrium analysis and haplotype analysis were performed, and genotype and allele frequencies were compared. The Hardy-Weinberg equilibrium was tested by the Chi-square test in SPSS software (version 20.0, SPSS Inc., USA). The severity of clinical symptoms was assessed by the Positive and Negative Syndrome Scale (PANSS). The correlation between DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs2424932, rs1569686, rs6119954 and rs2424908) and clinical features was analyzed. RESULTS There were no significant differences in genotype, allele frequency and haplotype of DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) between the case and healthy control group. There were significant differences in the PANSS total positive symptom scores, P3 (hallucinatory behavior), P6 (suspicious/persecution), G7 (motor retardation), and G15 (preoccupation) in patients with different DNMT1 gene rs 2114724 and rs 2228611 genotypes. The linkage disequilibrium analysis of gene polymorphic loci revealed that rs 2114724-rs 2228611 was complete linkage disequilibrium, and rs 1569686-rs 2424908, rs 2424932-rs 1569696 and rs 2424932-rs 2424908 were strongly linkage disequilibrium. CONCLUSION The polymorphisms alteration in genetic pathway may be associated with development of specific clinical features in schizophrenia.
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Affiliation(s)
- Junjiao Ping
- Department of Psychiatry, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
- Joint Laboratory of Psychiatric Genetic Research, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Jing Wan
- Department of Early Intervention, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Caiying Huang
- Department of Early Intervention, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Jinming Yu
- Department of Psychiatry, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Jiali Luo
- Joint Laboratory of Psychiatric Genetic Research, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Zhiqiang Xing
- Department of Psychiatry, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Baoguo Du
- Department of Clinical Psychology, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China
| | - Tingyun Jiang
- Department of Psychiatry, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China.
| | - Jie Zhang
- Joint Laboratory of Psychiatric Genetic Research, The Third People's Hospital, Zhongshan, 528451, Guangdong, People's Republic of China.
- Department of Psychiatry, Gannan Medical University, Ganzhou, 341000, Jiangxi , People's Republic of China.
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Guo X, Wang S, Lin X, Wang Z, Dou Y, Cao Y, Zhang Y, Luo X, Kang L, Yu T, Wang Z, Tan Y, Gao S, Zheng H, Zhao F, Wang H, Wang K, Xie F, Chen W, Luo X. A novel risk variant block across introns 36-45 of CACNA1C for schizophrenia: a cohort-wise replication and cerebral region-wide validation study. Psychiatr Genet 2023; 33:182-190. [PMID: 37706495 PMCID: PMC10502955 DOI: 10.1097/ypg.0000000000000344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
OBJECTIVES Numerous genome-wide association studies have identified CACNA1C as one of the top risk genes for schizophrenia. As a necessary post-genome-wide association study (GWAS) follow-up, here, we focused on this risk gene, carefully investigated its novel risk variants for schizophrenia, and explored their potential functions. METHODS We analyzed four independent samples (including three European and one African-American) comprising 5648 cases and 6936 healthy subjects to identify replicable single nucleotide polymorphism-schizophrenia associations. The potential regulatory effects of schizophrenia-risk alleles on CACNA1C mRNA expression in 16 brain regions (n = 348), gray matter volumes (GMVs) of five subcortical structures (n = 34 431), and surface areas and thickness of 34 cortical regions (n = 36 936) were also examined. RESULTS A novel 17-variant block across introns 36-45 of CACNA1C was significantly associated with schizophrenia in the same effect direction across at least two independent samples (1.8 × 10-4 ≤ P ≤ 0.049). Most risk variants within this block showed significant associations with CACNA1C mRNA expression (1.6 × 10-3 ≤ P ≤ 0.050), GMVs of subcortical structures (0.016 ≤ P ≤ 0.048), cortical surface areas (0.010 ≤ P ≤ 0.050), and thickness (0.004 ≤ P ≤ 0.050) in multiple brain regions. CONCLUSION We have identified a novel and functional risk variant block at CACNA1C for schizophrenia, providing further evidence for the important role of this gene in the pathogenesis of schizophrenia.
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Affiliation(s)
- Xiaoyun Guo
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Shibin Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, the Teaching Hospital of Fujian Medical University, Fuzhou, Fujian 350014, China
| | - Zuxing Wang
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, Chengdu, China
| | - Yikai Dou
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yuping Cao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin, China
| | - Xinqun Luo
- Department of Clinical Medicine, College of Integrated Traditional Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian 350004, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High Altitude Diseases of Tibet Autonomous Region, Xizang Minzu University School of Medicine, Xiangyang, Shaanxi 712082, China
| | - Ting Yu
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, China
| | - Shenshen Gao
- Shanghai Shenkang Hospital Development Center established the Clinical Research and Development Center of Shanghai Municipal Hospitals, Shanghai, China
| | - Hangxiao Zheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Fen Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Huifen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV 26506, USA
| | - Fan Xie
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Wenzhong Chen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, China
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
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Pei S, Liu N, Luo X, Don YL, Chen Z, Li D, Miao D, Duan J, Yan OY, Sheng L, Ouyang G, Wang S, Wang X. An Immune-Related Gene Prognostic Prediction Risk Model for Neoadjuvant Chemoradiotherapy in Rectal Cancer Using Artificial Intelligence. Int J Radiat Oncol Biol Phys 2023; 117:e350. [PMID: 37785213 DOI: 10.1016/j.ijrobp.2023.06.2422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To develop and validate an immune-related gene prognostic model (IRGPM) that can predict disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy and to clarify the immune characteristics of patients with different prognostic risks. MATERIALS/METHODS In this study, we obtained transcriptomic and clinical data from the Gene Expression Omnibus (GEO) database and rectal cancer database of West China Hospital. Genes in the RNA immune-oncology panel were extracted. Elastic net was used to identify the immune-related genes that significantly affected the DFS of patients. A prognostic risk model (IRGPM) for rectal cancer was constructed with the random forest method. The prognostic risk score was calculated by the model, and the patients were divided into high- and low-risk groups according to the median risk score. Immune characteristics were analyzed and compared between the high- and low-risk groups. RESULTS A total of 407 LARC samples were used in this study. A 20-gene signature was identified by elastic net and was found to be significantly correlated with DFS. The IRGPM was constructed on the basis of the 20 immune-related genes. Kaplan‒Meier survival analysis showed poorer 5-year DFS in the high-risk group than in the low-risk group, and the receiver operating characteristic (ROC) curve suggested good model prediction (areas under the curve (AUCs) of 0.87, 0.94, 0.95 at 1, 3, and 5 years, respectively). The model was validated in the GSE190826 cohort (AUCs of 0.79, 0.64, and 0.63 at 1, 3, and 5 years, respectively) and the cohort from our institution (AUCs of 0.64, 0.66, and 0. 64 at 1, 3, and 5 years, respectively). The differentially expressed genes between the high- and low-risk groups were enriched in cytokine‒cytokine receptor interactions. The patients in the low-risk group had higher immune scores than the patients in the high-risk group. Subsequently, we found that activated B cells, activated CD8 T cells, central memory CD8 T cells, macrophages, T follicular helper cells and type 2 helper cells were more abundant in the low-risk group. Moreover, we compared the expression of immune checkpoints and found that the low-risk group had a higher PDCD1 expression level. CONCLUSION The IRGPM, which was constructed based on the random forest and elastic net methods, is a promising method to distinguish DFS in LARC patients treated with a standard strategy. The low-risk group identified by IRGPM was characterized by the activation of adaptive immunity in tumor microenvironment.
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Affiliation(s)
- S Pei
- West China Hospital, Sichuan University, Chengdu, China
| | - N Liu
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - X Luo
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - Y L Don
- West China Hospital Sichuan University, China, Chengdu, China
| | - Z Chen
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - D Li
- West China Hospital, Sichuan University, Chengdu, China
| | - D Miao
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - J Duan
- West China Hospital of Sichuan University, Chengdu, China
| | - O Y Yan
- West China Hospital, Sichuan University, Chengdu, China
| | - L Sheng
- West China Hospital of Sichuan University, Chengdu, China
| | - G Ouyang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - S Wang
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - X Wang
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
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Yu T, Li Y, Li N, Huang J, Fan F, Luo X, Tan S, Yang F, Tian B, Tian L, Li CSR, Tan Y. Regional Homogeneity in schizophrenia patients with tardive dyskinesia: a resting-state fMRI study. Psychiatry Res Neuroimaging 2023; 335:111724. [PMID: 37871408 DOI: 10.1016/j.pscychresns.2023.111724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 09/24/2023] [Accepted: 10/05/2023] [Indexed: 10/25/2023]
Abstract
Neuronal degeneration and apoptosis may play an important role in the pathogenesis of tardive dyskinesia (TD). Previous studies suggested brain structural and functional abnormalities in patients with TD. We investigated changes in cerebral regional homogeneity (ReHo) in patients with TD using resting-state functional magnetic resonance imaging (rs-fMRI). Imaging data were collected from schizophrenia patients with TD (TD group, n=58) and without TD (non-TD group, n=66) and healthy controls (HC group, n=67), processed with SPM, and evaluated at a corrected threshold. Psychopathology and severity of TD were assessed with the Positive and Negative Syndrome Scale (PANSS) and Abnormal Involuntary Movement Scale (AIMS), respectively. Results: TD vs. non-TD group showed significantly higher ReHo in the Left Inferior Semilunar Lobule and Right Fusiform Gyrus and lower ReHo in Left Supramarginal Gyrus, Right Inferior Tempotal Gyrus, and Left Medial Frontal Gyrus. The ReHo value in the Left Inferior Semilunar Lobule was negatively correlated with AIMS upper limbs scores. Conclusions: The findings suggest altered regional neural connectivities in association with TD and may inform research of the etiology and monitor the course of TD in patients with schizophrenia and potentially other psychotic disorders.
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Affiliation(s)
- Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, China.
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Zhang J, Luo X, Zhou R, Dai Z, Guo C, Qu G, Li J, Zhang Z. The axial and sagittal CT values of the 7th thoracic vertebrae in screening for osteoporosis and osteopenia. Clin Radiol 2023; 78:763-771. [PMID: 37573241 DOI: 10.1016/j.crad.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/06/2023] [Accepted: 07/11/2023] [Indexed: 08/14/2023]
Abstract
AIM To evaluate the difference in computed tomography (CT) attenuation value of different planes of the 7th thoracic vertebra and investigate the efficacy of axial and sagittal vertebral CT measurements in predicting osteoporosis. MATERIALS AND METHODS Patients who underwent routine chest CT and dual-energy X-ray absorptiometry (DXA) within 1 month were included in this retrospective study. The CT attenuation values of different planes were compared. Logistic regression and receiver operating characteristic (ROC) were used to analyse the difference of each plane in the diagnosis of osteoporosis. RESULTS The study included 1,338 patients (mean age of 61.9±11.9; 54% female). The CT attenuation values decreased successively in the normal group, osteopenia group, and osteoporosis group. The paired t-test results showed that the mid-axial measurements were greater than mid-sagittal measurements, with a mean difference of 9 HU, the difference was statistically significant (p<0.001, 95% confidence interval [CI] = 7.8-10.1). For each one-unit reduction in mid-sagittal CT attenuation value, the risk of osteopenia or osteoporosis increased by 3.6%. To distinguish osteoporosis from non-osteoporosis (osteopenia + normal), the sensitivity was 90% and the specificity was 52.4% at the mid-sagittal threshold of 113.7 HU. CONCLUSIONS The CT attenuation values of mid-sagittal plane have higher diagnostic efficacy than axial planes in predicting osteoporosis. For patients with a sagittal CT attenuation value of <113.7 HU in the T7, further DXA examination is warranted.
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Affiliation(s)
- J Zhang
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - X Luo
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - R Zhou
- Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China
| | - Z Dai
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - C Guo
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - G Qu
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - J Li
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - Z Zhang
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China.
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Feng SM, Luo X, Xue C, Chen J, Wang K, Shao CQ, Ma C. [Effect of hollow compression screw internal fixation in treating McCrory-Bladin type Ⅱ lateral process fracture of the talus: open versus arthroscopy surgery]. Zhonghua Yi Xue Za Zhi 2023; 103:2808-2812. [PMID: 37723056 DOI: 10.3760/cma.j.cn112137-20230403-00541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
In order to explore the clinical efficacy of hollow compression screw internal fixation in the treatment of lateral process fracture of the talus under open surgery versus arthroscopy procedure, a retrospective cohort study was conducted to analyze the clinical data of 33 patients with lateral process fracture of the talus admitted to Xuzhou Central Hospital from January 2019 to December 2021. There were 19 males (19 feet) and 14 females (14 feet), aged 18 to 50 years, with an average age of (32.2±9.3) years. According to the modified McCrory-Bladin classification, all patients were classified as type Ⅱ. Based on the different surgical methods, the patients were divided into the arthroscopy group (21 cases, treated with double-tunnel subtalar arthroscopy combined with hollow compression screw internal fixation) and the open group (12 cases, treated with open reduction and internal fixation with hollow compression screw). The operation time was observed and the surgical effects were evaluated using the visual analogue scale (VAS) of pain, the American Orthopedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, the Foot Function Index (FFI), and the Foot and Ankle Ability Measure (FAAM), which includes the FAAM-ADL (activity of daily living subscale) and the FAAM-S (sport subscale). All the patients of the two groups achieved stage Ⅰ wound healing. On the first day after the operation, the mean VAS score of the arthroscopy group was 2.4±0.7, which was significantly lower than that of the open group (3.4±1.6) (P=0.020). No significant difference was observed in terms of the follow-up time, operation time and AOFAS score between the two groups (all P>0.05). The FFI score of the arthroscopy group was significantly lower than that of the open group, and the FAAM-ADL and FAAM-S scores were significantly higher than those in the open group (all P<0.05). Two cases of dorsal foot numbness occurred in the open group after the operation, and the incidence of complications was not significantly different from that of the arthroscopy group (P=0.054). For McCrory-Bladin type Ⅱ lateral process fracture of the talus, the use of compression screw internal fixation could achieve reliable results, however, compared to open surgery, arthroscopy procedure obtained mini trauma and better functions.
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Affiliation(s)
- S M Feng
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - X Luo
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Xue
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - J Chen
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - K Wang
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Q Shao
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Ma
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
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Lin LL, Liu HY, Luo X, Zheng Q, Shi B, Gong M, Li CH. [Untargeted metabolomics study of dexamethasone-induced congenital cleft palate in New Zealand rabbits]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:938-943. [PMID: 37659853 DOI: 10.3760/cma.j.cn112144-20230627-00254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/04/2023]
Abstract
Objective: To investigate the metabolic disorders in placental tissues of dexamethasone induced cleft palate mode. Methods: Twelve pregnant rabbits were randomly divided into dexamethasone group (experimental group, 8) and saline control group (4), and a certain amount of dexamethasone and saline were administered intramuscularly to the experimental and control groups respectively from embryonic days (ED) 13 to 16, and placental tissue samples were collected on day 21 of gestation. The corresponding profiles of the embryonic placental tissue samples were obtained by liquid chromatography-triple tandem quadrupole(LC-MS), and the metabolites of the embryonic placental tissues were characterized by principal component analysis among the dexamethasone-treated group with cleft palate (D-CP group), the dexamethasone-treated group without cleft palate (D-NCP group) and the control group. Results: There were significant metabolic differences among the D-CP group, D-NCP group and control group, with a total of 133 differential metabolites (VIP>1, P<0.05) involving in important metabolic pathways including vitamin B6 metabolism, lysine metabolism, arginine anabolic metabolism, and galactose metabolism. The four metabolites, vitamin B6, galactose, lysine and urea, differed among the three groups (P<0.05). There were significant differences in vitamin B6 (0.960±0.249, 0.856±0.368, 1.319±0.322), galactose (0.888±0.171, 1.033±0.182, 1.127±0.127), lysine (1.551±0.924, 1.789±1.435, 0.541±0.424) and urea (0.743±0.142, 1.137±0.301, 1.171±0.457, respectively) levels among control group, D-NCP group and D-CP group (F=5.90, P=0.008; F=5.59, P=0.009; F=4.26, P=0.025; F=5.29, P=0.012). Conclusions: The results indicated that dexamethasone induced cleft palate may be highly correlated with metabolic disorders including vitamin B6 metabolism, lysine metabolism, arginine anabolic metabolism and galactose metabolism.
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Affiliation(s)
- L L Lin
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - H Y Liu
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - X Luo
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - Q Zheng
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - B Shi
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - M Gong
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - C H Li
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
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30
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cohen EO, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector. Phys Rev Lett 2023; 131:101802. [PMID: 37739352 DOI: 10.1103/physrevlett.131.101802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/09/2023] [Accepted: 07/14/2023] [Indexed: 09/24/2023]
Abstract
We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - O Benevides Rodrigues
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
- Syracuse University, Syracuse, New York 13244, USA
| | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - E O Cohen
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Wang Z, Lin X, Luo X, Xiao J, Zhang Y, Xu J, Wang S, Zhao F, Wang H, Zheng H, Zhang W, Lin C, Tan Z, Cao L, Wang Z, Tan Y, Chen W, Cao Y, Guo X, Pittenger C, Luo X. Pleiotropic Association of CACNA1C Variants With Neuropsychiatric Disorders. Schizophr Bull 2023; 49:1174-1184. [PMID: 37306960 PMCID: PMC10483336 DOI: 10.1093/schbul/sbad073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Neuropsychiatric disorders are highly heritable and have overlapping genetic underpinnings. Single nucleotide polymorphisms (SNPs) in the gene CACNA1C have been associated with several neuropsychiatric disorders, across multiple genome-wide association studies. METHOD A total of 70,711 subjects from 37 independent cohorts with 13 different neuropsychiatric disorders were meta-analyzed to identify overlap of disorder-associated SNPs within CACNA1C. The differential expression of CACNA1C mRNA in five independent postmortem brain cohorts was examined. Finally, the associations of disease-sharing risk alleles with total intracranial volume (ICV), gray matter volumes (GMVs) of subcortical structures, cortical surface area (SA), and average cortical thickness (TH) were tested. RESULTS Eighteen SNPs within CACNA1C were nominally associated with more than one neuropsychiatric disorder (P < .05); the associations shared among schizophrenia, bipolar disorder, and alcohol use disorder survived false discovery rate correction (five SNPs with P < 7.3 × 10-4 and q < 0.05). CACNA1C mRNA was differentially expressed in brains from individuals with schizophrenia, bipolar disorder, and Parkinson's disease, relative to controls (three SNPs with P < .01). Risk alleles shared by schizophrenia, bipolar disorder, substance dependence, and Parkinson's disease were significantly associated with ICV, GMVs, SA, or TH (one SNP with P ≤ 7.1 × 10-3 and q < 0.05). CONCLUSION Integrating multiple levels of analyses, we identified CACNA1C variants associated with multiple psychiatric disorders, and schizophrenia and bipolar disorder were most strongly implicated. CACNA1C variants may contribute to shared risk and pathophysiology in these conditions.
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Affiliation(s)
- Zuxing Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, the Teaching Hospital of Fujian Medical University, Fuzhou, Fujian 350014, China
| | - Xinqun Luo
- Department of Neurosurgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350001, China
| | - Jun Xiao
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin 300180, China
| | - Jianying Xu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong 519000, China
| | - Shibin Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Fen Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Huifen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Hangxiao Zheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Wei Zhang
- Department of Pharmacology, Institute of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, 050017, P. R. China
| | - Chen Lin
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing 100096, China
| | - Zewen Tan
- Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510370, China
| | - Liping Cao
- Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510370, China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing 100096, China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing 100096, China
| | - Wenzhong Chen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
| | - Yuping Cao
- Department of Psychiatry, Second Xiangya Hospital, Central South University; China National Clinical Research Center on Mental Disorders, China National Technology Institute on Mental Disorders, Changsha, Hunan 410011, China
| | - Xiaoyun Guo
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of medicine, Shanghai 200030, China
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, US
| | - Christopher Pittenger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, US
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing 100096, China
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Salihoglu H, Shi J, Li Z, Wang Z, Luo X, Bondarev IV, Biehs SA, Shen S. Nonlocal Near-Field Radiative Heat Transfer by Transdimensional Plasmonics. Phys Rev Lett 2023; 131:086901. [PMID: 37683160 DOI: 10.1103/physrevlett.131.086901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 07/25/2023] [Indexed: 09/10/2023]
Abstract
Using transdimensional plasmonic materials (TDPM) within the framework of fluctuational electrodynamics, we demonstrate nonlocality in dielectric response alters near-field heat transfer at gap sizes on the order of hundreds of nanometers. Our theoretical study reveals that, opposite to the local model prediction, propagating waves can transport energy through the TDPM. However, energy transport by polaritons at shorter separations is reduced due to the metallic response of TDPM stronger than that predicted by the local model. Our experiments conducted for a configuration with a silica sphere and a doped silicon plate coated with an ultrathin layer of platinum as the TDPM show good agreement with the nonlocal near-field radiation theory. Our experimental work in conjunction with the nonlocal theory has important implications in thermophotovoltaic energy conversion, thermal management applications with metal coatings, and quantum-optical structures.
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Affiliation(s)
- H Salihoglu
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - J Shi
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Z Li
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Z Wang
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - X Luo
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - I V Bondarev
- Mathematics & Physics Department, North Carolina Central University, Durham, North Carolina 27707, USA
| | - S-A Biehs
- Institut für Physik, Carl von Ossietzky Universität, 26111, Oldenburg, Germany
| | - S Shen
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
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Adam J, Adamczyk L, Adams JR, Adkins JK, Agakishiev G, Aggarwal MM, Ahammed Z, Alekseev I, Anderson DM, Aparin A, Aschenauer EC, Ashraf MU, Atetalla FG, Attri A, Averichev GS, Bairathi V, Barish K, Behera A, Bellwied R, Bhasin A, Bielcik J, Bielcikova J, Bland LC, Bordyuzhin IG, Brandenburg JD, Brandin AV, Butterworth J, Caines H, Calderón de la Barca Sánchez M, Cebra D, Chakaberia I, Chaloupka P, Chan BK, Chang FH, Chang Z, Chankova-Bunzarova N, Chatterjee A, Chen D, Chen J, Chen JH, Chen X, Chen Z, Cheng J, Cherney M, Chevalier M, Choudhury S, Christie W, Chu X, Crawford HJ, Csanád M, Daugherity M, Dedovich TG, Deppner IM, Derevschikov AA, Didenko L, Dong X, Drachenberg JL, Dunlop JC, Edmonds T, Elsey N, Engelage J, Eppley G, Esumi S, Evdokimov O, Ewigleben A, Eyser O, Fatemi R, Fazio S, Federic P, Fedorisin J, Feng CJ, Feng Y, Filip P, Finch E, Fisyak Y, Francisco A, Fulek L, Gagliardi CA, Galatyuk T, Geurts F, Ghimire N, Gibson A, Gopal K, Gou X, Grosnick D, Guryn W, Hamad AI, Hamed A, Harabasz S, Harris JW, He S, He W, He XH, He Y, Heppelmann S, Heppelmann S, Herrmann N, Hoffman E, Holub L, Hong Y, Horvat S, Hu Y, Huang HZ, Huang SL, Huang T, Huang X, Humanic TJ, Huo P, Igo G, Isenhower D, Jacobs WW, Jena C, Jentsch A, Ji Y, Jia J, Jiang K, Jowzaee S, Ju X, Judd EG, Kabana S, Kabir ML, Kagamaster S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Ke HW, Keane D, Kechechyan A, Kelsey M, Khyzhniak YV, Kikoła DP, Kim C, Kimelman B, Kincses D, Kinghorn TA, Kisel I, Kiselev A, Kocan M, Kochenda L, Kosarzewski LK, Kramarik L, Kravtsov P, Krueger K, Kulathunga Mudiyanselage N, Kumar L, Kumar S, Kunnawalkam Elayavalli R, Kwasizur JH, Lacey R, Lan S, Landgraf JM, Lauret J, Lebedev A, Lednicky R, Lee JH, Leung YH, Li C, Li C, Li W, Li W, Li X, Li Y, Liang Y, Licenik R, Lin T, Lin Y, Lisa MA, Liu F, Liu H, Liu P, Liu P, Liu T, Liu X, Liu Y, Liu Z, Ljubicic T, Llope WJ, Longacre RS, Lukow NS, Luo S, Luo X, Ma GL, Ma L, Ma R, Ma YG, Magdy N, Majka R, Mallick D, Margetis S, Markert C, Matis HS, Mazer JA, Minaev NG, Mioduszewski S, Mohanty B, Mooney I, Moravcova Z, Morozov DA, Nagy M, Nam JD, Nasim M, Nayak K, Neff D, Nelson JM, Nemes DB, Nie M, Nigmatkulov G, Niida T, Nogach LV, Nonaka T, Nunes AS, Odyniec G, Ogawa A, Oh S, Okorokov VA, Page BS, Pak R, Pandav A, Panebratsev Y, Pawlik B, Pawlowska D, Pei H, Perkins C, Pinsky L, Pintér RL, Pluta J, Pokhrel BR, Porter J, Posik M, Pruthi NK, Przybycien M, Putschke J, Qiu H, Quintero A, Radhakrishnan SK, Ramachandran S, Ray RL, Reed R, Ritter HG, Rogachevskiy OV, Romero JL, Ruan L, Rusnak J, Sahoo NR, Sako H, Salur S, Sandweiss J, Sato S, Schmidke WB, Schmitz N, Schweid BR, Seck F, Seger J, Sergeeva M, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao M, Sheikh AI, Shen WQ, Shi SS, Shi Y, Shou QY, Sichtermann EP, Sikora R, Simko M, Singh J, Singha S, Smirnov N, Solyst W, Sorensen P, Spinka HM, Srivastava B, Stanislaus TDS, Stefaniak M, Stewart DJ, Strikhanov M, Stringfellow B, Suaide AAP, Sumbera M, Summa B, Sun XM, Sun X, Sun Y, Sun Y, Surrow B, Svirida DN, Szymanski P, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Timmins AR, Tlusty D, Tokarev M, Tomkiel CA, Trentalange S, Tribble RE, Tribedy P, Tripathy SK, Tsai OD, Tu Z, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vanek J, Vasiliev AN, Vassiliev I, Videbæk F, Vokal S, Voloshin SA, Wang F, Wang G, Wang JS, Wang P, Wang Y, Wang Y, Wang Z, Webb JC, Weidenkaff PC, Wen L, Westfall GD, Wieman H, Wissink SW, Witt R, Wu Y, Xiao ZG, Xie G, Xie W, Xu H, Xu N, Xu QH, Xu YF, Xu Y, Xu Z, Xu Z, Yang C, Yang Q, Yang S, Yang Y, Yang Z, Ye Z, Ye Z, Yi L, Yip K, Yu Y, Zbroszczyk H, Zha W, Zhang C, Zhang D, Zhang S, Zhang S, Zhang XP, Zhang Y, Zhang Y, Zhang ZJ, Zhang Z, Zhang Z, Zhao J, Zhong C, Zhou C, Zhu X, Zhu Z, Zurek M, Zyzak M. Erratum: Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV [Phys. Rev. Lett. 126, 162301 (2021)]. Phys Rev Lett 2023; 131:089901. [PMID: 37683178 DOI: 10.1103/physrevlett.131.089901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Indexed: 09/10/2023]
Abstract
This corrects the article DOI: 10.1103/PhysRevLett.126.162301.
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Xiong LB, Zou XP, Ning K, Luo X, Peng YL, Zhou ZH, Wang J, Li Z, Yu CP, Dong P, Guo SJ, Han H, Zhou FJ, Zhang ZL. [Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy]. Zhonghua Zhong Liu Za Zhi 2023; 45:681-689. [PMID: 37580273 DOI: 10.3760/cma.j.cn112152-20221027-00722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
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Affiliation(s)
- L B Xiong
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X P Zou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - J Wang
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z Li
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - C P Yu
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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Zhang X, Ma LN, Wang MT, Liu HJ, Tian YL, Luo X, Ding XC. [Short-term prognostic predictive value of the neutrophil/lymphocyte ratio combined with prognostic nutritional index in hepatitis B virus-related acute-on-chronic liver failure]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:847-854. [PMID: 37723067 DOI: 10.3760/cma.j.cn501113-20220402-00159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
Objective: To explore the prognostic predictive value of neutrophil/lymphocyte ratio (NLR) combined with prognostic nutritional index (PNI) in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). Methods: Clinical data from 149 HBV-ACLF patients admitted to the infectious diseases Department of the General Hospital of Ningxia Medical University were retrospectively analyzed. Demographic data of the enrolled patients and the initial clinical-related data after admission were collected. Patients were divided into survival (93 cases) and death groups (56 cases) according to their prognostic condition 90 days after discharge. Demographic and clinical differences were compared between the two groups data. Receiver operating characteristic (ROC) curves were plotted to determine the optimal cutoff values for NLR and PNI in predicting the 90-day mortality rate of HBV-ACLF patients. The COX regression model was used to conduct univariate and multivariate analyses to investigate the correlation between NLR and PNI and the prognosis of HBV-ACLF patients. Kaplan-Meier survival analysis was used to explore the effects of NLR and PNI on the survival of HBV-ACLF patients. Results: The death group NLR was higher than that of the survival group, while the PNI was lower than that of the survival group, with a statistically significant difference. The area under the receiver operating characteristic curve (0.842, 95% CI: 0.779-0.906) showed patients with adverse prognosis assessed by NLR combined with PNI had a superior prognosis than that of the Model for End-Stage Liver Disease (MELD) and its combined serum sodium (MELD-Na) and Child-Turcotte-Pugh (CTP) scores. COX regression analysis showed that NLR≥3.03 and MELD score were independent risk factors affecting the prognosis of HBV-ACLF patients. PNI > 36.13 was a protective factor for evaluating the prognosis of HBV-ACLF patients. Conclusion: NLR combined with PNI can enhance the prognostic predictive value of HBV-ACLF.
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Affiliation(s)
- X Zhang
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - L N Ma
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - M T Wang
- Ningxia Medical University, Yinchuan 750004, China
| | - H J Liu
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Y L Tian
- Ningxia Medical University, Yinchuan 750004, China
| | - X Luo
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X C Ding
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
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Zhou M, Luo X, Zhou QL, Zhou WH, Zheng R, Zhang YN, Wu XF, Wu S, Su J, Xiong GW, Cheng Y, Li YT, Zhang PP, Zhang K, Dai M, Huang XK, Shi ZH, Tao J, Zhou YQ, Feng PY, Chen ZG, Yang QT. [Diagnosis and treatment procedures and health management for patients with hereditary angioedema]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1280-1285. [PMID: 37574324 DOI: 10.3760/cma.j.cn112150-20230509-00359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
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Affiliation(s)
- M Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Q L Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - W H Zhou
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - R Zheng
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Y N Zhang
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - X F Wu
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - S Wu
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - J Su
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - G W Xiong
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Cheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y T Li
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P P Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - K Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Dai
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X K Huang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - J Tao
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Q Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Respiratory and Intensive Care, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P Y Feng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Dermatology and Cosmetic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z G Chen
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
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Luo X, Cheng Y, Wu C, He J. [An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2023; 43:1241-1247. [PMID: 37488807 PMCID: PMC10366517 DOI: 10.12122/j.issn.1673-4254.2023.07.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
OBJECTIVE To construct an inherent interpretability machine learning model as an explainable boosting machine model (EBM) for predicting one-year risk of death in patients with severe ischemic stroke. METHODS We randomly divided the data of 2369 eligible patients with severe ischemic stroke in the MIMIC-Ⅳ(2.0) database, who were admitted in ICU in 2008 to 2019, into a training dataset (80%) and a test dataset (20%), and assessed the prognosis of the patients using the EBM model. The prediction performance of the model was evaluated by calculating the area under the receiver operating characteristic (AUC) curve. The calibration curve and Brier score were used to evaluate the degree of calibration of the model, and a decision curve was generated to assess the net clinical benefit. RESULTS The EBM model constructed in this study had good discrimination power, calibration and net benefit, with an AUC of 0.857 (95% CI: 0.831-0.887) for predicting prognosis of severe ischemic stroke. Calibration curve analysis showed that the standard curve of the EBM model was the closest to the ideal curve. Decision curve analysis showed that the model had the greatest net benefit rate at the prediction probability threshold of 0.10 to 0.80. The top 5 independent predictive variables based on the EBM model were age, SOFA score, mean heart rate, mechanical ventilation, and mean respiratory rate, whose significance scores ranged from 0.179 to 0.370. CONCLUSION This EBM model has a good performance for predicting the risk of death within one year in patients with severe ischemic stroke and allows clinicians to better understand the contributing factors of the patients' outcomes through the model interpretability.
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Affiliation(s)
- X Luo
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - Y Cheng
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - C Wu
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - J He
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
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Li J, Li R, Li D, Zhang J, Luo X, Zhang Y. Serum BDNF levels and state anxiety are associated with somatic symptoms in patients with panic disorder. Front Psychiatry 2023; 14:1168771. [PMID: 37533888 PMCID: PMC10393281 DOI: 10.3389/fpsyt.2023.1168771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Background We aimed to explore the predictive role of serum BDNF and anxiety-related variables in changes in somatic symptoms post-escitalopram treatment in panic disorder (PD) patients. Methods Ninety PD patients and 99 healthy controls (HCs) were enrolled. PD patients received an 8-week escitalopram treatment. All patients were administered the Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and State-Trait Anxiety Inventory (STAI) to assess panic and anxiety-related symptoms, respectively. Patient Health Questionnaire 15-item scale (PHQ-15) was performed to measure somatic symptoms, and the blood sample was collected to detect serum BDNF levels in all participants. We performed partial correlation analysis and multiple linear regression to explore correlates of PHQ-15 and predictors of PHQ-15 changes post-escitalopram treatment after controlling for age, gender, education levels (set as a dummy variable), the current duration, comorbid AP, and/or GAD. Results Compared to HCs, PD patients had lower serum BDNF levels and higher PHQ-15 scores that could be improved post-escitalopram treatment. Lower baseline STAI state (b = -0.07, p = 0.004), and PDSS-CV scores (b = -0.25, p = 0.007), but higher baseline serum BDNF levels (b = 0.35, p = 0.007) contributed to the prediction of PHQ-15 changes post-escitalopram treatment. Conclusion State anxiety, serum BDNF levels, and panic severity could predict changes in somatic symptoms post-escitalopram treatment, our results highlighted that serum BDNF could serve as a biological indicator for improving somatic symptoms in PD patients.
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Affiliation(s)
- Jiaxin Li
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, China
| | - Ru Li
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, China
| | - Dazhi Li
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, China
| | - Jian Zhang
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Yong Zhang
- Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, China
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Zhu X, Li R, Zhu Y, Zhou J, Huang J, Zhou Y, Tong J, Zhang P, Luo X, Chen S, Li Y, Tian B, Tan SP, Wang Z, Han X, Tian L, Li CSR, Tan YL. Changes in Inflammatory Biomarkers in Patients with Schizophrenia: A 3-Year Retrospective Study. Neuropsychiatr Dis Treat 2023; 19:1597-1604. [PMID: 37465565 PMCID: PMC10350427 DOI: 10.2147/ndt.s411028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/19/2023] [Indexed: 07/20/2023] Open
Abstract
Objective Accumulating evidence suggested that immune system activation might be involved in the pathophysiology of schizophrenia. The neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), platelet/lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) can measure inflammation. This study aimed to investigate the inflammatory state in patients with schizophrenia by using these indicators. Methods In this study, the complete blood count data for 187 continuing hospitalized patients with schizophrenia and 187 age- and sex-matched healthy participants was collected annually from 2017 to 2019. Platelet (PLT), lymphocyte (LYM), monocyte (MON) and neutrophil (NEU) counts were aggregated and NLR, MLR, PLR, and SII were calculated. Using a generalized linear mixed model, we assessed the impact of age, sex, diagnosis, and sampling year on the above indicators and evaluated the interaction between the factors. Results According to the estimation results of the generalized linear mixed model, the NLR increased by 0.319 (p = 0.004), the MLR increased by 0.037 (p < 0.001), and the SII increased by 57.858 (p = 0.018) in patients with schizophrenia. Data after two years of continuous antipsychotic treatment showed that the NLR and MLR were higher in patients with schizophrenia than those in healthy controls, while the PLT and LYM counts were decreased in patients with schizophrenia. The schizophrenia diagnosis was correlated to the MON and LYM count, NLR, MLR, and SII (p < 0.05). Conclusion The differences in these markers were stable and cannot be eliminated by a full course of treatment. This study provides impetus for the inflammatory hypothesis of schizophrenia.
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Affiliation(s)
- Xiaoyu Zhu
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Ran Li
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Yu Zhu
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Jia Zhou
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Junchao Huang
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Yanfang Zhou
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Jinghui Tong
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Ping Zhang
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Song Chen
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Yanli Li
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Baopeng Tian
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Shu-Ping Tan
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Zhiren Wang
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Xiaole Han
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yun-Long Tan
- Psychosomatic Department, Beijing HuiLongGuan Hospital, Beijing, People’s Republic of China
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Luo X, Tang KY, Wang YY. Preparation of drug-loaded chitosan microspheres repair materials. Eur Rev Med Pharmacol Sci 2023; 27:6489-6495. [PMID: 37522660 DOI: 10.26355/eurrev_202307_33119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
OBJECTIVE With the development of society and the progress of science and technology, microspheres, as a new polymer material, have been applied to all aspects of human beings. Microspheres can play a huge role in food safety, electronic technology, sewage treatment, biomedicine, etc., and are non-toxic or harmless. There are three main types of substrates for the preparation of microspheres: natural polymers, semi-synthetic polymer materials, and synthetic polymer materials. MATERIALS AND METHODS In this study, the inorganic material kaolin was modified by the emulsification-crosslinking method with chitosan and composite microspheres with large interlayer spacing were prepared, which were characterized by Fourier Transform Ioncyclotron Resonancel (FTIR) analysis and Scanning Electron Microscope (SEM). The prepared kaolin/chitosan microspheres were then placed in different amounts of aspirin and the optimal dose was investigated by encapsulation efficiency and drug loading rate. The drug release rate of 0.5 h, 1 h, 1.5 h, 2 h, 4 h, 6 h, and 12 h was then determined by simulating the human colon to determine the performance of the sustained-release drug. RESULTS The experimental results showed that after the prepared composite microspheres were loaded with aspirin drug, we got the optimal dosage of 0.1 g by discussing the encapsulation efficiency and drug loading rate of the drug-loaded microspheres, and the encapsulation efficiency reached 80.80%, while the drug loading rate was 24.40%, the drug release capacity reached about 83% in about 12 hours. CONCLUSIONS The research shows that the kaolin/chitosan drug-loaded microspheres prepared by the emulsification and cross-linking method are excellent drug-loading materials.
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Affiliation(s)
- X Luo
- School of Material Science and Engineering, Zhengzhou University, Zhengzhou, Henan, China.
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Chen W, Gou M, Wang L, Li N, Li W, Tong J, Zhou Y, Xie T, Yu T, Feng W, Li Y, Chen S, Tian B, Tan S, Wang Z, Pan S, Luo X, Zhang P, Huang J, Tian L, Li CSR, Tan Y. Inflammatory disequilibrium and lateral ventricular enlargement in treatment-resistant schizophrenia. Eur Neuropsychopharmacol 2023; 72:18-29. [PMID: 37058967 DOI: 10.1016/j.euroneuro.2023.03.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/28/2023] [Accepted: 03/30/2023] [Indexed: 04/16/2023]
Abstract
Treatment-resistant schizophrenia (TRS) patient respond poorly to antipsychotics. Inflammatory imbalance involving pro- and anti-inflammatory cytokines may play an important role in the mechanism of antipsychotic-medication response. This study aimed to investigate immune imbalance and how the latter relates to clinical manifestations in patients with TRS. The level of net inflammation was estimated by evaluating the immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) in 52 patients with TRS, 47 with non-TRS, and 56 sex and age matched healthy controls. The immune biomarkers mainly included macrophagic M1, T helper, Th-1, Th-2, Th-17, and T regulatory cytokines and receptors. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay. Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). Subcortical volumes were quantified using a 3-T Prisma Magnetic Resonance Imaging scanner. The results showed that (1) patients with TRS were characterized by activated pro-inflammatory cytokines and relatively insufficient anti-inflammatory cytokines, with an elevated IRS/CIRS ratio indicating a new homeostatic immune setpoint; (2) IRS/CIRS ratio was positively correlated with larger lateral ventricle volume and higher PANSS score in patients with TRS. Our findings highlighted the inflammatory disequilibrium as a potential pathophysiological process of TRS.
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Affiliation(s)
- Wenjin Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Mengzhuang Gou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Leilei Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Na Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Xie
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Yanli Li
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Shujuan Pan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector. Phys Rev Lett 2023; 130:231802. [PMID: 37354393 DOI: 10.1103/physrevlett.130.231802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 06/26/2023]
Abstract
We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40} cm^{2}/Ar, where statistical and systematic uncertainties are combined.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Acciarri R, Adams C, Baller B, Basque V, Cavanna F, Co RT, Fitzpatrick RS, Fleming B, Green P, Harnik R, Kelly KJ, Kumar S, Lang K, Lepetic I, Liu Z, Luo X, Lyu KF, Palamara O, Scanavini G, Soderberg M, Spitz J, Szelc AM, Wu W, Yang T. First Constraints on Heavy QCD Axions with a Liquid Argon Time Projection Chamber Using the ArgoNeuT Experiment. Phys Rev Lett 2023; 130:221802. [PMID: 37327426 DOI: 10.1103/physrevlett.130.221802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/21/2023] [Indexed: 06/18/2023]
Abstract
We present the results of a search for heavy QCD axions performed by the ArgoNeuT experiment at Fermilab. We search for heavy axions produced in the NuMI neutrino beam target and absorber decaying into dimuon pairs, which can be identified using the unique capabilities of ArgoNeuT and the MINOS near detector. This decay channel is motivated by a broad class of heavy QCD axion models that address the strong CP and axion quality problems with axion masses above the dimuon threshold. We obtain new constraints at a 95% confidence level for heavy axions in the previously unexplored mass range of 0.2-0.9 GeV, for axion decay constants around tens of TeV.
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Affiliation(s)
- R Acciarri
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - C Adams
- Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - B Baller
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - V Basque
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - R T Co
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
- William I. Fine Theoretical Physics Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Fleming
- Yale University, New Haven, Connecticut 06520, USA
| | - P Green
- University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - R Harnik
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - K J Kelly
- CERN, Esplande des Particules, 1211 Geneva 23, Switzerland
| | - S Kumar
- University of California, Berkeley, California 94720, USA
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - K Lang
- University of Texas at Austin, Austin, Texas 78712, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - Z Liu
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - X Luo
- University of California, Santa Barbara, California, 93106, USA
| | - K F Lyu
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - O Palamara
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - G Scanavini
- Yale University, New Haven, Connecticut 06520, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Wu
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - T Yang
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
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Mao Q, Huang S, Luo X, Liu P, Wang X, Wang K, Zhang Y, Chen B, Luo X. Spatial Multiomics Analysis in Psychiatric Disorders. EC Psychol Psychiatr 2023; 12:1-5. [PMID: 37424930 PMCID: PMC10328214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The aim of this study is to provide a comprehensive overview of spatial multiomics analysis, including its definition, processes, applications, significance and relevant research in psychiatric disorders. To achieve this, a literature search was conducted, focusing on three major spatial omics techniques and their application to three common psychiatric disorders: Alzheimer's disease (AD), schizophrenia, and autism spectrum disorders. Spatial genomics analysis has revealed specific genes associated with neuropsychiatric disorders in certain brain regions. Spatial transcriptomics analysis has identified genes related to AD in areas such as the hippocampus, olfactory bulb, and middle temporal gyrus. It has also provided insight into the response to AD in mouse models. Spatial proteogenomics has identified autism spectrum disorder (ASD)-risk genes in specific cell types, while schizophrenia risk loci have been linked to transcriptional signatures in the human hippocampus. In summary, spatial multiomics analysis offers a powerful approach to understand AD pathology and other psychiatric diseases, integrating multiple data modalities to identify risk genes for these disorders. It is valuable for studying psychiatric disorders with high or low cellular heterogeneity and provides new insights into the brain nucleome to predict disease progression and aid diagnosis and treatment.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People’s Hospital of Deyang City, Deyang, Sichuan 618000, China
| | - Shiren Huang
- Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xinqun Luo
- Department of Neurosurgery, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350001, China
| | - Ping Liu
- Department of Psychosomatic Medicine, People’s Hospital of Deyang City, Deyang, Sichuan 618000, China
| | - Xiaoping Wang
- Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV 26506, USA
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin 300222, China
| | - Bin Chen
- Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University; Department of Cardiovascular Medicine, Fujian Provincial Hospital, Fuzhou, Fujian 350001, China
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
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Zou XP, Ning K, Zhang ZL, Xiong LB, Peng YL, Zhou ZH, Huang YX, Luo X, Li JB, Dong P, Guo SJ, Han H, Zhou FJ. [Efficacy of partial nephrectomy in patients with localized renal carcinoma: a 20-year experience of 2 046 patients in a single center]. Zhonghua Wai Ke Za Zhi 2023; 61:395-402. [PMID: 36987674 DOI: 10.3760/cma.j.cn112139-20221002-00416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Objectives: To analyze the long-term survival of patients with localized renal cell carcinoma after partical nephrectomy. Methods: The clinicopathological records and survival follow-up data of 2 046 patients with localized renal cell carcinoma, who were treated with partial nephrectomy from August 2001 to February 2021 in the Department of Urology, Sun Yat-sen University Cancer Center, were retrospectively analyzed. There were 1 402 males and 644 females, aged (M(IQR)) 51 (19) years (range: 6 to 86 years). The primary end point of this study was cancer-specific survival. Survival curves were estimated using the Kaplan-Meier method, and the difference test was performed by Log-rank test. Univariate and multivariate Cox analysis were fitted to determine factors associated with cancer-specific survival. Results: The follow-up time was 49.2 (48.0) months (range: 1 to 229 months), with 1 974 patients surviving and 72 dying. The median cancer-specific survival time has not yet been reached. The 5- and 10-year cancer specific survival rates were 97.0% and 91.2%, respectively. The 10-year cancer-specific survival rates for stage pT1a (n=1 447), pT1b (n=523) and pT2 (n=58) were 95.3%, 81.8%, and 81.7%, respectively. The 10-year cancer-specific survival rates of patients with nuclear grade 1 (n=226), 2 (n=1 244) and 3 to 4 (n=278) were 96.6%, 89.4%, and 85.5%, respectively. There were no significant differences in 5-year cancer-specific survival rates among patients underwent open, laparoscopic, or robotic surgery (96.7% vs. 97.1% vs. 97.5%, P=0.600). Multivariate analysis showed that age≥50 years (HR=3.93, 95%CI: 1.82 to 8.47, P<0.01), T stage (T1b vs. T1a: HR=3.31, 95%CI: 1.83 to 5.99, P<0.01; T2+T3 vs. T1a: HR=2.88, 95%CI: 1.00 to 8.28, P=0.049) and nuclear grade (G3 to 4 vs. G1: HR=2.81, 95%CI: 1.01 to 7.82, P=0.048) were independent prognostic factors of localized renal cell carcinoma after partial nephrectomy. Conclusions: The long-term cancer-specific survival rates of patients with localized renal cancer after partial nephrectomy are satisfactory. The type of operation (open, laparoscopic, or robotic) has no significant effect on survival. However, patients with older age, higher nuclear grade, and higher T stage have a lower cancer-specific survival rate. Grasping surgical indications, attaching importance to preoperative evaluation, perioperative management, and postoperative follow-up, could benefit achieving satisfactory long-term survival.
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Affiliation(s)
- X P Zou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - L B Xiong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y X Huang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - J B Li
- Department of Clinical Research, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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Munns CF, Yoo HW, Jalaludin MY, Vasanwala RF, Chandran M, Rhee Y, But WM, Kong AP, Su PH, Numbenjapon N, Namba N, Imanishi Y, Clifton‐Bligh R, Luo X, Xia W. Asia‐Pacific
Consensus Recommendations on
X‐Linked
Hypophosphatemia: Diagnosis, Multidisciplinary Management, and Transition from Pediatric to Adult Care. JBMR Plus 2023. [DOI: 10.1002/jbm4.10744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
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Lin Z, Shi G, Liao X, Liu W, Luo X, Zhan H, Cai X. Effect of pulmonary function on bone mineral density in the United States: results from the NHANES 2007-2010 study. Osteoporos Int 2023; 34:955-963. [PMID: 36952024 DOI: 10.1007/s00198-023-06727-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/16/2023] [Indexed: 03/24/2023]
Abstract
UNLABELLED The relationship between pulmonary function (PF) and bone mineral density (BMD) remains controversial. In the US population, we found a positive association between PF and BMD. Mixed variables such as age, gender, and race may influence this association. INTRODUCTION Based on the data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2010, this study explored whether there is a correlation between PF (1st second forceful expiratory volume as a percentage of expected value (FEV1(% predicted)), (one-second rate (FEV1/FVC)), and bone mineral density. METHODS We evaluated the relationship between PF and BMD in 6327 NHANES subjects (mean age 44.51 ± 15.64 years) from 2007 to 2010. The bone mineral density of the whole femur was measured by dual-energy X-ray absorptiometry (DXA). After adjusting for a wide range of confounders, we examined the relationship between PF and total femur BMD using a multiple linear regression model. RESULTS Correction of race, age, alcohol consumption, body mass index (BMI), height, poor income ratio (PIR), total protein, serum calcium, serum uric acid, cholesterol, serum phosphorus, blood urea nitrogen, FEV1(% predicted), and femur BMD were positively correlated (β = 0.032, 95% CI: 0.010-0.054, P = 0.004). FEV1/FVC was positively correlated with spine BMD (β = 0.275 95%CI: 0.102-0.448, P = 0.002). CONCLUSIONS Our study shows that PF is positively associated with BMD in the US population. A variety of factors such as race and age influence this relationship. the relationship between PF and BMD needs to be further investigated, including specific regulatory mechanisms and confounding factors.
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Affiliation(s)
- Z Lin
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - G Shi
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Liao
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - W Liu
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Luo
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - H Zhan
- Department of Rehabilitation, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Cai
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China.
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Mao Q, Lin X, Yin Q, Liu P, Zhang Y, Qu S, Xu J, Cheng W, Luo X, Kang L, Taximaimaiti R, Zheng C, Zhang H, Wang X, Ren H, Cao Y, Lin J, Luo X. A significant, functional and replicable risk KTN1 variant block for schizophrenia. Sci Rep 2023; 13:3890. [PMID: 36890161 PMCID: PMC9995530 DOI: 10.1038/s41598-023-27448-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/02/2023] [Indexed: 03/10/2023] Open
Abstract
Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10-5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10-12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10-4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10-3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10-3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10-19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10-19 ≤ p ≤ 1.0 × 10-4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, the Teaching Hospital of Fujian Medical University, Fuzhou, 350014, Fujian, China
| | - Qin Yin
- Department of Respiratory and Critical Care Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan, 430000, Hubei, China
| | - Ping Liu
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin, 300222, China
| | - Shihao Qu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Jianying Xu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Wenhong Cheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xinqun Luo
- Department of Neurosurgery, The First Hospital, Fujian Medical University, Fuzhou, 350004, Fujian, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research On High Altitude Diseases of Tibet Autonomous Region, Xizang Minzu University School of Medicine, Xiangyang, 712082, Shaanxi, China
| | - Reyisha Taximaimaiti
- Department of Neurology, Shanghai Tongren Hospital, Shanghai Jiao Tong University, Shanghai, 200080, China
| | - Chengchou Zheng
- Minqing Psychiatric Hospital, Minqing, 350800, Fujian, China
| | - Huihao Zhang
- The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350001, China
| | - Xiaoping Wang
- Department of Neurology, The 1st People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 201620, USA
| | - Honggang Ren
- Department of Internal Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuping Cao
- Department of Psychiatry, Second Xiangya Hospital, Central South University, China National Clinical Research Center On Mental Disorders, China National Technology Institute On Mental Disorders, Changsha, 410011, Hunan, China.
| | - Jie Lin
- Fujian Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
- Fujian Institute of Preventive Medicine, Fuzhou, 350012, Fujian, China.
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, 100096, China.
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Yang K, Du R, Yang Q, Zhao R, Fan F, Chen S, Luo X, Tan S, Wang Z, Yu T, Tian B, Le TM, Li CSR, Tan Y. Cortical thickness of the inferior parietal lobule as a potential predictor of relapse in men with alcohol dependence. Res Sq 2023:rs.3.rs-2628081. [PMID: 36945425 PMCID: PMC10029073 DOI: 10.21203/rs.3.rs-2628081/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
Background Alcohol dependence (AD) is a disorder with a high recurrence rate that leads to a considerable public health burden. The risk of relapse appears to be related to a complex interplay of multiple factors. Herein, we aimed to explore the potential neural predictors of relapse in Chinese male patients with AD. Methods This study enrolled 58 male patients with AD who had undergone acute detoxification. General demographic information and clinical features were collected. Magnetic resonance imaging (MRI) data were used to measure cortical thickness across 34 regions of the brain. Patients were followed up at 6 months, and 51 patients completed the follow-up visit. These patients were divided into a relapser and an abstainer group. A binary logistic regression analysis was performed to investigate the potential risk factors of relapse. Results Compared to abstainers, relapsers showed higher inattention and non-planning impulsivity on the 11th version of the Barratt Impulsive Scale. The cortical thicknesses of the inferior-parietal lobule were significantly greater in abstainers compared with those in relapsers. Furthermore, binary logistic regression analysis showed that the thickness of the inferior parietal lobule predicted relapse. Conclusions Relapsers show poorer impulse control than abstainers, and MRI imaging shows a decreased thickness of the inferior parietal lobule in relapsers. Our results indicate the thickness of the inferior parietal lobule as a potential relapse predictor in male patients with AD.
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Affiliation(s)
- Kebing Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Ruonan Du
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Qingyan Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Rongjiang Zhao
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | | | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | | | | | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
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50
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Luo X, Fang W, Ji J, Zhang Y, Garcia-Milian R, Wang Z, Tan Y, Wang S, Wang X, Guo X, Luo X. Association of lesion location with post-stroke depression in China: a systematic review and meta-analysis. EC Psychol Psychiatr 2023; 12:34-45. [PMID: 36913221 PMCID: PMC9997510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
Background Post-stroke depression (PSD) is a mental health condition that can develop after a stroke, with a higher risk of death and negative outcomes. However, limited research has explored how PSD incidence relates to brain locations in Chinese patients. This study aims to fill this gap by examining the link between PSD occurrence and brain lesion location, as well as the type of stroke experienced by the patient. Methods We conducted a systematic search in databases to gather post-stroke depression literature published between January 1, 2015 and May 31, 2021. Following this, we performed a meta-analysis using RevMan to analyze the incidence of PSD associated with different brain regions and types of stroke separately. Results We analyzed seven studies, with a total of 1604 participants. Our findings indicated that the incidence of PSD was higher when the stroke occurred in the left hemisphere compared to the right hemisphere (RevMan: Z = 8.93, P <0.001, OR = 2.69, 95% CI: 2.16-3.34, fixed model); PSD was more common when the stroke affected the cerebral cortex rather than the subcerebral cortex (RevMan: Z = 3.96, P <0.001, OR = 2.00, 95% CI: 1.42-2.81) and when it affected the anterior cortex compared to the posterior cortex (RevMan: Z = 3.85, P <0.001, OR = 1.89, 95% CI: 1.37-2.62). However, we did not find a significant difference in the occurrence of PSD between ischemic and hemorrhagic strokes (RevMan: Z = 0.62, P = 0.53, OR = 0.02, 95% CI: -0.05-0.09). Conclusions Our findings revealed a higher likelihood of PSD in the left hemisphere, specifically in the cerebral cortex and anterior region.
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Affiliation(s)
- Xinqun Luo
- Department of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350001, China
| | - Wenhua Fang
- Department of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian 350001, China
| | - Jiawu Ji
- Department of Psychiatry, Fujian Medical University Affiliated Fuzhou Neuropsychiatric Hospital, Fuzhou, Fujian 350001, China
| | - Yong Zhang
- Department of Bipolar Disorder, Tianjin Anding Hospital, Tianjin 300222, China
| | - Rolando Garcia-Milian
- Bioinformatics Support Program, The Cushing/Whitney Medical Library, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
| | - Shibin Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Xiaoping Wang
- Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 201800, China
| | - Xiaoyun Guo
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical School of Medicine, Beijing 100096, China
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