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Sun J, Wang W, Ma Q, Pan X, Zhai H, Wang J, Han Y, Li Y, Wang Y. Necrostatin-1s Suppresses RIPK1-driven Necroptosis and Inflammation in Periventricular Leukomalacia Neonatal Mice. Neurochem Res 2024; 49:129-141. [PMID: 37642893 DOI: 10.1007/s11064-023-04013-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/31/2023]
Abstract
Periventricular leukomalacia (PVL), a predominant form of brain injury in preterm survivors, is characterized by hypomyelination and microgliosis and is also the major cause of long-term neurobehavioral abnormalities in premature infants. Receptor-interacting protein kinase 1 (RIPK1) plays a pivotal role in mediating cell death and inflammatory signaling cascade. However, very little is known about the potential effect of RIPK1 in PVL and the underlying mechanism. Herein, we found that the expression level of RIPK1 was drastically increased in the brain of PVL neonatal mice models, and treatment of PVL neonatal mice with Necrostatin-1s (Nec-1s), an inhibitor of RIPK1, greatly ameliorated cerebral ischemic injury, exhibiting an increase of body weights, reduction of cerebral infarct size, neuronal loss, and occurrence of necrosis-like cells, and significantly improved the long-term abnormal neurobehaviors of PVL. In addition, Nec-1s significantly suppressed hypomyelination and promoted the differentiation of oligodendrocyte precursor cells (OPCs), as demonstrated by the increased expression levels of MBP and Olig2, the decreased expression level of GPR17, a significant increase in the number of CC-1-positive cells, and suppression of myelin ultrastructure impairment. Moreover, the mechanism of neuroprotective effects of Nec-1s against PVL is closely associated with its suppression of the RIPK1-mediated necrosis signaling molecules, RIPK1, PIPK3, and MLKL. More importantly, inhibition of RIPK1 could reduce microglial inflammatory injury by triggering the M1 to M2 microglial phenotype, appreciably decreasing the levels of M1 marker CD86 and increasing the levels of M2 markers Arg1 or CD206 in PVL mice. Taken together, inhibition of RIPK1 markedly ameliorates the brain injury and long-term neurobehavioral abnormalities of PVL mice through the reduction of neural cell necroptosis and reversing neuroinflammation.
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Cassim Bawa FN, Hu S, Gopoju R, Shiyab A, Mongan K, Xu Y, Pan X, Clark A, Wang H, Zhang Y. Adipocyte retinoic acid receptor α prevents obesity and steatohepatitis by regulating energy expenditure and lipogenesis. Obesity (Silver Spring) 2024; 32:120-130. [PMID: 37873741 PMCID: PMC10840967 DOI: 10.1002/oby.23929] [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: 05/23/2023] [Revised: 08/13/2023] [Accepted: 09/03/2023] [Indexed: 10/25/2023]
Abstract
OBJECTIVE The adipose tissue-liver axis is a major regulator of the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Retinoic acid signaling plays an important role in development and metabolism. However, little is known about the role of adipose retinoic acid signaling in the development of obesity-associated NAFLD. In this work, the aim was to investigate whether and how retinoic acid receptor alpha (RARα) regulated the development of obesity and NAFLD. METHODS RARα expression in adipose tissue of db/db or ob/ob mice was determined. Rarαfl/fl mice and adipocyte-specific Rarα-/- (RarαAdi-/- ) mice were fed a chow diet for 1 year or high-fat diet (HFD) for 20 weeks. Primary adipocytes and primary hepatocytes were co-cultured. Metabolic regulation and inflammatory response were characterized. RESULTS RARα expression was reduced in adipose tissue of db/db or ob/ob mice. RarαAdi-/- mice had increased obesity and steatohepatitis (NASH) when fed a chow diet or HFD. Loss of adipocyte RARα induced lipogenesis and inflammation in adipose tissue and the liver and reduced thermogenesis. In the co-culture studies, loss of RARα in adipocytes induced inflammatory and lipogenic programs in hepatocytes. CONCLUSIONS The data demonstrate that RARα in adipocytes prevents obesity and NASH via inhibiting lipogenesis and inflammation and inducing energy expenditure.
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Pan X, Zhao Z, Huang X, Cen X. Circ-Slain2 Alleviates Cartilage Degradation and Inflammation of TMJOA. J Dent Res 2023; 102:1498-1506. [PMID: 37817544 DOI: 10.1177/00220345231198448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/12/2023] Open
Abstract
Temporomandibular joint osteoarthritis (TMJOA) is a degenerative disease with the cessation of matrix anabolism and aggravation of inflammation, which results in severe pain and impaired joint function. However, the mechanisms are not well understood. Circular RNAs (circRNAs) are reported to have various biological functions and participate in the development, diagnosis, prognosis, and treatment of different diseases. This study aimed to investigate the roles and mechanisms of circ-slain2 in TMJOA. We first established TMJOA mouse models and found circ-slain2 was lowly expressed in the cartilage of TMJOA through sequencing data. We observed that circ-slain2 is predominantly localized in the cytoplasm and downregulated in mouse condylar chondrocytes (mCCs) treated with tumor necrosis factor α (TNFα) and interferon γ (IFNγ). Micro-computed tomography and histological examination showed that intra-articular injection of circ-slain2 overexpressing adeno-associated virus could alleviate cartilage catabolism and synovial inflammation to relieve TMJOA in vivo. In addition, elevated circ-slain2 also showed anticatabolic and anti-inflammatory effects on IFNγ- and TNFα-stimulated mouse condylar chondrocytes (mCCs). Functional enrichment analysis indicated that protein processing in endoplasmic reticulum (ER) was associated with TMJOA, and further functional experiments confirmed that circ-slain2 could suppress ER stress in OA mCCs. RNA binding protein immunoprecipitation assay revealed an overt interaction between activating transcription factor 6 (ATF6) and circ-slain2. Inhibition of the expression of both ATF6 and circ-slain2 resulted in dilation of the ER and enhanced the expression of ER stress markers, whose ER stress level was higher than inhibition of ATF6 but lower than knockdown of circ-slain2 expression. Collectively, our research demonstrated that circ-slain2 could regulate ATF6 to relieve ER stress, reducing temporomandibular joint cartilage degradation and synovial inflammation. These findings provide prospects for developing novel osteoarthritis therapies based on circ-slain2 by focusing on reducing the inflammation of synovium and the imbalance between matrix synthesis and degradation.
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Pan X, Huang C, Peng A, Zhang Z. Immunohistochemical localisation of aquaporin 2 and vasopressin type 2 receptor in the human endolymphatic sac. J Laryngol Otol 2023; 137:1340-1344. [PMID: 36502818 DOI: 10.1017/s0022215122002444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE This study aimed to determine the distribution and subcellular localisation of aquaporin 2 and vasopressin type 2 receptor in the human endolymphatic sac. METHODS Ten samples of human endolymphatic sac were collected during acoustic neurinoma removal using the translabyrinthine approach. Immunohistochemistry and immunofluorescence were performed using aquaporin 2 and vasopressin type 2 receptor monoclonal antibodies. RESULTS Confocal microscopy demonstrated that vasopressin type 2 receptor labelling was expressed in both the apical and basolateral plasma membranes, and in the cytoplasm of the endolymphatic sac epithelium, whereas aquaporin 2 was strongly expressed at the basolateral site of the endolymphatic sac epithelium, in both the intraosseous and extraosseous parts of the endolymphatic sac. CONCLUSION Both aquaporin 2 and vasopressin type 2 receptor were detected in the epithelial cells of the human endolymphatic sac, suggesting that this channel may be involved in inner-ear fluid homeostasis. However, strong basolateral expression of aquaporin 2 in endolymphatic sac epithelium suggested that the function of aquaporin 2 may differ between the endolymphatic sac and kidney.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, 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 MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner MK, Kui X, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner 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, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang 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. Test of CP Symmetry in Hyperon to Neutron Decays. PHYSICAL REVIEW LETTERS 2023; 131:191802. [PMID: 38000397 DOI: 10.1103/physrevlett.131.191802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 10/03/2023] [Indexed: 11/26/2023]
Abstract
The quantum entangled J/ψ→Σ^{+}Σ[over ¯]^{-} pairs from (1.0087±0.0044)×10^{10} J/ψ events taken by the BESIII detector are used to study the nonleptonic two-body weak decays Σ^{+}→nπ^{+} and Σ[over ¯]^{-}→n[over ¯]π^{-}. The CP-odd weak decay parameters of the decays Σ^{+}→nπ^{+} (α_{+}) and Σ[over ¯]^{-}→n[over ¯]π^{-} (α[over ¯]_{-}) are determined to be 0.0481±0.0031_{stat}±0.0019_{syst} and -0.0565±0.0047_{stat}±0.0022_{syst}, respectively. The decay parameter α[over ¯]_{-} is measured for the first time, and the accuracy of α_{+} is improved by a factor of 4 compared to the previous results. The simultaneously determined decay parameters allow the first precision CP symmetry test for any hyperon decay with a neutron in the final state with the measurement of A_{CP}=(α_{+}+α[over ¯]_{-})/(α_{+}-α[over ¯]_{-})=-0.080±0.052_{stat}±0.028_{syst}. Assuming CP conservation, the average decay parameter is determined as ⟨α_{+}⟩=(α_{+}-α[over ¯]_{-})/2=-0.0506±0.0026_{stat}±0.0019_{syst}, while the ratios α_{+}/α_{0} and α[over ¯]_{-}/α[over ¯]_{0} are -0.0490±0.0032_{stat}±0.0021_{syst} and -0.0571±0.0053_{stat}±0.0032_{syst}, where α_{0} and α[over ¯]_{0} are the decay parameters of the decays Σ^{+}→pπ^{0} and Σ[over ¯]^{-}→p[over ¯]π^{0}, respectively.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YHY, 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, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu 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, Qiao XK, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Measurement of Energy-Dependent Pair-Production Cross Section and Electromagnetic Form Factors of a Charmed Baryon. PHYSICAL REVIEW LETTERS 2023; 131:191901. [PMID: 38000396 DOI: 10.1103/physrevlett.131.191901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/29/2023] [Accepted: 09/15/2023] [Indexed: 11/26/2023]
Abstract
We study the process e^{+}e^{-}→Λ_{c}^{+}Λ[over ¯]_{c}^{-} at twelve center-of-mass energies from 4.6119 to 4.9509 GeV using data samples collected by the BESIII detector at the BEPCII collider. The Born cross sections and effective form factors (|G_{eff}|) are determined with unprecedented precision after combining the single and double-tag methods based on the decay process Λ_{c}^{+}→pK^{-}π^{+}. Flat cross sections around 4.63 GeV are obtained and no indication of the resonant structure Y(4630), as reported by Belle, is found. In addition, no oscillatory behavior is discerned in the |G_{eff}| energy dependence of Λ_{c}^{+}, in contrast to what is seen for the proton and neutron cases. Analyzing the cross section together with the polar-angle distribution of the Λ_{c}^{+} baryon at each energy point, the moduli of electric and magnetic form factors (|G_{E}| and |G_{M}|) are extracted and separated. For the first time, the energy dependence of the form factor ratio |G_{E}/G_{M}| is observed, which can be well described by an oscillatory function.
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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 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, Hou 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, Kui 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 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, 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. Determination of Spin-Parity Quantum Numbers for the Narrow Structure near the pΛ[over ¯] Threshold in e^{+}e^{-}→pK^{-}Λ[over ¯]+c.c. PHYSICAL REVIEW LETTERS 2023; 131:151901. [PMID: 37897776 DOI: 10.1103/physrevlett.131.151901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/22/2023] [Accepted: 09/15/2023] [Indexed: 10/30/2023]
Abstract
A narrow structure in the pΛ[over ¯] system near the mass threshold, named as X(2085), is observed in the process e^{+}e^{-}→pK^{-}Λ[over ¯] with a statistical significance greater than 20σ. Its spin and parity are determined for the first time to be J^{P}=1^{+} in an amplitude analysis, with a statistical significance greater than 5σ over other quantum numbers (0^{-},1^{-} and 2^{+}). The pole positions of X(2085) are measured to be M_{pole}=(2084_{-2}^{+4}±9) MeV and Γ_{pole}=(58_{-3}^{+4}±25) MeV, where the first uncertainties are statistical and the second ones are systematic. The analysis is based on the study of the process e^{+}e^{-}→pK^{-}Λ[over ¯] and uses the data samples collected with the BESIII detector at the center-of-mass energies sqrt[s]=4.008, 4.178, 4.226, 4.258, 4.416, and 4.682 GeV with a total integrated luminosity of 8.35 fb^{-1}.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, X K, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner 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, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang 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. Precise Measurement of the e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} Cross Sections at Center-of-Mass Energies from Threshold to 4.95 GeV. PHYSICAL REVIEW LETTERS 2023; 131:151903. [PMID: 37897771 DOI: 10.1103/physrevlett.131.151903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/16/2023] [Accepted: 08/29/2023] [Indexed: 10/30/2023]
Abstract
The process e^{+}e^{-}→D_{s}^{*+}D_{s}^{*-} is studied with a semi-inclusive method using data samples at center-of-mass energies from threshold to 4.95 GeV collected with the BESIII detector operating at the Beijing Electron Positron Collider. The Born cross sections of the process are measured for the first time with high precision in this energy region. Two resonance structures are observed in the energy-dependent cross sections around 4.2 and 4.4 GeV. By fitting the cross sections with a coherent sum of three Breit-Wigner amplitudes and one phase-space amplitude, the two significant structures are assigned masses of (4186.8±8.7±30) and (4414.6±3.4±6.1) MeV/c^{2}, widths of (55±15±53) and (122.5±7.5±8.1) MeV, where the first errors are statistical and the second ones are systematic. The inclusion of a third Breit-Wigner amplitude is necessary to describe a structure around 4.79 GeV.
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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, Hou 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, Kui 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, 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 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 Experimental Study of the Purely Leptonic Decay D_{s}^{*+}→e^{+}ν_{e}. PHYSICAL REVIEW LETTERS 2023; 131:141802. [PMID: 37862669 DOI: 10.1103/physrevlett.131.141802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/25/2023] [Accepted: 09/05/2023] [Indexed: 10/22/2023]
Abstract
Using 7.33 fb^{-1} of e^{+}e^{-} collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay D_{s}^{*+}→e^{+}ν_{e}. Our data contain a signal of this decay with a statistical significance of 2.9σ. The branching fraction of D_{s}^{*+}→e^{+}ν_{e} is measured to be (2.1_{-0.9_{stat}}^{+1.2}±0.2_{syst})×10^{-5}, corresponding to an upper limit of 4.0×10^{-5} at the 90% confidence level. Taking the total width of the D_{s}^{*+} [(0.070±0.028) keV] predicted with the radiative D_{s}^{*+} decay from the lattice QCD calculation as input, the decay constant of the D_{s}^{*+} is determined to be f_{D_{s}^{*+}}=(214_{-46_{stat}}^{+61}±44_{syst}) MeV, corresponding to an upper limit of 354 MeV at the 90% confidence level.
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Willers H, Pan X, Chamseddine I, Grassberger C, Benes CH. Landscape of the Radiosensitizing Properties of Targeted Agents from the NCI CTEP Portfolio across Genomically Diverse 3D Tumor Models. Int J Radiat Oncol Biol Phys 2023; 117:S101. [PMID: 37784269 DOI: 10.1016/j.ijrobp.2023.06.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Clinical translation of molecular targeted radiosensitizers remains challenging. To improve the robustness of preclinical data, we sought to broadly examine across a wide spectrum of genomic cancer features the radiosensitizing properties of targeted drugs from the NCI Cancer Therapy Evaluation Program (CTEP). MATERIALS/METHODS As part of a U01 Consortium, we adapted a robotic high-throughput platform for testing ionizing radiation (IR) plus drug combinations in 3D cultures derived from non-small cell lung carcinoma (NSCLC), head/neck (HNSCC), and pancreatic cancers. All cell lines were annotated, mycoplasma free, and re-authenticated. Signal windows were established for all 3D growth formats. CTEP drugs were added in four concentrations 24 hours prior to IR exposure of 384-well plates. Five days after IR, cell viability was assessed, an endpoint previously benchmarked using colony formation. Each data point was based on 4-6 technical replicates with 2 biological repeats. A multistep statistical method combining Wilcoxon signed-rank and Spearman rank-order correlation tests together with adjusted Benjamini-Hochberg corrections for multiple comparisons was used to identify radiosensitization hits. Select validation experiments of hits were carried out. RESULTS We screened 73 3D tumor models with 34-42 CTEP drugs each plus IR (n = 10,744 cell line/drug concentration combinations). IR/drug patterns were comparable for the three cancer types. DNA damage response (DDR) inhibitors constituted the most active class of radiosensitizers with DNA-PKcs, PARP, and ATR being the top targets. In contrast, the majority of the other agents radiosensitized only a minority of models. Highlighting NSCLC, out of 1,120 cell line/drug combinations, 328 (29.3%) were associated with statistically significant radiosensitization. PARP inhibitors, of particular interest for clinical translation in this space, demonstrated relatively broad radiosensitization for talazoparib (62%) and olaparib (44%) but less so for veliparib (28%), which correlated with differential PARP trapping potentials. Radiosensitization was evident even for tumor genotypes associated with radioresistance such as mutant KRAS, KEAP1, and STK11. Interestingly, single-agent activity of olaparib was more pronounced in 11/30 3D cultures compared to 2D growth conditions but with only 2/11 having known homologous recombination defects. Lastly, for HPV negative HNSCC (735 combinations), there was radiosensitization in subsets of models for IAP, ATR, and AKT targets, which are under clinical investigation. CONCLUSION We present a unique resource for examining radiosensitizing drug properties in 3D cultures. The observed radiosensitization patterns strongly argue for the use of larger panels of clinically relevant tumor models rather than a few non-representative cell lines. Our data highlight the urgent need for predictive biomarkers to guide IR/drug combinations, even for some DDR inhibitors.
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Pan X, Feng T, Liu J, Liu C, Qi X. An Adaptive Multi-Feature Fusion Network for Predicting Overall Survival of Patients with Head and Neck Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e611-e612. [PMID: 37785840 DOI: 10.1016/j.ijrobp.2023.06.1986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Accurate prognostic prediction could allow personalized treatment to achieve optimal clinical outcome. We aimed to develop a highly predictive overall survival model, considering the complementary relationships between clinical information, traditional radiomics and deep image information, to further improve the overall prediction accuracy by constructing a richer feature set and adaptive weighting. MATERIALS/METHODS A total of 427 patients with Oropharyngeal Cancer (OPC) patients from the TCIA database were included. 341 cases were used for training, 86 cases were used as an independent cohort. Patient characteristics, including TMN, age, gender, HPV status, smoking or drinking status, etc. were considered as potential predictors. Traditional radiomics features of gross tumor volume (GTV) was extracted from planning CT using open-source software. In addition, a two-dimensional convolutional network (2D_CNN) was designed to extract deep image features. An adaptive multi-feature fusion network was developed to predict overall survival of patients based on three types of features. The fusion network integrates an attention mechanism to the channel dimension to obtain proper weighting of each channel in the feature graph through the fully connected network by focusing on effective feature channels and automatic learning according to the loss, thus improving the utilization rate of effective features. The model performance was evaluated using the area-under-ROC-curve (AUC), accuracy, precision, recall, f1-score. RESULTS The AUCs of predictive models based on clinical features, traditional radiomics features and deep image features were 0.7, 0.61 and 0.72, respectively. Combining patient characteristics, radiomic features and deep imaging features, the AUCs of the prediction models was significantly improved to 0.85 and 0.86 (with attention mechanisms) for the independent test cohort (Table 1). CONCLUSION The proposed adaptive multi-channel network assigned effective weights to the potential predictors, selectively enhanced useful features while suppressed irrelevant features, enabling more accurate feature map weights. We demonstrated the improved predictive value, with a multi-channel fusion network integrated with an attention mechanism, for overall survival of OPC patients.
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Zhang P, Xiao J, Luo C, Liu X, Li C, Zhao J, Liu X, Pan X, Tian M. The Effect of JAK Inhibitor Tofacitinib on Chondrocyte Autophagy. Inflammation 2023; 46:1764-1776. [PMID: 37310645 DOI: 10.1007/s10753-023-01840-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/03/2023] [Accepted: 05/15/2023] [Indexed: 06/14/2023]
Abstract
Osteoarthritis (OA) is a multifactorial disease of the whole joint that has a complex pathogenesis. There is currently no cure for OA. Tofacitinib is a broad JAK inhibitor that can have an anti-inflammatory effect. The objective of this study was to investigate the effect of tofacitinib on the cartilage extracellular matrix in OA and determine whether tofacitinib exerts a protective effect by inhibiting the JAK1/STAT3 signaling pathway and upregulating autophagy in chondrocytes. We investigated the expression profile of OA in vitro by exposing SW1353 cells to interleukin-1β (IL-1β), and induced OA in vivo using the modified Hulth method in rats. We found that IL-1β promoted the expression of OA-related matrix metalloproteinases (MMP3 and MMP13), reduced the expression of collagen II, reduced the expression of beclin1 and LC3-II/I, and promoted the accumulation of p62 in SW1353 cells. Tofacitinib attenuated IL-1β-stimulated changes in MMPs and collagen II and restored autophagy. In IL-1β-stimulated SW1353 cells, the JAK1/STAT3 signaling pathway was activated. Tofacitinib inhibited the IL-1β-stimulated expression of p-JAK1 and p-STAT3 and prevented translocation of p-STAT3 to the nucleus. In the rat model of OA, tofacitinib reduced articular cartilage degeneration by delaying cartilage extracellular matrix degradation and increasing chondrocyte autophagy. Our study demonstrates that chondrocyte autophagy was impaired in experimental models of OA. Tofacitinib reduced the inflammatory response and restored the damaged autophagic flux in OA.
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Pan X, Liu C, Feng T, Qi X. A Novel Multi-Objective Based Feature Selection Method for Response Prediction. Int J Radiat Oncol Biol Phys 2023; 117:e611. [PMID: 37785839 DOI: 10.1016/j.ijrobp.2023.06.1985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Accurate response prediction is essential towards personalized treatment in radiation therapy. Excessive imaging features, extracted from medical images, pose a great challenge in radiomic analyses. Feature selection is an essential step to remove redundant and irrelevant features for model construction. MATERIALS/METHODS We proposed a novel multi-objective based radiomic feature selection method (MRMOPSO), where the number of features, sensitivity, and specificity are jointly considered as optimization objectives for feature selection. The MRMOPSO innovated by three aspects: 1) Fisher score initialize the feature population to speed up the convergence; 2) Min-redundancy particle generation operations to reduce the redundancy between radiomic features, a truncation strategy was also introduced; 3) Particle selection operation guided by elitism strategies to improve local search ability of the algorithm. We evaluated the effectiveness of the proposed MRMOPSO method using a cohort of oropharyngeal cancer patients from The Cancer Imaging Archive (TCIA). 357 patients were used for model training and additional 64 patients were used for independent evaluation. The proposed methods were compared with (a) classical feature selection methods, i.e., Lasso, minimal-redundancy-maximal-relevance criterion (mRMR), F-score, and mutual information (MI), (b) single-objective feature selection methods, i.e., genetic algorithm (GA), particle swarm optimization algorithm (PSO) and (c) multi-objective feature selection methods, i.e., multiple objective particle swarm optimization (MOPSO), nondominated sorting genetic algorithm II (NSGA II). RESULTS The other feature selection methods yielded AUCs, sensitivity, specificity of (0.48-0.71), (0.49-0.86), (0.33-0.67), respectively. The MRMOPSO achieved significantly highly AUC of 0.84 with smaller number of selected features on the independent dataset (Table 1). Additionally, the MRMOPSO remarkably improved the sensitivity (0.81), specificity (0.81) and achieved an excellent balance between sensitively and specificity. CONCLUSION We demonstrated a novel multi-objective based radiomic feature selection method. The proposed algorithm effectively reduced feature dimension, and achieved superior AUC with simultaneous improved sensitivity and specificity, for radiomic response prediction.
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Peng Z, Liu L, Sheng X, Liu H, Ding C, Wang B, Hong Y, Pan X, Meng Y. Risk Factors of Nonfusion after Anterior Cervical Decompression and Fusion in the Early Postoperative Period: A Retrospective Study. Orthop Surg 2023; 15:2574-2581. [PMID: 37538029 PMCID: PMC10549804 DOI: 10.1111/os.13835] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/16/2023] [Accepted: 06/24/2023] [Indexed: 08/05/2023] Open
Abstract
OBJECTIVE Although high fusion rates have been reported for anterior cervical decompression and fusion (ACDF) in the medium and long term, the risk of nonfusion in the early period after ACDF remains substantial. This study investigates early risk factors for cage nonfusion in patients undergoing single- or multi-level ACDF. METHODS This was a retrospective study. From August 2020 to December 2021, 107 patients with ACDF, including 197 segments, were enrolled, with a follow-up of 3 months. Among the 197 segments, 155 were diagnosed with nonfusion (Nonfusion group), and 42 were diagnosed with fusion (Fusion group) in the early period after ACDF. We assessed the significance of the patient-specific factors, radiographic indicators, serum factors, and clinical outcomes. The Wilcoxon rank sum test, t-tests, analysis of variance, and stepwise multivariate logistic regression were used for statistical analysis. RESULTS Univariate analysis showed that smoking, insufficient improvement in the C2-7 Cobb angle (p = 0.024) and the functional spinal unit Cobb angle (p = 0.022) between preoperative and postoperative stages and lower serum calcium (fusion: 2.34 ± 0.12 mmol/L; nonfusion: 2.28 ± 0.17 mmol/L, p = 0.003) β-carboxyterminal telopeptide end of type 1 collagen (β-CTX) (fusion: 0.51 [0.38, 0.71]; nonfusion: 0.43 [0.31, 0.57], p = 0.008), and N-terminal fragment of osteocalcin (N-MID-BGP) (fusion: 18.30 [12.15, 22.60]; nonfusion: 14.45 [11.65, 18.60], p = 0.023) are risk factors for nonfusion in the early period after ACDF. Stepwise logistic regression analysis revealed that poor C2-7 Cobb angle improvement (odds ratio [OR], 1.107 [1.019-1.204], p = 0.017) and lower serum calcium (OR, 3.700 [1.138-12.032], p = 0.030) are risk factors. CONCLUSIONS Patients with successful fusion after ACDF had higher preoperative serum calcium and improved C2-7 Cobb angle than nonfusion patients at 3 months. These findings suggest that serum calcium could be used to identify patients at risk of nonfusion following ACDF and that correcting the C2-7 Cobb angle during surgery could potentially increase fusion in the early period after ACDF.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An Q, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Dai HL, Dai JP, Dai XC, 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, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Gao YN, Gao Y, Gao Y, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Hao XQ, Harris FA, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Hussain T, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuemmel M, Kuessner MK, Kupsc A, Kurth MG, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li JQ, Li JW, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song WM, Song YX, Sosio S, Spataro S, Su KX, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang SL, Yang YH, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan W, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng Y, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang SF, Zhang XD, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, 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, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Search for Λ[over ¯]-Λ Baryon-Number-Violating Oscillations in the Decay J/ψ→pK^{-}Λ[over ¯]+c.c. PHYSICAL REVIEW LETTERS 2023; 131:121801. [PMID: 37802947 DOI: 10.1103/physrevlett.131.121801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/14/2023] [Accepted: 08/29/2023] [Indexed: 10/08/2023]
Abstract
We report on the first search for Λ[over ¯]-Λ oscillations in the decay J/ψ→pK^{-}Λ[over ¯]+c.c. by analyzing 1.31×10^{9} J/ψ events accumulated with the BESIII detector at the BEPCII collider. The J/ψ events are produced using e^{+}e^{-} collisions at a center of mass energy sqrt[s]=3.097 GeV. No evidence for hyperon oscillations is observed. The upper limit for the oscillation rate of Λ[over ¯] to Λ hyperons is determined to be P(Λ)=[B(J/ψ→pK^{-}Λ+c.c.)/B(J/ψ→pK^{-}Λ[over ¯]+c.c.)]<4.4×10^{-6} corresponding to an oscillation parameter δm_{ΛΛ[over ¯]} of less than 3.8×10^{-18} GeV at the 90% confidence level.
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Yang M, Xin L, Li H, Lu X, Pan X, Lei S, Li Y, Zhu L, Zhu Q, Jiang R, Jia Z, Cheng G, Zeng L, Zhang L. Risk factors for bloodstream infection in paediatric haematopoietic stem cell transplantation: a systematic review and meta-analysis. J Hosp Infect 2023; 139:11-22. [PMID: 37308062 DOI: 10.1016/j.jhin.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023]
Abstract
BACKGROUND Haematopoietic stem cell transplantation (HSCT), a standard treatment for paediatric haematological diseases, is highly associated with bloodstream infection (BSI), which may increase mortality. AIM To explore the risk factors for BSI in paediatric HSCT recipients. METHODS Three English databases and four Chinese databases were searched from inception to March 17th, 2022. Eligible studies included randomized controlled trials, cohort studies, and case-control studies that enrolled HSCT recipients aged ≤18 years and reported BSI risk factors. Two reviewers independently screened studies, extracted data, and assessed the risk of bias. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE), certainty of body of evidence was assessed. FINDINGS Fourteen studies involving 4602 persons were included. The incidences of BSI and associated mortality in paediatric HSCT recipients were approximately 10-50% and 5-15%, respectively. Meta-analysis of all studies revealed that previous BSI before HSCT (relative effect (RE): 2.28; 95% confidence interval (CI) 1.19-4.34, moderate certainty) and receiving an umbilical cord blood transplant (RE: 1.55; 95% CI: 1.22-1.97, moderate certainty) were probably associated with an increased risk of BSI. Meta-analysis of studies with low risk of bias reassured that previous BSI before HSCT probably increased the risk of BSI (RE: 2.28; 95% CI: 1.19-4.34, moderate certainty), and revealed that steroid use (RE: 2.72; 95% CI: 1.31-5.64, moderate certainty) was likely a risk factor whereas autologous HSCT was probably a protective factor of BSI (RE: 0.65; 95% CI: 0.45-0.94, moderate certainty). CONCLUSION These findings could inform the management of paediatric HSCT recipients, helping identify who may benefit from prophylactic antibiotics.
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Li YJ, Pan X, Ma L, Wang C, He B. [Interventional treatment of outflow tract obstruction and iatrogenic ventricular septal defect after transcatheter aortic valve replacement: a case report]. ZHONGHUA XIN XUE GUAN BING ZA ZHI 2023; 51:862-865. [PMID: 37583336 DOI: 10.3760/cma.j.cn112148-20230628-00377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
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Zhu Y, Hu S, Pan X, Gopoju R, Cassim Bawa FN, Yin L, Xu Y, Zhang Y. Hepatocyte Sirtuin 6 Protects against Atherosclerosis and Steatohepatitis by Regulating Lipid Homeostasis. Cells 2023; 12:2009. [PMID: 37566087 PMCID: PMC10417046 DOI: 10.3390/cells12152009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/30/2023] [Accepted: 08/03/2023] [Indexed: 08/12/2023] Open
Abstract
Histone deacetylase Sirtuin 6 (SIRT6) regulates many biological processes. SIRT6 is known to regulate hepatic lipid metabolism and inhibit the development of nonalcoholic fatty liver disease (NAFLD). We aimed to investigate the role of hepatocyte SIRT6 in the development of atherosclerosis and further characterize the mechanism underlying SIRT6's effect on NAFLD. Ldlr-/- mice overexpressing or lacking hepatocyte SIRT6 were fed a Western diet for 16 weeks. The role of hepatic SIRT6 in the development of nonalcoholic steatohepatitis (NASH), atherosclerosis, and obesity was investigated. We also investigated whether p53 participates in the pathogenesis of NAFLD in mice overexpressing hepatic SIRT6. Our data show that loss of hepatocyte SIRT6 aggravated the development of NAFLD, atherosclerosis, and obesity in Ldlr-/- mice, whereas adeno-associated virus (AAV)-mediated overexpression of human SIRT6 in the liver had opposite effects. Mechanistically, hepatocyte SIRT6 likely inhibited the development of NAFLD by inhibiting lipogenesis, lipid droplet formation, and p53 signaling. Hepatocyte SIRT6 also likely inhibited the development of atherosclerosis by inhibiting intestinal lipid absorption and hepatic VLDL secretion. Hepatic SIRT6 also increased energy expenditure. In conclusion, our data indicate that hepatocyte SIRT6 protects against atherosclerosis, NAFLD, and obesity by regulating lipid metabolism in the liver and intestine.
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Cai W, Li L, Sang S, Pan X, Zhong C. Physiological Roles of β-amyloid in Regulating Synaptic Function: Implications for AD Pathophysiology. Neurosci Bull 2023; 39:1289-1308. [PMID: 36443453 PMCID: PMC10387033 DOI: 10.1007/s12264-022-00985-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/02/2022] [Indexed: 11/29/2022] Open
Abstract
The physiological functions of endogenous amyloid-β (Aβ), which plays important role in the pathology of Alzheimer's disease (AD), have not been paid enough attention. Here, we review the multiple physiological effects of Aβ, particularly in regulating synaptic transmission, and the possible mechanisms, in order to decipher the real characters of Aβ under both physiological and pathological conditions. Some worthy studies have shown that the deprivation of endogenous Aβ gives rise to synaptic dysfunction and cognitive deficiency, while the moderate elevation of this peptide enhances long term potentiation and leads to neuronal hyperexcitability. In this review, we provide a new view for understanding the role of Aβ in AD pathophysiology from the perspective of physiological meaning.
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Pan X, Li YJ, He B. [Reacquaint and treatment options for patients with paravalvular leakage after aortic valve replacement]. ZHONGHUA XIN XUE GUAN BING ZA ZHI 2023; 51:696-701. [PMID: 37460422 DOI: 10.3760/cma.j.cn112148-20230531-00319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
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Xing CF, Pan X, Wang C, Ma L, Wang XL, Li YJ, He B. [Long-term outcome of transcatheter repair of paravalvular leak post surgical mitral valve replacement]. ZHONGHUA XIN XUE GUAN BING ZA ZHI 2023; 51:742-749. [PMID: 37460428 DOI: 10.3760/cma.j.cn112148-20230604-00327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Objective: To explore the long-term clinical efficacy of transcatheter repair of mitral paravalvular leak (PVL) post surgical mitral valve replacement. Methods: This study is a retrospective study. Patients who completed transcatheter repair of paravalvular leak after surgical mitral valve replacement at Shanghai Chest Hospital, Shanghai Jiaotong University School of Medicine from March 2010 to December 2018 were included. Technical success was defined as the occluder being stably implanted in the paravalvular leak site without affecting the function of the mitral valve and surrounding tissues; and there were no intervention-related complications, such as new hemolysis or aggravated hemolysis, and echocardiography confirmed mitral paravalvular regurgitation reduced by more than 1 grade. Patients were followed up at 30 days, 1, and 3 years after the intervention. The main endpoints were all-cause death and re-surgery due to interventional failure or serious complications. The occurrence of occluder-mediated hemolysis and chronic renal insufficiency was recorded, and patients were monitored with echocardiography during follow up. Results: A total of 75 patients were included, aged (54.3±22.9) years old, and 38 patients were males. All patients had decreased cardiac function and/or hemolysis before intervention. Procedural success was achieved in 54 patients (72.0%). Incidence of device-mediated hemolysis was 18.7% (14/75). During the follow-up period, all-cause death occurred in 7 patients (9.3%), and 3 were cardiac deaths.The 3-year event-free survival rate was 81.3% (61/75). The need for cardiac surgery was 9.3% (7/75): 3 cases due to severe device-mediated hemolysis, 2 cases due to prosthetic valve failure and 2 cases due to moderate to severe residual regurgitation. The echocardiography follow-up results showed that the position of the occluder was stable, there was no impact on the artificial valve function and surrounding structures, and the residual regurgitation was stable without progressive increase in event-free patients. Compared with pre-intervention, the left ventricular end systolic diameter ((33.9±7.4)mm vs. (38.3±8.9) mm, P=0.036), end diastolic diameter ((53.7±8.3) mm vs. (58.4±9.1) mm, P=0.045) and left atrial diameter (59.3 (44.5, 90.7) mm vs. 64.3 (44.8, 96.6) mm, P=0.049) were significantly reduced, pulmonary artery systolic pressure was also significantly decreased ((36.5±15.8) mmHg vs. (46.3±14.9) mmHg, P=0.022, 1 mmHg=0.133 kPa). There was no significant difference between 3 years and 1 year after transcatheter repair of mitral paravalvular leak post surgical mitral valve replacement (all P>0.05). Conclusion: Transcatheter repair of mitral paravalvular leak post surgical mitral valve replacement is an effective treatment option in selective patients.
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Guo J, Zhang W, Liang P, Zhang L, Peng L, Min Y, Pan X, Yang Z, Deng H. [Puerarin alleviates lipopolysaccharide-induced acute kidney injury in mice by modulating the SIRT1/NF-κB pathway]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2023; 43:1248-1253. [PMID: 37488808 PMCID: PMC10366522 DOI: 10.12122/j.issn.1673-4254.2023.07.22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
OBJECTIVE To investigate the role of the SIRT1/NF-κB pathway in mediating the effect of puerarin against lipopolysaccharide (LPS)-induced acute kidney injury (AKI). METHODS Fifteen BALB/C mice were randomized into control group, LPS group and puerarin treatment group, and in the latter two groups, the mice were given an intraperitoneal injection of LPS (5 mg/kg), followed by daily injection of normal saline for 3 days or injection of puerarin (25 mg/kg) given 1 h later and then on a daily basis for 3 days. On day 5 after modeling, the kidney tissues were taken for histological observation and detection of cell apoptosis. The renal function indexes including urea nitrogen (BUN), serum creatinine (Scr) and kidney injury molecule 1 (KIM-1) and the levels of tumor necrosis factor (TNF-α) and interleukin 1β (IL-1β) were measured, and the expressions of SIRT1 and NF-κB-p65(acetyl K310) in the renal tissues were detected. RESULTS Intraperitoneal injection of LPS caused obvious glomerular capillary dilatation, hyperemia, renal interstitial edema, and renal tubular epithelial cell swelling and deformation in the mice. The mouse models of LPS-induced AKI also showed significantly increased renal tubular injury score and renal cell apoptosis (P < 0.01) with increased serum levels of BUN, Scr, KIM-1, TNF-α and IL-1β (P < 0.01), enhanced renal expressions of TNF-α, IL-1β and NF-κB p65(acetyl K310) (P < 0.01) and lowered renal expression of SIRT1 (P < 0.05). Treatment with puerarin effectively alleviated LPS-induced renal interstitial edema and renal tubular epithelial cell shedding, lowered renal tubular injury score (P < 0.01) and renal cell apoptosis rate (P < 0.01), and decreased serum levels of BUN, Scr, KIM, TNF-α and IL-1β (P < 0.01). Puerarin treatment significantly reduced TNF-α, IL-1β and NF-κB p65 (acetyl K310) expression in the renal tissue (P < 0.05) and increased SIRT1 expression by 17% (P < 0.05) in the mouse models. CONCLUSION Puerarin can effectively alleviate LPS-induced AKI in mice possibly by modulating the SIRT1/NF-κB signaling pathway.
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Zhong L, Zhao J, Huang L, Liu Y, Pang X, Zhan K, Li S, Xue Q, Pan X, Deng L. Runx2 activates hepatic stellate cells to promote liver fibrosis via transcriptionally regulating Itgav expression. Clin Transl Med 2023; 13:e1316. [PMID: 37403784 PMCID: PMC10320748 DOI: 10.1002/ctm2.1316] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUNDS AND AIMS As a central event during liver fibrosis, hepatic stellate cells (HSC) have been thought to be a potential therapeutic target for liver fibrosis. Previous studies have shown that runt-related transcription factor 2 (Runx2) is associated with the development of non-alcoholic fatty liver disease, while its specific role in HSC activation and hepatic fibrosis remains elusive. APPROACH AND RESULTS In this study, we found that Runx2 expression was significantly upregulated in human liver fibrosis with different aetiologies. Runx2 expression was also gradually elevated in mouse liver during fibrosis, and Runx2 was mainly expressed in the activated HSC. Knockdown of Runx2 in HSC markedly alleviated CCl4 -induced, 3,5-diethoxycarbonyl-1,4-dihydrocollidine-induced or methionine-choline deficient (MCD)-induced liver fibrosis, while hepatic overexpression of Runx2 via HBAAV-Runx2 or VA-Lip-Runx2 injection exacerbated CCl4 -induced liver fibrosis. In vitro analysis demonstrated that Runx2 promoted HSC activation and proliferation, whereas Runx2 knockdown in HSC suppressed these effects. RNA-seq and Runx2 ChIP-seq analysis demonstrated that Runx2 could promote integrin alpha-V (Itgav) expression by binding to its promoter. Blockade of Itgav attenuated Runx2-induced HSC activation and liver fibrosis. Additionally, we found that cytokines (TGF-β1, PDGF, EGF) promote the expression and nuclear translocation of Runx2 through protein kinase A (PKA) in HSC. CONCLUSIONS Runx2 is critical for HSC activation via transcriptionally regulating Itgav expression during liver fibrosis, and may be a promising therapeutic target for liver fibrosis.
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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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Duan HB, Pan X, Yu SS, Zhang H. Two Schiff base iodide compounds as iodide ion conductors showing high conductivity. RSC Adv 2023; 13:18775-18778. [PMID: 37346954 PMCID: PMC10281492 DOI: 10.1039/d3ra02416d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 05/28/2023] [Indexed: 06/23/2023] Open
Abstract
Here, we reported the crystal structures, dielectric and conducting properties of two Schiff base iodide compounds [m-BrBz-1-APy]I3 (1) and [o-FBz-1-APy]I3 (2). The Schiff base cations build irregular channel frameworks, and the polyiodide anions are located in the channel. The impedance spectra demonstrated that the two compounds show intrinsic iodide ion conductance with higher conductivity of 1.03(4) × 10-4 S cm-1 at 343 K for 1 and 4.94(3) × 10-3 S cm-1 at 353 K for 2. The dielectric modulus analysis further confirmed that the conductance contributed to the migration of iodide ions.
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