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Wang TH, Hao R, Xu BN, Chang L, Liu ZB, Yao JL, Wang W, Xie WJ, Yan WW, Xiao ZJ, Qiu LG, An G. [Safety and feasibility of 120 min rapid infusion regimen of daratumumab in patients with multiple myeloma]. ZHONGHUA XUE YE XUE ZA ZHI = ZHONGHUA XUEYEXUE ZAZHI 2023; 44:696-699. [PMID: 37803849 PMCID: PMC10520231 DOI: 10.3760/cma.j.issn.0253-2727.2023.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Indexed: 10/08/2023]
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Zheng HS, Zhu WJ, Liu CH, Li YX, Song X, Han TT, Wang W, Guan K, Sha L. [Clinical characteristics of children with IgE-mediated cow's milk protein allergy]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2023; 57:1271-1279. [PMID: 37574323 DOI: 10.3760/cma.j.cn112150-20230514-00370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Objective: To analyze the clinical characteristics of children with IgE-mediated cow's milk protein allergy (CMPA) and provide a basis for disease management and prevention. Methods: A cross-sectional study was conducted to analyze 142 children aged 0-12 years who were diagnosed with IgE-mediated CMPA in Capital Institute of Pediatrics Affiliated Children's Hospital from 2020 to 2022. There were 79 males (55.6%) and 63 females (44.4%), with an average age of 14 (8, 27) months. 61 cases (43.0%) were in the <1-year-old group, 54 cases (38.0%) in the 1-3-year-old group, and 27 cases (19.0%) in the >3-year-old group. Data on demographic data, clinical manifestations, mean wheel diameter of skin prick test and serum specific IgE level were collected. The serum cow's milk protein sIgE and component sIgE were measured by ImmunoCAP fully automated system of fluorescence enzyme-linked immunosorbent assay, and statistically analyzed using chi-square test, nonparametric tests, correlation. Results: Cutaneous symptoms were the first and most frequent in 142 children (97.9%, 139/142 cases), followed by digestive (29.6%, 42/142 cases) and respiratory symptoms (27.5%, 39/142 cases).The proportion of children with respiratory symptoms after consuming cow's milk was significantly higher in the>3 years age group than those in the infant and toddler groups(66.7% vs 19.7%,χ2=18.396,P<0.01;66.7% vs 16.7%,χ2=20.250,P<0.01), and the symptoms involving ≥3 systems were also significantly higher than those in the other two groups(37.0% vs 13.1%,χ2=6.597,P<0.05;37.0% vs 7.4%,χ2=12.120,P<0.01). The average cow's milk SPT diameter and serum sIgE levels in the>3 years age group were significantly higher than those in the infant and toddler groups (Z=-4.682, P<0.01; Z=-3.498, P<0.01); (Z=-4.463, P<0.01; Z=-6.463, P<0.01). The most common cow's milk component protein were β-lactoglobulin(65.1%,56/86 cases) and casein (57.0%, 49/86 cases). Multiple-sensitization rate of the patients were 54.9%. Egg white (43.7%, 62/142 cases) was the most common co-sensitization food allergen while mold (12.7%, 18/142 cases) and weed pollen (12.7%, 18/142 cases) were the main co-sensitization aeroallergens. The proportion of multiple-sensitization to aeroallergens in the children group was the highest (51.9%, 14/27 cases), followed by the toddler group (29.6%, 16/54 cases), and the infant group was the least (3.3%, 2/61 cases). There was a significant difference among these three groups (χ2=7.476, P<0.05). Conclusion: Skin and mucosal symptoms are the most common in CMPA patients. The proportion of respiratory symptoms and multisystem involvement increased with age as well as the wheal diameter in skin test and serum sIgE level elevated. CMPA patients older than 3 years had the highest proportion of aeroallergen sensitization and airway allergic diseases.
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Xiao L, Yang JP, Wang W. [Application of TIGIT combined with interleukin-6 detection in the evaluation of Crohn's disease status]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2023; 57:1253-1258. [PMID: 37574320 DOI: 10.3760/cma.j.cn112150-20230319-00202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
To explore the application of IL-6, PCT, T lymphocyte subsets and TIGIT expression on T lymphocytes in the evaluation of Crohn's disease status. Using a cross-sectional study, total of 119 confirmed patients with Crohn's disease who were treated in the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine from June 2020 to December 2022 were selected. The age range was 18-59 years old, and the median age (interquartile range) was 37 (29, 45) years old, including 57 cases in active disease group (30 males, 27 females), 62 cases in disease remission group (33 males, 29 females); 50 healthy control groups (27 males, 23 females), the age range was 19-60 years old, and the median age (interquartile range) was 38 (31, 46) years old. The level of IL-6 was detected by flow fluorescence microsphere method, the concentration of PCT was detected by immunochromatography, and the levels of T lymphocyte subsets and TIGIT were detected by flow cytometry. The differences and correlations between the detection indicators in each group were compared, logistic regression was used to analyze the factors influencing the progression of Crosne's disease and the clinical value of each detection indicator was analyzed by ROC curve. The results showed that there were no statistically significant differences in age and gender among the control group, the remission group, and the active group (H=1.422,χ2=0.020;P=0.491, P=0.990); in the active group, IL-6 was 17.55(9.67, 21.72)pg/ml, PCT was 0.38(0.14, 0.43)ng/ml, CD3+CD4+ was 35.47%±6.01%, CD3+CD8+ was 30.50%±5.20%, TIGIT was 25.08%±6.30%; in the remission group, IL-6 was 8.46(5.21, 10.04) pg/ml, PCT was 0.26(0.11, 0.35) ng/ml, CD3+CD4+ was 37.62%±4.86%, CD3+CD8+ was 28.30%±5.28%, TIGIT was 34.22%±5.45%; in the control group, IL-6 was 6.13(3.57, 8.12)pg/ml, PCT was 0.17(0.10, 0.21)ng/m, CD3+CD4+ was 39.74%±3.94%, CD3+CD8+ was 26.59%±4.50%, and TIGIT was 37.64%±6.22%.There were significant differences in IL-6, PCT, CD3+CD4+%, CD3+CD8+%, and TIGIT among the three groups(H=58.688, H=18.003, F=9.600, F=8.124, F=65.059;P<0.001, P<0.001, P<0.001, P<0.001, P<0.001), Among them, IL-6 and TIGIT in the active group were significantly different from those in the remission group (P<0.001, P<0.001), and only TIGIT was significantly different between the remission group and the control group (P=0.007);Spearman correlation analysis showed that the expression of TIGIT on T lymphocytes was negatively correlated with the levels of IL-6; the results of Logistic regression analysis showed that IL-6, PCT and TIGIT were independent factors affecting the progression of Crohn's disease;Comparing the ROC curves of the active group and the remission group, found that TIGIT was significantly different from PCT, CD3+CD4+, CD3+CD8+(Z=4.011, Z=4.091, Z=4.157; P<0.001, P<0.001, P<0.001), no statistical difference with IL-6 (Z=1.193, P=0.233). Selected the combined detection of IL-6 and TIGIT with the best AUC area and Youden index, which shows that the clinical value is improved, the AUC area of IL-6+TIGIT was significantly different from that of IL-6 (Z=2.674, P=0.008). In summary, TIGIT of T lymphocytes and IL-6 detection may be valuable in the diagnosis and treatment of Crohn's disease, and the combined detection of TIGIT and IL-6 may be meaningful for evaluating the status of Crohn's disease.
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Deng W, He M, Wang W, Xue H. Gastrointestinal: Pancreatic NETs with GCGR heterozygous mutation: Mahvash disease. J Gastroenterol Hepatol 2023; 38:1243. [PMID: 36698259 DOI: 10.1111/jgh.16104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 11/25/2022] [Accepted: 01/01/2023] [Indexed: 01/27/2023]
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Missirlian M, Firdaouss M, Richou M, Hernandez C, Gargiulo L, Bucalossi J, Brun C, Corre Y, Delmas E, Greuner H, Guillermin B, Gunn J, Hatchressian J, Jalageas R, Li Q, Lipa M, Lozano M, Luo G, Pocheau C, Roche H, Tsitrone E, Vignal N, Wang W, Saille A, Zago B. Manufacturing, testing and installation of the full tungsten actively cooled ITER-like divertor in the WEST tokamak. FUSION ENGINEERING AND DESIGN 2023. [DOI: 10.1016/j.fusengdes.2023.113683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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Aalbers J, Akerib DS, Akerlof CW, Al Musalhi AK, Alder F, Alqahtani A, Alsum SK, Amarasinghe CS, Ames A, Anderson TJ, Angelides N, Araújo HM, Armstrong JE, Arthurs M, Azadi S, Bailey AJ, Baker A, Balajthy J, Balashov S, Bang J, Bargemann JW, Barry MJ, Barthel J, Bauer D, Baxter A, Beattie K, Belle J, Beltrame P, Bensinger J, Benson T, Bernard EP, Bhatti A, Biekert A, Biesiadzinski TP, Birch HJ, Birrittella B, Blockinger GM, Boast KE, Boxer B, Bramante R, Brew CAJ, Brás P, Buckley JH, Bugaev VV, Burdin S, Busenitz JK, Buuck M, Cabrita R, Carels C, Carlsmith DL, Carlson B, Carmona-Benitez MC, Cascella M, Chan C, Chawla A, Chen H, Cherwinka JJ, Chott NI, Cole A, Coleman J, Converse MV, Cottle A, Cox G, Craddock WW, Creaner O, Curran D, Currie A, Cutter JE, Dahl CE, David A, Davis J, Davison TJR, Delgaudio J, Dey S, de Viveiros L, Dobi A, Dobson JEY, Druszkiewicz E, Dushkin A, Edberg TK, Edwards WR, Elnimr MM, Emmet WT, Eriksen SR, Faham CH, Fan A, Fayer S, Fearon NM, Fiorucci S, Flaecher H, Ford P, Francis VB, Fraser ED, Fruth T, Gaitskell RJ, Gantos NJ, Garcia D, Geffre A, Gehman VM, Genovesi J, Ghag C, Gibbons R, Gibson E, Gilchriese MGD, Gokhale S, Gomber B, Green J, Greenall A, Greenwood S, van der Grinten MGD, Gwilliam CB, Hall CR, Hans S, Hanzel K, Harrison A, Hartigan-O'Connor E, Haselschwardt SJ, Hernandez MA, Hertel SA, Heuermann G, Hjemfelt C, Hoff MD, Holtom E, Hor JYK, Horn M, Huang DQ, Hunt D, Ignarra CM, Jacobsen RG, Jahangir O, James RS, Jeffery SN, Ji W, Johnson J, Kaboth AC, Kamaha AC, Kamdin K, Kasey V, Kazkaz K, Keefner J, Khaitan D, Khaleeq M, Khazov A, Khurana I, Kim YD, Kocher CD, Kodroff D, Korley L, Korolkova EV, Kras J, Kraus H, Kravitz S, Krebs HJ, Kreczko L, Krikler B, Kudryavtsev VA, Kyre S, Landerud B, Leason EA, Lee C, Lee J, Leonard DS, Leonard R, Lesko KT, Levy C, Li J, Liao FT, Liao J, Lin J, Lindote A, Linehan R, Lippincott WH, Liu R, Liu X, Liu Y, Loniewski C, Lopes MI, Lopez Asamar E, López Paredes B, Lorenzon W, Lucero D, Luitz S, Lyle JM, Majewski PA, Makkinje J, Malling DC, Manalaysay A, Manenti L, Mannino RL, Marangou N, Marzioni MF, Maupin C, McCarthy ME, McConnell CT, McKinsey DN, McLaughlin J, Meng Y, Migneault J, Miller EH, Mizrachi E, Mock JA, Monte A, Monzani ME, Morad JA, Morales Mendoza JD, Morrison E, Mount BJ, Murdy M, Murphy ASJ, Naim D, Naylor A, Nedlik C, Nehrkorn C, Neves F, Nguyen A, Nikoleyczik JA, Nilima A, O'Dell J, O'Neill FG, O'Sullivan K, Olcina I, Olevitch MA, Oliver-Mallory KC, Orpwood J, Pagenkopf D, Pal S, Palladino KJ, Palmer J, Pangilinan M, Parveen N, Patton SJ, Pease EK, Penning B, Pereira C, Pereira G, Perry E, Pershing T, Peterson IB, Piepke A, Podczerwinski J, Porzio D, Powell S, Preece RM, Pushkin K, Qie Y, Ratcliff BN, Reichenbacher J, Reichhart L, Rhyne CA, Richards A, Riffard Q, Rischbieter GRC, Rodrigues JP, Rodriguez A, Rose HJ, Rosero R, Rossiter P, Rushton T, Rutherford G, Rynders D, Saba JS, Santone D, Sazzad ABMR, Schnee RW, Scovell PR, Seymour D, Shaw S, Shutt T, Silk JJ, Silva C, Sinev G, Skarpaas K, Skulski W, Smith R, Solmaz M, Solovov VN, Sorensen P, Soria J, Stancu I, Stark MR, Stevens A, Stiegler TM, Stifter K, Studley R, Suerfu B, Sumner TJ, Sutcliffe P, Swanson N, Szydagis M, Tan M, Taylor DJ, Taylor R, Taylor WC, Temples DJ, Tennyson BP, Terman PA, Thomas KJ, Tiedt DR, Timalsina M, To WH, Tomás A, Tong Z, Tovey DR, Tranter J, Trask M, Tripathi M, Tronstad DR, Tull CE, Turner W, Tvrznikova L, Utku U, Va'vra J, Vacheret A, Vaitkus AC, Verbus JR, Voirin E, Waldron WL, Wang A, Wang B, Wang JJ, Wang W, Wang Y, Watson JR, Webb RC, White A, White DT, White JT, White RG, Whitis TJ, Williams M, Wisniewski WJ, Witherell MS, Wolfs FLH, Wolfs JD, Woodford S, Woodward D, Worm SD, Wright CJ, Xia Q, Xiang X, Xiao Q, Xu J, Yeh M, Yin J, Young I, Zarzhitsky P, Zuckerman A, Zweig EA. First Dark Matter Search Results from the LUX-ZEPLIN (LZ) Experiment. PHYSICAL REVIEW LETTERS 2023; 131:041002. [PMID: 37566836 DOI: 10.1103/physrevlett.131.041002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 03/06/2023] [Accepted: 06/07/2023] [Indexed: 08/13/2023]
Abstract
The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search for weakly interacting massive particles (WIMPs) with an exposure of 60 live days using a fiducial mass of 5.5 t. A profile-likelihood ratio analysis shows the data to be consistent with a background-only hypothesis, setting new limits on spin-independent WIMP-nucleon, spin-dependent WIMP-neutron, and spin-dependent WIMP-proton cross sections for WIMP masses above 9 GeV/c^{2}. The most stringent limit is set for spin-independent scattering at 36 GeV/c^{2}, rejecting cross sections above 9.2×10^{-48} cm at the 90% confidence level.
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Wang J, Xu H, Chu XX, Wang W. [The efficacy and safety of bortezomib, pomalidomide and dexamethasone regimen in the treatment of relapsed/refractory multiple myeloma]. ZHONGHUA XUE YE XUE ZA ZHI = ZHONGHUA XUEYEXUE ZAZHI 2023; 44:602-605. [PMID: 37749045 PMCID: PMC10509612 DOI: 10.3760/cma.j.issn.0253-2727.2023.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Indexed: 09/27/2023]
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Shen CY, Li GR, Wei D, Wang W, Yang XS, Jiang C, Sheng YT, Yang ZK, Nie XW, Chen JY. [Expression and protective effect of chemerin in idiopathic pulmonary fibrosis]. ZHONGHUA JIE HE HE HU XI ZA ZHI = ZHONGHUA JIEHE HE HUXI ZAZHI = CHINESE JOURNAL OF TUBERCULOSIS AND RESPIRATORY DISEASES 2023; 46:688-696. [PMID: 37402659 DOI: 10.3760/cma.j.cn112147-20221119-00910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/06/2023]
Abstract
Objective: To explore the expression and the role of chemerin in idiopathic pulmonary fibrosis (IPF). Methods: Quantitative PCR and Western blotting were used to determine the mRNA and protein levels of chemerin in lung tissues from IPF patients and the controls. Clinical serum level of chemerin was analyzed by enzyme-linked immunosorbent assay. The mouse lung fibroblasts isolated and cultured in vitro were divided into the control, TGF-β, TGF-β+chemerin and chemerin groups. Immunofluorescence staining was used to observe the expression of α-smooth muscle actin (α-SMA). C57BL/6 mice were randomly divided into the control, bleomycin, bleomycin+chemerin, and chemerin groups. Masson and immunohistochemical staining were performed to evaluate the severity of pulmonary fibrosis. Expression of epithelial to mesenchymal transition (EMT) markers was detected by quantitative PCR and immunohistochemical staining in the in vitro and in vivo models of pulmonary fibrosis, respectively. Results: Compared with the control group, the expression of chemerin was downregulated in both the lung tissue and the serum of IPF patients. Immunofluorescence showed that treatment of fibroblasts with TGF-β alone resulted in a robust expression of α-SMA, whereas treatment with TGF-β and chemerin together exhibited the similar expression levels of α-SMA as the control group. Masson staining indicated that the bleomycin-induced pulmonary fibrosis model was constructed successfully, while treatment of chemerin partially alleviated the damage of lung tissue. Immunohistochemical staining showed that the expression of chemerin in the lung tissue was significantly decreased in the bleomycin group. Quantitative PCR and immunohistochemistry showed that chemerin attenuated EMT induced by TGF-β and bleomycin both in vitro and in vivo. Conclusions: The expression of chemerin was reduced in patients with IPF. Chemerin may play a protective role in the development of IPF by regulating EMT, providing a new idea for the clinical treatment of IPF.
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Li P, Wu Y, Xie Y, Chen F, Chen SS, Li YH, Lu QQ, Li J, Li YW, Pei DX, Chen YJ, Chen H, Li Y, Wang W, Wang H, Yu HT, Ba Z, Cheng D, Ning LP, Luo CL, Qin XS, Zhang J, Wu N, Xie HJ, Pan JH, Shui J, Wang J, Yang JP, Liu XH, Xu FX, Yang L, Hu LY, Zhang Q, Li B, Liu QL, Zhang M, Shen SJ, Jiang MM, Wu Y, Hu JW, Liu SQ, Gu DY, Xie XB. [HbA1c comparison and diagnostic efficacy analysis of multi center different glycosylated hemoglobin detection systems]. ZHONGHUA YU FANG YI XUE ZA ZHI [CHINESE JOURNAL OF PREVENTIVE MEDICINE] 2023; 57:1047-1058. [PMID: 37482740 DOI: 10.3760/cma.j.cn112150-20221221-01220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: Compare and analyze the results of the domestic Lanyi AH600 glycated hemoglobin analyzer and other different detection systems to understand the comparability of the detection results of different detectors, and establish the best cut point of Lanyi AH600 determination of haemoglobin A1c (HbA1c) in the diagnosis of diabetes. Methods: Multi center cohort study was adopted. The clinical laboratory departments of 18 medical institutions independently collected test samples from their respective hospitals from March to April 2022, and independently completed comparative analysis of the evaluated instrument (Lanyi AH600) and the reference instrument HbA1c. The reference instruments include four different brands of glycosylated hemoglobin meters, including Arkray, Bio-Rad, DOSOH, and Huizhong. Scatter plot was used to calculate the correlation between the results of different detection systems, and the regression equation was calculated. The consistency analysis between the results of different detection systems was evaluated by Bland Altman method. Consistency judgment principles: (1) When the 95% limits of agreement (95% LoA) of the measurement difference was within 0.4% HbA1c and the measurement score was≥80 points, the comparison consistency was good; (2) When the measurement difference of 95% LoA exceeded 0.4% HbA1c, and the measurement score was≥80 points, the comparison consistency was relatively good; (3) The measurement score was less than 80 points, the comparison consistency was poor. The difference between the results of different detection systems was tested by paired sample T test or Wilcoxon paired sign rank sum test; The best cut-off point of diabetes was analyzed by receiver operating characteristic curve (ROC). Results: The correlation coefficient R2 of results between Lanyi AH600 and the reference instrument in 16 hospitals is≥0.99; The Bland Altman consistency analysis showed that the difference of 95% LoA in Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180) was -0.486%-0.325%, and the measurement score was 94.6 points (473/500); The difference of 95% LoA in the Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant II) was -0.727%-0.612%, and the measurement score was 89.8 points; The difference of 95% LoA in the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT) was -0.231%-0.461%, and the measurement score was 96.6 points; The difference of 95% LoA in the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT) was -0.469%-0.479%, and the measurement score was 91.9 points. The other 14 hospitals, Lanyi AH600, were compared with 4 reference instrument brands, the difference of 95% LoA was less than 0.4% HbA1c, and the scores were all greater than 95 points. The results of paired sample T test or Wilcoxon paired sign rank sum test showed that there was no statistically significant difference between Lanyi AH600 and the reference instrument Arkray HA8180 (Z=1.665,P=0.096), with no statistical difference. The mean difference between the measured values of the two instruments was 0.004%. The comparison data of Lanyi AH600 and the reference instrument of all other institutions had significant differences (all P<0.001), however, it was necessary to consider whether it was within the clinical acceptable range in combination with the results of the Bland-Altman consistency analysis. The ROC curve of HbA1c detected by Lanyi AH600 in 985 patients with diabetes and 3 423 patients with non-diabetes was analyzed, the area under curve (AUC) was 0.877, the standard error was 0.007, and the 95% confidence interval 95%CI was (0.864, 0.891), which was statistically significant (P<0.001). The maximum value of Youden index was 0.634, and the corresponding HbA1c cut point was 6.235%. The sensitivity and specificity of diabetes diagnosis were 76.2% and 87.2%, respectively. Conclusion: Among the hospitals and instruments currently included in this study, among these four hospitals included Nanjing Maternity and Child Health Care Hospital in Jiangsu Province (reference instrument: Arkray HA8180), Tibetan Traditional Medical Hospital of TAR (reference instrument: Bio-Rad Variant Ⅱ), the People's Hospital of Chongqing Liang Jiang New Area (reference instrument: Huizhong MQ-2000PT), and the Taihe Hospital of traditional Chinese Medicine in Anhui Province (reference instrument: Huizhong MQ-2000PT), the comparison between Lanyi AH600 and the reference instruments showed relatively good consistency, while the other 14 hospitals involved four different brands of reference instruments: Arkray, Bio-Rad, DOSOH, and Huizhong, Lanyi AH600 had good consistency with its comparison. The best cut point of the domestic Lanyi AH600 for detecting HbA1c in the diagnosis of diabetes is 6.235%.
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Abbasi R, Ackermann M, Adams J, Aguilar JA, Ahlers M, Ahrens M, Alameddine JM, Alves AA, Amin NM, Andeen K, Anderson T, Anton G, Argüelles C, Ashida Y, Athanasiadou S, Axani S, Bai X, Balagopal V A, Barwick SW, Basu V, Baur S, Bay R, Beatty JJ, Becker KH, Tjus JB, Beise J, Bellenghi C, Benda S, BenZvi S, Berley D, Bernardini E, Besson DZ, Binder G, Bindig D, Blaufuss E, Blot S, Boddenberg M, Bontempo F, Book JY, Borowka J, Böser S, Botner O, Böttcher J, Bourbeau E, Bradascio F, Braun J, Brinson B, Bron S, Brostean-Kaiser J, Burley RT, Busse RS, Campana MA, Carnie-Bronca EG, Chen C, Chen Z, Chirkin D, Choi K, Clark BA, Clark K, Classen L, Coleman A, Collin GH, Connolly A, Conrad JM, Coppin P, Correa P, Cowen DF, Cross R, Dappen C, Dave P, De Clercq C, DeLaunay JJ, López DD, Dembinski H, Deoskar K, Desai A, Desiati P, de Vries KD, de Wasseige G, DeYoung T, Diaz A, Díaz-Vélez JC, Dittmer M, Dujmovic H, Dunkman M, DuVernois MA, Ehrhardt T, Eller P, Engel R, Erpenbeck H, Evans J, Evenson PA, Fan KL, Fazely AR, Fedynitch A, Feigl N, Fiedlschuster S, Fienberg AT, Finley C, Fischer L, Fox D, Franckowiak A, Friedman E, Fritz A, Fürst P, Gaisser TK, Gallagher J, Ganster E, Garcia A, Garrappa S, Gerhardt L, Ghadimi A, Glaser C, Glauch T, Glüsenkamp T, Goehlke N, Goldschmidt A, Gonzalez JG, Goswami S, Grant D, Grégoire T, Griswold S, Günther C, Gutjahr P, Haack C, Hallgren A, Halliday R, Halve L, Halzen F, Minh MH, Hanson K, Hardin J, Harnisch AA, Haungs A, Helbing K, Henningsen F, Hettinger EC, Hickford S, Hignight J, Hill C, Hill GC, Hoffman KD, Hoshina K, Hou W, Huang F, Huber M, Huber T, Hultqvist K, Hünnefeld M, Hussain R, Hymon K, In S, Iovine N, Ishihara A, Jansson M, Japaridze GS, Jeong M, Jin M, Jones BJP, Kang D, Kang W, Kang X, Kappes A, Kappesser D, Kardum L, Karg T, Karl M, Karle A, Katz U, Kauer M, Kellermann M, Kelley JL, Kheirandish A, Kin K, Kiryluk J, Klein SR, Kochocki A, Koirala R, Kolanoski H, Kontrimas T, Köpke L, Kopper C, Kopper S, Koskinen DJ, Koundal P, Kovacevich M, Kowalski M, Kozynets T, Krupczak E, Kun E, Kurahashi N, Lad N, Gualda CL, Lanfranchi JL, Larson MJ, Lauber F, Lazar JP, Lee JW, Leonard K, Leszczyńska A, Li Y, Lincetto M, Liu QR, Liubarska M, Lohfink E, Mariscal CJL, Lu L, Lucarelli F, Ludwig A, Luszczak W, Lyu Y, Ma WY, Madsen J, Mahn KBM, Makino Y, Mancina S, Mariş IC, Martinez-Soler I, Maruyama R, McHale S, McElroy T, McNally F, Mead JV, Meagher K, Mechbal S, Medina A, Meier M, Meighen-Berger S, Merckx Y, Micallef J, Mockler D, Montaruli T, Moore RW, Morik K, Morse R, Moulai M, Mukherjee T, Naab R, Nagai R, Nahnhauer R, Naumann U, Necker J, Nguyen LV, Niederhausen H, Nisa MU, Nowicki SC, Nygren D, Pollmann AO, Oehler M, Oeyen B, Olivas A, O'Sullivan E, Pandya H, Pankova DV, Park N, Parker GK, Paudel EN, Paul L, de Los Heros CP, Peters L, Peterson J, Philippen S, Pieper S, Pizzuto A, Plum M, Popovych Y, Porcelli A, Rodriguez MP, Pries B, Przybylski GT, Raab C, Rack-Helleis J, Raissi A, Rameez M, Rawlins K, Rea IC, Rechav Z, Rehman A, Reichherzer P, Reimann R, Renzi G, Resconi E, Reusch S, Rhode W, Richman M, Riedel B, Roberts EJ, Robertson S, Roellinghoff G, Rongen M, Rott C, Ruhe T, Ryckbosch D, Cantu DR, Safa I, Saffer J, Salazar-Gallegos D, Sampathkumar P, Herrera SES, Sandrock A, Santander M, Sarkar S, Sarkar S, Satalecka K, Schaufel M, Schieler H, Schindler S, Schmidt T, Schneider A, Schneider J, Schröder FG, Schumacher L, Schwefer G, Sclafani S, Seckel D, Seunarine S, Sharma A, Shefali S, Shimizu N, Silva M, Skrzypek B, Smithers B, Snihur R, Soedingrekso J, Sogaard A, Soldin D, Spannfellner C, Spiczak GM, Spiering C, Stamatikos M, Stanev T, Stein R, Stettner J, Stezelberger T, Stokstad B, Stürwald T, Stuttard T, Sullivan GW, Taboada I, Ter-Antonyan S, Thwaites J, Tilav S, Tischbein F, Tollefson K, Tönnis C, Toscano S, Tosi D, Trettin A, Tselengidou M, Tung CF, Turcati A, Turcotte R, Turley CF, Twagirayezu JP, Ty B, Elorrieta MAU, Valtonen-Mattila N, Vandenbroucke J, van Eijndhoven N, Vannerom D, van Santen J, Veitch-Michaelis J, Verpoest S, Walck C, Wang W, Watson TB, Weaver C, Weigel P, Weindl A, Weiss MJ, Weldert J, Wendt C, Werthebach J, Weyrauch M, Whitehorn N, Wiebusch CH, Willey N, Williams DR, Wolf M, Wrede G, Wulff J, Xu XW, Yanez JP, Yildizci E, Yoshida S, Yu S, Yuan T, Zhang Z, Zhelnin P. Observation of high-energy neutrinos from the Galactic plane. Science 2023; 380:1338-1343. [PMID: 37384687 DOI: 10.1126/science.adc9818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 05/04/2023] [Indexed: 07/01/2023]
Abstract
The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.
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Yang Q, Jia W, Wang X, Cai Q, Ge X, Wang W, Han X. [Single-cell RNA sequencing deciphers transcriptional profiles of hepatocytes in mouse with hepatic alveolar echinococcosis]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2023; 35:236-243. [PMID: 37455093 DOI: 10.16250/j.32.1374.2022275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
OBJECTIVE To investigate the cell composition and the transcriptional characteristics in microenvironments of hepatic tissues in mice at late stage of Echinococcus multilocularis infection at a single-cell level. METHODS Peri-lesion and paired distal hepatic specimens were collected from two BALB/c mice (6 to 8 weeks old) infected with E. multilocularis for single-cell RNA sequencing. The Seurat package in the R software was employed for quality control of data, multi-sample integration and correction of batch effects, and uniform manifold approximation and projection (UMAP) algorithm was used for cell clustering. Cell types were annotated using classical marker genes. Differentially expressed genes were screened in each cell type through differential gene expression analysis, and the biological roles of cells were predicted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. RESULTS A total of 43 710 cells from peri-lesion and distal hepatic tissues of E. multilocularis-infected mice were analyzed, and were classified into 11 cell types, including neutrophils, T cells, macrophages, granulocyte-monocyte progenitor cells, B cells, plasma cells, basophils, hepatic stellate cells, endothelial cells, hepatocytes, and platelets. T cells were the largest population of immune cells in the microenvironment of hepatic tissues, including five CD4+ T cell subsets, two CD8+ T cell subsets and phosphoantigen-reactive γδT cells. The proportions of CD4+ helper T cells and cytotoxic CD4+ T cells decreased and the proportion of T helper 2 (Th2) cells increased in peri-lesion tissues relative to distal hepatic tissues. In addition, the differentially expressed genes in Th2 cells were associated with negative regulation of the immune system, and the highly expressed genes in cytotoxic CD4+ T cells correlated with activation of the immune system. CONCLUSIONS Single-cell RNA sequencing deciphers the cell composition and distribution in microenvironments of hepatic tissues from mice infected with E. multilocularis, and the increased proportion of Th2 cells in peri-lesion hepatic tissues may be associated with formation of immunosuppressive microenvironments.
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Zhang Y, Cao Y, Yang K, Wang W, Yang M, Chai L, Gu J, Li M, Lu Y, Zhou H, Zhu G, Cao J, Lu G. [Risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on the machine learning]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2023; 35:225-235. [PMID: 37455092 DOI: 10.16250/j.32.1374.2022290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
OBJECTIVE To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province. METHODS Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency. RESULTS A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%). CONCLUSIONS Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.
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Wang W, Zhang YL, Huang L, Kang L. [Application of triangle stability mechanical model in the layer separation of transanal total mesorectal excision]. ZHONGHUA WEI CHANG WAI KE ZA ZHI = CHINESE JOURNAL OF GASTROINTESTINAL SURGERY 2023; 26:603-606. [PMID: 37583015 DOI: 10.3760/cma.j.cn441530-20221028-00437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
Transanal total mesorectal resection (taTME) has come a long way since it was first used in the clinic in 2010.The learning curve of this procedure is long due to different surgical approaches, different perspectives and different anatomical positions. Many surgeons experience complications during this procedure. Although the advantages and problems of this procedure have been reported in much literature, the anatomy and operation methods of taTME introduced in literatures and training centers are too complicated, which makes many surgeons encounter difficulties in carrying out taTME surgery. According to the author's experience in learning and carrying out this operation, spatial expansion process of ultralow rectal cancer was divided into three stages. At each stage, according to different pulling forces, three different schemes of triangular stability mechanics model were adopted for separation. From point to line, from line to plane, the model can protect the safety of peripheral blood vessels and nerves while ensuring total mesorectal excision . This model simplifies the complex surgical process and is convenient for beginners to master taTME surgical separation skills.
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Ablikim M, Achasov MN, Adlarson P, 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, Bloms J, 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 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 RP, Guo YP, Guskov A, H XT, 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 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 ZK, 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, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, 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 K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, 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 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, Maldaner S, Malde S, 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 B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, 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 UW, 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 H, 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, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, 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, 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 XY, 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. First Study of Reaction Ξ^{0}n→Ξ^{-}p Using Ξ^{0}-Nucleus Scattering at an Electron-Positron Collider. PHYSICAL REVIEW LETTERS 2023; 130:251902. [PMID: 37418739 DOI: 10.1103/physrevlett.130.251902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/20/2023] [Accepted: 05/25/2023] [Indexed: 07/09/2023]
Abstract
Using (1.0087±0.0044)×10^{10} J/ψ events collected with the BESIII detector at the BEPCII storage ring, the process Ξ^{0}n→Ξ^{-}p is studied, where the Ξ^{0} baryon is produced in the process J/ψ→Ξ^{0}Ξ[over ¯]^{0} and the neutron is a component of the ^{9}Be, ^{12}C, and ^{197}Au nuclei in the beam pipe. A clear signal is observed with a statistical significance of 7.1σ. The cross section of the reaction Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be is determined to be σ(Ξ^{0}+^{9}Be→Ξ^{-}+p+^{8}Be)=(22.1±5.3_{stat}±4.5_{sys}) mb at the Ξ^{0} momentum of 0.818 GeV/c, where the first uncertainty is statistical and the second is systematic. No significant H-dibaryon signal is observed in the Ξ^{-}p final state. This is the first study of hyperon-nucleon interactions in electron-positron collisions and opens up a new direction for such research.
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Liu T, Wang W, Zhang T, Liu S, Bian Y, Zhang C, Xiao R. [Expression of TUBB4B in mouse primary spermatocyte GC-2 cells and its regulatory effect on NF-κB and MAPK signaling pathway]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2023; 43:1002-1009. [PMID: 37439173 DOI: 10.12122/j.issn.1673-4254.2023.06.16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
OBJECTIVE To explore the interaction between Tubulin beta 4B class IVb (TUBB4B) and Agtpbp1/cytosolic carboxypeptidase- like1 (CCP1) in mouse primary spermatocytes (GC-2 cells) and the role of TUBB4B in regulating the development of GC-2 cells. METHODS Lentiviral vectors were used to infect GC-2 cells to construct TUBB4B knockdown and negative control (NC-KD) cells. The stable cell lines with TUBB4B overexpression (Tubb4b-OE) and the negative control (NC-OE) cells were screened using purinomycin. RT-qPCR and Western blotting were used to verify successful cell modeling and explore the relationship between TUBB4B and CCP1 expressions in GC-2 cells. The effects of TUBB4B silencing and overexpression on the proliferation and cell cycle of GC-2 cells were evaluated using CCK8 assay and flow cytometry. The signaling pathway proteins showing significant changes in response to TUBB4B silencing or overexpression were identified using Western blotting and immunofluorescence assay and then labeled for verification at the cellular level. RESULTS Both TUBB4B silencing and overexpression in GC-2 cells caused consistent changes in the mRNA and protein expressions of CCP1 (P < 0.05). Similarly, TUBB4B expression also showed consistent changes at the mRNA and protein after CCP1 knockdown and restoration (P < 0.05). TUBB4B knockdown and overexpression had no significant effect on proliferation rate or cell cycle of GC-2 cells, but caused significant changes in the key proteins of the nuclear factor kappa-B (NF-κB) signaling pathway (p65 and p-p65) and the mitogen-activated protein kinase (MAPK) signaling pathway (ErK1/2 and p-Erk1/2) (P < 0.05); CCP1 knockdown induced significant changes in PolyE expression in GC-2 cells (P < 0.05). CONCLUSIONS TUBB4B and CCP1 interact via a mutual positive regulation mechanism in GC-2 cells. CCP-1 can deglutamize TUBB4B, and the latter is involved in the regulation of NF-κB and MAPK signaling pathways in primary spermatocytes.
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Husain MO, Khoso AB, Kiran T, Chaudhry N, Husain MI, Asif M, Ansari M, Rajput AH, Dawood S, Naqvi HA, Nizami AT, Tareen Z, Rumi J, Sherzad S, Khan HA, Bhatia MR, Siddiqui KMS, Zadeh Z, Mehmood N, Talib U, de Oliveira C, Naeem F, Wang W, Voineskos A, Husain N, Foussias G, Chaudhry IB. Culturally adapted psychosocial interventions (CaPSI) for early psychosis in a low-resource setting: study protocol for a large multi-center RCT. BMC Psychiatry 2023; 23:444. [PMID: 37328751 PMCID: PMC10276384 DOI: 10.1186/s12888-023-04904-8] [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: 05/18/2023] [Accepted: 05/26/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Psychosis treatment guidelines recommend cognitive behaviour therapy (CBT) and family intervention (FI), for all patients with first episode psychosis (FEP), though guidance borrows heavily from literature in adults from high income countries. To our knowledge, there are few randomized controlled trials (RCTs) examining the comparative effect of these commonly endorsed psychosocial interventions in individuals with early psychosis from high-income countries and no such trials from low and middle-income countries (LMICs). The present study aims to confirm the clinical-efficacy and cost-effectiveness of delivering culturally adapted CBT (CaCBT) and culturally adapted FI (CulFI) to individuals with FEP in Pakistan. METHOD A multi-centre, three-arm RCT of CaCBT, CulFI, and treatment as usual (TAU) for individuals with FEP (n = 390), recruited from major centres across Pakistan. Reducing overall symptoms of FEP will be the primary outcome. Additional aims will include improving patient and carer outcomes and estimating the economic impact of delivering culturally appropriate psychosocial interventions in low-resource settings. This trial will assess the clinical-efficacy and cost-effectiveness of CaCBT and CulFI compared with TAU in improving patient (positive and negative symptoms of psychosis, general psychopathology, depressive symptoms, quality of life, cognition, general functioning, and insight) and carer related outcomes (carer experience, wellbeing, illness attitudes and symptoms of depression and anxiety). CONCLUSIONS A successful trial may inform the rapid scale up of these interventions not only in Pakistan but other low-resource settings, to improve clinical outcomes, social and occupational functioning, and quality of life in South Asian and other minority groups with FEP. TRIAL REGISTRATION NCT05814913.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, 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 SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, 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 Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, 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, Gao H, Gao XL, 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, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, 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, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, 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 L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, 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 LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, 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, 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, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, 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 JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, 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 XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, 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, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, 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 XY, 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 YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurements of Normalized Differential Cross Sections of Inclusive π^{0} and K_{S}^{0} Production in e^{+}e^{-} Annihilation at Energies from 2.2324 to 3.6710 GeV. PHYSICAL REVIEW LETTERS 2023; 130:231901. [PMID: 37354421 DOI: 10.1103/physrevlett.130.231901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/22/2023] [Accepted: 04/03/2023] [Indexed: 06/26/2023]
Abstract
Based on electron positron collision data collected with the BESIII detector operating at the BEPCII storage rings, the differential cross sections of inclusive π^{0} and K_{S}^{0} production as a function of hadron momentum, normalized by the total cross section of the e^{+}e^{-}→hadrons process, are measured at six center-of-mass energies from 2.2324 to 3.6710 GeV. Our results, which cover a relative hadron energy range from 0.1 to 0.9, significantly deviate from several theoretical calculations based on existing fragmentation functions.
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Cao Z, Aharonian F, An Q, Bai LX, Bai YX, Bao YW, Bastieri D, Bi XJ, Bi YJ, Cai JT, Cao Q, Cao WY, Cao Z, Chang J, Chang JF, Chen ES, Chen L, Chen L, Chen L, Chen MJ, Chen ML, Chen QH, Chen SH, Chen SZ, Chen TL, Chen Y, Cheng HL, Cheng N, Cheng YD, Cui SW, Cui XH, Cui YD, Dai BZ, Dai HL, Dai ZG, Della Volpe D, Dong XQ, Duan KK, Fan JH, Fan YZ, Fang J, Fang K, Feng CF, Feng L, Feng SH, Feng XT, Feng YL, Gao B, Gao CD, Gao LQ, Gao Q, Gao W, Gao WK, Ge MM, Geng LS, Gong GH, Gou QB, Gu MH, Guo FL, Guo XL, Guo YQ, Guo YY, Han YA, He HH, He HN, He JY, He XB, He Y, Heller M, Hor YK, Hou BW, Hou C, Hou X, Hu HB, Hu Q, Hu SC, Huang DH, Huang TQ, Huang WJ, Huang XT, Huang XY, Huang Y, Huang ZC, Ji XL, Jia HY, Jia K, Jiang K, Jiang XW, Jiang ZJ, Jin M, Kang MM, Ke T, Kuleshov D, Kurinov K, Li BB, Li C, Li C, Li D, Li F, Li HB, Li HC, Li HY, Li J, Li J, Li J, Li K, Li WL, Li WL, Li XR, Li X, Li YZ, Li Z, Li Z, Liang EW, Liang YF, Lin SJ, Liu B, Liu C, Liu D, Liu H, Liu HD, Liu J, Liu JL, Liu JL, Liu JS, Liu JY, Liu MY, Liu RY, Liu SM, Liu W, Liu Y, Liu YN, Long WJ, Lu R, Luo Q, Lv HK, Ma BQ, Ma LL, Ma XH, Mao JR, Min Z, Mitthumsiri W, Nan YC, Ou ZW, Pang BY, Pattarakijwanich P, Pei ZY, Qi MY, Qi YQ, Qiao BQ, Qin JJ, Ruffolo D, Sáiz A, Shao CY, Shao L, Shchegolev O, Sheng XD, Song HC, Stenkin YV, Stepanov V, Su Y, Sun QN, Sun XN, Sun ZB, Tam PHT, Tang ZB, Tian WW, Wang C, Wang CB, Wang GW, Wang HG, Wang HH, Wang JC, Wang JS, Wang K, Wang LP, Wang LY, Wang PH, Wang R, Wang W, Wang XG, Wang XY, Wang Y, Wang YD, Wang YJ, Wang ZH, Wang ZX, Wang Z, Wang Z, Wei DM, Wei JJ, Wei YJ, Wen T, Wu CY, Wu HR, Wu S, Wu XF, Wu YS, Xi SQ, Xia J, Xia JJ, Xiang GM, Xiao DX, Xiao G, Xin GG, Xin YL, Xing Y, Xiong Z, Xu DL, Xu RF, Xu RX, Xue L, Yan DH, Yan JZ, Yan T, Yang CW, Yang F, Yang FF, Yang HW, Yang JY, Yang LL, Yang MJ, Yang RZ, Yang SB, Yao YH, Yao ZG, Ye YM, Yin LQ, Yin N, You XH, You ZY, Yu YH, Yuan Q, Yue H, Zeng HD, Zeng TX, Zeng W, Zeng ZK, Zha M, Zhang B, Zhang BB, Zhang F, Zhang HM, Zhang HY, Zhang JL, Zhang LX, Zhang L, Zhang PF, Zhang PP, Zhang R, Zhang SB, Zhang SR, Zhang SS, Zhang X, Zhang XP, Zhang YF, Zhang Y, Zhang Y, Zhao B, Zhao J, Zhao L, Zhao LZ, Zhao SP, Zheng F, Zheng JH, Zhou B, Zhou H, Zhou JN, Zhou P, Zhou R, Zhou XX, Zhu CG, Zhu FR, Zhu H, Zhu KJ, Zuo X. A tera-electron volt afterglow from a narrow jet in an extremely bright gamma-ray burst. Science 2023:eadg9328. [PMID: 37289911 DOI: 10.1126/science.adg9328] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 05/25/2023] [Indexed: 06/10/2023]
Abstract
Some gamma-ray bursts (GRBs) have a tera-electron volt (TeV) afterglow, but the early onset of this has not been observed. We report observations with the Large High Altitude Air Shower Observatory of the bright GRB 221009A, which serendipitously occurred within the instrument field of view. More than 64,000 photons >0.2 TeV were detected within the first 3000 seconds. The TeV flux began several minutes after the GRB trigger, then rose to a peak about 10 seconds later. This was followed by a decay phase, which became more rapid ~650 seconds after the peak. We interpret the emission using a model of a relativistic jet with half-opening angle ~0.8°. This is consistent with the core of a structured jet and could explain the high isotropic energy of this GRB.
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Xiao X, Liu Y, Zheng F, Xiong T, Zeng Y, Wang W, Zheng X, Wu Q, Xu J, Crous P, Jiao C, Li H. High species diversity in Diaporthe associated with citrus diseases in China. PERSOONIA 2023; 51:229-256. [PMID: 38665984 PMCID: PMC11041894 DOI: 10.3767/persoonia.2023.51.06] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 09/08/2023] [Indexed: 04/28/2024]
Abstract
Species in Diaporthe have broad host ranges and cosmopolitan geographic distributions, occurring as endophytes, saprobes and plant pathogens. Previous studies have indicated that many Diaporthe species are associated with Citrus. To further determine the diversity of Diaporthe species associated with citrus diseases in China, we conducted extensive surveys in major citrus-producing areas from 2017-2020. Diseased tissues were collected from leaves, fruits, twigs, branches and trunks showing a range of symptoms including melanose, dieback, gummosis, wood decay and canker. Based on phylogenetic comparisons of DNA sequences of the internal transcribed spacer regions (ITS), calmodulin (cal), histone H3 (his3), translation elongation factor 1-alpha (tef1) and beta-tubulin (tub2), 393 isolates from 10 provinces were identified as belonging to 36 species of Diaporthe, including 32 known species, namely D. apiculata, D. biconispora, D. biguttulata, D. caryae, D. citri, D. citriasiana, D. compacta, D. discoidispora, D. endophytica, D. eres, D. fusicola, D. fulvicolor, D. guangxiensis, D. hongkongensis, D. hubeiensis, D. limonicola, D. litchii, D. novem, D. passifloricola, D. penetriteum, D. pescicola, D. pometiae, D. sackstonii, D. sennicola, D. sojae, D. spinosa, D. subclavata, D. tectonae, D. tibetensis, D. unshiuensis, D. velutina and D. xishuangbanica, and four new species, namely D. gammata, D. jishouensis, D. ruiliensis and D. sexualispora. Among the 32 known species, 14 are reported for the first time on Citrus, and two are newly reported from China. Among the 36 species, D. citri was the dominant species as exemplified by its high frequency of isolation and virulence. Pathogenicity tests indicated that most Diaporthe species obtained in this study were weakly aggressive or non-pathogenic to the tested citrus varieties. Only D. citri produced the longest lesion lengths on citrus shoots and induced melanose on citrus leaves. These results further demonstrated that a rich diversity of Diaporthe species occupy Citrus, but only a few species are harmful and D. citri is the main pathogen for Citrus in China. The present study provides a basis from which targeted monitoring, prevention and control measures can be developed. Citation: Xiao XE, Liu YD, Zheng F, et al. 2023. High species diversity in Diaporthe associated with citrus diseases in China. Persoonia 51: 229-256. doi: 10.3767/persoonia.2023.51.06.
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Hensel ME, Landsgaard K, Wang W, Neupane S, Su C, Blue-McClendon A, Porter BF, Uzal FA, Rech R. Toxoplasmosis in ring-tailed lemurs (Lemur catta) and a peahen (Pavo cristatus) in a zoological collection caused by the common toxoplasma genotype in wild animals in the US. Vet Parasitol Reg Stud Reports 2023; 41:100876. [PMID: 37208075 DOI: 10.1016/j.vprsr.2023.100876] [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: 11/28/2022] [Revised: 04/06/2023] [Accepted: 04/14/2023] [Indexed: 05/21/2023]
Abstract
Toxoplasmosis is caused by the ubiquitous Apicomplexan protozoan Toxoplasma gondii. This pathogen affects domestic and wildlife species, but prosimians including ring-tailed lemurs (Lemur catta) are highly susceptible to infection with high mortality rates. Avian species are considered resistant to infection and are often used in surveillance efforts to determine genotypes of T. gondii present in geographical areas. This study describes the gross and histologic lesions of an outbreak of toxoplasmosis in a university-run zoological collection involving three ring-tailed lemurs and a peahen (Pavo cristatus). DNA was extracted from the liver of the lemurs and peahen to determine the genotype of T. gondii by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP), which revealed that all samples were ToxoDB PCR-RFLP genotype #5 (haplogroup 12) that is common in wildlife in North America.
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Cao HW, Zhang JD, Wang W, Xu QZ. [Prevalence of frailty and associated factors among kidney transplant recipients]. ZHONGHUA YI XUE ZA ZHI 2023; 103:1531-1537. [PMID: 37246002 DOI: 10.3760/cma.j.cn112137-20221104-02307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Objective: To investigate the prevalence of frailty among kidney transplant recipients and to analyze the influential factors of frailty after kidney transplantation. Methods: We retrospectively included 201 kidney transplant recipients who were followed up in the Department of Urology, Beijing Chao-yang Hospital, Capital Medical University from November 2020 to May 2022. We investigated the prevalence of frailty based on the Fried Frailty Scale (including unexpected shrinking, slow walking speed, poor grip strength, low physical activity, and exhaustion). Then the logistic regression model and CART decision tree model were established separately to explore the influential factors of frailty after kidney transplantation. Results: Frail kidney transplant recipients accounted for 25.9% (n=52) of all participants. The age [M (Q1, Q3)] of the frailty group was higher than that of the non-frailty group, and the median ages of the two groups were 57(49, 62) and 46(38, 56) (P<0.001); the males accounted for 51.9% (n=27) and 62.4% (n=93), respectively. There was no significant difference in gender composition (P=0.244). Among the five components of Fried Frailty Scale, the incidence of unexpected shrinking was the lowest (19.4%, 39/201). In the frailty group, the frailty combination with the highest incidence was slow walking speed+low physical activity+exhaustion, which was 19.2% (10/52). The logistic regression model showed that advanced age (OR=1.062, 95%CI: 1.005-1.123), history of acute rejection (OR=16.776, 95%CI: 2.288-123.028), increased neutrophil/lymphocyte ratio (NLR) (OR=2.096, 95%CI: 1.158-3.792), and comorbidity (OR=10.600, 95%CI: 1.828-61.482) were risk factors for frailty among kidney transplant recipients, and high serum albumin level (OR=0.623, 95%CI: 0.488-0.795) was a protective factor. The CART decision tree grew in three layers with four terminal nodes, and three explanatory variables were screened out: serum albumin, NLR, and age. The accuracy, sensitivity, and specificity of the logistic regression model were 87.1% (95%CI: 82.5%-91.7%), 69.2% (95%CI: 54.7%-80.9%), and 93.3% (95%CI: 87.7%-96.6%), respectively. The area under the ROC curve (AUC) of the logistic regression model was 0.951 (95%CI: 0.923-0.978). The accuracy, sensitivity, and specificity of the CART decision tree model were 91.0% (95%CI: 87.0%-95.0%), 82.7% (95%CI: 69.2%-91.3%), and 94.0% (95%CI: 88.5%-97.0%), respectively. The AUC of the CART decision tree model was 0.883 (95%CI: 0.819-0.948). Conclusions: The prevalence of frailty among kidney transplant recipients in this study is 25.9%. Advanced age, history of acute rejection, low serum albumin level, increased NLR, and comorbidity are likely to be associated with the long-term frailty among kidney transplant recipients.
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An FP, Bai WD, Balantekin AB, Bishai M, Blyth S, Cao GF, Cao J, Chang JF, Chang Y, Chen HS, Chen HY, Chen SM, Chen Y, Chen YX, Cheng J, Cheng J, Cheng YC, Cheng ZK, Cherwinka JJ, Chu MC, Cummings JP, Dalager O, Deng FS, Ding YY, Diwan MV, Dohnal T, Dolzhikov D, Dove J, Dugas KV, Duyang HY, Dwyer DA, Gallo JP, Gonchar M, Gong GH, Gong H, Gu WQ, Guo JY, Guo L, Guo XH, Guo YH, Guo Z, Hackenburg RW, Han Y, Hans S, He M, Heeger KM, Heng YK, Hor YK, Hsiung YB, Hu BZ, Hu JR, Hu T, Hu ZJ, Huang HX, Huang JH, Huang XT, Huang YB, Huber P, Jaffe DE, Jen KL, Ji XL, Ji XP, Johnson RA, Jones D, Kang L, Kettell SH, Kohn S, Kramer M, Langford TJ, Lee J, Lee JHC, Lei RT, Leitner R, Leung JKC, Li F, Li HL, Li JJ, Li QJ, Li RH, Li S, Li SC, Li WD, Li XN, Li XQ, Li YF, Li ZB, Liang H, Lin CJ, Lin GL, Lin S, Ling JJ, Link JM, Littenberg L, Littlejohn BR, Liu JC, Liu JL, Liu JX, Lu C, Lu HQ, Luk KB, Ma BZ, Ma XB, Ma XY, Ma YQ, Mandujano RC, Marshall C, McDonald KT, McKeown RD, Meng Y, Napolitano J, Naumov D, Naumova E, Nguyen TMT, Ochoa-Ricoux JP, Olshevskiy A, Park J, Patton S, Peng JC, Pun CSJ, Qi FZ, Qi M, Qian X, Raper N, Ren J, Morales Reveco C, Rosero R, Roskovec B, Ruan XC, Russell B, Steiner H, Sun JL, Tmej T, Treskov K, Tse WH, Tull CE, Tung YC, Viren B, Vorobel V, Wang CH, Wang J, Wang M, Wang NY, Wang RG, Wang W, Wang X, Wang Y, Wang YF, Wang Z, Wang Z, Wang ZM, Wei HY, Wei LH, Wen LJ, Whisnant K, White CG, Wong HLH, Worcester E, Wu DR, Wu Q, Wu WJ, Xia DM, Xie ZQ, Xing ZZ, Xu HK, Xu JL, Xu T, Xue T, Yang CG, Yang L, Yang YZ, Yao HF, Ye M, Yeh M, Young BL, Yu HZ, Yu ZY, Yue BB, Zavadskyi V, Zeng S, Zeng Y, Zhan L, Zhang C, Zhang FY, Zhang HH, Zhang JL, Zhang JW, Zhang QM, Zhang SQ, Zhang XT, Zhang YM, Zhang YX, Zhang YY, Zhang ZJ, Zhang ZP, Zhang ZY, Zhao J, Zhao RZ, Zhou L, Zhuang HL, Zou JH. Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay. PHYSICAL REVIEW LETTERS 2023; 130:211801. [PMID: 37295075 DOI: 10.1103/physrevlett.130.211801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 02/10/2023] [Accepted: 04/27/2023] [Indexed: 06/12/2023]
Abstract
Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, 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 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 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 RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, 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 ZK, 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, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, 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 K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, 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 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, Maas FE, Maggiora M, Maldaner S, Malde S, 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, 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 JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, 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 B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, 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 H, 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 WL, Xu XP, Xu YC, Xu ZP, 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, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, 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, 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 LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, 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. Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}. PHYSICAL REVIEW LETTERS 2023; 130:211901. [PMID: 37295102 DOI: 10.1103/physrevlett.130.211901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 05/08/2023] [Indexed: 06/12/2023]
Abstract
Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.
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Wang Y, Li F, Hu Y, Sun Y, Tian C, Cao Y, Wang W, Feng W, Yan J, Wei J, Du X, Wang H. Clinical outcomes of intra-arterial chemotherapy combined with iodine-125 seed brachytherapy in the treatment of malignant superior vena cava syndrome caused by small cell lung cancer. Cancer Radiother 2023:S1278-3218(23)00068-9. [PMID: 37230904 DOI: 10.1016/j.canrad.2023.01.008] [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: 10/13/2022] [Revised: 12/29/2022] [Accepted: 01/14/2023] [Indexed: 05/27/2023]
Abstract
PURPOSE Currently there is a lack of effective treatment strategies for malignant superior vena cava syndrome (SVCS). We aim to investigate the therapeutic effect of intra-arterial chemotherapy (IAC) combined with the Single Needle Cone Puncture method for the 125I brachytherapy (SNCP-125I) in treating SVCS caused by stage III/IV Small Cell Lung Cancer (SCLC). MATERIALS AND METHODS Sixty-two patients with SCLC who developed SVCS from January 2014 to October 2020 were investigated in this study. Out of these 62 patients, 32 underwent IAC combined with SNCP-125I (Group A) and 30 patients received IAC treatment only (Group B). Clinical symptom remission, response rate, disease control rate, and overall survival of these two groups of patients were analyzed and compared. RESULTS The remission rate of symptoms including dyspnea, edema, dysphagia, pectoralgia, and cough of malignant SVCS in Group A was significantly higher than that in Group B (70.5 and 50.53%, P=0.0004, respectively). The disease control rates (DCR, PR+CR+SD) of Group A and B were 87.5 and 66.7%, respectively (P=0.049). Response rates (RR, PR+CR) of Group A and Group B were 71.9 and 40% (P=0.011). The median overall survival (OS) of Group A was significantly longer than that in Group B which was 18 months compared to 11.75 months (P=0.0360). CONCLUSIONS IAC treatment effectively treated malignant SVCS in advanced SCLC patients. IAC combined with SNCP-125I in the treatment of malignant SVCS caused by SCLC showed improved clinical outcomes including symptom remission and local tumor control rates than IAC treatment only in treating SCLC-induced malignant SVCS.
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Jin XJ, Teng ZQ, Xu PX, Sun XR, Wang W, Qin XC, Qin T. [Simultaneous detection of 7 important Rickettsiales pathogens by TaqMan-probe quantitative real-time PCR]. ZHONGHUA LIU XING BING XUE ZA ZHI = ZHONGHUA LIUXINGBINGXUE ZAZHI 2023; 44:816-822. [PMID: 37221073 DOI: 10.3760/cma.j.cn112338-20221011-00875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Objective: To establish and optimize a TaqMan-probe quantitative real-time PCR (qPCR) assay for the detection of 7 important Rickettsiales pathogens and simultaneous identification of the infection types. Methods: Based on the ompB gene of Rickettsia prowazekii, Rickettsia mooseri and spotted fever group rickettsiae, the groEL gene of Orientia tsutsugamushi, the 16S rRNA of Ehrlichia chaffeensis, the gltA gene of Anaplasma phagocytophilum and the com1 gene of Coxiella burnetii, we synthesized primers and TaqMan-probes and optimized the reaction system and reaction process to same solution. The sensitivity, specificity and reproducibility of this assay were evaluated and the assay was used for the detection of simulated and actual samples. Results: The Ct value of the standard curves of the 7 pathogens showed a good linear relationship with the number of DNA copies (all R2 >0.990 0), the minimum detection limit was 10 copies/μl, showing good specificity. In the 96 tick nucleic acid extracts, Coxiella burnetii was detected in 1 sampleand spotted fever group Rickettsiae was detected in 3 samples. In the 80 blood samples from patients with undefined febrile illness, Orientia tsutsugamushi was detected in 1 sample and spotted fever group rickettsiae was detected in 2 samples. Conclusions: In this study, based on the established TaqMan-probe qPCR assay, the reaction system and reaction condition of the 7 important pathogens of Rickettsiales were optimized to the same solution. This method overcomes the shortcomings of using different reaction systems and reaction conditions for different pathogens, which can precisely identify the species of 7 important pathogens of Rickettsiales in clinical sample detections and is important for the infection type identification and laboratory detection time reduction to facilitate precise treatment of the patients.
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