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Holt F, Ivanova A, Wang Z, Darby S, Duane F, Ntentas G, Oliveros S, Lavery B, Shah K, Eichholz A, Dodwell D, Taylor C. Estimated Doses to the Heart, Lungs and Oesophagus and Risks From Typical UK Radiotherapy for Early Breast Cancer During 2015-2023. Clin Oncol (R Coll Radiol) 2024:S0936-6555(24)00177-8. [PMID: 38853062 DOI: 10.1016/j.clon.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 04/24/2024] [Accepted: 05/01/2024] [Indexed: 06/11/2024]
Abstract
PURPOSE Breast cancer radiotherapy can increase the risks of heart disease, lung cancer and oesophageal cancer. At present, the best dosimetric predictors of these risks are mean doses to the whole heart, lungs and oesophagus, respectively. We aimed to estimate typical doses to these organs and resulting risks from UK breast cancer radiotherapy. METHODS A systematic review and meta-analysis was conducted of planned or delivered mean doses to the whole heart, lungs or oesophagus from UK breast cancer radiotherapy in studies published during 2015-2023. Average mean doses were summarised for combinations of laterality and clinical targets. Heart disease and lung cancer mortality risks were then estimated using established models. RESULTS For whole heart, thirteen studies reported 2893 doses. Average mean doses were higher in left than in right-sided radiotherapy and increased with extent of clinical targets. For left-sided radiotherapy, average mean heart doses were: 2.0 Gy (range 1.2-8.0 Gy) breast/chest wall, 2.7 Gy (range 0.6-5.6 Gy) breast/chest wall with either axilla or supraclavicular nodes and 2.9 Gy (range 1.3-4.7 Gy) breast/chest wall with nodes including internal mammary. For right-sided radiotherapy, average mean heart doses were: 1.0 Gy (range 0.3-1.0 Gy) breast/chest wall and 1.2 Gy (range 1.0-1.4 Gy) breast/chest wall with either axilla or supraclavicular nodes. There were no whole heart dose estimates from right internal mammary radiotherapy. For whole lung, six studies reported 2230 doses. Average mean lung doses increased with extent of targets irradiated: 2.6 Gy (range 1.4-3.0 Gy) breast/chest wall, 3.0 Gy (range 0.9-5.1 Gy) breast/chest wall with either axilla or supraclavicular nodes and 7.1 Gy (range 6.7-10.0 Gy) breast/chest wall with nodes including internal mammary. For whole oesophagus, two studies reported 76 doses. Average mean oesophagus doses increased with extent of targets irradiated: 1.4 Gy (range 1.0-2.0 Gy) breast/chest wall with either axilla or supraclavicular nodes and 5.8 Gy (range 1.9-10.0 Gy) breast/chest wall with nodes including internal mammary. CONCLUSIONS The typical doses to these organs may be combined with dose-response relationships to estimate radiation risks. Estimated 30-year absolute lung cancer mortality risks from modern UK breast cancer radiotherapy for patients irradiated when aged 50 years were 2-6% for long-term continuing smokers, and <1% for non-smokers. Estimated 30-year mortality risks for heart disease were <1%.
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Gao W, Peng C, Wang Z, Li Y, Liu M. Genetic association and causal relationship between multiple modifiable risk factors and autoimmune liver disease: a two-sample mendelian randomization study. J Transl Med 2024; 22:425. [PMID: 38704596 PMCID: PMC11070123 DOI: 10.1186/s12967-024-05247-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 04/28/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND The intricate etiology of autoimmune liver disease (AILD) involves genetic, environmental, and other factors that yet to be completely elucidated. This study comprehensively assessed the causal association between genetically predicted modifiable risk factors and AILD by employing Mendelian randomization. METHODS Genetic variants associated with 29 exposure factors were obtained from genome-wide association studies (GWAS). Genetic association data with autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) were also obtained from publicly available GWAS. Univariate and multivariate Mendelian randomization analyses were performed to identify potential risk factors for AILD. RESULTS Genetically predicted rheumatoid arthritis (RA) (OR = 1.620, 95%CI 1.423-1.843, P = 2.506 × 10- 13) was significantly associated with an increased risk of AIH. Genetically predicted smoking initiation (OR = 1.637, 95%CI 1.055-2.540, P = 0.028), lower coffee intake (OR = 0.359, 95%CI 0.131-0.985, P = 0.047), cholelithiasis (OR = 1.134, 95%CI 1.023-1.257, P = 0.017) and higher C-reactive protein (CRP) (OR = 1.397, 95%CI 1.094-1.784, P = 0.007) were suggestively associated with an increased risk of AIH. Genetically predicted inflammatory bowel disease (IBD) (OR = 1.212, 95%CI 1.127-1.303, P = 2.015 × 10- 7) and RA (OR = 1.417, 95%CI 1.193-1.683, P = 7.193 × 10- 5) were significantly associated with increased risk of PBC. Genetically predicted smoking initiation (OR = 1.167, 95%CI 1.005-1.355, P = 0.043), systemic lupus erythematosus (SLE) (OR = 1.086, 95%CI 1.017-1.160, P = 0.014) and higher CRP (OR = 1.199, 95%CI 1.019-1.410, P = 0.028) were suggestively associated with an increased risk of PBC. Higher vitamin D3 (OR = 0.741, 95%CI 0.560-0.980, P = 0.036) and calcium (OR = 0.834, 95%CI 0.699-0.995, P = 0.044) levels were suggestive protective factors for PBC. Genetically predicted smoking initiation (OR = 0.630, 95%CI 0.462-0.860, P = 0.004) was suggestively associated with a decreased risk of PSC. Genetically predicted IBD (OR = 1.252, 95%CI 1.164-1.346, P = 1.394 × 10- 9), RA (OR = 1.543, 95%CI 1.279-1.861, P = 5.728 × 10- 6) and lower glycosylated hemoglobin (HbA1c) (OR = 0.268, 95%CI 0.141-0.510, P = 6.172 × 10- 5) were positively associated with an increased risk of PSC. CONCLUSIONS Evidence on the causal relationship between 29 genetically predicted modifiable risk factors and the risk of AIH, PBC, and PSC is provided by this study. These findings provide fresh perspectives on the management and prevention strategies for AILD.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Fang YQ, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Feng YT, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Gutierrez J, Han KL, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu BY, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khachatryan V, Khoukaz A, Kiuchi R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Moses B, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang NY, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YL, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZD, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Determination of Spin-Parity Quantum Numbers of X(2370) as 0^{-+} from J/ψ→γK_{S}^{0}K_{S}^{0}η^{'}. PHYSICAL REVIEW LETTERS 2024; 132:181901. [PMID: 38759175 DOI: 10.1103/physrevlett.132.181901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/05/2024] [Accepted: 03/28/2024] [Indexed: 05/19/2024]
Abstract
Based on (10087±44)×10^{6} J/ψ events collected with the BESIII detector, a partial wave analysis of the decay J/ψ→γK_{S}^{0}K_{S}^{0}η^{'} is performed. The mass and width of the X(2370) are measured to be 2395±11(stat)_{-94}^{+26}(syst) MeV/c^{2} and 188_{-17}^{+18}(stat)_{-33}^{+124}(syst) MeV, respectively. The corresponding product branching fraction is B[J/ψ→γX(2370)]×B[X(2370)→f_{0}(980)η^{'}]×B[f_{0}(980)→K_{S}^{0}K_{S}^{0}]=(1.31±0.22(stat)_{-0.84}^{+2.85}(syst))×10^{-5}. The statistical significance of the X(2370) is greater than 11.7σ and the spin parity is determined to be 0^{-+} for the first time. The measured mass and spin parity of the X(2370) are consistent with the predictions of the lightest pseudoscalar glueball.
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Raghuwanshi S, Zhang X, Arbieva Z, Khan I, Mohammed H, Wang Z, Domling A, Camacho CJ, Gartel AL. Novel FOXM1 inhibitor STL001 sensitizes human cancers to a broad-spectrum of cancer therapies. Cell Death Discov 2024; 10:211. [PMID: 38697979 PMCID: PMC11066125 DOI: 10.1038/s41420-024-01929-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 05/05/2024] Open
Abstract
Forkhead box protein M1 (FOXM1) is often overexpressed in human cancers and strongly associated with therapy resistance and less good patient survival. The chemotherapy options for patients with the most aggressive types of solid cancers remain very limited because of the acquired drug resistance, making the therapy less effective. NPM1 mutation through the inactivation of FOXM1 via FOXM1 relocalization to the cytoplasm confers more favorable treatment outcomes for AML patients, confirming FOXM1 as a crucial target to overcome drug resistance. Pharmacological inhibition of FOXM1 could be a promising approach to sensitize therapy-resistant cancers. Here, we explore a novel FOXM1 inhibitor STL001, a first-generation modification drug of our previously reported FOXM1 inhibitor STL427944. STL001 preserves the mode of action of the STL427944; however, STL001 is up to 50 times more efficient in reducing FOXM1 activity in a variety of solid cancers. The most conventional cancer therapies studied here induce FOXM1 overexpression in solid cancers. The therapy-induced FOXM1 overexpression may explain the failure or reduced efficacy of these drugs in cancer patients. Interestingly, STL001 increased the sensitivity of cancer cells to conventional cancer therapies by suppressing both the high-endogenous and drug-induced FOXM1. Notably, STL001 does not provide further sensitization to FOXM1-KD cancer cells, suggesting that the sensitization effect is conveyed specifically through FOXM1 suppression. RNA-seq and gene set enrichment studies revealed prominent suppression of FOXM1-dependent pathways and gene ontologies. Also, gene regulation by STL001 showed extensive overlap with FOXM1-KD, suggesting a high selectivity of STL001 toward the FOXM1 regulatory network. A completely new activity of FOXM1, mediated through steroid/cholesterol biosynthetic process and protein secretion in cancer cells was also detected. Collectively, STL001 offers intriguing translational opportunities as combination therapies targeting FOXM1 activity in a variety of human cancers driven by FOXM1.
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Wang Z, Van Faassen M, Groen H, Cantineau AEP, Van Oers A, Van der Veen A, Hawley JM, Keevil BG, Kema IP, Hoek A. Resumption of ovulation in anovulatory women with PCOS and obesity is associated with reduction of 11β-hydroxyandrostenedione concentrations. Hum Reprod 2024; 39:1078-1088. [PMID: 38503490 PMCID: PMC11063562 DOI: 10.1093/humrep/deae058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 02/02/2024] [Indexed: 03/21/2024] Open
Abstract
STUDY QUESTION Is resumption of ovulation after a 6-month lifestyle intervention in women with PCOS and obesity associated with differential changes in endocrine and metabolic parameters (weight, insulin resistance, anti-Müllerian hormone (AMH), and androgens) compared to women with PCOS who remained anovulatory? SUMMARY ANSWER Resumption of ovulation after a 6-month lifestyle intervention in women with PCOS and obesity is associated with changes in serum 11β-hydroxyandrostenedione (11OHA4) concentrations. WHAT IS KNOWN ALREADY Lifestyle interventions have been shown to reduce clinical and biochemical hyperandrogenism in women with PCOS. Weight loss of 5-10% may reverse anovulatory status, thereby increasing natural conception rates. However, the mechanisms underlying why some women with PCOS remain anovulatory and others resume ovulation after weight loss are unclear. Reproductive characteristics at baseline and a greater degree of change in endocrine and metabolic features with lifestyle intervention may be crucial for ovulatory response. STUDY DESIGN, SIZE, DURATION We used data and samples originating from an earlier randomized controlled trial (RCT), which examined the efficacy of a 6-month lifestyle intervention prior to infertility treatment compared to prompt infertility treatment on live birth rate in women with obesity. A total of 577 women with obesity (BMI > 29 kg/m2) were randomized between 2009 and 2012. Anovulatory women with PCOS who were allocated to the intervention arm of the original RCT (n = 95) were included in the current analysis. PARTICIPANTS/MATERIALS, SETTING, METHODS We defined women as having resumed ovulation (RO+) based on the following criteria: spontaneous pregnancy; or assignment to expectant management; or IUI in natural cycles as the treatment strategy after lifestyle intervention. Steroid hormones were measured using liquid chromatography tandem mass spectrometry. Generalized estimating equations with adjustment for baseline measures and interaction between group and time was used to examine differences in changes of endocrine and metabolic parameters between RO+ (n = 34) and persistently anovulatory women (RO-, n = 61) at 3 and 6 months after intervention. MAIN RESULTS AND THE ROLE OF CHANCE At baseline, the mean ± SD age was 27.5 ± 3.6 years in the RO+ group and 27.9 ± 4.1 years in the RO- group (P = 0.65), and the mean ± SD weights were 101.2 ± 9.5 kg and 105.0 ± 14.6 kg, respectively (P = 0.13). Baseline AMH concentrations showed significant differences between RO+ and RO- women (median and interquartile range [IQR] 4.7 [3.2; 8.3] versus 7.2 [5.3; 10.8] ng/ml, respectively). Baseline androgen concentrations did not differ between the two groups. During and after lifestyle intervention, both groups showed weight loss; changes in 11OHA4 were significantly different between the RO+ and RO groups (P-value for interaction = 0.03). There was a similar trend for SHBG (interaction P-value = 0.07), and DHEA-S (interaction P-value = 0.06), with the most pronounced differences observed in the first 3 months. Other parameters, such as AMH and FAI, decreased over time but with no difference between the groups. LIMITATIONS, REASONS FOR CAUTION No high-resolution transvaginal ultrasonography was used to confirm ovulatory status at the end of the lifestyle program. The small sample size may limit the robustness of the results. WIDER IMPLICATIONS OF THE FINDINGS Reduction of androgen concentrations during and after lifestyle intervention is associated with recovery of ovulatory cycles. If our results are confirmed in other studies, androgen concentrations could be monitored during lifestyle intervention to provide individualized recommendations on the timing of resumption of ovulation in anovulatory women with PCOS and obesity. STUDY FUNDING/COMPETING INTEREST(S) The study was supported by a grant from ZonMw, the Dutch Organization for Health Research and Development (50-50110-96-518). The Department of Obstetrics and Gynecology of the UMCG received an unrestricted educational grant from Ferring Pharmaceuticals BV, The Netherlands. A.H. reports consultancy for the development and implementation of a lifestyle App MyFertiCoach developed by Ferring Pharmaceutical Company. All other authors have no conflicts to declare. TRIAL REGISTRATION NUMBER The LIFEstyle RCT was registered at the Dutch trial registry (NTR 1530).
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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] [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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Luo L, Wang Z, Wang X, Gao J, Zheng A, Duan X. Fluorine-18 prostate-specific membrane antigen-1007-avid indeterminate bone lesions in prostate cancer: clinical and PET/CT features to predict outcomes and prognosis. Clin Radiol 2024; 79:346-353. [PMID: 38216370 DOI: 10.1016/j.crad.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/29/2023] [Accepted: 12/11/2023] [Indexed: 01/14/2024]
Abstract
AIM To determine clinical and fluorine-18 prostate-specific membrane antigen-1007 (18F-PSMA-1007) integrated positron-emission tomography (PET)/computed tomography (CT) features that could be used to interpret indeterminate bone lesions (IBLs) and assess the prognosis of prostate cancer (PCa) in patients with IBLs. MATERIALS AND METHODS Consecutive patients who underwent PSMA PET/CT were analysed retrospectively. IBLs were identified as benign or malignant based on follow-up imaging and clinical management. Lesion- and patient-based assessments were performed to define features predictive of bone lesion results and determine clinical risk. Patients' prognosis was analysed based on clinical characteristics, including prostate-specific antigen (PSA) and alkaline phosphatase (ALP), respectively. RESULTS A total of 105 patients (mean age ± SD, 72.1 ± 8 years) were evaluated and 158 IBLs were identified. Fifty-three (33.5%), 36 (22.8%), and 69 (43.7%) IBLs were benign, malignant, and equivocal, respectively. Variables including location, maximum standard uptake value (SUVmax), and lymph node metastases (LNM) were related to the benignancy or malignancy of IBLs (p=0.046, p<0.001 and p<0.001, respectively). Regression analysis indicated that LNM, SUVmax, and location of IBLs could be predictors of lesion interpretation (p<0.001, p=0.002 and p=0.035). Patients with benign IBLs experienced the most considerable decreases in PSA and ALP levels. CONCLUSIONS LNM, SUVmax, and location may contribute to IBL interpretation. A rapid decrease in PSA and ALP levels might suggest a better prognosis for patients with benign IBLs.
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Gao SH, Wang GZ, Wang LP, Feng L, Zhou YC, Yu XJ, Liang F, Yang FY, Wang Z, Sun BB, Wang D, Liang LJ, Xie DW, Zhao S, Feng HP, Li X, Li KK, Tang TS, Huang YC, Wang SQ, Zhou GB. Corrigendum to "Mutations and clinical significance of calcium voltage-gated channel subunit alpha 1E (CACNA1E) in non-small cell lung cancer" [Cell Calcium 102 (2022) 102527]. Cell Calcium 2024; 119:102866. [PMID: 38428281 DOI: 10.1016/j.ceca.2024.102866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
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Li S, Ding F, Flury M, Wang Z, Xu L, Li S, Jones DL, Wang J. Corrigendum to "Macro- and microplastic accumulation in soil after 32 years of plastic film mulching" [Environ. Pollut. 300, (2022), 118945]. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 348:123794. [PMID: 38521394 DOI: 10.1016/j.envpol.2024.123794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/25/2024]
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Wang Z, Bi H, Wang YD, Liu Q, Shao B, Li CQ, Fu C, Fu S, Shan GY, Chen A, Lv CC, Zeng Y. Tislelizumab, a novel PD-1 monoclonal antibody in urothelial cancer: A real-world study. Actas Urol Esp 2024; 48:295-303. [PMID: 38160794 DOI: 10.1016/j.acuroe.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 10/26/2023] [Accepted: 10/28/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVE Tislelizumab, a monoclonal antibody against programed death protein-1 (PD-1), has shown encouraging antitumor activity in urothelial cancer. This study was designed to assess the efficacy and safety of tislelizumab in urotelial cancer in a real-world setting. METHODS The study was a real-world retrospective study undertaken at Liaoning Cancer Hospital & Institute, China. Eligible patients were ≥18 years. Patients received 200-mg tislelizumab monotherapy intravenously every 3 weeks until the disease progressed to intolerable toxicity. Outcomes included an objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS) and safety. RESULTS Between March 2020 and December 2022, 33 patients were enrolled. The median follow-up was 10.17 (IQR 5.73-12.47) months. Of all 33 patients, ORR and DCR were 30.30% (95% CI 15.6%-48.7%) and 42.42% (95% CI 25.48%-60.78%), respectively. The median PFS was 5.73 (95% CI 3.27-13.00) months, with a 12-month PFS rate of 31.90% (95% CI 19.20%-53.00%). The median OS was 17.7 (95% CI 12.80-not reach) months, with a 12-month OS rate of 67.50% (95% CI 52.70%-86.40%). Eleven (33.33%) and 8 (24.24%) experienced ≥grade 3 treatment-related adverse events (TRAEs) and immune-related Aes, respectively. No treatment-related deaths occurred. CONCLUSION The excellent efficacy and controllable safety of tislelizumab in locally advanced or metastatic urothelial cancer suggest that it may be a promising therapeutic option for this population.
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Wu S, Duan WX, Yang X, Wei WZ, Ma QY, Wang Z, Wu Z. [Pancreaticoduodenectomy combined with longitudinal pancreaticojejunostomy in the treatment of chronic pancreatitis: initial experience in 11 cases]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:412-418. [PMID: 38548610 DOI: 10.3760/cma.j.cn112139-20231202-00251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
Objective: To investigate the surgical strategy for chronic pancreatitis complicated with suspected malignant lesions in the pancreatic head and pancreatolithiasis in the distal pancreas. Methods: This is a retrospective cohort study. Clinical data from 11 patients with chronic pancreatitis who underwent pancreaticoduodenectomy combined with longitudinal pancreaticojejunostomy(PD-L) were retrospectively collected(PD-L group) from the Department of Hepatobiliary Surgery of the First Affiliated Hospital of Xi'an Jiaotong University between December 2021 and September 2023. All patients were male with an age of (49.0±11.2) years(range:32 to 70 years). Their primary preoperative diagnoses included pancreatic lesions, chronic pancreatitis, pancreatolithiasis, and dilatation of the pancreatic duct. Data from 248 patients who underwent pancreaticoduodenectomy(PD) during the same period were retrospectively collected(PD group). There were 157 males and 91 females in the PD group, with an age of (61.5±10.8) years(range:27 to 82 years). Among them, 87 cases were diagnosed as pancreatic cancer or chronic pancreatitis. The propensity score matching method was used to reduce confounding bias between the two groups. The caliper value of 0.1 was used and the 1∶4 nearest neighbor matching method was used for the matching. Comparisons between the two groups were made using the independent sample t test, Mann-Whitney U test or χ2 test,respectively. Results: After complete excision of the specimen during pancreaticoduodenectomy, the key surgical step of PD-L was longitudinal pancreaticojejunostomy in the remaining pancreas. Intraoperative blood loss in the PD-L group was lower than that in the PD group [M(IQR)](300(200)ml vs. 500(500)ml, respectively; P<0.05). Similarly, hospitalization days(21.0(7.0)days vs. 25.0(8.5)days) and postoperative hospitalization days(13.0(8.0)days vs. 17.0(5.0) days) were also lower in the PD-L group compared to the PD group (P<0.05). There were no significant differences in the operation time and postoperative complication rate between the two groups(P>0.05). In the PD-L group, the postoperative follow-up time was 5(5)months(range: 3 to 21 months). One case was lost for follow-up. Abdominal pain was relieved in 10 patients. Additionally, abdominal distension and steatosis were alleviated in 8 cases. Furthermore, 5 cases of diabetes mellitus showed improved control of HbA1c and fasting blood glucose levels after surgery. Conclusions: PD-L treatment can be used to treat chronic pancreatitis complicated by suspected malignant lesions in the pancreatic head and pancreatolithiasis in the distal pancreas. PD-L also has advantages in removing stones from the pancreatic duct and evaporation of pancreatic fluid. However, due to the single-center design and the small sample size of this study, further practice and long-term follow-up are still necessary.
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Wang C, Wang Z, Fu L, Du J, Ji F, Qiu X. CircNRCAM up-regulates NRCAM to promote papillary thyroid carcinoma progression. J Endocrinol Invest 2024; 47:1215-1226. [PMID: 38485895 DOI: 10.1007/s40618-023-02241-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 11/04/2023] [Indexed: 04/23/2024]
Abstract
PURPOSE Papillary Thyroid Carcinoma (PTC) is the most prevalent subtype of Thyroid Carcinoma (THCA), a type of malignancy in the endocrine system. According to prior studies, Neural Cell Adhesion Molecule (NRCAM) has been found to be up-regulated in PTC and stimulates the proliferation and migration of PTC cells. However, the specific mechanism of NRCAM in PTC cells is not yet fully understood. Consequently, this study aimed to investigate the underlying mechanism of NRCAM in PTC cells, the findings of which could provide new insights for the development of potential treatment targets for PTC. METHODS AND RESULTS Bioinformatics tools were utilized and a series of experiments were conducted, including Western blot, colony formation, and dual-luciferase reporter assays. The data collected indicated that NRCAM was overexpressed in THCA tissues and PTC cells. Circular RNA NRCAM (circNRCAM) was found to be highly expressed in PTC cells and to positively regulate NRCAM expression. Through loss-of-function assays, both circNRCAM and NRCAM were shown to promote the proliferation, invasion, and migration of PTC cells. Mechanistically, this study confirmed that precursor microRNA-506 (pre-miR-506) could bind with m6A demethylase AlkB Homolog 5 (ALKBH5), leading to its m6A demethylation. It was also discovered that circNRCAM could competitively bind to ALKBH5, which restrained miR-506-3p expression and promoted NRCAM expression. CONCLUSION In summary, circNRCAM could up-regulate NRCAM by down-regulating miR-506-3p, thereby enhancing the biological behaviors of PTC cells.
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Wan L, Lv Y, Wang Z, Tian Y. The synergistic evolution of supply-demand composite system for airport green development: A case study in Guangzhou Baiyun International Airport, China. PLoS One 2024; 19:e0302303. [PMID: 38687729 PMCID: PMC11060580 DOI: 10.1371/journal.pone.0302303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 04/02/2024] [Indexed: 05/02/2024] Open
Abstract
Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development.
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Wang Z, Yang M, Li S, Chi H, Wang J, Xiao C. [A transcriptomic analysis of correlation between mitochondrial function and energy metabolism remodeling in mice with myocardial fibrosis following myocardial infarction]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024; 44:666-674. [PMID: 38708499 DOI: 10.12122/j.issn.1673-4254.2024.04.07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
OBJECTIVE To investigate the changes of mitochondrial respiratory function during myocardial fibrosis in mice with myocardial infarction (MI) and its correlation with the increase of glycolytic flux. METHODS Forty C57BL/6N mice were randomized into two equal groups to receive sham operation or ligation of the left anterior descending coronary artery to induce acute MI. At 28 days after the operation, 5 mice from each group were euthanized and left ventricular tissue samples were collected for transcriptomic sequencing. FPKM method was used to calculate gene expression levels to identify the differentially expressed genes (DEGs) in MI mice, which were analyzed using GO and KEGG databases to determine the pathways affecting the disease process. Heat maps were drawn to show the differential expressions of the pathways and the related genes in the enrichment analysis. In primary cultures of neonatal mouse cardiac fibroblasts (CFs), the changes in mitochondrial respiration and glycolysis levels in response to treatment with the pro-fibrotic agonist TGF-β1 were analyzed using Seahorse experiment. RESULTS The mouse models of MI showed significantly increased diastolic and systolic left ventricular diameter (P < 0.05) and decreased left ventricular ejection fraction (P < 0.0001). A total of 124 up-regulated and 106 down-regulated DEGs were identified in the myocardial tissues of MI mice, and GO and KEGG enrichment analysis showed that these DEGs were significantly enriched in fatty acid metabolism, organelles and other metabolic pathways and in the mitochondria. Heat maps revealed fatty acid beta oxidation, mitochondrial dysfunction and increased glycolysis levels in MI mice. In the primary culture of CFs, treatment with TGF-β1 significantly reduced the basal and maximum respiratory levels and increased the basal and maximum glycolysis levels (P < 0.0001). CONCLUSION During myocardial fibrosis, energy metabolism remodeling occurs in the CFs, manifested by lowered mitochondrial function and increased energy generation through glycolysis.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}. PHYSICAL REVIEW LETTERS 2024; 132:161901. [PMID: 38701481 DOI: 10.1103/physrevlett.132.161901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 03/13/2024] [Accepted: 03/22/2024] [Indexed: 05/05/2024]
Abstract
We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0 fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8) MeV/c^{2} and Γ=(110.5±15.0±2.9) MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7) MeV/c^{2} and Γ=(116.1±33.5±1.7) MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.
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Zhang Y, Xu S, Cui EN, Yu L, Wang Z. Research and Application Progress of Laser-Processing Technology in Diamond Micro-Fabrication. MICROMACHINES 2024; 15:547. [PMID: 38675358 PMCID: PMC11052283 DOI: 10.3390/mi15040547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 04/15/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024]
Abstract
Laser-processing technology has been widely used in the ultra-precision machining of diamond materials. It has the advantages of high precision and high efficiency, especially in the field of super-hard materials and high-precision parts manufacturing. This paper explains the fundamental principles of diamond laser processing, introduces the interaction mechanisms between various types of lasers and diamond materials, focuses on analyzing the current development status of various modes of laser processing of diamond, briefly discusses the relevant applications in diamond cutting, micro-hole forming, and micro-groove machining, etc., and finally discusses the issues, challenges, and potential future advancements of laser technology in the field of diamond processing at this point.
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Craven CK, Highfield L, Basit M, Bernstam EV, Choi BY, Ferrer RL, Gelfond JA, Pruitt SL, Kannan V, Shireman PK, Spratt H, Morales KJT, Wang CP, Wang Z, Zozus MN, Sankary EC, Schmidt S. Erratum: Toward standardization, harmonization, and integration of social determinants of health data: A Texas Clinical and Translational Science Award institutions collaboration - CORRIGENDUM. J Clin Transl Sci 2024; 8:e62. [PMID: 38655452 PMCID: PMC11036420 DOI: 10.1017/cts.2024.516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024] Open
Abstract
[This corrects the article DOI: 10.1017/cts.2024.2.].
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Liu YJ, Li R, Xiao D, Yang C, Li YL, Chen JL, Wang Z, Zhao XG, Shan ZG. Incorporating machine learning and PPI networks to identify mitochondrial fission-related immune markers in abdominal aortic aneurysms. Heliyon 2024; 10:e27989. [PMID: 38590878 PMCID: PMC10999885 DOI: 10.1016/j.heliyon.2024.e27989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 02/26/2024] [Accepted: 03/09/2024] [Indexed: 04/10/2024] Open
Abstract
Purpose The aim of this study is to investigate abdominal aortic aneurysm (AAA), a disease characterised by inflammation and progressive vasodilatation, for novel gene-targeted therapeutic loci. Methods To do this, we used weighted co-expression network analysis (WGCNA) and differential gene analysis on samples from the GEO database. Additionally, we carried out enrichment analysis and determined that the blue module was of interest. Additionally, we performed an investigation of immune infiltration and discovered genes linked to immune evasion and mitochondrial fission. In order to screen for feature genes, we used two PPI network gene selection methods and five machine learning methods. This allowed us to identify the most featrue genes (MFGs). The expression of the MFGs in various cell subgroups was then evaluated by analysis of single cell samples from AAA. Additionally, we looked at the expression levels of the MFGs as well as the levels of inflammatory immune-related markers in cellular and animal models of AAA. Finally, we predicted potential drugs that could be targeted for the treatment of AAA. Results Our research identified 1249 up-regulated differential genes and 3653 down-regulated differential genes. Through WGCNA, we also discovered 44 genes in the blue module. By taking the point where several strategies for gene selection overlap, the MFG (ITGAL and SELL) was produced. We discovered through single cell research that the MFG were specifically expressed in T regulatory cells, NK cells, B lineage, and lymphocytes. In both animal and cellular models of AAA, the MFGs' mRNA levels rose. Conclusion We searched for the AAA novel targeted gene (ITGAL and SELL), which most likely function through lymphocytes of the B lineage, NK cells, T regulatory cells, and B lineage. This analysis gave AAA a brand-new goal to treat or prevent the disease.
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Guo P, Wang Z, Shi J, Zheng H, Liu J, Hu L, Zhao P. Structural Characterization and Physiological Role of Bombyx mori Fibroinase in the Silk Gland Development. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024. [PMID: 38619539 DOI: 10.1021/acs.jafc.3c09405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Silkworm is a highly valuable insect that produces silk through secretion by a silk gland. Within this gland, a type of cathepsin L protease called Fibroinase was identified as an enzyme for hydrolyzing the primary components of silk, including fibroin and sericin. Here, we determined the crystal structure of Fibroinase fromBombyx mori at a resolution of 1.56 Å. Comparative structural analysis revealed that Fibroinase adopted a similar structural pattern with papain-type cathepsin, consisting of an N-terminal domain and a C-terminal domain. The interface between the domains forms a substrate-binding cleft, where the E64 inhibitor noncovalently binds in a novel manner. Additionally, computational simulations combined with biochemical analysis allowed us to define the binding mode and inhibition mechanism of physiological inhibitor Bombyx cysteine protease inhibitor (BCPI) with Fibroinase. Moreover, the expression profiles and RNA interference of Fibroinase indicated its critical role in removing silk proteins in the silk gland lumen and the destruction of silk gland tissue during the larval-pupal metamorphosis. These findings enhance our understanding of the structural and biochemical features of Fibroinase and its inhibitors, while also providing evidence for the physiological role of Fibroinase in silk gland development.
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Wang Z, Xue F, Sui X, Han W, Song W, Jiang J. Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study. Pulmonology 2024:S2531-0437(24)00040-0. [PMID: 38614860 DOI: 10.1016/j.pulmoe.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography. METHODS We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year). RESULTS In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules. CONCLUSIONS The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data. PHYSICAL REVIEW LETTERS 2024; 132:151903. [PMID: 38682963 DOI: 10.1103/physrevlett.132.151903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/03/2024] [Accepted: 03/11/2024] [Indexed: 05/01/2024]
Abstract
We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06}) MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07} MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14} MeV.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, In der Wiesche N, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kui X, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold. PHYSICAL REVIEW LETTERS 2024; 132:151901. [PMID: 38682972 DOI: 10.1103/physrevlett.132.151901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/16/2024] [Accepted: 02/23/2024] [Indexed: 05/01/2024]
Abstract
Using a sample of (10087±44)×10^{6} J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84 GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7 MeV/c^{2} and 30.7±5.5±2.4 MeV, respectively, which indicates the existence of a pp[over ¯] bound state.
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He Z, Li Z, Chen Z, Wang Z, Shen J, Wang S, Song C, Zhao T, Cai J, Lin SZ, Zhang Y, Shen B. Experimental observation of current-driven antiskyrmion sliding in stripe domains. NATURE MATERIALS 2024:10.1038/s41563-024-01870-8. [PMID: 38605194 DOI: 10.1038/s41563-024-01870-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 03/18/2024] [Indexed: 04/13/2024]
Abstract
Magnetic skyrmions are promising as next-generation information units. Their antiparticle-the antiskyrmion-has also been discovered in chiral magnets. Here we experimentally demonstrate antiskyrmion sliding in response to a pulsed electric current at room temperature without the requirement of an external magnetic field. This is realized by embedding antiskyrmions in helical stripe domains, which naturally provide one-dimensional straight tracks along which antiskyrmion sliding can be easily launched with low current density and without transverse deflection from the antiskyrmion Hall effect. The higher mobility of the antiskyrmions in the background of helical stripes in contrast to the typical ferromagnetic state is a result of intrinsic material parameters and elastic energy of the stripe domain, thereby smearing out the random pinning potential, as supported by micromagnetic simulations. The demonstration and comprehensive understanding of antiskyrmion movement along naturally straight tracks offers a new perspective for (anti)skyrmion application in spintronics.
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Wang Z, Li YP, Huang GH, Gong JW, Li YF, Zhang Q. A factorial-analysis-based Bayesian neural network method for quantifying China's CO 2 emissions under dual-carbon target. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170698. [PMID: 38342455 DOI: 10.1016/j.scitotenv.2024.170698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/10/2024] [Accepted: 02/02/2024] [Indexed: 02/13/2024]
Abstract
Energy-structure transformation and CO2-emission reduction are becoming particularly urgent for China and many other countries. Development of effective methods that are capable of quantifying and predicting CO2 emissions to achieve carbon neutrality is desired. This study advances a factorial-analysis-based Bayesian neural network (abbreviated as FABNN) method to reflect the complex relationship between inputs and outputs as well as reveal the individual and interactive effects of multiple factors affecting CO2 emissions. FABNN is then applied to analyzing CO2 emissions of China (abbreviated as CEC), where multiple factors involve in energy (e.g., the consumption of natural gas, CONG), economic (e.g., Gross domestic product, GDP) and social (e.g., the rate of urbanization, ROU) aspects are investigated and 512 scenarios are designed to achieve the national dual carbon targets (i.e., carbon peak before 2030 and carbon neutrality by 2060). Comparing to the conventional machine learning methods, FABNN performs better in calibration and validation results, indicating that FABNN is suitable for CEC simulation and prediction. Results disclose that the top three factors affecting CEC under the dual‑carbon target are GDP, CONG, and ROU; energy, economic and social contributions are 43.5 %, 34.6 % and 21.9 %, respectively. CEC reaches its carbon peak during 2027-2032 and achieve carbon neutrality during 2053-2057 under all scenarios. Under the optimal scenario (S195), the CO2-emission reduction potential is about 772.2 million tonnes and the consumptions of coal, petroleum and natural gas can be respectively reduced by 3.1 %, 9.9 % and 23.0 % compared to the worst scenario (S466). The results can provide solid support for national energy-structure transformation and CO2-emission reduction to achieve carbon-peak and carbon-neutrality targets.
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Del Mauro G, Wang Z. Cross-subject brain entropy mapping. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588307. [PMID: 38645267 PMCID: PMC11030347 DOI: 10.1101/2024.04.05.588307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
We present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data. While we only showed the cross-subject brain entropy (BEN) mapping results in this manuscript, the same concept can be directly extended to map the cross-sessional BEN and the cross-regional cross-subject or subject-session BEN.
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