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Groenewald M, Hittinger C, Bensch K, Opulente D, Shen XX, Li Y, Liu C, LaBella A, Zhou X, Limtong S, Jindamorakot S, Gonçalves P, Robert V, Wolfe K, Rosa C, Boekhout T, Čadež N, éter G, Sampaio J, Lachance MA, Yurkov A, Daniel HM, Takashima M, Boundy-Mills K, Libkind D, Aoki K, Sugita T, Rokas A. A genome-informed higher rank classification of the biotechnologically important fungal subphylum Saccharomycotina. Stud Mycol 2023; 105:1-22. [PMID: 38895705 PMCID: PMC11182611 DOI: 10.3114/sim.2023.105.01] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 05/12/2023] [Indexed: 06/21/2024] Open
Abstract
The subphylum Saccharomycotina is a lineage in the fungal phylum Ascomycota that exhibits levels of genomic diversity similar to those of plants and animals. The Saccharomycotina consist of more than 1 200 known species currently divided into 16 families, one order, and one class. Species in this subphylum are ecologically and metabolically diverse and include important opportunistic human pathogens, as well as species important in biotechnological applications. Many traits of biotechnological interest are found in closely related species and often restricted to single phylogenetic clades. However, the biotechnological potential of most yeast species remains unexplored. Although the subphylum Saccharomycotina has much higher rates of genome sequence evolution than its sister subphylum, Pezizomycotina, it contains only one class compared to the 16 classes in Pezizomycotina. The third subphylum of Ascomycota, the Taphrinomycotina, consists of six classes and has approximately 10 times fewer species than the Saccharomycotina. These data indicate that the current classification of all these yeasts into a single class and a single order is an underappreciation of their diversity. Our previous genome-scale phylogenetic analyses showed that the Saccharomycotina contains 12 major and robustly supported phylogenetic clades; seven of these are current families (Lipomycetaceae, Trigonopsidaceae, Alloascoideaceae, Pichiaceae, Phaffomycetaceae, Saccharomycodaceae, and Saccharomycetaceae), one comprises two current families (Dipodascaceae and Trichomonascaceae), one represents the genus Sporopachydermia, and three represent lineages that differ in their translation of the CUG codon (CUG-Ala, CUG-Ser1, and CUG-Ser2). Using these analyses in combination with relative evolutionary divergence and genome content analyses, we propose an updated classification for the Saccharomycotina, including seven classes and 12 orders that can be diagnosed by genome content. This updated classification is consistent with the high levels of genomic diversity within this subphylum and is necessary to make the higher rank classification of the Saccharomycotina more comparable to that of other fungi, as well as to communicate efficiently on lineages that are not yet formally named. Taxonomic novelties: New classes: Alloascoideomycetes M. Groenew., Hittinger, Opulente & A. Rokas, Dipodascomycetes M. Groenew., Hittinger, Opulente & A. Rokas, Lipomycetes M. Groenew., Hittinger, Opulente, A. Rokas, Pichiomycetes M. Groenew., Hittinger, Opulente & A. Rokas, Sporopachydermiomycetes M. Groenew., Hittinger, Opulente & A. Rokas, Trigonopsidomycetes M. Groenew., Hittinger, Opulente & A. Rokas. New orders: Alloascoideomycetes: Alloascoideales M. Groenew., Hittinger, Opulente & A. Rokas; Dipodascomycetes: Dipodascales M. Groenew., Hittinger, Opulente & A. Rokas; Lipomycetes: Lipomycetales M. Groenew., Hittinger, Opulente & A. Rokas; Pichiomycetes: Alaninales M. Groenew., Hittinger, Opulente & A. Rokas, Pichiales M. Groenew., Hittinger, Opulente & A. Rokas, Serinales M. Groenew., Hittinger, Opulente & A. Rokas; Saccharomycetes: Phaffomycetales M. Groenew., Hittinger, Opulente & A. Rokas, Saccharomycodales M. Groenew., Hittinger, Opulente & A. Rokas; Sporopachydermiomycetes: Sporopachydermiales M. Groenew., Hittinger, Opulente & A. Rokas; Trigonopsidomycetes: Trigonopsidales M. Groenew., Hittinger, Opulente & A. Rokas. New families: Alaninales: Pachysolenaceae M. Groenew., Hittinger, Opulente & A. Rokas; Pichiales: Pichiaceae M. Groenew., Hittinger, Opulente & A. Rokas; Sporopachydermiales: Sporopachydermiaceae M. Groenew., Hittinger, Opulente & A. Rokas. Citation: Groenewald M, Hittinger CT, Bensch K, Opulente DA, Shen X-X, Li Y, Liu C, LaBella AL, Zhou X, Limtong S, Jindamorakot S, Gonçalves P, Robert V, Wolfe KH, Rosa CA, Boekhout T, Čadež N, Péter G, Sampaio JP, Lachance M-A, Yurkov AM, Daniel H-M, Takashima M, Boundy-Mills K, Libkind D, Aoki K, Sugita T, Rokas A (2023). A genome-informed higher rank classification of the biotechnologically important fungal subphylum Saccharomycotina. Studies in Mycology 105: 1-22. doi: 10.3114/sim.2023.105.01 This study is dedicated to the memory of Cletus P. Kurtzman (1938-2017), a pioneer of yeast taxonomy.
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Ablikim M, Achasov MN, Adlarson P, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, H XT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu WL, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Precision Measurement of the Decay Σ^{+}→pγ in the Process J/ψ→Σ^{+}Σ[over ¯]^{-}. PHYSICAL REVIEW LETTERS 2023; 130:211901. [PMID: 37295102 DOI: 10.1103/physrevlett.130.211901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 05/08/2023] [Indexed: 06/12/2023]
Abstract
Using (10 087±44)×10^{6} J/ψ events collected with the BESIII detector, the radiative hyperon decay Σ^{+}→pγ is studied at an electron-positron collider experiment for the first time. The absolute branching fraction is measured to be (0.996±0.021_{stat}±0.018_{syst})×10^{-3}, which is lower than its world average value by 4.2 standard deviations. Its decay asymmetry parameter is determined to be -0.652±0.056_{stat}±0.020_{syst}. The branching fraction and decay asymmetry parameter are the most precise to date, and the accuracies are improved by 78% and 34%, respectively.
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Li H, Zheng J, Qian Y, Lü S, Xia S, Zhou X. [Comparison of the disease burden of schistosomiasis globally and in China and Zimbabwe]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2023; 35:128-136. [PMID: 37253561 DOI: 10.16250/j.32.1374.2022263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
OBJECTIVE To investigate the trends in the disease burden of schistosomiasis worldwide and in China, and Zimbabwe from 1990 to 2019, so as to provide insights into the formulation of the schistosomiasis control strategy in Zimbabwe. METHODS Based on Global Burden of Disease Study 2019 (GBD 2019) data sources, the age-standardized prevalence, mortality, disability-adjusted life year (DALY) rate of schistosomiasis were compared in the world, China, and Zimbabwe and the trends in the disease burden of schistosomiasis from 1990 to 2019 were investigated using Joinpoint regression analysis. In addition, the associations between the burden of schistosomiasis worldwide and in China and Zimbabwe from 1990 to 2019 and socio-demographic index (SDI) were examined using Pearson correlation analysis. RESULTS The age-standardized prevalence, mortality, and DALY rate of schistosomiasis were 1 804.95/105, 0.14/105 and 20.92/105 in the world, 707.09/105, 0.02/105 and 5.06/105 in China, and 2 218.90/105, 2.39/105 and 90.09/105 in Zimbabwe in 2019, respectively. The global prevalence, mortality, and DALY rate of schistosomiasis appeared a tendency towards a rise followed by a decline with age in 2019, while the prevalence and DALY rate of schistosomiasis appeared a tendency towards a sharp rise followed by a fluctuating decline in both China and Zimbabwe, and the mortality of schistosomiasis appeared a tendency towards a rise. The age-standardized prevalence [average annual percent change (AAPC) = -1.31%, -2.22% and -6.12%; t = -20.07, -83.38 and -53.06; all P values < 0.05)] and DALY rate of schistosomiasis (AAPC = -1.91%,-4.17% and -2.08%; t = -31.89, -138.70 and -16.45; all P values < 0.05) appeared a tendency towards a decline in the world, China and Zimbabwe from 1990 to 2019, and the age-standardized mortality of schistosomiasis appeared a tendency towards a decline in the world and China (AAPC = -3.46% and -8.10%, t = -41.03 and -61.74; both P values < 0.05), and towards a rise followed by a decline in Zimbabwe (AAPC = 1.35%, t = 4.88, P < 0.05). In addition, Pearson correlation analysis showed that the age-standardized prevalence (r = -0.75, P < 0.05), mortality (r = -0.73, P < 0.05), and DALY rate of schistosomiasis (r = -0.77, P < 0.05) correlated negatively with SDI in the world, China and Zimbabwe from 1990 to 2019. CONCLUSIONS The disease burden of schistosomiasis appeared a remarkable decline in China from 1990 to 2019, and the prevalence of schistosomiasis showed a tendency towards a decline in Zimbabwe from 1990 to 2019; however, the mortality and DALY rate of schistosomiasis in Zimbabwe topped in the world. A schistosomiasis control strategy with adaptations to local epidemiology and control needs of schistosomiasis is needed to facilitate the elimination of schistosomiasis in Zimbabwe.
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Liu M, Li R, Bai C, Chen Q, Yin Y, Chen Y, Zhou X, Zhao X. Predictive value of DEEPVESSEL-fractional flow reserve and quantitative plaque analysis based on coronary CT angiography for major adverse cardiac events. Clin Radiol 2023:S0009-9260(23)00179-4. [PMID: 37258332 DOI: 10.1016/j.crad.2023.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 03/26/2023] [Accepted: 04/25/2023] [Indexed: 06/02/2023]
Abstract
AIM To investigate the predictive value of the combination of DEEPVESSEL-fractional flow reserve (DVFFR) and quantitative plaque analysis using coronary computed tomographic angiography (CCTA) for major adverse cardiac events (MACE). METHOD In this retrospective study, data from 69 vessels from 58 consecutive patients were collected. These patients who underwent coronary angiography (CAG) with DVFFR were divided into MACE-positive and MACE-negative groups. DVFFR measurements were obtained from CCTA images acquired before CAG, and an FFR or DVFFR value ≤ 0.80 was considered haemodynamically significant. CCTA images were analysed quantitatively using automated software to obtain the following indices: total plaque volume (TPV) and burden (TPB), calcified plaque volume (CPV) and burden (CPB), non-calcified plaque volume (NCPV) and burden (NCPB), low-attenuation plaque (LAP), minimum lumen area (MLA), stenosis grade (SG) and lesion length (LL). Univariate and multivariate logistic regression, correlation, and receiver operating characteristic (ROC) analyses were used for statistical analysis. RESULTS DVFFR was highly correlated with invasive FFR (R=0.728), and the Bland-Altman plot showed good agreement between DVFFR and FFR (95% CI: -0.109-0.087) on a per-vessel level. DVFFR showed a high diagnostic performance in identifying abnormal haemodynamic vessels, with an area under the ROC curve (AUC) of 0.984. In multivariate analysis, the following biomarkers were predictors of MACE: DVFFR ≤ 0.8, SG, TPB, NCPB, and LL values. The combination of the above independent risk factors yielded the most valuable prediction for MACE (AUC:0.888). CONCLUSIONS DVFFR was highly correlated with FFR with satisfactory diagnostic accuracy. DVFFR, together with plaque analysis indices, yielded valuable predictions for MACE.
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Wang M, Zhang YH, Zhou X, Zhou XH, Xu HS, Liu ML, Li JG, Niu YF, Huang WJ, Yuan Q, Zhang S, Xu FR, Litvinov YA, Blaum K, Meisel Z, Casten RF, Cakirli RB, Chen RJ, Deng HY, Fu CY, Ge WW, Li HF, Liao T, Litvinov SA, Shuai P, Shi JY, Song YN, Sun MZ, Wang Q, Xing YM, Xu X, Yan XL, Yang JC, Yuan YJ, Zeng Q, Zhang M. Mass Measurement of Upper fp-Shell N=Z-2 and N=Z-1 Nuclei and the Importance of Three-Nucleon Force along the N=Z Line. PHYSICAL REVIEW LETTERS 2023; 130:192501. [PMID: 37243656 DOI: 10.1103/physrevlett.130.192501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 03/01/2023] [Accepted: 03/17/2023] [Indexed: 05/29/2023]
Abstract
Using a novel method of isochronous mass spectrometry, the masses of ^{62}Ge, ^{64}As, ^{66}Se, and ^{70}Kr are measured for the first time, and the masses of ^{58}Zn, ^{61}Ga, ^{63}Ge, ^{65}As, ^{67}Se, ^{71}Kr, and ^{75}Sr are redetermined with improved accuracy. The new masses allow us to derive residual proton-neutron interactions (δV_{pn}) in the N=Z nuclei, which are found to decrease (increase) with increasing mass A for even-even (odd-odd) nuclei beyond Z=28. This bifurcation of δV_{pn} cannot be reproduced by the available mass models, nor is it consistent with expectations of a pseudo-SU(4) symmetry restoration in the fp shell. We performed ab initio calculations with a chiral three-nucleon force (3NF) included, which indicate the enhancement of the T=1 pn pairing over the T=0 pn pairing in this mass region, leading to the opposite evolving trends of δV_{pn} in even-even and odd-odd nuclei.
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Wang C, Zhou X, Liu GY, Qu CY, Yuan CY, Zhang YX. [Analysis of different protein expression levels in peripheral blood circulating tumor cells from patients with diffuse large B-cell lymphoma and their predictive efficiency for recurrence]. ZHONGHUA YI XUE ZA ZHI 2023; 103:1328-1333. [PMID: 37150683 DOI: 10.3760/cma.j.cn112137-20220817-01753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Objective: To analyze the expression levels of differentiation cluster 47 (CD47), signal regulatory protein α (SIRP-α), proto-oncogene (MYC) and proliferating cell associated antigen (Ki67) proteins in peripheral blood circulating tumor cells (CTC) from patients with diffuse large B-cell lymphoma and their predictive efficiency for tumor recurrence. Methods: The data of 82 patients with diffuse large B-cell lymphoma who were confirmed by histopathology and were in remission after chemotherapy in the Hematology Department of Linyi People's Hospital from January 2018 to January 2021 were retrospectively analyzed. There were 44 males and 38 females, and aged from 50 to 75 (63.8±4.6) years. The patients were divided into recurrent group (n=36) and non-recurrent group (n=46) according to their recurrence within 1 year after remission. The fasting peripheral venous blood samples (4 ml) from patients in the morning were collected, and the CTC were isolated. The expression levels of CD47, SIRP-α, MYC and Ki67 proteins in CTC were detected by Western blotting. The correlations between CD47 expression level and SIRP-α, MYC and Ki67 expression levels were analyzed by Pearson correlation analysis. The predictive efficiency of CD47, SIRP-α, MYC and Ki67 expression levels on tumor recurrence was evaluated by receiver operating characteristic (ROC) curves, and the areas under the curve (AUC) were calculated. Results: The expression levels of CD47, SIRP-α, MYC and Ki67 in recurrent group were 2.24±0.23, 1.17±0.12, 1.98±0.20 and 2.63±0.27, while those in non-recurrent group were 2.04±0.21, 1.31±0.13, 1.53±0.16 and 2.24±0.25. The expression levels of CD47, MYC and Ki67 in the recurrent group were higher than those in the non-recurrent group, while the expression levels of SIRP-α were lower than those in the non-recurrent group (all P<0.001). In 82 patients, the expression levels of CD47, SIRP-α, MYC and Ki67 were 2.13±0.22, 1.25±0.13, 1.73±0.18 and 2.41±0.26, respectively. The expression level of CD47 was negatively correlated with the expression level of SIRP-α (r=-0.308, P=0.005), but positively correlated with the expression level of MYC and Ki67 (r=0.484 and 0.332, P=0.012 and 0.003). The sensitivity of CD47, SIRP-α, MYC and Ki67 expression levels in predicting recurrence of diffuse large B-cell lymphoma was 66.7%, 72.2%, 72.2% and 66.7%, with the specificity of 67.4%, 71.7%, 67.4% and 71.7%, and AUC (95%CI) of 0.694 (0.582-0.791), 0.693 (0582-0.790), 0.714 (0.603-0.808) and 0.709 (0.598-0.804), respectively. The sensitivity of the combined detection of the above four indicators was 83.3%, with the specificity of 78.3% and the AUC (95%CI) of 0.864 (0.771-0.930), which was higher than those of the individual detection of each indicator (all P<0.05). Conclusions: The expression level of CD47 was negatively correlated with the expression level of SIRP-α, but positively correlated with the expression level of MYC and Ki67. The expression levels of CD47, SIRP-α, MYC and Ki67 have certain predictive value for tumor recurrence in patients with diffuse large B-cell lymphoma, and the predictive efficiency of combined detection is higher than single indicator detection.
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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 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, 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 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. Measurements of the Electric and Magnetic Form Factors of the Neutron for Timelike Momentum Transfer. PHYSICAL REVIEW LETTERS 2023; 130:151905. [PMID: 37115883 DOI: 10.1103/physrevlett.130.151905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/27/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
We present the first measurements of the electric and magnetic form factors of the neutron in the timelike (positive q^{2}) region as function of four-momentum transfer. We explored the differential cross sections of the reaction e^{+}e^{-}→n[over ¯]n with data collected with the BESIII detector at the BEPCII accelerator, corresponding to an integrated luminosity of 354.6 pb^{-1} in total at twelve center-of-mass energies between sqrt[s]=2.0-2.95 GeV. A relative uncertainty of 18% and 12% for the electric and magnetic form factors, respectively, is achieved at sqrt[s]=2.3935 GeV. Our results are comparable in accuracy to those from electron scattering in the comparable spacelike region of four-momentum transfer. The electromagnetic form factor ratio R_{em}≡|G_{E}|/|G_{M}| is within the uncertainties close to unity. We compare our result on |G_{E}| and |G_{M}| to recent model predictions, and the measurements in the spacelike region to test the analyticity of electromagnetic form factors.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of a New X(3872) Production Process e^{+}e^{-}→ωX(3872). PHYSICAL REVIEW LETTERS 2023; 130:151904. [PMID: 37115900 DOI: 10.1103/physrevlett.130.151904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 06/19/2023]
Abstract
Using 4.7 fb^{-1} of e^{+}e^{-} collision data at center-of-mass energies from 4.661 to 4.951 GeV collected by the BESIII detector at the BEPCII collider, we observe the X(3872) production process e^{+}e^{-}→ωX(3872) for the first time. The significance is 7.8σ, including both the statistical and systematic uncertainties. The e^{+}e^{-}→ωX(3872) Born cross section and the corresponding upper limit at 90% confidence level at each energy point are reported. The line shape of the cross section indicates that the ωX(3872) signals may be from the decays of some nontrivial structures.
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Hu M, Fan JY, Zhou X, Cao GW, Tan X. [Global incidence and mortality of renal cell carcinoma in 2020]. ZHONGHUA LIU XING BING XUE ZA ZHI = ZHONGHUA LIUXINGBINGXUE ZAZHI 2023; 44:575-580. [PMID: 37147828 DOI: 10.3760/cma.j.cn112338-20220624-00558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Objective: To analyze the global epidemiology of renal cell carcinoma (RCC) in 2020. Methods: The incidence and mortality data of RCC in the cooperative database GLOBOCAN 2020 of International Agency for Research on Cancer of WHO and the human development index (HDI) published by the United Nations Development Programme in 2020 were collated. The crude incidence rate (CIR), age-standardized incidence rate (ASIR), crude mortality rate (CMR), age-standardized mortality rate (ASMR) and mortality/incidence ratio (M/I) of RCC were calculated. Kruskale-Wallis test was used to analyze the differences in ASIR or ASMR among HDI countries. Results: In 2020, the global ASIR of RCC was 4.6/100 000, of which 6.1/100 000 for males and 3.2/100 000 for females and ASIR was higher in very high and high HDI countries than that in medium and low HDI countries. With the rapid increase of age after the age of 20, the growth rate of ASIR in males was faster than that in females, and slowed down at the age of 70 to 75. The truncation incidence rate of 35-64 years old was 7.5/100 000 and the cumulative incidence risk of 0-74 years old was 0.52%. The global ASMR of RCC was 1.8/100 000, 2.5/100 000 for males and 1.2/100 000 for females. The ASMR of males in very high and high HDI countries (2.4/100 000-3.7/100 000) was about twice that of males (1.1/100 000-1.4/100 000) in medium and low HDI countries, while the ASMR of female (0.6/100 000-1.5/100 000) did not show significant difference. ASMR continued to increase rapidly with age after the age of 40, and the growth rate of males was faster than that of females. The truncation mortality rate of 35-64 years old was 2.1/100 000, and the cumulative mortality risk of 0-74 years old was 0.20%. M/I decreases with the increase of HDI, with M/I as 0.58 in China, which was higher than the global average of 0.39 and the United States' 0.17. Conclusion: The ASIR and ASMR of RCC presented significant regional and gender disparities globally, and the heaviest burden was in very high HDI countries.
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Wu Q, Li Z, Zhang Y, Luo K, Xu X, Li J, Peng X, Zhou X. Cyclic di-AMP Rescues Porphyromonas gingivalis-Aggravated Atherosclerosis. J Dent Res 2023:220345231162344. [PMID: 37029659 DOI: 10.1177/00220345231162344] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2023] Open
Abstract
Growing evidence demonstrates the relationship between periodontitis and atherosclerotic cardiovascular diseases. The periodontal pathogen Porphyromonas gingivalis (Pg) has been shown to contribute to the progression of atherosclerosis. Cyclic diadenylate monophosphate (c-di-AMP) has been widely studied as an immune adjuvant for tumor immunotherapy, given its ability to activate the stimulator of interferon genes (STING) and regulate trained immunity. This study sought to elucidate the role of c-di-AMP in Pg-associated atherosclerosis. Periodontitis and atherosclerosis mouse models were established by ligature application around maxillary second molars and feeding ApoE knockout mice with a high-fat diet. We found that periodontitis and atherosclerosis were more severe in mice exposed to Pg than mice that underwent ligature placement only, while prophylactic treatment with c-di-AMP activated trained immunity and elicited significant alleviation of alveolar bone resorption, as well as reduced blood lipid levels and atherosclerotic plaque accumulation. After 3 mo of intervention, c-di-AMP limited the elevation of cytokines interleukin (IL)-6, IL-1β, tumor necrosis factor α, and interferon β; extracellular matrix remodeling enzymes MMP-2 and MMP-9; and adhesion molecules ICAM-1 and VCAM-1 gene expression. The mechanism underlying Pg-aggravated atherosclerosis may be attributed to changes in microbiota composition in oral and aortic plaques and excess inflammatory response, whereas c-di-AMP could prevent the effects of Pg infection due to its potential ability to activate trained immunity and regulate microecological balance. Our findings suggest a positive role of c-di-AMP in alleviating Pg-aggravated atherosclerosis by regulating the immune response and influencing the local microenvironment.
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Yang R, Wang M, Dong Q, Zhou X. Transcranial Doppler versus CT angiography: a comparative analysis for the diagnosis of ischaemic cerebrovascular disease. Clin Radiol 2023; 78:e350-e357. [PMID: 36746722 DOI: 10.1016/j.crad.2022.12.014] [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: 08/26/2022] [Revised: 11/23/2022] [Accepted: 12/22/2022] [Indexed: 01/14/2023]
Abstract
AIMS To compare the sensitivity, specificity, accuracy, and clinical usefulness of transcranial Doppler (TCD) ultrasound against computed tomography angiography (CTA) for the diagnosis of ischaemic cerebrovascular disease. METHODS A total of 1,183 sites (vascular segments) of 169 patients who had been diagnosed with cerebrovascular disease using digital subtraction angiography (DSA) were evaluated by CTA and TCD for the diagnosis of the arterial lesions. RESULTS Lesions were identified in 509 sites and 674 sites did not have lesions according to the DSA examination. Each individual site had higher sensitivity, specificity, and accuracy for TCD than those for CTA, respectively. For all sites, TCD had higher true-positive (p=0.0029) and -negative (p=0.0151) values and fewer false-positive and -negative (p<0.0001 for both) values than those of CTA. The sensitivity, specificity, and accuracy of CTA for all sites to detect lesions were 77%, 88%, and 84%, respectively. The same parameters for TCD were 94%, 97%, and 95%, respectively. The beneficial scores for CTA and TCD to detect lesions were 0-0.795 diagnostic confidence and 0-0.91 diagnostic confidence, respectively. Beneficial scores >0.795 and >0.91 indicated a risk of underdiagnosis of lesions at CTA and TCD, respectively. CONCLUSIONS Compared with DSA (reference standard) and CTA, the study underscores the use of TCD in cerebrovascular pathology.
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Schaenman J, Weigt S, Pan M, Zhou X, Elashoff D, Shino M, Reynolds J, Budev M, Shah P, Singer L, Snyder L, Palmer S, Belperio J. Peripheral Blood Cytokines Predict Primary Graft Dysfunction after Lung Transplantation. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Luo R, Su Z, Kang K, Yu M, Zhou X, Wu Y, Yao Z, Xiu W, Yu Y, Zhou L, Na F, Li Y, Zhang X, Zou B, Peng F, Wang J, Xue J, Gong Y, Lu Y. 197P Combining stereotactic body radiation and low-dose radiation (EclipseRT) with PD-1 inhibitor in mice models and patients with bulky tumor. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00450-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Bai Q, Chen Y, Xiao X, Chang H, Xin B, Jia L, Li J, Wang Z, Yu C, Xiong H, Zhou X. 203P MET gene copy number heterogeneity in non-small cell lung cancer patients resistant to EGFR-TKIs. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00456-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Zhou X, Sorbo LD, Hough O, Chao B, Ali A, Brambate E, Ribeiro R, Gomes B, Nardo MD, Yeung J, Liu M, Cypel M, Wang B, Keshavjee S, Sage A. A Computational Approach to Breath-By-Breath Ventilator Waveform Data Extraction and Analysis During Ex Vivo Lung Perfusion Enables Enhanced Physiological Lung Assessment. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Chao B, Ma J, Zhou X, McInnis M, Yeung J, Cypel M, Liu M, Sage A, Wang B, Keshavjee S. A Machine Learning Approach to Processing and Interpreting Ex Vivo Lung Radiographs Predicts Transplant Outcomes. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Hough O, Zhou X, Nardo MD, Ali A, Brambate E, Ribeiro R, Gomes B, Cypel M, Slutsky A, Sage A, Keshavjee S, Sorbo LD. Pulmonary Stress Index During Ex Vivo Lung Perfusion is Associated with Evlp and Lung Transplant Recipient Outcomes. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Tan S, Zhou X, Xu X, Lu Y, Zeng X, Wu Q, Wang Y. Diagnostic Performance of High-Resolution Vessel Wall MR Imaging Combined with TOF-MRA in the Follow-up of Intracranial Vertebrobasilar Dissecting Aneurysms after Reconstructive Endovascular Treatment. AJNR Am J Neuroradiol 2023; 44:453-459. [PMID: 36958804 PMCID: PMC10084898 DOI: 10.3174/ajnr.a7838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/14/2023] [Indexed: 03/25/2023]
Abstract
BACKGROUND AND PURPOSE Few studies have reported the utility of high-resolution vessel wall MR imaging in the follow-up of endovascularly treated vertebrobasilar dissecting aneurysms. This study aimed to evaluate the diagnostic performance of high-resolution vessel wall MR imaging combined with TOF-MRA in the follow-up of intracranial vertebrobasilar dissecting aneurysms after reconstructive endovascular treatment. MATERIALS AND METHODS Patients with intracranial vertebrobasilar dissecting aneurysms with reconstructive endovascular treatment and followed up with TOF-MRA, high-resolution vessel wall MR imaging, and DSA were included. With DSA as the criterion standard, the diagnostic performance of TOF-MRA, high-resolution vessel wall MR imaging, and high-resolution vessel wall MR imaging combined with TOF-MRA in the evaluation of aneurysm occlusion status and parent artery patency was assessed. Visualization of the stented artery on TOF-MRA and high-resolution vessel wall MR imaging was rated on a 5-point scale. RESULTS Twenty-seven patients with 29 aneurysms were included. The sensitivity, specificity, positive predictive value, and negative predictive value of TOF-MRA, high-resolution vessel wall MR imaging, and high-resolution vessel wall MR imaging combined with TOF-MRA for diagnosing aneurysm remnants were 80.0%, 100.0%, 100.0%, and 82.4%; 53.3%, 100.0%, 100.0%, and 66.7%; and 93.3%, 100.0%, 100.0%, and 93.3%, respectively. For the visualization of the stented artery, the mean score of high-resolution vessel wall MR imaging was significantly higher than that of TOF-MRA (4.88 [SD, 0.32] versus 2.53 [SD, 1.25], P < .001). In the evaluation of parent artery patency (normal or pathologic), whereas TOF-MRA had a sensitivity, specificity, positive predictive value, and negative predictive value of 100.0%, 8.0%, 14.8%, and 100.0%, respectively, high-resolution vessel wall MR imaging was completely consistent with the DSA. CONCLUSIONS High-resolution vessel wall MR imaging combined with TOF-MRA at 3T showed good diagnostic performance in the follow-up of intracranial vertebrobasilar dissecting aneurysms after reconstructive endovascular treatment.
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Ju Y, Liu K, Ma G, Zhu B, Wang H, Hu Z, Zhao J, Zhang L, Cui K, He XR, Huang M, Li Y, Xu S, Gao Y, Liu K, Liu H, Zhuo Z, Zhang G, Guo Z, Ye Y, Zhang L, Zhou X, Ma S, Qiu Y, Zhang M, Tao Y, Zhang M, Xian L, Xie W, Wang G, Wang Y, Wang C, Wang DH, Yu K. Bacterial antibiotic resistance among cancer inpatients in China: 2016-20. QJM 2023; 116:213-220. [PMID: 36269193 DOI: 10.1093/qjmed/hcac244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/16/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The incidence of infections among cancer patients is as high as 23.2-33.2% in China. However, the lack of information and data on the number of antibiotics used by cancer patients is an obstacle to implementing antibiotic management plans. AIM This study aimed to investigate bacterial infections and antibiotic resistance in Chinese cancer patients to provide a reference for the rational use of antibiotics. DESIGN This was a 5-year retrospective study on the antibiotic resistance of cancer patients. METHODS In this 5-year surveillance study, we collected bacterial and antibiotic resistance data from 20 provincial cancer diagnosis and treatment centers and three specialized cancer hospitals in China. We analyzed the resistance of common bacteria to antibiotics, compared to common clinical drug-resistant bacteria, evaluated the evolution of critical drug-resistant bacteria and conducted data analysis. FINDINGS Between 2016 and 2020, 216 219 bacterial strains were clinically isolated. The resistance trend of Escherichia coli and Klebsiella pneumoniae to amikacin, ciprofloxacin, cefotaxime, piperacillin/tazobactam and imipenem was relatively stable and did not significantly increase over time. The resistance of Pseudomonas aeruginosa strains to all antibiotics tested, including imipenem and meropenem, decreased over time. In contrast, the resistance of Acinetobacter baumannii strains to carbapenems increased from 4.7% to 14.7%. Methicillin-resistant Staphylococcus aureus (MRSA) significantly decreased from 65.2% in 2016 to 48.9% in 2020. CONCLUSIONS The bacterial prevalence and antibiotic resistance rates of E. coli, K. pneumoniae, P. aeruginosa, A. baumannii, S. aureus and MRSA were significantly lower than the national average.
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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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Zang Z, Qiao R, Zhu Q, Zhou X, Gu W, Han B, Yang R. [Peripheral blood KCNMA1 methylation level is associated with the occurrence and progression of lung cancer]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2023; 43:349-359. [PMID: 37087578 PMCID: PMC10122738 DOI: 10.12122/j.issn.1673-4254.2023.03.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 04/24/2023]
Abstract
OBJECTIVE To explore the association of KCNMA1 gene methylation levels in peripheral blood with lung cancer. METHODS The methylation levels of 4 CpG sites in KCNMA1 gene were quantitatively detected in 285 patients with lung cancer, 186 age- and sex-matched patients with benign pulmonary nodules and 278 matched healthy control subjects using mass spectrometry (MALDI-TOF-MS). The association of KCNMA1 methylation levels with lung cancer was analyzed using logistic regression models adjusted for covariates. The KCNMA1 methylation levels in different subgroups of lung cancer patients were compared using Mann-Whitney U test. RESULTS In subjects over 55 years and in female subjects, the highest quartile (Q4) vs the lowest quartile (Q1) of KCNMA1_CpG_5 methylation levels were significantly correlated with lung cancer (for subjects over 55 years: OR=2.60, 95% CI: 1.25-5.41, P=0.011; for female subjects: OR=2.09, 95% CI: 1.03?4.26, P=0.042). From Q2 to Q4 of KCNMA1_CpG_5 methylation levels, their correlation with lung cancer became gradually stronger (P=0.003 and 0.038, respectively). In male subjects, the OR of Q4 of KCNMA1_CpG_5 methylation levels was 0.35 in patients with lung cancer as compared with patients with benign nodules (95% CI: 0.16-0.79, P=0.012). KCNMA1_CpG_3 methylation level was significantly lower in invasive adenocarcinoma than in noninvasive adenocarcinoma (P=0.028), and that of KCNMA1_CpG_1 was significantly higher in patients with larger tumors (T2-4) than in those with smaller tumors (T1) (P=0.021). CONCLUSION The change of peripheral blood KCNMA1 methylation level is correlated with the occurrence and development of lung cancer.
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Wang RH, Hu M, Yang ZY, Niu ZY, Chen HS, Zhou X, Cao GW. [Global liver cancer incidence and mortality and future trends from 2000 to 2020: GLOBOCAN data analysis]. ZHONGHUA GAN ZANG BING ZA ZHI = ZHONGHUA GANZANGBING ZAZHI = CHINESE JOURNAL OF HEPATOLOGY 2023; 31:271-280. [PMID: 37137853 DOI: 10.3760/cma.j.cn501113-20221127-00579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Objective: To compare the geographical differences and time trends of liver cancer incidence and mortality in different regions around the world so as to predict the future burden of liver cancer. Methods: The incidence and mortality data of liver cancer in different Human Development Index (HDI) countries from 2000 to 2020 were collected from the GLOBOCAN 2020 database. The joinpoint model and annual percent change (APC) were used to analyze the liver cancer global incidence and mortality as well as future epidemic trends from 2000 to 2020. Results: ASMR for male liver cancer was increased from 8.0/100, 000 in 2000 to 7.1/100,000 in 2015 (APC = -0.7, 95%CI: -1.2 ~ -0.3, P = 0.002), while ASMR for female liver cancer was increased from 3.0/100, 000 in 2000 to 2.8/100, 000 in 2015 (APC = -0.5, 95%CI: -0.8 ~ -0.2, P < 0.001). The ratio of male to female ASMR was 2.67:1 in 2000 and 2.51:1 in 2015, indicating a slight narrowing of the difference in mortality between men and women. In 2020, the global ASIR and ASMR for liver cancer were 9.5/100 000 and 8.7/100 000, respectively. Male ASIR and ASMR (14.1/100, 000 and 12.9/100, 000, respectively) were 2 ~ 3 times higher than females (5.2/100, 000 and 4.8/100, 000, respectively). There were significant differences between ASIR and ASMR in different HDI countries and regions (P(ASIR) = 0.008, P(ASMR) < 0.001), and the distributions of ASMR and ASIR were very similar. New cases and deaths were expected to increase by 58.6% (143,6744) and 60.9% (133, 5 375) in 2040, with the number of cases and deaths increasing by 39,7003 and 37,4208 in Asia, respectively. Conclusion: ASMR due to liver cancer worldwide has had a downward trend between 2000 and 2015. However, the latest epidemiological status and predictions of liver cancer in 2020 indicate that prevention and control will still be a major challenge globally in the next 20 years.
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Girardi F, Matz M, Stiller C, You H, Marcos Gragera R, Valkov MY, Bulliard JL, De P, Morrison D, Wanner M, O'Brian DK, Saint-Jacques N, Coleman MP, Allemani C, Hamdi-Chérif M, Kara L, Meguenni K, Regagba D, Bayo S, Cheick Bougadari T, Manraj SS, Bendahhou K, Ladipo A, Ogunbiyi OJ, Somdyala NIM, Chaplin MA, Moreno F, Calabrano GH, Espinola SB, Carballo Quintero B, Fita R, Laspada WD, Ibañez SG, Lima CA, Da Costa AM, De Souza PCF, Chaves J, Laporte CA, Curado MP, de Oliveira JC, Veneziano CLA, Veneziano DB, Almeida ABM, Latorre MRDO, Rebelo MS, Santos MO, Azevedo e Silva G, Galaz JC, Aparicio Aravena M, Sanhueza Monsalve J, Herrmann DA, Vargas S, Herrera VM, Uribe CJ, Bravo LE, Garcia LS, Arias-Ortiz NE, Morantes D, Jurado DM, Yépez Chamorro MC, Delgado S, Ramirez M, Galán Alvarez YH, Torres P, Martínez-Reyes F, Jaramillo L, Quinto R, Castillo J, Mendoza M, Cueva P, Yépez JG, Bhakkan B, Deloumeaux J, Joachim C, Macni J, Carrillo R, Shalkow Klincovstein J, Rivera Gomez R, Perez P, Poquioma E, Tortolero-Luna G, Zavala D, Alonso R, Barrios E, Eckstrand A, Nikiforuk C, Woods RR, Noonan G, Turner D, Kumar E, Zhang B, Dowden JJ, Doyle GP, Saint-Jacques N, Walsh G, Anam A, De P, McClure CA, Vriends KA, Bertrand C, Ramanakumar AV, Davis L, Kozie S, Freeman T, George JT, Avila RM, O’Brien DK, Holt A, Almon L, Kwong S, Morris C, Rycroft R, Mueller L, Phillips CE, Brown H, Cromartie B, Ruterbusch J, Schwartz AG, Levin GM, Wohler B, Bayakly R, Ward KC, Gomez SL, McKinley M, Cress R, Davis J, Hernandez B, Johnson CJ, Morawski BM, Ruppert LP, Bentler S, Charlton ME, Huang B, Tucker TC, Deapen D, Liu L, Hsieh MC, Wu XC, Schwenn M, Stern K, Gershman ST, Knowlton RC, Alverson G, Weaver T, Desai J, Rogers DB, Jackson-Thompson J, Lemons D, Zimmerman HJ, Hood M, Roberts-Johnson J, Hammond W, Rees JR, Pawlish KS, Stroup A, Key C, Wiggins C, Kahn AR, Schymura MJ, Radhakrishnan S, Rao C, Giljahn LK, Slocumb RM, Dabbs C, Espinoza RE, Aird KG, Beran T, Rubertone JJ, Slack SJ, Oh J, Janes TA, Schwartz SM, Chiodini SC, Hurley DM, Whiteside MA, Rai S, Williams MA, Herget K, Sweeney C, Kachajian J, Keitheri Cheteri MB, Migliore Santiago P, Blankenship SE, Conaway JL, Borchers R, Malicki R, Espinoza J, Grandpre J, Weir HK, Wilson R, Edwards BK, Mariotto A, Rodriguez-Galindo C, Wang N, Yang L, Chen JS, Zhou Y, He YT, Song GH, Gu XP, Mei D, Mu HJ, Ge HM, Wu TH, Li YY, Zhao DL, Jin F, Zhang JH, Zhu FD, Junhua Q, Yang YL, Jiang CX, Biao W, Wang J, Li QL, Yi H, Zhou X, Dong J, Li W, Fu FX, Liu SZ, Chen JG, Zhu J, Li YH, Lu YQ, Fan M, Huang SQ, Guo GP, Zhaolai H, Wei K, Chen WQ, Wei W, Zeng H, Demetriou AV, Mang WK, Ngan KC, Kataki AC, Krishnatreya M, Jayalekshmi PA, Sebastian P, George PS, Mathew A, Nandakumar A, Malekzadeh R, Roshandel G, Keinan-Boker L, Silverman BG, Ito H, Koyanagi Y, Sato M, Tobori F, Nakata I, Teramoto N, Hattori M, Kaizaki Y, Moki F, Sugiyama H, Utada M, Nishimura M, Yoshida K, Kurosawa K, Nemoto Y, Narimatsu H, Sakaguchi M, Kanemura S, Naito M, Narisawa R, Miyashiro I, Nakata K, Mori D, Yoshitake M, Oki I, Fukushima N, Shibata A, Iwasa K, Ono C, Matsuda T, Nimri O, Jung KW, Won YJ, Alawadhi E, Elbasmi A, Ab Manan A, Adam F, Nansalmaa E, Tudev U, Ochir C, Al Khater AM, El Mistiri MM, Lim GH, Teo YY, Chiang CJ, Lee WC, Buasom R, Sangrajrang S, Suwanrungruang K, Vatanasapt P, Daoprasert K, Pongnikorn D, Leklob A, Sangkitipaiboon S, Geater SL, Sriplung H, Ceylan O, Kög I, Dirican O, Köse T, Gurbuz T, Karaşahin FE, Turhan D, Aktaş U, Halat Y, Eser S, Yakut CI, Altinisik M, Cavusoglu Y, Türkköylü A, Üçüncü N, Hackl M, Zborovskaya AA, Aleinikova OV, Henau K, Van Eycken L, Atanasov TY, Valerianova Z, Šekerija M, Dušek L, Zvolský M, Steinrud Mørch L, Storm H, Wessel Skovlund C, Innos K, Mägi M, Malila N, Seppä K, Jégu J, Velten M, Cornet E, Troussard X, Bouvier AM, Guizard AV, Bouvier V, Launoy G, Dabakuyo Yonli S, Poillot ML, Maynadié M, Mounier M, Vaconnet L, Woronoff AS, Daoulas M, Robaszkiewicz M, Clavel J, Poulalhon C, Desandes E, Lacour B, Baldi I, Amadeo B, Coureau G, Monnereau A, Orazio S, Audoin M, D’Almeida TC, Boyer S, Hammas K, Trétarre B, Colonna M, Delafosse P, Plouvier S, Cowppli-Bony A, Molinié F, Bara S, Ganry O, Lapôtre-Ledoux B, Daubisse-Marliac L, Bossard N, Uhry Z, Estève J, Stabenow R, Wilsdorf-Köhler H, Eberle A, Luttmann S, Löhden I, Nennecke AL, Kieschke J, Sirri E, Justenhoven C, Reinwald F, Holleczek B, Eisemann N, Katalinic A, Asquez RA, Kumar V, Petridou E, Ólafsdóttir EJ, Tryggvadóttir L, Murray DE, Walsh PM, Sundseth H, Harney M, Mazzoleni G, Vittadello F, Coviello E, Cuccaro F, Galasso R, Sampietro G, Giacomin A, Magoni M, Ardizzone A, D’Argenzio A, Di Prima AA, Ippolito A, Lavecchia AM, Sutera Sardo A, Gola G, Ballotari P, Giacomazzi E, Ferretti S, Dal Maso L, Serraino D, Celesia MV, Filiberti RA, Pannozzo F, Melcarne A, Quarta F, Andreano A, Russo AG, Carrozzi G, Cirilli C, Cavalieri d’Oro L, Rognoni M, Fusco M, Vitale MF, Usala M, Cusimano R, Mazzucco W, Michiara M, Sgargi P, Boschetti L, Marguati S, Chiaranda G, Seghini P, Maule MM, Merletti F, Spata E, Tumino R, Mancuso P, Cassetti T, Sassatelli R, Falcini F, Giorgetti S, Caiazzo AL, Cavallo R, Piras D, Bella F, Madeddu A, Fanetti AC, Maspero S, Carone S, Mincuzzi A, Candela G, Scuderi T, Gentilini MA, Rizzello R, Rosso S, Caldarella A, Intrieri T, Bianconi F, Contiero P, Tagliabue G, Rugge M, Zorzi M, Beggiato S, Brustolin A, Gatta G, De Angelis R, Vicentini M, Zanetti R, Stracci F, Maurina A, Oniščuka M, Mousavi M, Steponaviciene L, Vincerževskienė I, Azzopardi MJ, Calleja N, Siesling S, Visser O, Johannesen TB, Larønningen S, Trojanowski M, Macek P, Mierzwa T, Rachtan J, Rosińska A, Kępska K, Kościańska B, Barna K, Sulkowska U, Gebauer T, Łapińska JB, Wójcik-Tomaszewska J, Motnyk M, Patro A, Gos A, Sikorska K, Bielska-Lasota M, Didkowska JA, Wojciechowska U, Forjaz de Lacerda G, Rego RA, Carrito B, Pais A, Bento MJ, Rodrigues J, Lourenço A, Mayer-da-Silva A, Coza D, Todescu AI, Valkov MY, Gusenkova L, Lazarevich O, Prudnikova O, Vjushkov DM, Egorova A, Orlov A, Pikalova LV, Zhuikova LD, Adamcik J, Safaei Diba C, Zadnik V, Žagar T, De-La-Cruz M, Lopez-de-Munain A, Aleman A, Rojas D, Chillarón RJ, Navarro AIM, Marcos-Gragera R, Puigdemont M, Rodríguez-Barranco M, Sánchez Perez MJ, Franch Sureda P, Ramos Montserrat M, Chirlaque López MD, Sánchez Gil A, Ardanaz E, Guevara M, Cañete-Nieto A, Peris-Bonet R, Carulla M, Galceran J, Almela F, Sabater C, Khan S, Pettersson D, Dickman P, Staehelin K, Struchen B, Egger Hayoz C, Rapiti E, Schaffar R, Went P, Mousavi SM, Bulliard JL, Maspoli-Conconi M, Kuehni CE, Redmond SM, Bordoni A, Ortelli L, Chiolero A, Konzelmann I, Rohrmann S, Wanner M, Broggio J, Rashbass J, Stiller C, Fitzpatrick D, Gavin A, Morrison DS, Thomson CS, Greene G, Huws DW, Grayson M, Rawcliffe H, Allemani C, Coleman MP, Di Carlo V, Girardi F, Matz M, Minicozzi P, Sanz N, Ssenyonga N, James D, Stephens R, Chalker E, Smith M, Gugusheff J, You H, Qin Li S, Dugdale S, Moore J, Philpot S, Pfeiffer R, Thomas H, Silva Ragaini B, Venn AJ, Evans SM, Te Marvelde L, Savietto V, Trevithick R, Aitken J, Currow D, Fowler C, Lewis C. Global survival trends for brain tumors, by histology: analysis of individual records for 556,237 adults diagnosed in 59 countries during 2000-2014 (CONCORD-3). Neuro Oncol 2023; 25:580-592. [PMID: 36355361 PMCID: PMC10013649 DOI: 10.1093/neuonc/noac217] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Survival is a key metric of the effectiveness of a health system in managing cancer. We set out to provide a comprehensive examination of worldwide variation and trends in survival from brain tumors in adults, by histology. METHODS We analyzed individual data for adults (15-99 years) diagnosed with a brain tumor (ICD-O-3 topography code C71) during 2000-2014, regardless of tumor behavior. Data underwent a 3-phase quality control as part of CONCORD-3. We estimated net survival for 11 histology groups, using the unbiased nonparametric Pohar Perme estimator. RESULTS The study included 556,237 adults. In 2010-2014, the global range in age-standardized 5-year net survival for the most common sub-types was broad: in the range 20%-38% for diffuse and anaplastic astrocytoma, from 4% to 17% for glioblastoma, and between 32% and 69% for oligodendroglioma. For patients with glioblastoma, the largest gains in survival occurred between 2000-2004 and 2005-2009. These improvements were more noticeable among adults diagnosed aged 40-70 years than among younger adults. CONCLUSIONS To the best of our knowledge, this study provides the largest account to date of global trends in population-based survival for brain tumors by histology in adults. We have highlighted remarkable gains in 5-year survival from glioblastoma since 2005, providing large-scale empirical evidence on the uptake of chemoradiation at population level. Worldwide, survival improvements have been extensive, but some countries still lag behind. Our findings may help clinicians involved in national and international tumor pathway boards to promote initiatives aimed at more extensive implementation of clinical guidelines.
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Li Q, Yang G, Zheng J, Xu J, Zhou X. [Optimized pathway to schistosomiasis elimination in China: a scrutiny using a marginal benefit approach]. ZHONGGUO XUE XI CHONG BING FANG ZHI ZA ZHI = CHINESE JOURNAL OF SCHISTOSOMIASIS CONTROL 2023; 35:1-6. [PMID: 36974008 DOI: 10.16250/j.32.1374.2023016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Following concerted efforts for over 7 decades, great achievements have been gained in the national schistosomiasis control program of China. Currently, China is moving towards the stage of schistosomiasis elimination, when the major task is to make full use of available resources to improve schistosomiasis surveillance and response to sustainably consolidate gained schistosomiasis control achievements and prevent re-emerging schistosomiasis. There is therefore an urgent need for optimization of interventions for schistosomiasis elimination. Based on analysis of socioeconomic features at different stages of the national schistosomiasis control program in China, this review discusses the relationship between the needs of assessment of schistosomiasis elimination interventions and the optimized strategy of schistosomiasis elimination at different stages of the national schistosomiasis control program using a marginal benefit approach and proposes the optimized schistosomiasis elimination strategy that allows the highest marginal benefit with currently available schistosomiasis elimination costs, so as to provide the optimal strategic pathway to schistosomiasis elimination and facilitate the achievement of the targets set in Healthy China 2030.
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Ni X, Guan W, Jiang Y, Li X, Chi Y, Pang Q, Liu W, Jiajue R, Wang O, Li M, Xing X, Wu H, Huo L, Liu Y, Jin J, Zhou X, Lv W, Zhou L, Xia Y, Gong Y, Yu W, Xia W. High prevalence of vertebral deformity in tumor-induced osteomalacia associated with impaired bone microstructure. J Endocrinol Invest 2023; 46:487-500. [PMID: 36097315 DOI: 10.1007/s40618-022-01918-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 09/02/2022] [Indexed: 10/14/2022]
Abstract
PURPOSE Patients with tumor-induced osteomalacia (TIO) often suffer from irreversible height loss due to vertebral deformity. However, the prevalence of vertebral deformity in TIO patients varies among limited studies. In addition, the distribution and type of vertebral deformity, as well as its risk factors, remain unknown. This study aimed to identify the prevalence, distribution, type and risk factors for vertebral deformity in a large cohort of TIO patients. METHODS A total of 164 TIO patients were enrolled in this retrospective study. Deformity in vertebrae T4-L4 by lateral thoracolumbar spine radiographs was evaluated according to the semiquantitative method of Genant. Bone microstructure was evaluated by trabecular bone score (TBS) and high-resolution peripheral QCT (HR-pQCT). RESULTS Ninety-nine (99/164, 60.4%) patients had 517 deformed vertebrae with a bimodal pattern of distribution (T7-9 and T11-L1), and biconcave deformity was the most common type (267/517, 51.6%). Compared with patients without vertebral deformity, those with vertebral deformity had a higher male/female ratio, longer disease duration, more height loss, lower serum phosphate, higher bone turnover markers, lower TBS, lower areal bone mineral density (aBMD), lower peripheral volumetric BMD (vBMD) and worse microstructure. Lower trabecular vBMD and worse trabecular microstructure in the peripheral bone and lower spine TBS were associated with an increased risk of vertebral deformity independently of aBMD. After adjusting for the number of deformed vertebrae, we found little difference in clinical indexes among the patients with different types of vertebral deformity. However, we found significant correlations of clinical indexes with the number of deformed vertebrae and the spinal deformity index. CONCLUSION We reported a high prevalence of vertebral deformity in the largest cohort of TIO patients and described the vertebral deformity in detail for the first time. Risk factors for vertebral deformity included male sex, long disease duration, height loss, abnormal biochemical indexes and bone impairment. Clinical manifestation, biochemical indexes and bone impairment were correlated with the number of deformed vertebrae and degree of deformity, but not the type of deformity.
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