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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 BX, 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 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 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, 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, 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. Observation of Three Charmoniumlike States with J^{PC}=1^{--} in e^{+}e^{-}→D^{*0}D^{*-}π^{+}. PHYSICAL REVIEW LETTERS 2023; 130:121901. [PMID: 37027853 DOI: 10.1103/physrevlett.130.121901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/16/2023] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
The Born cross sections of the process e^{+}e^{-}→D^{*0}D^{*-}π^{+} at center-of-mass energies from 4.189 to 4.951 GeV are measured for the first time. The data samples used correspond to an integrated luminosity of 17.9 fb^{-1} and were collected by the BESIII detector operating at the BEPCII storage ring. Three enhancements around 4.20, 4.47, and 4.67 GeV are visible. The resonances have masses of 4209.6±4.7±5.9 MeV/c^{2}, 4469.1±26.2±3.6 MeV/c^{2}, and 4675.3±29.5±3.5 MeV/c^{2} and widths of 81.6±17.8±9.0 MeV, 246.3±36.7±9.4 MeV, and 218.3±72.9±9.3 MeV, respectively, where the first uncertainties are statistical and the second systematic. The first and third resonances are consistent with the ψ(4230) and ψ(4660) states, respectively, while the second one is compatible with the ψ(4500) observed in the e^{+}e^{-}→K^{+}K^{-}J/ψ process. These three charmoniumlike ψ states are observed in the e^{+}e^{-}→D^{*0}D^{*-}π^{+} process for the first time.
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Liu R, Wang Q, Xiao D, Zhu Y, Yang B, Ding Y, Bai J, Wen H, Wu H, Duan JA, Zhao M. Discovery of elaphuri davidiani cornu-specific peptide biomarkers by peptidomics analysis-based method. Electrophoresis 2023. [PMID: 36945190 DOI: 10.1002/elps.202300023] [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: 11/11/2022] [Revised: 03/07/2023] [Accepted: 03/09/2023] [Indexed: 03/23/2023]
Abstract
Elaphuri Davidiani Cornu (EDC) is the antler of the male Père David's deer, which has been reported to have multiple biological activities, and its use as a traditional Chinese medicine (TCM) in China has been known for thousands of years. However, EDC is difficult to distinguish from other related species-derived antlers in powder or extract form in TCM clinic use, such as Cervus Elaphus Cornu (CEC) and Cervus Nippon Cornu (CNC) both derived from Cervidae and easily confused with EDC. In this study, a strategy using peptidomics combined with mathematics set analysis was used to identify EDC-specific peptide biomarkers, and four specific peptide biomarkers (Pep-E1 to E4) were identified and validated. Pep-E1, Pep-E3 and Pep-E4 could be exclusively detected in EDC samples, with relative peak areas of 0.298 ± 0.060, 0.039 ± 0.015 and 0.037 ± 0.008, while Pep-E2 showed relative peak area of 0.516 ± 0.101 in EDC, 0.132 ± 0.026 in CEC and 0.136 ± 0.047 in CNC samples, respectively. These four peptides are applicable to distinguish EDC from CEC and CNC, which is of great significance for the quality control of EDC. This article is protected by copyright. All rights reserved.
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Zang Z, Xiao D, Wang Q, Jiao Z, Chen Y, Li DDU. Compact and robust deep learning architecture for fluorescence lifetime imaging and FPGA implementation. Methods Appl Fluoresc 2023; 11. [PMID: 36863024 DOI: 10.1088/2050-6120/acc0d9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/01/2023] [Indexed: 03/04/2023]
Abstract
This paper reports a bespoke adder-based deep learning network for time-domain fluorescence lifetime imaging (FLIM). By leveraging thel1-norm extraction method, we propose a 1D Fluorescence Lifetime AdderNet (FLAN) without multiplication-based convolutions to reduce the computational complexity. Further, we compressed fluorescence decays in temporal dimension using a log-scale merging technique to discard redundant temporal information derived as log-scaling FLAN (FLAN+LS). FLAN+LS achieves 0.11 and 0.23 compression ratios compared with FLAN and a conventional 1D convolutional neural network (1D CNN) while maintaining high accuracy in retrieving lifetimes. We extensively evaluated FLAN and FLAN+LS using synthetic and real data. A traditional fitting method and other non-fitting, high-accuracy algorithms were compared with our networks for synthetic data. Our networks attained a minor reconstruction error in different photon-count scenarios. For real data, we used fluorescent beads' data acquired by a confocal microscope to validate the effectiveness of real fluorophores, and our networks can differentiate beads with different lifetimes. Additionally, we implemented the network architecture on a field-programmable gate array (FPGA) with a post-quantization technique to shorten the bit-width, thereby improving computing efficiency. FLAN+LS on hardware achieves the highest computing efficiency compared to 1D CNN and FLAN. We also discussed the applicability of our network and hardware architecture for other time-resolved biomedical applications using photon-efficient, time-resolved sensors.
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Zhai C, Li X, Xiao D, Chen L, Wang C, Zheng M. Severe hyperlipidemia pancreatitis induced by taking tamoxifen after breast cancer surgery—Case report. Front Oncol 2023; 13:1103637. [PMID: 36994195 PMCID: PMC10042229 DOI: 10.3389/fonc.2023.1103637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 02/20/2023] [Indexed: 03/12/2023] Open
Abstract
IntroductionThe research investigates the mechanism, diagnosis, treatment, and subsequent endocrine therapy of severe pancreatitis induced by tamoxifen treatment in patients who have undergone breast cancer surgery.Case presentationWe studied two cases of breast cancer in whom severe acute pancreatitis developed after taking tamoxifen for endocrine therapy in our hospital. A brief literature review was provided to analyze the causes, clinical manifestations, treatment process, and prognosis of severe acute pancreatitis. Both cases involved patients with severe hyperlipidemic pancreatitis. After conservative treatment, none of them died. Pancreatitis did not recur after changing endocrine therapy drugs.Discussion/conclusionEndocrine therapy with tamoxifen in breast cancer patients can induce hyperlipidemia, which can subsequently cause severe pancreatitis. The treatment of severe pancreatitis should strengthen the regulation of blood lipids. The application of low-molecular-weight heparin combined with insulin therapy can rapidly lower blood lipids. Involved treatments, including acid suppression, enzyme suppression, and peritoneal dialysis, can accelerate the recovery of pancreatitis and reduce the occurrence of serious complications. Patients with severe pancreatitis should not continue to use tamoxifen for endocrine therapy. To complete follow-up endocrine therapy, switching to a steroidal aromatase inhibitor is better if the situation allows it.
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Xiao D, Vu QH, Le BT, Ha TTL. A method for mapping and monitoring of iron ore stopes based on hyperspectral remote sensing-ground data and a 3D deep neural network. Neural Comput Appl 2023. [DOI: 10.1007/s00521-023-08353-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, 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, 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, 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, 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, Dong J, Dong LY, Dong MY, Dong X, Du SX, 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 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 TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, 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 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, 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 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 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, Pathak A, Pelizaeus M, Peng HP, Peters K, Pettersson J, 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, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, 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 BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YH, Wang YQ, 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 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 SY, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, 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 XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, 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 BS, Zou JH. Evidence for the Cusp Effect in η' Decays into ηπ^{0}π^{0}. PHYSICAL REVIEW LETTERS 2023; 130:081901. [PMID: 36898113 DOI: 10.1103/physrevlett.130.081901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 11/19/2022] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Using a sample of 4.3×10^{5} η^{'}→ηπ^{0}π^{0} events selected from the ten billion J/ψ event dataset collected with the BESIII detector, we study the decay η^{'}→ηπ^{0}π^{0} within the framework of nonrelativistic effective field theory. Evidence for a structure at π^{+}π^{-} mass threshold is observed in the invariant mass spectrum of π^{0}π^{0} with a statistical significance of around 3.5σ, which is consistent with the cusp effect as predicted by the nonrelativistic effective field theory. After introducing the amplitude for describing the cusp effect, the ππ scattering length combination a_{0}-a_{2} is determined to be 0.226±0.060_{stat}±0.013_{syst}, which is in good agreement with theoretical calculation of 0.2644±0.0051.
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Xiao D, Yan Z, Li J, Fu Y, Li Z. Rapid proximate analysis of coal based on reflectance spectroscopy and deep learning. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 287:122042. [PMID: 36356397 DOI: 10.1016/j.saa.2022.122042] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 10/14/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Proximate analysis of coal is of profound significance for understanding coal quality and promoting rational utilization of coal resources. Traditional coal proximate analysis mainly uses chemical analysis methods, which have the disadvantages of slow speed and high cost. This paper proposed an approach combining reflectance spectroscopy with deep learning (DL) for rapid proximate analysis of coal. First, 80 sets of coal spectral data are enhanced by data augmentation, outlier detection, and dimensional transformation to improve the number and quality of samples. Then, an analytical model combining dilated convolution, multi-level residual connection, and a two-hidden-layer extreme learning machine (TELM), named DR_TELM, was proposed. The model extracted effective features from coal spectral data by a convolutional neural network (CNN) and utilized TELM as a regressor to achieve feature identification and content prediction. The experimental results showed that DR_TELM achieved coefficients of determination (R2) of 0.981, 0.989, 0.990, 0.985, 0.989 and root mean square errors (RMSE) of 0.533, 1.833, 1.111, 1.808, 0.723 for the content prediction of moisture, ash, volatile matter, fixed carbon and higher heating value (HHV), respectively. And while ensuring high accuracy, the test time is only 0.034 s. It is fully demonstrated that DR_TELM can rapidly and accurately analyze coal.
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Lv X, Shi X, Maihemuti M, Yang D, Xiao D. Correlation of
HMGB1
,
TLR2
and
TLR4
with left ventricular diastolic dysfunction in sepsis patients. Scand J Immunol 2023. [DOI: 10.1111/sji.13260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
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Zhang D, Wang L, Wang Z, Shi X, Tang W, Jiang L, Bo Ran Yi BYCH, Lv X, Hu C, Xiao D. Immunological responses of septic rats to combination therapy with thymosin α1 and vitamin C. Open Life Sci 2023; 18:20220551. [PMID: 36816800 PMCID: PMC9922062 DOI: 10.1515/biol-2022-0551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 12/09/2022] [Accepted: 12/14/2022] [Indexed: 02/10/2023] Open
Abstract
This study investigated the effect of combined thymosin α1 and vitamin C (Tα1 + VitC) on the immunological responses of septic rats. Five groups were designed. The septic model was established by the cecal ligation puncture (CLP) method. The sham group did not undergo CLP, the model group was given normal saline solution, the Tα1 group was given Tα1 (200 µg/kg), the VitC group was given VitC (200 mg/kg), and the Tα1 + VitC group was given Tα1 + VitC. Specimens for immunological analyses were collected at 6, 12, 24, and 48 h posttreatment in each group except for the sham group (only at 48 h). CD4 + CD25 + T cells in the peripheral blood and dendritic cell (DC) proportions in the spleen were analyzed by flow cytometry. Tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), transforming growth factor-β (TGF-ß1), and nuclear factor kappa-B (NF-κB) were measured by ELISA. CD4 + CD25 + T cells and OX62 + DCs levels significantly increased in the model group and decreased in the Tα1 and/or VitC treatment groups. Similarly, the levels of TNF-α, IL-6, TGF-ß1, and NF-κB significantly increased in the model group and decreased in the Tα1, VitC, and Tα1 + VitC groups, indicating that combined Tα1 and VitC therapy may help regulate the immunological state of patients with sepsis, thereby improving prognosis.
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Wang L, Bayinchahan B, Zhang D, Wang Z, Xiao D. The novel biomarker circ_0020339 drives septic acute kidney injury by targeting miR-17-5p/IPMK axis. Int Urol Nephrol 2023; 55:437-448. [PMID: 35986866 DOI: 10.1007/s11255-022-03331-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 07/25/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE Sepsis is a systemic life-threatening inflammatory disease, which leads to septic acute kidney injury (AKI). Circular RNAs (circRNAs) are involved in septic AKI. Herein, we aimed to expound the action of circ_0020339 in septic AKI. The dysregulation of plasma circRNAs between patients with septic non-AKI and patients with septic AKI were screened by circRNA chip. METHODS The dysregulation of circ_0020339, microRNA (miR)-17-5p, and inositol polyphosphate multi kinase (IPMK) mRNA was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. The release of serum creatinine (SCr), tissue inhibitor metalloproteinase-2 (TIMP-2), insulin-like growth factor binding protein-7 (IGFBP7), tumor necrosis factor (TNF)α and interleukin (IL)-1β was evaluated by enzyme-linked immunosorbent assay (ELISA). Bioinformatic analysis, dual-luciferase reporter assay and miRNA pull down assay were used to confirm the interaction between miR-17-5p and circ_0020339 or IPMK 3'untranslated region (UTR). Protein level of IPMK, TNF receptor-associated factor 6 (TRAF6), phosphorylated AKT (p-AKT)/total (t)-AKT, p-nuclear factor kappa-B (NF-κB) kinase (p-IKK)/t-IKK, p-inhibitor of NF-κB (p-IκB)α/t-IκBα, and p-p65/t-p65 were conducted by western blot. RESULTS Circ_0020339 was upregulated in the plasma of patients with septic AKI as well as LPS-treated HK2 cells and C57BL/6 mice relative to the corresponding counterparts. Functionally, circ_0020339 was positively correlated with markers of renal functional injury and inflammation in patients with septic AKI; si-circ_0020339 facilitated cell proliferation, while restrained cell apoptosis and inflammation in LPS-triggered HK2 cells; meanwhile, si-circ_0020339 restrained survival rate, renal functional injury and inflammation in LPS-triggered C57BL/6 mice. Furthermore, circ_0020339 and IPMK 3'UTR shared the same complementary sites with miR-17-5p. CONCLUSION si-circ_0020339 attenuated LPS-induced cell damage by targeting miR-17-5p/IPMK axis and inactivation of TRAF6/p-AKT/p-IKK/p-IκBα/p-p65. Altogether, plasma circ_0020339 serves as a novel diagnostic marker of patients with septic AKI.
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Zheng Z, Wu L, Li Z, Tang R, Li H, Huang Y, Wang T, Xu S, Cheng H, Ye Z, Xiao D, Lin X, Wu G, Jaspers RT, Pathak JL. Mir155 regulates osteogenesis and bone mass phenotype via targeting S1pr1 gene. eLife 2023; 12:77742. [PMID: 36598122 PMCID: PMC9839347 DOI: 10.7554/elife.77742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 01/03/2023] [Indexed: 01/05/2023] Open
Abstract
MicroRNA-155 (miR155) is overexpressed in various inflammatory diseases and cancer, in which bone resorption and osteolysis are frequently observed. However, the role of miR155 on osteogenesis and bone mass phenotype is still unknown. Here, we report a low bone mass phenotype in the long bone of Mir155-Tg mice compared with wild-type mice. In contrast, Mir155-KO mice showed a high bone mass phenotype and protective effect against inflammation-induced bone loss. Mir155-KO mice showed robust bone regeneration in the ectopic and orthotopic model, but Mir155-Tg mice showed compromised bone regeneration compared with the wild-type mice. Similarly, the osteogenic differentiation potential of bone marrow stromal stem cells (BMSCs) from Mir155-KO mice was robust and Mir155-Tg was compromised compared with that of wild-type mice. Moreover, Mir155 knockdown in BMSCs from wild-type mice showed higher osteogenic differentiation potential, supporting the results from Mir155-KO mice. TargetScan analysis predicted sphingosine 1-phosphate receptor-1 (S1pr1) as a target gene of Mir155, which was further confirmed by luciferase assay and Mir155 knockdown. S1pr1 overexpression in BMSCs robustly promoted osteogenic differentiation without affecting cell viability and proliferation. Furthermore, osteoclastogenic differentiation of Mir155-Tg bone marrow-derived macrophages was inhibited compared with that of wild-type mice. Thus, Mir155 showed a catabolic effect on osteogenesis and bone mass phenotype via interaction with the S1pr1 gene, suggesting inhibition of Mir155 as a potential strategy for bone regeneration and bone defect healing.
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Luo S, Pan C, Liu S, Liao G, Li A, Wang Y, Wang A, Xiao D, He LF, Zhan J. Identification and functional characterization of the xyloglucan endotransglucosylase/hydrolase 32 (AhXTH32) in peanut during aluminum-induced programmed cell death. PLANT PHYSIOLOGY AND BIOCHEMISTRY : PPB 2023; 194:161-168. [PMID: 36410145 DOI: 10.1016/j.plaphy.2022.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/30/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
The toxicity of aluminum (Al) in acidic soil is a prevalent problem and causes reduced crop yields. In the plant response to Al toxicity, programmed cell death (PCD) appears to be an important mechanism. The plant cell wall of crop roots is the predominant site targeted by Al. Here, studies of the capacities of different cell wall constituents (pectin, hemicellulose 1 {HC1} and HC2) to adsorb Al indicated that HC1 has the greater ability to bind Al. The activity of xyloglucan endotransglucosylase (XET) was significantly inhibited by Al in the Al-tolerant peanut cultivar '99-1507' compared to that in 'ZH 2' (Al-sensitive). Results from qPCR analysis suggested that the suppression of XET activity by Al was transcriptionally regulated and that xyloglucan endotransglucosylase/hydrolase 32 (AhXTH32) was the major contributor to these changes. The overexpression of AhXTH32 in Arabidopsis strongly inhibited root growth with a loss of viability in root cells and the occurrence of typical hallmarks of PCD, while largely opposite effects were observed after xth32 suppression. AhXTH32 contributed to the modulation XET and xyloglucan endohydrolase (XEH) activity in vivo. Taken together, our results demonstrate that Al-tolerant peanut cultivar root tips cell walls bind Al predominantly in the HC1 fraction, which results in the inhibition of AhXTH32, with consequences to root growth, Al sensitivity, the occurrence of PCD and the XET/XEH activity ratio.
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Sha Y, Mao AQ, Liu YJ, Li JP, Gong YT, Xiao D, Huang J, Gao YW, Wu MY, Shen H. Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma. Pharmgenomics Pers Med 2023; 16:153-172. [PMID: 36908806 PMCID: PMC9994630 DOI: 10.2147/pgpm.s399886] [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: 12/08/2022] [Accepted: 02/25/2023] [Indexed: 03/06/2023] Open
Abstract
Background The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition. Methods We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2). Results Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells. Conclusion We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.
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Xiao D, Huang J, Li J, Fu Y, Li Z. Inversion study of cadmium content in soil based on reflection spectroscopy and MSC-ELM model. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 283:121696. [PMID: 35987037 DOI: 10.1016/j.saa.2022.121696] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/21/2022] [Accepted: 07/28/2022] [Indexed: 06/15/2023]
Abstract
Heavy metal pollution in saline-alkali land has a significant impact on the ecological environment and human health. Rapid and accurate inversion of cadmium (Cd) element content in the saline-alkali land is important for environmental protection, saline-alkali soil improvement and conversion of saline-alkali land to cultivated land. Using traditional chemical detection methods to detect the content of heavy metal elements requires a long testing time and has the drawback of high prices. In this paper, we select the saline-alkali land of Zhenlai County as the study area and combine visible-NIR spectroscopy with machine learning models to invert the Cd content in the saline-alkali land. We preprocess the original reflection spectra using fractional order derivatives (FOD), then construct six three-band spectral indices (TBIs) and obtain the corresponding optimal band combination parameters by the optimal band combination (OBC) algorithm. To address the shortcomings of two-hidden-layer extreme learning machine (TELM), this paper introduces new weight parameters among the nodes of the first hidden layer, further extends it to multiple layers on this basis, and proposes the MSC-ELM model. The improved model is compared with several models, such as random forest (RF), partial least squares (PLS) and extreme learning machine (ELM). And the model performance is analyzed and compared by introducing several performance indicators, such as root mean square error (RMSE) and the ratio of the performance to interquartile (RPIQ). The experimental results show that the FOD transformation can eliminate the baseline drift and reduce the spectral noise. The constructed TBIs can effectively enhance the correlation with Cd content relative to the original single band, reduce redundant information and enhance the spectral features. The MSC-ELM model achieves better performance metrics compared to the other models and obtains the optimal prediction performance. This study provides an accurate and rapid method for the detection of Cd content in saline soil, which is important for the improvement and ecological recovery of saline soil.
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Zhu L, Xiao D, Ou YWX, He JJ, Yao YJ, Peng ZQ, Feng Y, Li JB, Chen M. [Analysis of the characteristics of delayed high-degree atrioventricular block after transcatheter aortic valve replacement]. ZHONGHUA YI XUE ZA ZHI 2022; 102:3611-3616. [PMID: 36480865 DOI: 10.3760/cma.j.cn112137-20220817-01754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Objective: To investigate the characteristics of delayed high-degree atrioventricular block (DHAVB) after transcatheter aortic valve replacement (TAVR). Methods: One hundred and seventy-six patients who underwent TAVR with a self-extending valve between May 2014 and November 2018 in the Department of Cardiology, West China Hospital of Sichuan University, were retrospectively enrolled, including 101 males and 75 females, aged 54-92 (73±7) years, and the data were collected during the perioperative and 30 d follow-up periods. According to the occurrence of HAVB after TAVR, 160 patients were divided into no-HAVB group (145 cases) and DHAVB group (15 cases), except 16 patients who developed HAVB within 2 days after TAVR. Baseline data, intraoperative data, and immediate postoperative ECG characteristics were compared between the two groups, and logistic regression models were used to analyze the factors associated with the occurrence of DHAVB after TAVR. Meanwhile, the diagnostic ability of the postoperative routine 12-lead ECG for DHAVB was evaluated using the ambulatory ECG findings as the standard diagnosis. Results: The incidence of DHAVB was 8.5% (15/176) and occurred at 5 (4, 6) d. Compared with the no-HAVB group. The percentage of no new conduction block on the immediate postoperative ECG was lower in the DHAVB group [6/15 vs 66.2%(96/145), P=0.044], and the percentage of new right bundle branch block on the immediate postoperative ECG was higher [4/15 vs 3.4%(5/145), P=0.002]. Multifactorial logistic regression analysis showed that right bundle branch block on the immediate postoperative ECG [OR (95%CI):6.60 (1.26-34.47), P=0.025] was an associated factor for the development of DHAVB after TAVR. The specificity of postoperative routine 12-lead ECG for the diagnosis of DHAVB was 100% (145/145), but the sensitivity was only 73.3% (11/15). Conclusions: The incidence of DHAVB after TAVR is also high in Chinese. The immediate postoperative ECG characteristics of patients who underwent TAVR are associated with DHAVB events, and applying these characteristics to risk stratify patients may optimize the management of DHAVB after TAVR.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, 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, 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, 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, Dong J, Dong LY, Dong MY, Dong X, Du SX, 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 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 TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, 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 HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, 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 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, 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 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 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, Pelizaeus M, Peng HP, Peters K, Pettersson J, 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, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, 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 BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, 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 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 SY, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang L, Yang SL, Yang T, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, 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 XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, 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 BS, Zou JH. Study of the Semileptonic Decay Λ_{c}^{+}→Λe^{+}ν_{e}. PHYSICAL REVIEW LETTERS 2022; 129:231803. [PMID: 36563214 DOI: 10.1103/physrevlett.129.231803] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 11/01/2022] [Indexed: 06/17/2023]
Abstract
The study of the Cabibbo-favored semileptonic decay Λ_{c}^{+}→Λe^{+}ν_{e} is reported using a 4.5 fb^{-1} data sample of e^{+}e^{-} annihilations collected at center-of-mass energies ranging from 4.600 GeV to 4.699 GeV with the BESIII detector at the BEPCII collider. The branching fraction of the decay is measured to be B(Λ_{c}^{+}→Λe^{+}ν_{e})=(3.56±0.11_{stat}±0.07_{syst})%, which is the most precise measurement to date. Furthermore, we perform an investigation of the internal dynamics in Λ_{c}^{+}→Λe^{+}ν_{e}. We provide the first direct comparisons of the differential decay rate and form factors with those predicted from lattice quantum chromodynamics (LQCD) calculations. Combining the measured branching fraction with a q^{2}-integrated rate predicted by LQCD, we determine |V_{cs}|=0.936±0.017_{B}±0.024_{LQCD}±0.007_{τ_{Λ_{c}}}.
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Jiang L, Wang Z, Wang L, Liu Y, Chen D, Zhang D, Shi X, Xiao D. Predictive value of the serum anion gap for 28-day in-hospital all-cause mortality in sepsis patients with acute kidney injury: a retrospective analysis of the MIMIC-IV database. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:1373. [PMID: 36660703 PMCID: PMC9843358 DOI: 10.21037/atm-22-5916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/19/2022] [Indexed: 01/01/2023]
Abstract
Background The kidney is one of the most vulnerable organs in sepsis patients, which mainly manifests as sepsis-associated acute kidney injury (SA-AKI). The case fatality rate of SA-AKI is high, and thus, predicting the risk of SA-AKI-related death is hugely significant. Anion gap (AG) is an important indicator in critical illness patients. The present study aimed to analyze the predictive value of the AG for the short-term prognosis of SA-AKI patients. Methods SA-AKI patient data from the Medical Information Mart for Intensive Care (MIMIC-IV) database were collected retrospectively. Hospitalized septic patients who meet the inclusion criteria were included in the final analysis. All laboratory test parameters only included the data generated within the first 24 hours after the patient entered the intensive care unit (ICU) and the extreme value. Univariate and multivariate logistic regression analyses were performed to analyze the risk factors related to the death of SA-AKI patients within 28 days during hospitalization in the ICU. Results A total of 3,684 SA-AKI patients were included, including 3,305 patients with low AG (<18 mmol/L) and 379 patients with high AG (≥18 mmol/L). Among these patients, 497 cases (13.5%) died during hospitalization, including 376 cases (11.4%) in the low AG group and 121 cases (31.9%) in the high AG group. Multivariate logistic regression analysis showed that elevated AG increased the risk of death in SA-AKI patients within 28 days during hospitalization in the ICU (odds ratio =1.2, 95% confidence interval: 1.2-1.3). Further analysis showed that the risk of death of SA-AKI patients within 28 days during hospitalization in the ICU was increased when AG ≥14 mmol/L. The relationship between AG level and the risk of death of SA-AKI patients during hospitalization was S-shaped. Conclusions In clinical practice, AG levels can serve as a valuable predictor of the death risk of SA-AKI patients during hospitalization.
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Wang Y, Yuan S, Shao C, Zhu W, Xiao D, Zhang C, Hou X, Li Y. BcOPR3 Mediates Defense Responses to Biotrophic and Necrotrophic Pathogens in Arabidopsis and Non-heading Chinese Cabbage. PHYTOPATHOLOGY 2022; 112:2523-2537. [PMID: 35852468 DOI: 10.1094/phyto-02-22-0049-r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In plants, the salicylic acid (SA) and jasmonic acid (JA) signaling pathways usually mediate the defense response to biotrophic and necrotrophic pathogens, respectively. Our previous work showed that after non-heading Chinese cabbage (NHCC) was infected with the biotrophic pathogen Hyaloperonospora parasitica, expression of the JA biosynthetic gene BcOPR3 is induced; however, its molecular mechanism remains unclear. Here, we overexpressed BcOPR3 in Arabidopsis and silenced BcOPR3 in NHCC001 plants to study the defensive role of BcOPR3 in plants against pathogen invasion. The results showed that overexpression of BcOPR3 increased the susceptibility of Arabidopsis to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000) but enhanced its resistance to Botrytis cinerea. BcOPR3-silenced NHCC001 plants with a 50% reduction in BcOPR3 expression increased their resistance to downy mildew by reducing the hyphal density and spores of H. parasitica. In addition, BcOPR3-partly silenced NHCC001 plants were also resistant to B. cinerea, which could be the result of a synergistic effect of JA and SA. These findings indicate a complicated role of BcOPR3 in the mediating defense responses to biotrophic and necrotrophic pathogens.
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Auer JMT, Murphy LC, Xiao D, Li DU, Wheeler AP. Non-fitting FLIM-FRET facilitates analysis of protein interactions in live zebrafish embryos. J Microsc 2022. [PMID: 36448983 DOI: 10.1111/jmi.13162] [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: 09/12/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 12/05/2022]
Abstract
Molecular interactions are key to all cellular processes, and particularly interesting to investigate in the context of gene regulation. Protein-protein interactions are challenging to examine in vivo as they are dynamic, and require spatially and temporally resolved studies to interrogate them. Foerster Resonance Energy Transfer (FRET) is a highly sensitive imaging method, which can interrogate molecular interactions. FRET can be detected by Fluorescence Lifetime Imaging Microscopy (FLIM-FRET), which is more robust to concentration variations and photobleaching than intensity-based FRET but typically needs long acquisition times to achieve high photon counts. New variants of non-fitting lifetime-based FRET perform well in samples with lower signal and require less intensive instrument calibration and analysis, making these methods ideal for probing protein-protein interactions in more complex live 3D samples. Here we show that a non-fitting FLIM-FRET variant, based on the Average Arrival Time of photons per pixel (AAT- FRET), is a sensitive and simple way to detect and measure protein-protein interactions in live early stage zebrafish embryos.
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Wu Y, Huang D, Kong G, Zhang C, Zhang H, Zhao G, Zhang T, Liu Z, Xiao D, Tan T, Li W, Wang J. Geographical Origin Determination of Cigar at Different Spatial Scales Based on C and N Metabolites and Mineral Elements Combined with Chemometric Analysis. Biol Trace Elem Res 2022:10.1007/s12011-022-03499-7. [PMID: 36441496 DOI: 10.1007/s12011-022-03499-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/18/2022] [Indexed: 11/29/2022]
Abstract
In this paper, five C and N metabolites and eighteen mineral elements were used to identify the cigar's geographical origin on a country scale (Dominica, Indonesia, and China) and on a prefecture scale (Yuxi, Puer, and Lincang in China). The results show that the best origin traceability method is the combination of C and N metabolites and mineral elements method. Its. Its accuracy of cross-validation can achieve 95% on a country scale and 94% on a prefecture scale. Determination accuracy is ranked as identification by combination > mineral elements > C and N metabolites. For geo-origin determination of cigars, mineral element identification is better than that metabolite identification. The algorithm and factors for origin determination are selected. The results can be used to guide cigar agricultural practices and monitor and regulate the cigar in production and circulation.
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Cao T, Xiao D, Ji P, Zhang Z, Cai WX, Han C, Li W, Tao K. [Effects of exosomes from hepatocyte growth factor-modified human adipose mesenchymal stem cells on full-thickness skin defect in diabetic mice]. ZHONGHUA SHAO SHANG YU CHUANG MIAN XIU FU ZA ZHI 2022; 38:1004-1013. [PMID: 36418257 DOI: 10.3760/cma.j.cn501225-20220731-00330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To investigate the effects and mechanism of exosomes from hepatocyte growth factor (HGF)-modified human adipose mesenchymal stem cells (ADSCs) on full-thickness skin defect wounds in diabetic mice. Methods: The experimental study method was adopted. Discarded adipose tissue of 3 healthy females (10-25 years old) who underwent abdominal surgery in the Department of Plastic Surgery of First Affiliated Hospital of Air Force Medical University from February to May 2021 was collected, and primary ADSCs were obtained by collagenase digestion method and cultured for 7 days. Cell morphology was observed by inverted phase contrast microscope. The ADSCs of third passage were transfected with HGF lentivirus and cultured for 5 days, and then the fluorescence of cells was observed by imaging system and the transfection rate was calculated. The exosomes of ADSCs of the third to sixth passages and the HGF transfected ADSCs of the third to sixth passages were extracted by density gradient centrifugation, respectively, and named, ADSC exosomes and HGF-ADSC exosomes. The microscopic morphology of exosomes was observed by transmission electron microscopy, and the positive expressions of CD9, CD63, and CD81 of exosomes were detected by flow cytometry, respectively. Twenty-four 6-week-old male Kunming mice were selected to make the diabetic models, and full-thickness skin defect wounds were made on the backs of mice. According to the random number table method, the mice were divided into phosphate buffer solution (PBS) group, HGF alone group, ADSC exosome alone group, and HGF-ADSC exosome group, with 6 mice in each group, and treated accordingly. On post injury day (PID) 3, 7, 10, and 14, the wounds were observed and the wound healing rate was calculated; the blood flow intensity of wound base was detected by Doppler flowmeter and the ratio of relative blood flow intensity on PID 10 was calculated. On PID 10, the number of Ki67 positive cells in wounds was detected by immunofluorescence method, and the number of new-vascularity of CD31 positive staining and tubular neovascularization in the wounds was detected by immunohistochemistry method; the protein expressions of protein endothelial nitric oxide synthase (eNOS), phosphatidylinositol 3-kinase (PI3K), phosphorylated PI3K (p-PI3K), protein kinase B (Akt) and phosphorylated Akt (p-Akt) in wounds were detected by Western blotting, and the ratios of p-PI3K to PI3K and p-Akt to Akt were calculated. On PID 14, the defect length and collagen regeneration of wound skin tissue were detected by hematoxylin and eosin staining and Masson staining, respectively, and the collagen volume fraction (CVF) was calculated. The number of samples is 3 in all cases. Data were statistically analyzed with repeated measurement analysis of variance, one-way analysis of variance, and Tukey test. Results: After 7 days of culture, the primary ADSCs were spindle shaped and arranged in vortex shape after dense growth. After 5 days of culture, HGF transfected ADSCs of the third passage carried green fluorescence, and the transfection rate was 85%. The ADSC exosomes and HGF-ADSC exosomes were similar in microscopic morphology, showing vesicular structures with an average particle size of 103 nm and 98 nm respectively, and both were CD9, CD63, and CD81 positive. On PID 3, the wounds of mice in the 4 groups were all red and swollen, with a small amount of exudate. On PID 7, the wounds of HGF-ADSC exosome group were gradually reduced, while the wounds of the other three groups were not significantly reduced. On PID 10, the wounds in the 4 groups were all reduced and scabbed. On PID 14, the wounds in HGF-ADSC exosome group were basically healed, while the residual wounds were found in the other three groups. On PID 3, the healing rates of wounds in the four groups were similar (P>0.05); On PID 7 and 10, the wound healing rates in HGF-ADSC exosome group were significantly higher than those in PBS group, HGF alone group, and ADSC exosome alone group, respectively (with q values of 13.11, 13.11, 11.89, 12.85, 11.28, and 7.74, respectively, all P<0.01); on PID 14, the wound healing rate in HGF-ADSC exosome group was significantly higher than that in PBS group, HGF alone group, and ADSC exosome alone group (with q values of 15.50, 11.64, and 6.36, respectively, all P<0.01). On PID 3, there was no obvious blood supply in wound base of mice in the 4 groups. On PID 7, microvessels began to form in the wound base of HGF-ADSC exosome group, while the wound base of the other three groups was only congested at the wound edge. On PID 10, microvessel formation in wound base was observed in the other 3 groups except in PBS group, which had no obvious blood supply. On PID 14, the blood flow intensity of wound base in HGF-ADSC exosome group was stronger than that in the other 3 groups, and the distribution was uniform. On PID 10, the ratio of wound base relative blood flow intensity in HGF-ADSC exosome group was significantly higher than that in PBS group, HGF alone group, and ADSC exosome alone group (with q values of 23.73, 19.32, and 9.48, respectively, all P<0.01); The numbers of Ki67-positive cells and new-vascularity of wounds in HGF-ADSC exosome group were significantly higher than those in PBS group, HGF alone group, and ADSC exosome alone group, respectively (with q values of 19.58, 18.20, 11.04, 20.68, 13.79, and 8.12, respectively, P<0.01). On PID 10, the protein expression level of eNOS of wounds in HGF-ADSC exosome group was higher than that in PBS group, HGF alone group, and ADSC exosome alone group (with q values of 53.23, 42.54, and 26.54, respectively, all P<0.01); the ratio of p-PI3K to PI3K and the ratio of p-Akt to Akt of wounds in HGF-ADSC exosome group were significantly higher than those in PBS group, HGF alone group, and ADSC exosome alone group, respectively (with q values of 16.11, 11.78, 6.08, 65.54, 31.63, and 37.86, respectively, P<0.01). On PID 14, the length of skin tissue defect in the wounds of HGF-ADSC exosome group was shorter than that in PBS group, HGF alone group, and ADSC exosome alone group (with q values of 20.51, 18.50, and 11.99, respectively, all P<0.01); the CVF of wounds in HGF-ADSC exosome group was significantly higher than that in PBS group, HGF alone group and ADSC exosome alone group (with q values of 31.31, 28.52, and 12.35, respectively, all P<0.01). Conclusions: Human HGF-ADSC exosomes can significantly promote wound healing in diabetic mice by increasing neovascularization in wound tissue, and the mechanism may be related to the increased expression of eNOS in wounds by activating PI3K/Akt signaling pathway.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, 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, 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, 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, Dong J, Dong LY, Dong MY, Dong X, Du SX, 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 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 TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, 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 HB, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, 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 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, 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 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 J, 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, 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, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sang HS, 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 XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, 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 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 L, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, 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 ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, 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 BS, Zou JH. Measurement of the Absolute Branching Fraction and Decay Asymmetry of Λ→nγ. PHYSICAL REVIEW LETTERS 2022; 129:212002. [PMID: 36461970 DOI: 10.1103/physrevlett.129.212002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/27/2022] [Accepted: 10/24/2022] [Indexed: 06/17/2023]
Abstract
The radiative hyperon decay Λ→nγ is studied using (10087±44)×10^{6} J/ψ events collected with the BESIII detector operating at BEPCII. The absolute branching fraction of the decay Λ→nγ is determined to be (0.832±0.038_{stat}±0.054_{syst})×10^{-3}, which is a factor of 2.1 lower and 5.6 standard deviations different than the previous measurement. By analyzing the joint angular distribution of the decay products, the first determination of the decay asymmetry α_{γ} is reported with a value of -0.16±0.10_{stat}±0.05_{syst}.
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Liang CX, Liang GY, Liu HF, Zheng XQ, Xiao D, Huang YX, Chen C, Yu T, Yin D, Chang YB. [Characteristics and risk factors of spinal epidural hematoma after unilateral biportal endoscopic lumbar interbody fusion]. ZHONGHUA YI XUE ZA ZHI 2022; 102:3267-3273. [PMID: 36319178 DOI: 10.3760/cma.j.cn112137-20220512-01040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To investigate the incidence, characteristics and risk factors of spinal epidural hematoma after unilateral biportal endoscopic (UBE) lumbar spine surgery. Methods: The clinical data of 105 patients who underwent lumbar spine surgery under UBE in Guangdong Provincial People's Hospital from February 2020 to March 2021 were retrospectively reviewed. Of the patients, 48(45.7%) were male and 57(54.3%) were female, the mean age was (60.1±11.4) years (ranged 26 to 85 years). The MRI images at the third day post-surgery were observed, and the occurrence of hematoma was counted. Patients were assigned to normal group and hematoma group based on the presence of hematoma or not. The related clinical indicators of each patients were collected and used for comparison between two different groups. Logistic stepwise regression model was used to analyze whether each index was a risk factor for hematoma after the UBE lumbar fusion. Results: The total hematoma incidence rate was 28.6%(30/105), the symptomatic hematoma rate was 6.7%(7/105), and the hematoma reoperation rate was 0.9%(1/105). Univariate logistic regression analysis showed that hypertension (OR=3.368, 95%CI: 1.389-8.171), diabetes (OR=3.589, 95%CI: 1.230-10.476), admission systolic blood pressure>140 mmHg (1 mmHg=0.133 kPa,OR=3.687, 95%CI: 1.493-9.017), platelets<200×109/L (OR=0.300, 95%CI: 0.119-0.785), preoperative blood calcium<2.25 mmol/L (OR=0.340, 95%CI: 0.142-0.818), spinal stenosis grade D (OR=4.462, 95%CI: 1.810-10.996) were possible risk factors for spinal hematoma after UBE lumbar fusion. Multivariate logistic regression analysis showed that admission blood pressure systolic blood pressure>140 mmHg (OR=3.788, 95%CI:1.055-13.606), preoperative blood calcium<2.25 mmol/L (OR=78.544, 95%CI:3.895-1 584.058) and spinal stenosis grade D (OR=3.698, 95%CI:1.110-12.325) were risk factors for spinal hematoma after UBE lumbar fusion (all P<0.05). Conclusion: The types of spinal canal hematoma after UBE lumbar fusion include localized and extended type. The risk factors for hematoma include high systolic blood pressure on admission, low preoperative blood calcium and severe spinal stenosis.
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Zhu H, Xie D, Yang Y, Wang Y, Huang R, Chen X, Wang B, Peng Y, Wang J, Xiao D, Wu D, Qian C, Deng X. The Immune Response and Intestinal Injury after X-Ray FLASH Irradiation in Murine Breast Cancer Transplanted Models. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Observation of an a_{0}-like State with Mass of 1.817 GeV in the Study of D_{s}^{+}→K_{S}^{0}K^{+}π^{0} Decays. PHYSICAL REVIEW LETTERS 2022; 129:182001. [PMID: 36374689 DOI: 10.1103/physrevlett.129.182001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 07/08/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
Using e^{+}e^{-} annihilation data corresponding to an integrated luminosity of 6.32 fb^{-1} collected at center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we perform the first amplitude analysis of the decay D_{s}^{+}→K_{S}^{0}K^{+}π^{0} and determine the relative branching fractions and phases for intermediate processes. We observe an a_{0}-like state with mass of 1.817 GeV in its decay to K_{S}^{0}K^{+} for the first time. In addition, we measure the ratio {B[D_{s}^{+}→K[over ¯]^{*}(892)^{0}K^{+}]/B[D_{s}^{+}→K[over ¯]^{0}K^{*}(892)^{+}]} to be 2.35_{-0.23stat}^{+0.42}±0.10_{syst}. Finally, we provide a precision measurement of the absolute branching fraction B(D_{s}^{+}→K_{S}^{0}K^{+}π^{0})=(1.46±0.06_{stat}±0.05_{syst})%.
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