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Liu SY, Dong S, Liao RQ, Jiang B, Zhang JT, Lin JT, Zhang S, Yang J, Nie Q, Yang X, Wang Q, Yan HH, Yan L, Tu H, Wang BC, Yang JJ, Zhou Q, Liu SY, Zhong WZ, Wu YL. LBA2 Phase II study of PD-L1 expression guidance on neoadjuvant (NA) nivolumab (Nivo) monotherapy with or without platinum-doublet chemotherapy in resectable NSCLC. IMMUNO-ONCOLOGY AND TECHNOLOGY 2022. [DOI: 10.1016/j.iotech.2022.100363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Xie YZ, Shi Y, Zhou Q, Feng CQ, Zhou Y, Li T, Yu Y, Fan XH. Comparison of the safety and efficacy of unilateral biportal endoscopic lumbar interbody fusion and uniportal endoscopic lumbar interbody fusion: a 1-year follow-up. J Orthop Surg Res 2022; 17:360. [PMID: 35870934 PMCID: PMC9308319 DOI: 10.1186/s13018-022-03249-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 07/12/2022] [Indexed: 11/10/2022] Open
Abstract
Objectives To compare the short-term outcomes of unilateral biportal endoscopic lumbar interbody fusion (BLIF) and uniportal endoscopic lumbar interbody fusion (ULIF). Methods Sixty patients diagnosed with L4/5 spinal stenosis who underwent BLIF and ULIF were included (30 in each group). Clinical evaluation was performed preoperatively and postoperatively in the 1st week, 1st month, and 1st year. Factors such as the visual analogue score (VAS), Oswestry Disability Index (ODI), operative time, surgical complications, and radiological outcomes (fusion rate, screw loosening, and cage subsidence) were compared between the two groups. Results All patients showed improved mean VAS and ODI at all three postoperative follow-ups, and no statistically significant differences were detected between the BLIF and ULIF groups. The mean operative time in the BLIF group was shorter than that in the ULIF group. Nerve root injury occurred in two patients in the BLIF group, while leakage of cerebrospinal fluid occurred in one patient in the ULIF group. All adverse events were treated adequately prior to discharge. The fusion rates with definite and probable grades were significantly higher in the BLIF group than that in the ULIF group. One case of cage subsidence with no screw loosening occurred in each group. Conclusion Both BLIF and ULIF are safe and effective surgical techniques. Compared with ULIF, BLIF has the advantages of shorter operative time and a higher fusion rate. Other merits of BLIF include a wider surgical field, greater maneuverability of instruments, visibility during cage implantation, and transverse orientation of the cage.
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Wu YL, Zhou Q, Pan Y, Yang X, Zhao Y, Han G, Pang Q, Zhang Z, Wang Q, Yao J, Wang H, Yang W, Liu B, Chen Q, Du X, Cai K, Li B, Shuang J, Song L, Shi W. LBA5 A phase II study of neoadjuvant SHR-1701 with or without chemotherapy (chemo) followed by surgery or radiotherapy (RT) in stage III unresectable NSCLC (uNSCLC). IMMUNO-ONCOLOGY AND TECHNOLOGY 2022. [DOI: 10.1016/j.iotech.2022.100361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui JJ, Cui XF, 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 C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu MH, Gu YT, Guan CY, Guo AQ, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang SS, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, 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 XX, 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, 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, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao QT, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiang T, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu CF, Xu CJ, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng XZ, Zeng Y, Zhang AQ, Zhang BL, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of an Isoscalar Resonance with Exotic J^{PC}=1^{-+} Quantum Numbers in J/ψ→γηη^{'}. PHYSICAL REVIEW LETTERS 2022; 129:192002. [PMID: 36399732 DOI: 10.1103/physrevlett.129.192002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 05/03/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Using a sample of (10.09±0.04)×10^{9} J/ψ events collected with the BESIII detector operating at the BEPCII storage ring, a partial wave analysis of the decay J/ψ→γηη^{'} is performed. The first observation of an isoscalar state with exotic quantum numbers J^{PC}=1^{-+}, denoted as η_{1}(1855), is reported in the process J/ψ→γη_{1}(1855) with η_{1}(1855)→ηη^{'}. Its mass and width are measured to be (1855±9_{-1}^{+6}) MeV/c^{2} and (188±18_{-8}^{+3}) MeV, respectively, where the first uncertainties are statistical and the second are systematic, and its statistical significance is estimated to be larger than 19σ.
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Zhang W, Li Z, Peng Y, Yin Y, Zhou Q. Patient-Specific Daily Updated Deep Learning Auto-Segmentation for MRI-Guided Adaptive Radiotherapy. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Liu J, Fang C, Zhou Q, He L, Yu J, Li Y, Feng M, Pan M, Zhao L, Tang D, Li X, Tan B, An R, Zheng X, Si M, Zhang B, Li L, Kang X. 179O A phase II, open-label, single-arm study of QL1604 plus paclitaxel-cisplatin/carboplatin as first-line treatment in patients with recurrent or metastatic cervical cancer. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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Liu SY, Tu HY, Wei XW, Yan HH, Dong X, Cui J, Zhou Z, Xu C, Zheng M, Li Y, Wang Z, Du Y, Chen Y, Ma R, Wang B, Cang S, Yang JJ, Chen H, Zhou Q, Wu YL. 385P Efficacy and safety of pyrotinib in untreated, advanced non-small cell lung cancer with HER2 mutations: A parallel, multi-center, multi-cohort patient-centric study (CTONG1702 and 1705). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.10.422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2022] Open
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Tan TT, Chen J, Zhang YJ, Chen YY, Zhou Q, Bao MW, Zhu WJ. Transcriptomic profiling reveals connection to lung autonomic nervous system dysfunction and inflammation in pulmonary artery hypertension rats. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.3066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Pulmonary arterial hypertension (PAH) is a progressive disorder characterized by elevated pulmonary artery pressure, right ventricular failure, and premature death. Previous studies showed autonomic nervous system (ANS) such as sympathetic nerve overactivity or impaired parasympathetic activity was implicated in the pathogenesis of PAH. However, PA remodeling and molecular mechanisms involved in ANS in PAH remain unclear.
Purpose
To unravel transcriptional regulation, underlying genes and signaling pathways linking to ANS in PAH.
Methods
Publicly available two RNA sequencing (RNAseq) datasets and one single-cell RNA sequencing (scRNAseq) data of lung from rats with PAH induced by high-dose monocrotaline (MCT) were downloaded and reprocessed. For RNA-seq data, STAR and RSEM were used for read alignment and gene expression qualification. Differential expression genes (DEGs) were identified using DSEseq2, after which enrichment analyses were implemented by clusterProfiler. scRNAseq data were analyzed using Seurat.
Results
Two RNAseq datasets identified a total of 6,046 and 2,172 DEGs respectively, including 2,945 and 1,228 up-regulated and 3,101 and 944 down-regulated. Overlapped DEGs genes among datasets were 1,123 genes. Functional enrichment analysis of downregulated DEGs in one data pointed out many dysregulated pathways related to nerve system, such as nervous system process, neuron projection, integral component of synaptic membrane in MCT-induced PAH rat (Fig. 1a). Both RNAseq datasets supported upregulated DEGs were also involved in pathways related to ANS including humoral immune response and synapse pruning (P<0.001) (Fig. 1a). Intriguingly, all four genes (Trem2, C1qa, C1qb and C1qc) in synapse pruning were progressively upregulated with severe PAH condition (P<0.05) (Fig. 1b, c). And RT-PCR results confirmed the expression level of these four genes were remarkably increased in PAH rats (P<0.0001) (Fig. 1d). These four genes are known marker genes for macrophages from lung and microglial cell from brain. scRNAseq data of lungs demonstrated these four genes were significantly upregulated in alveolar macrophages from MCT-PAH rats (P<0.001) (Fig. 1e). However, the pathogenic mechanisms of these four genes in nerve fibers from lungs underlying PAH have never been studied and would be further explored using histological analysis in this study.
Conclusions
Integrated bioinformatic analysis indicated the association of lung nervous system with PAH. Further, we identified four genes implicated in nervous system, previously reported to link to immune system and provide novel insights into the mechanisms underlying relationship between lung ANS and inflammation in the pathogenesis of PAH. The pathogenetic mechanism of these four genes is being further investigated.
Funding Acknowledgement
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The National Natural Science Foundation of Chinathe Nature Science Foundation of Hubei Province
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Zhou Q, Yin JY, Tan JW, Li ST, Jiang CL, He YF. [Effects of arsenic and its main metabolites on A549 cell apoptosis and the expression of pro-apoptotic genes Bad and Bik]. ZHONGHUA LAO DONG WEI SHENG ZHI YE BING ZA ZHI = ZHONGHUA LAODONG WEISHENG ZHIYEBING ZAZHI = CHINESE JOURNAL OF INDUSTRIAL HYGIENE AND OCCUPATIONAL DISEASES 2022; 40:661-667. [PMID: 36229210 DOI: 10.3760/cma.j.cn121094-20201208-00676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Objective: To investigate the effect of arsenic and its main metabolites on the apoptosis of human lung adenocarcinoma cell line A549 and the expression of pro-apoptotic genes Bad and Bik. Methods: In October 2020, A549 cells were recovered and cultured, and the cell viability was detected by the cell counting reagent CCK-8 to determine the concentration and time of sodium arsenite exposure to A549. The study was divided into NaAsO(2) exposure groups and metobol: le expoure groups: the metabolite comparison groups were subdivided into the control group, the monomethylarsinic acid exposure group (60 μmol/L) , and the dimethylarsinic acid exposure group (60 μmol/L) ; sodium arsenite dose groups were subdivided into 4 groups: control group (0) , 20, 40, 60 μmol/L sodium arsenite NaAsO(2). Hoechst 33342/propidium iodide double staining (Ho/PI) was used to observe cell apoptosis and real-time quantitative polymerase chain reaction (qRT-PCR) was used to detect the expression levels of Bad and Bik mRNA in cells after exposure. Western blotting was used to detect the protein expressions of Bad, P-Bad-S112, Bik, cleaved Bik and downstream proteins poly ADP-ribose polymerase PARP1 and cytochrome C (Cyt-C) , using spectrophotometry to detect the activity changes of caspase 3, 6, 8, 9. Results: Compared with the control group, the proportion of apoptotic cells in the 20, 40, and 60 μmol/L NaAsO(2) dose groups increased significantly (P<0.01) , and the expression levels of Bad, Bik mRNA, the protein expression levels of Bad, P-Bad-S112, Bik, cleaved Bik, PARP1, Cyt-C were increased (all P<0.05) , and the activities of Caspase 3, 6, 8, and 9 were significantly increased with significantly differences (P<0.05) . Compared with the control group, the expression level of Bad mRNA in the DMA exposure group (1.439±0.173) was increased with a significant difference (P=0.024) , but there was no significant difference in the expression level of Bik mRNA (P=0.788) . There was no significant differences in the expression levels of Bad and Bik mRNA in the poison groups (P=0.085, 0.063) . Compared with the control group, the gray values of proteins Bad, Bik, PARP1 and Cyt-C exposed to MMA were 0.696±0.023, 0.707±0.014, 0.907±0.031, 1.032±0.016, and there was no significant difference between the two groups (P=0.469, 0.669, 0.859, 0.771) ; the gray values of proteins Bad, Bik, PARP1 and Cyt-C exposed to DMA were 0.698±0.030, 0.705±0.022, 0.908±0.015, 1.029±0.010, and there was no difference between the two groups (P=0.479, 0.636, 0.803, 0.984) . Conclusion: Sodium arsenite induces the overexpression of Bad and Bik proteins, initiates the negative feedback regulation of phosphorylated Bad and the degradation of Bik, activates the downstream proteins PARP1, Cyt-C and Caspase pathways, and mediates the apoptosis of A549 cells.
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Zhou Q, Zhang HL, Jiang LY, Shi YK, Chen Y, Yu JM, Zhou CC, He Y, Hu YP, Liang ZA, Pan YY, Zhuo WL, Song Y, Wu G, Chen GY, Lu Y, Zhang CY, Zhang CY, Zhang YP, Chen Y, Lu S, Wu YL. EP08.02-064 ASTRIS China: A Real-world Study of Osimertinib in Patients with EGFR T790M Positive Non-small-cell Lung Cancer (NSCLC). J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Wang R, Wang T, Zhou Q. EP14.01-003 Parotid Metastases from Primary Lung Cancer: Case Series and Systematic Review on the Clinical Features. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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WANG Z, Lin ZB, Tu HY, Zhou Q, Xu BF, Wu YL. EP10.01-010 Real-world Study of the Incidence and Risk Factors of Venous Thromboembolism in Chinese Lung Cancer (RIVAL). J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Zhou Q, Li J, Wang J, Yang L, Fang J, Dong X, Yi T, Min X, Xu F, Chen J, Zhong D, Bai J, Liu L, Zeng A, Tang J, Wu H, Luo X, Yu J, Su W, Wu YL. EP08.02-063 SANOVO: A Phase 3 Study of Savolitinib or Placebo in Combination with Osimertinib in Patients with EGFR-mutant and MET Overexpressed NSCLC. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Wu YL, Zhou Q, Chen M, Pan Y, Jian O, Hu D, Lin Q, Wu G, Cui J, Chang J, Cheng Y, Huang C, Liu A, Yang N, Gong Y, Zhu C, Ma Z, Fang J, Chen G, Zhao J, Shi A, Lin Y, Li G, Liu Y, Wang D, Wu R, Xu X, Shi J, Liu Z, Wang J, Yang J. OA02.05 Sugemalimab vs Placebo after cCRT or sCRT in pts with Unresectable Stage III NSCLC: Final PFS Analysis of a Phase 3 Study. J Thorac Oncol 2022. [DOI: 10.1016/j.jtho.2022.07.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Liu X, Huang X, Han T, Li S, Xue C, Deng J, Zhou Q, Sun Q, Zhou J. Discrimination between microcystic meningioma and atypical meningioma using whole-lesion apparent diffusion coefficient histogram analysis. Clin Radiol 2022; 77:864-869. [PMID: 36030110 DOI: 10.1016/j.crad.2022.07.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 07/06/2022] [Accepted: 07/06/2022] [Indexed: 11/03/2022]
Abstract
AIM To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in discriminating microcystic meningioma (MCM) from atypical meningioma (AM). MATERIALS AND METHODS Clinical and preoperative MRI data of 20 patients with MCM and 26 patients with AM were analysed retrospectively. Whole-lesion apparent diffusion coefficient (ADC) histogram analysis was performed on each patient's lesion to obtain histogram parameters, including mean, variance, skewness, kurtosis, the 1st (ADCp1), 10th (ADCp10), 50th (ADCp50), 90th (ADCp90), and 99th (ADCp99) percentiles of ADC. The differences between the ADC histogram parameters of the two tumours were compared, and the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of statistically significant parameters in distinguishing the two tumours. RESULTS The mean, ADCp1, ADCp10, ADCp50, and ADCp90 of MCM were greater than those of AM, and significant differences were observed in these parameters between MCM and AM (all p<0.05). ROC analysis showed that the mean had the highest area under the curve value (AUC) in distinguishing the two tumours (AUC = 0.852), when using 120.46 × 10-6 mm2/s as the optimal threshold, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for discriminating the two groups were 84.6%, 75%, 80.4%, 81.5%, and 78.9%, respectively. CONCLUSION Histogram analysis based on whole-lesion ADC maps was useful for discriminating between MCM from AM preoperatively, with the mean being the most promising potential parameter.
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Chen XD, Chen LJ, Huang B, Liu HS, Zhou Q. [Mucin-production of follicular carcinoma of thyroid: report of a case]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2022; 51:773-775. [PMID: 35922174 DOI: 10.3760/cma.j.cn112151-20211217-00910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui JJ, Cui XF, 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 C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao YN, Gao Y, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu MH, Guan CY, Guo AQ, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang SS, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, 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 ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, 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 XX, 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, 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, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen XY, Shi BA, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Su YJ, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Y, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiang T, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu CF, Xu CJ, Xu GF, Xu QJ, Xu SY, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng X, Zeng Y, Zhang AQ, Zhang BL, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of a State X(2600) in the π^{+}π^{-}η' System in the Process J/ψ→γπ^{+}π^{-}η'. PHYSICAL REVIEW LETTERS 2022; 129:042001. [PMID: 35939017 DOI: 10.1103/physrevlett.129.042001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 06/24/2022] [Indexed: 06/15/2023]
Abstract
Based on (10087±44)×10^{6} J/ψ events collected with the BESIII detector, the process J/ψ→γπ^{+}π^{-}η^{'} is studied using two largest decay channels of the η^{'} meson, η^{'}→γπ^{+}π^{-} and η^{'}→ηπ^{+}π^{-}, η→γγ. A new resonance, which we denote as the X(2600), is observed with a statistical significance larger than 20σ in the π^{+}π^{-}η^{'} invariant mass spectrum, and it has a connection to a structure around 1.5 GeV/c^{2} in the π^{+}π^{-} invariant mass spectrum. A simultaneous fit on the π^{+}π^{-}η^{'} and π^{+}π^{-} invariant mass spectra with the two η^{'} decay modes indicates that the mass and width of the X(2600) state are 2618.3±2.0_{-1.4}^{+16.3} MeV/c^{2} and 195±5_{-17}^{+26} MeV, where the first uncertainties are statistical, and the second systematic.
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Nie L, Chen XQ, Song YK, Zhang MN, Xu M, Gong J, Zhou Q, Chen N. [Microfocal prostate cancer: a clinicopathological analysis of 206 cases]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2022; 51:634-639. [PMID: 35785834 DOI: 10.3760/cma.j.cn112151-20210928-00718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To investigate the clinical and pathological features and prognosis of patients with microfocal prostate adenocarcinoma. Methods: Clinical and pathological data of the patients diagnosed with microfocal adenocarcinoma on prostate biopsy at the West China Hospital from 2013 to 2019 were collected. Microfocal adenocarcinoma was defined as follows: Gleason score of 3+3=6, total number of the cores ≥10, number of the positive cores ≤2, and proportion of the tumor in each positive core<50%. Clinicopathological parameters, treatment plans and follow-up data were collected. Pathological information of the biopsy and radical resection specimens was used to analyze the correlation between pathological parameters in the biopsy report and adverse pathological features of radical resection specimens, including increased Gleason score, capsule invasion, positive surgical margin and perineural invasion. Results: A total of 206 cases of microfocal adenocarcinoma were diagnosed on prostate biopsies from 2013 to 2019, accounting for 6.7% of all adenocarcinoma cases. There were 139 cases of 1 positive core and 67 cases of 2 positive cores. Patients with microfocal adenocarcinoma were younger than those with non-microfocal adenocarcinoma (69 years versus 71 years, P<0.001). Compared with patients with non-microfocal adenocarcinoma, the pre-biopsy total prostate specific antigen (tPSA) and free prostate specific antigen (fPSA) levels in patients with microfocal adenocarcinoma were both lower (11.2 μg/L2 versus 23.7 μg/L2; 1.4 μg/L2 versus 3.0 μg/L2, P<0.001), the fPSA/tPSA level was higher (12.9% versus 10.7%, P<0.05), the prostate volume was larger (38.9 mL versus 34.3 mL, P<0.05), and the PSA density was lower (0.3 μg/L2 versus 0.8 μg/L2, P<0.001). 130 patients underwent radical prostatectomy, 30 patients chose active monitoring, 31 patients chose endocrine or radiation therapy, and 15 patients were lost to follow-up. Three patients in the active surveillance group underwent radical prostatectomy for disease progression after 21-39 months observation. Biochemical relapses occurred in two patients in the radical prostatectomy group. The remaining patients have no disease progression or recurrence at present. Compared with radical prostatectomy specimens, Gleason score in the biopsy material was increased in 64/115 patients (55.7%). Among resection excision specimens, 14 cases (12.2%) had extraprostatic extension (EPE), 35 cases (30.4%) had perineural invasion, and 16 cases (13.9%) had a positive margin. Univariate and multivariate analyses showed that low fPSA/tPSA ratio and 2 positive cores were independent risk factors for Gleason score increase in the radical prostatectomy specimens. A low fPSA/tPSA ratio was an independent risk factor for perineural invasion. Low fPSA/tPSA ratio and low prostate volume were associated with a positive margin in radical prostatectomy specimens. Conclusions: In this study, patients diagnosed with microfocal adenocarcinoma on prostate biopsy account for a high proportion of the patients with increased Gleason score in the radical prostatectomy specimens, and there is a certain proportion of adverse pathological features in the radical specimens. Therefore, for the patients with only a small amount of low-grade adenocarcinoma found in biopsy, PSA levels and PSA density should be taken into consideration in treatment selection.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, 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 DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, 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, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Held T, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu Y, 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 PW, Luo T, Luo XL, 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, Mo YJ, 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, Pettersson J, Ping JL, Ping RG, Poling R, Prasad V, Qi H, Qi HR, Qi KH, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun WY, Sun X, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, 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 YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng X, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of J/ψ Electromagnetic Dalitz Decays to X(1835), X(2120), and X(2370). PHYSICAL REVIEW LETTERS 2022; 129:022002. [PMID: 35867444 DOI: 10.1103/physrevlett.129.022002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/07/2022] [Accepted: 06/08/2022] [Indexed: 06/15/2023]
Abstract
Using a sample of about 10^{10} J/ψ events collected at a center-of-mass energy sqrt[s]=3.097 GeV with the BESIII detector, the electromagnetic Dalitz decays J/ψ→e^{+}e^{-}π^{+}π^{-}η^{'}, with η^{'}→γπ^{+}π^{-} and η^{'}→π^{+}π^{-}η, have been studied. The decay J/ψ→e^{+}e^{-}X(1835) is observed with a significance of 15σ, and also an e^{+}e^{-} invariant-mass dependent transition form factor of J/ψ→e^{+}e^{-}X(1835) is presented for the first time. The intermediate states X(2120) and X(2370) are also observed in the π^{+}π^{-}η^{'} invariant-mass spectrum with significances of 5.3σ and 7.3σ. The corresponding product branching fractions for J/ψ→e^{+}e^{-}X, X→π^{+}π^{-}η^{'} [X=X(1835), X(2120), and X(2370)] are reported.
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Zhou Q, Zhao L, Cao J. 406 Comparing Different Segmentation Models For The Aorta Based On St. Francis Heart Study. J Cardiovasc Comput Tomogr 2022. [DOI: 10.1016/j.jcct.2022.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Zhou Q, Zhongzhen L, Tingyu Y, Wen-jing W. P-204 Transcriptome analysis of cell-free RNAs in embryonic culture medium reveals their potentials on non-invasive testing. Hum Reprod 2022. [DOI: 10.1093/humrep/deac107.197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Study question
Could cell-free RNA (cfRNA) in culture medium be non-invasive strategy to select in vitro fertilized (IVF) embryos?
Summary answer
CfRNAs in culture medium could be potential markers correlated with embryo qualities.
What is known already
Infertility is a critical component of reproductive health and couples with infertility may choose assisted reproductive technology (ART) to increase their chances of conception. However, the effectiveness remains low. One way to improve the outcome is to screen the embryo prior to implantation. Noninvasive testing opens new perspectives in analyzing embryo qualities and current pending includes microscopy images coupled with artificial intelligence and omics analysis of the spent blastocyst medium (SBM). Cell-free DNA in SBM could be used to identify the embryo ploidy and metabolomic/proteomic markers could be correlated with embryo potential, while the research of cfRNA is lacking.
Study design, size, duration
We developed a new library method of polyadenylation ligation-mediated sequencing (PALM-Seq) to capture the low amount of cfRNA and collected twelve culture mediums of in vitro embryos on Day 3 and five samples of embryos on Day 5.
Participants/materials, setting, methods
We employed PALM-Seq on culture medium of embryos generated by IVF or Intracytoplasmic sperm injection (ICSI). Owing to the new method, we could comprehensively profile the cfRNAs, including miRNA, tRNA, piRNA, lncRNA and mRNA. The morphology and fragmentation of the recruited embryos were also recorded.
Main results and the role of chance
Generally, thousands of genes could be detected in all culture mediums and the number greatly increased in SBM. We identified several reported miRNA markers in our study, such as miR-21-5p and miR-92a-3p, while highly expressed miRNAs varied across samples and stages. We indeed found piRNA in mediums and several specific piRNAs had large amount of expression. In contrast, detected number and expression of tRNA were stable across samples. Besides of reported mRNA markers, we could profile the expression of all detected mRNAs and no differences were found between embryos with and without fragmentation. We found that the majority of mRNA fragments were shorter than 30 nucleotides. In addition, some granular-specific expressed mRNAs could be detected in medium on Day 3 and they decreased of medium on Day 5.
Limitations, reasons for caution
We have only conducted preliminary exploration in the culture medium of pre-implantation embryos and studies of larger sample size are needed.
Wider implications of the findings
Our research proved the feasibility of performing high-throughput sequencing of cfRNAs in SBM. It opens new perspectives on defining non-invasive markers and selection of embryos with the most potential. Our results also contribute a new insight on improving the treatment of infertility.
Trial registration number
2018YFC1004900
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Guo C, Zheng K, Xie Z, Lu X, Wu S, Ye Q, He Y, Zhou Q, Sun E. Intravoxel incoherent motion diffusion-weighted imaging as a quantitative tool for evaluating disease activity in patients with axial spondyloarthritis. Clin Radiol 2022; 77:e434-e441. [PMID: 35232574 DOI: 10.1016/j.crad.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 02/02/2022] [Indexed: 12/31/2022]
Abstract
AIM To determine the correlations between four quantitative magnetic resonance imaging (MRI) parameters derived from intravoxel incoherent motion diffusion-weighted images (IVIM DWI) and the semi-quantitative Spondyloarthritis Research Consortium of Canada (SPARCC) score of the sacroiliac joint (SIJ) and five clinical activity indices in patients with axial spondyloarthritis (axSpA). AND METHODS A total of 75 patients with axSpA and complete clinical activity indices and SIJ MRI were enrolled to this prospective study. Univariable and multivariable linear regression analyses were performed to evaluate correlations between MRI parameters and clinical activity indices after controlling for confounders. All data were further analysed using Pearson's correlation coefficients (r). RESULTS Only pure diffusion coefficient (D) and incoherent perfusion related microcirculation (D∗) were found to be independently positively correlated with several clinical activity indices (all p<0.05). Positive correlations were observed between D and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), Patient Global Assessment (PGA), extent of influence of pain, with r of 0.605, 0.402, 0.319, and 0.485 (all p<0.0125). D∗ correlated positively with BASDAI, BASFI, and PGA (r=0.436, 0.356, 0.301, respectively; all p<0.0125). CONCLUSION D and D∗ derived from IVIM DWI could be associated with some disease activity indices in patients with axSpA; apparent diffusion coefficient (ADC) and SPARCC scores were not correlated with these indices. IVIM DWI may be a useful tool for the quantitative assessment of disease activity in patients with axSpA.
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Liu J, Zhou Q, Chen X, Guo H, Long L. AB0206 STUDY ON THE SIGNIFICANCE OF SERUM COMPLEMENT C5 IN PATIENTS WITH RHEUMATOID ARTHRITIS. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundRecent studies have pointed out that complement system activation is a major alteration in early atherosclerotic plaques, and complement C5 has promising value as a novel circulating biomarker of atherosclerosis, but the relationship between C5 and carotid atherosclerotic (CAS) plaque in rheumatoid arthritis (RA) is still unclear.ObjectivesTo investigate the clinical significance of serum complement C5 and the association with CAS plaque in patients with RA.Methods143 patients with RA were included in the study, and 46 cases with age- and sex- matched healthy physical examination without RA or CAS plaque served as a normal control. All RA patients were divided into RA with CAS plaque group and RA without CAS plaque group according to the presence or absence of plaque formation in the carotid artery. The subject’s demographic data, laboratory investigations and serum samples were collected. Body mass index (BMI) and Disease Activity Score 28-joint counts (DAS28) were calculated. Glucocorticoid and DMARDS use were recorded in the past 3 months. ELISA method was used to determine the concentration of complement C5 in the serum of each participation. CAS plaque was determined by color Doppler ultrasound.ResultsSerum complement C5 in RA group was significantly lower than that in control group (P<0.05), whereas C5 level in RA with CAS plaque group was significantly higher than that in RA without CAS plaque group (P<0.05). In RA group, serum C5 level was positively correlated with CAS plaque, high-sensitivity C-reactive protein (hs-CRP) and fibrinogen (FIB) (r=0.204, P=0.017; r=0.225, P=0.009; r=0.186, P=0.029;). In addition, there was no significant correlation between serum C5 and sex, age, BMI, course of disease, DAS28, lipid profile (TG, serum triglyceride; TC, total cholesterol; LDLC, low density lipoprotein cholesterol; HDLC, high density lipoprotein cholesterol; TC/HDLC; LDLC/HDLC), immune markers (RF, rheumatoid factor; anti-CCP, anti-cyclic citrullinated peptide antibodies), cytokine (IL-6, Interleukin-6; TNF-α, Tumor necrosis factor-α), erythrocyte sedimentation rate (ESR) (all P>0.05), or drug therapy (all P>0.05).ConclusionC5 may be a novel circulating marker of atherosclerosis in RA patients, it might promise to assist in risk stratification for cardiovascular disease in the future.References[1]Martínez-López D, et al. Complement C5 Protein as a Marker of Subclinical Atherosclerosis. J Am Coll Cardiol. 2020 Apr 28;75(16):1926-1941.Disclosure of InterestsNone declared
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Biernat J, 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 DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, 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, Han WY, Hansson J, Hao XQ, Harris FA, Hüsken N, He KL, Heinsius FH, Heinz CH, Held T, 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, Huang Z, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, 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, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li HJ, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo PW, 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, Mo YJ, 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, Poling R, Prasad V, Qi H, Qi HR, Qi KH, Qi M, Qi TY, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schönning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun WY, Sun X, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner U, 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 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 YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng Y, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Probing CP symmetry and weak phases with entangled double-strange baryons. Nature 2022; 606:64-69. [PMID: 35650355 PMCID: PMC9159954 DOI: 10.1038/s41586-022-04624-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 03/08/2022] [Indexed: 12/03/2022]
Abstract
Though immensely successful, the standard model of particle physics does not offer any explanation as to why our Universe contains so much more matter than antimatter. A key to a dynamically generated matter-antimatter asymmetry is the existence of processes that violate the combined charge conjugation and parity (CP) symmetry1. As such, precision tests of CP symmetry may be used to search for physics beyond the standard model. However, hadrons decay through an interplay of strong and weak processes, quantified in terms of relative phases between the amplitudes. Although previous experiments constructed CP observables that depend on both strong and weak phases, we present an approach where sequential two-body decays of entangled multi-strange baryon-antibaryon pairs provide a separation between these phases. Our method, exploiting spin entanglement between the double-strange Ξ- baryon and its antiparticle2 [Formula: see text], has enabled a direct determination of the weak-phase difference, (ξP - ξS) = (1.2 ± 3.4 ± 0.8) × 10-2 rad. Furthermore, three independent CP observables can be constructed from our measured parameters. The precision in the estimated parameters for a given data sample size is several orders of magnitude greater than achieved with previous methods3. Finally, we provide an independent measurement of the recently debated Λ decay parameter αΛ (refs. 4,5). The [Formula: see text] asymmetry is in agreement with and compatible in precision to the most precise previous measurement4.
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Wang ZM, Liu Q, Liu YX, Chen YJ, Zhou Q, Deng XL, Zhang XD, Xu BH, Zhu YQ, Gao CZ, Yin L, Xie H, Fei W, Zhou J, Yuan CQ, He XN, Wang X, Chen LL. [Consensus of experts on the oral health management and medical risk prevention for the patients with chronic airway diseases (2022 edition)]. ZHONGHUA KOU QIANG YI XUE ZA ZHI = ZHONGHUA KOUQIANG YIXUE ZAZHI = CHINESE JOURNAL OF STOMATOLOGY 2022; 57:455-461. [PMID: 35484667 DOI: 10.3760/cma.j.cn112144-20220228-00081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.
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Wang CM, Xu CY, Jiang S, Zhou Q, Jiang ZJ, Cheng GP, Wu MJ, Feng TT, Yin WJ. [Pathological features related to onco-immunity and their clinical significance of pancreatic ductal adenocarcinoma]. ZHONGHUA BING LI XUE ZA ZHI = CHINESE JOURNAL OF PATHOLOGY 2022; 51:419-424. [PMID: 35511637 DOI: 10.3760/cma.j.cn112151-20210902-00641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To investigate the tumor immunity-related pathologic features and clinical significance in pancreatic ductal adenocarcinoma (PDAC). Methods: All pathologic materials and clinical information of 192 PDAC patients from the Cancer Hospital of the University of Chinese Academy of Sciences from January 2010 to December 2020 were collected. The onco-immune microenvironment associated morphologic features were evaluated, and MHC-Ⅰ, PD-L1, CD3, and CD8 expression were detected by immunohistochemistry (IHC). Then the correlation between the factors and their influence on prognosis was analyzed. Results: There were 163 cases of non-specific adenocarcinoma (163/192, 84.90%), 18 cases of adeno-squamous carcinoma (18/192, 9.37%), and 11 cases of other rare subtypes (11/192, 5.73%). Perineural invasion was observed in 110 cases (110/192, 57.29%) and vascular invasion in 86 cases (86/192, 44.79%). There were 84 cases (84/182, 46.15%) with severe chronic inflammation. Tumor infiltrating immune cell numbers (TII-N) were increased in 52 cases (52/192, 27.08%). Lymphocytes and plasma cells were the main infiltrating immune cells in 60 cases (60/192, 31.25%), whereas in 34 cases (34/192, 17.71%) the tumors were mainly infiltrated by granulocytes, and 98 cases (98/192, 51.04%) showed mixed infiltration. CD3+T cells were deficient in 124 cases (124/192, 66.31%). CD8+T cells were deficient in 152 cases (152/192, 79.58%). MHC-Ⅰ expression was down-regulated in 156 cases (156/192, 81.25%), and PD-L1 was positive (CPS≥1) in 46 cases (46/192, 23.96%). Statistical analysis showed that TII-N was negatively correlated with vascular invasion (P=0.035), perineural invasion (P=0.002), stage (P=0.004) and long-term alcohol consumption (P=0.039). The type of immune cells correlated positively with chronic pancreatic inflammation (P=0.002), and negatively with tumor differentiation (P=0.024). CD8+T cells were positively correlated with CD3+T cells (P=0.032), MHC-Ⅰ expression (P<0.001) and PD-L1 expression (P=0.001), and negatively correlated with long-term smoking (P=0.016). Univariate analysis showed that histological nonspecific type (P=0.013) and TII-N (P<0.001) were the factors for good prognosis. Vascular invasion (P=0.032), perineural invasion (P=0.001), high stage (P=0.003) and long-term alcohol consumption (P=0.004) were adverse prognostic factors. COX multivariate risk analysis found that TII-N was an independent favorable factor for PDAC, while perineural invasion was an independent adverse risk factor. Conclusions: TII-N is an independent superior prognostic factor for PDAC, and significantly correlated with many factors; chronic alcohol consumption and smoking may inhibit onco-immunity in PDAC patients.
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Li Y, Zhou Q, Luo X, Li H, Feng Y, Zhao Y, Yang X, Wu Y, Han M, Qie R, Wu X, Zhang Y, Huang S, Li T, Yuan L, Zhang J, Hu H, Liu D, Hu F, Zhang M, Hu D. Association between Sedentary Time and 6-Year All-Cause Mortality in Adults: The Rural Chinese Cohort Study. J Nutr Health Aging 2022; 26:236-242. [PMID: 35297465 DOI: 10.1007/s12603-022-1727-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES This study aims to prospectively explore the association between sedentary time and the risk of all-cause mortality in adults based on a cohort from rural areas of China. METHODS The study population included 20,194 adults at baseline (2007-2008) who participated in the Rural Chinese Cohort Study. Cox's proportional hazard regression model was used to analyze the hazard ratios (HRs) and 95% confidence intervals (CIs) of sedentary time and all-cause mortality, and a restricted cubic spline was used to model the dose-response relation. We also carried out a series of sensitivity analyses to verify the robustness of our main results. RESULTS The median follow-up duration was 6 years, with a total of 17,265 participants (response rate 85.5%) followed up, and 1,106 deaths observed. Data for 17,048 participants were analyzed, with the mean age of participants being 52.00. Compared with sedentary time <4 h/day group, the risk of all-cause mortality was significantly increased in the 8-11 h/day (HR=1.27, 95%CI:1.03-1.56) and ≥11 h/day groups (HR=1.48, 95%CI:1.20-1.84). With increases in sedentary time, the risk of all-cause mortality increased gradually (Ptrend <0.001). For each 1 h/day increase in sedentary time, the risk of all-cause mortality increased by 3% (HR=1.03, 95%CI: 1.01-1.05). Sensitivity analyses showed our main results were consistent. CONCLUSIONS Prolonged sedentary time increases the risk of all-cause mortality in the adult rural Chinese population. Reducing sedentary time may have important implications for reducing mortality risk.
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Ablikim M, Achasov M, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An M, An Q, Bai X, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere R, Cai H, Cai X, Calcaterra A, Cao G, Cao N, Cetin S, Chang J, Chang W, Chelkov G, Chen D, Chen G, Chen H, Chen M, Chen S, Chen X, Chen Y, Chen Z, Cheng W, Cibinetto G, Cossio F, Cui X, Dai H, Dai J, Dai X, Dbeyssi A, de Boer R, Dedovich D, Deng Z, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong L, Dong M, Dong X, Du S, Egorov P, Fan Y, Fang J, Fang S, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng C, Feng J, Fritsch M, Fu C, Gao Y, Gao Y, Gao Y, Garzia I, Ge P, Geng C, Gersabeck E, Gilman A, Goetzen K, Gong L, Gong W, Gradl W, Greco M, Gu L, Gu M, Guan C, Guo A, Guo A, Guo L, Guo R, Guo Y, Guskov A, Han T, Han W, Hao X, Harris F, He K, He K, Heinsius F, Heinz C, Heng Y, Herold C, Himmelreich M, Holtmann T, Hou G, Hou Y, Hou Z, Hu H, Hu J, Hu T, Hu Y, Huang G, Huang L, Huang X, Huang Y, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji Q, Ji X, Ji X, Ji Y, Jiang H, Jiang X, Jiao J, Jiao Z, Jin S, Jin Y, Jing M, Johansson T, Kalantar-Nayestanaki N, Kang X, Kappert R, Kavatsyuk M, Ke B, Keshk I, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu O, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lane J, Lange J, Larin P, Lavania A, Lavezzi L, Lei Z, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li C, Li D, Li F, Li G, Li H, Li H, Li H, Li H, Li H, Li J, Li J, Li J, Li K, Li L, Li L, Li P, Li S, Li W, Li W, Li X, Li X, Li X, Li Z, Liang H, Liang H, Liang H, Liang Y, Liang Y, Liao G, Liao L, Libby J, Limphirat A, Lin C, Lin D, Lin T, Liu B, Liu C, Liu D, Liu F, Liu F, Liu F, Liu G, Liu H, Liu H, Liu H, Liu J, Liu J, Liu J, Liu K, Liu K, Liu K, Liu L, Liu M, Liu P, Liu Q, Liu Q, Liu S, Liu T, Liu T, Liu W, Liu X, Liu Y, Liu Y, Liu Z, Liu Z, Lou X, Lu F, Lu H, Lu J, Lu J, Lu X, Lu Y, Lu Y, Luo C, Luo M, Luo P, Luo T, Luo X, Lyu X, Ma F, Ma H, Ma L, Ma M, Ma Q, Ma R, Ma R, Ma X, Ma X, Maas F, Maggiora M, Maldaner S, Malde S, Malik Q, Mangoni A, Mao Y, Mao Z, Marcello S, Meng Z, Messchendorp J, Mezzadri G, Min T, Mitchell R, Mo X, Muchnoi N, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev I, Ning Z, Nisar S, Olsen S, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng H, Peters K, Pettersson J, Ping J, Ping R, Plura S, Pogodin S, Poling R, Prasad V, Qi H, Qi H, Qi M, Qi T, Qian S, Qian W, Qian Z, Qiao C, Qin J, Qin L, Qin X, Qin X, Qin Z, Qiu J, Qu S, Rashid K, Ravindran K, Redmer C, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang H, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan X, Shangguan J, Shao M, Shen C, Shen H, Shen X, Shi H, Shi R, Shi X, Shi X, Song J, Song J, Song W, Song Y, Sosio S, Spataro S, Stieler F, Su K, Su P, Sui F, Sun G, Sun H, Sun J, Sun L, Sun S, Sun T, Sun W, Sun X, Sun Y, Sun Y, Sun Z, Tan Y, Tan Y, Tang C, Tang G, Tang J, Teng J, Thoren V, Tian W, Tian Y, Uman I, Wang B, Wang C, Wang D, Wang H, Wang H, Wang K, Wang L, Wang M, Wang M, Wang M, Wang S, Wang W, Wang W, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Wang Z, Wei D, Weidner F, Wen S, White D, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu J, Wu L, Wu L, Wu X, Wu X, Wu Z, Xia L, Xiao H, Xiao S, Xiao Z, Xie X, Xie Y, Xie Y, Xing T, Xu C, Xu G, Xu Q, Xu W, Xu X, Xu Y, Yan F, Yan L, Yan W, Yan W, Yang H, Yang H, Yang L, Yang S, Yang Y, Yang Y, Yang Z, Ye M, Ye M, Yin J, You Z, Yu B, Yu C, Yu G, Yu J, Yu T, Yuan C, Yuan L, Yuan Y, Yuan Z, Yue C, Zafar A, Zeng XZ, Zeng Y, Zhang A, Zhang B, Zhang G, Zhang H, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang L, Zhang L, Zhang L, Zhang S, Zhang S, Zhang S, Zhang X, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhao G, Zhao J, Zhao J, Zhao J, Zhao L, Zhao L, Zhao M, Zhao Q, Zhao S, Zhao Y, Zhao Y, Zhao Z, Zhemchugov A, Zheng B, Zheng J, Zheng Y, Zhong B, Zhong C, Zhou L, Zhou Q, Zhou X, Zhou X, Zhou X, Zhou X, Zhu A, Zhu J, Zhu K, Zhu K, Zhu S, Zhu T, Zhu W, Zhu W, Zhu Y, Zhu Z, Zou B, Zou J. Partial wave analysis of
J/ψ→γη′η′. Int J Clin Exp Med 2022. [DOI: 10.1103/physrevd.105.072002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Yu S, Cai F, Feng YL, Zhou Q, Zheng ZH, Xiao Y, Zhu LM, Chen YJ. [Methylation of p16 gene and reduced expression of p16 protein in insulinoma associated with clinicopathological features]. ZHONGHUA YI XUE ZA ZHI 2022; 102:1028-1033. [PMID: 35399023 DOI: 10.3760/cma.j.cn112137-20211029-02404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To study the alterations of p16 gene and its expression in insulinoma and to correlate the findings with clinicopathological characteristics. Methods: Expression of p16 protein was detected in 72 insulinomas and 49 para-tumoral or normal pancreatic tissues by immunohistochemical staining. Genomic DNA was isolated from 32 tumor tissue and 17 paired pancreatic tissues and bisulfite-modified. Promoter methylation status of p16 gene was detected in 32 tumor tissue and 17 paired pancreatic tissues by methylation specific PCR. The findings were correlated with the clinicopathological features. Results: There were 30 males and 42 females in all 72 patients, aged (46.5±14.0) years. Loss or reduced expression of p16 protein was found in 42 of 72 insulinomas (58.3%) while loss or reduced expression of p16 was seen in only 34.7% (17/49) of para-tumoral or normal pancreatic tissues (χ²=6.52, P=0.011). Promoter methylation of p16 gene was found in 13 of 32 insulinomas (40.6%) and only 2 of 17 (11.8%) para-tumoral tissues (χ²=4.35, P=0.037). The expression of p16 protein in insulinoma was not associated with clinicopathological features such as gender, age, tumor size and tumor grade. Conclusions: Loss or reduced expression of p16 protein was found in insulinomas, and associated with p16 gene promoter methylation.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, 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 DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, 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 C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Egorov P, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Guan CY, Guo AQ, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu T, Liu T, Liu WM, Liu X, Liu Y, 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 PW, Luo T, Luo XL, 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, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Plura S, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu CJ, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng X, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XM, 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, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Observation of the Singly Cabibbo Suppressed Decay Λ_{c}^{+}→nπ^{+}. PHYSICAL REVIEW LETTERS 2022; 128:142001. [PMID: 35476477 DOI: 10.1103/physrevlett.128.142001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 02/05/2022] [Accepted: 03/01/2022] [Indexed: 06/14/2023]
Abstract
The singly Cabibbo-suppressed decay Λ_{c}^{+}→nπ^{+} is observed for the first time with a statistical significance of 7.3σ by using 3.9 fb^{-1} of e^{+}e^{-} collision data collected at center-of-mass energies between 4.612 and 4.699 GeV with the BESIII detector at BEPCII. The branching fraction of Λ_{c}^{+}→nπ^{+} is measured to be (6.6±1.2_{stat}±0.4_{syst})×10^{-4}. By taking the upper limit of branching fractions of Λ_{c}^{+}→pπ^{0} from the Belle experiment, the ratio of branching fractions between Λ_{c}^{+}→nπ^{+} and Λ_{c}^{+}→pπ^{0} is calculated to be larger than 7.2 at the 90% confidence level, which disagrees with most predictions of the available phenomenological models. In addition, the branching fractions of the Cabibbo-favored decays Λ_{c}^{+}→Λπ^{+} and Λ_{c}^{+}→Σ^{0}π^{+} are measured to be (1.31±0.08_{stat}±0.05_{syst})×10^{-2} and (1.22±0.08_{stat}±0.07_{syst})×10^{-2}, respectively, which are consistent with previous results.
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Huang W, Deng HY, Wang YQ, Wang YF, Xu K, Lin MY, Weng JH, He SK, Zhou Q. 93P Noncancer-specific mortality in patients with stage IA1 NSCLC after surgical resection: The role of comorbidities in prognosis. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.02.103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Zhou Q, Yu X, Gao B, Ma Z, Chu Q, Huang D, Zhao J, Day D, Body A, Pan H, Cui J, Li H, Sun J, Zhang J, Fei C, Wu YL. 2P Sitravatinib + tislelizumab in patients with metastatic non-small cell lung cancer (NSCLC). Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.01.064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Yu SS, Ma MY, Zhou R, Liang R, Duan Z, Wang J, Tian Y, Jiang J, He X, Zhou Q. Methotrexate/mifepristone-combined with embryo removal in the treatment of caesarean scar pregnancy. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2022; 26:1984-1993. [PMID: 35363349 DOI: 10.26355/eurrev_202203_28347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE The aim of this study was to compare the effect of different administration modalities of methotrexate (MTX)/mifepristone in the initial medication stage, followed by embryo transfer in the treatment of caesarean scar pregnancy (CSP). PATIENTS AND METHODS A retrospective analysis of 66 CSP patients who received treatment in our hospital from January 2015 to July 2021 was performed, and participants were divided into three groups: Group one (n=14) received mifepristone followed by embryo removal treatment, Group two (n=29) received MTX followed by embryo removal, and Group three (n=23) received a methotrexate/mifepristone combined treatment followed by embryo removal. The basic findings were analysed, along with the curative effects between the three groups. Risk factors predicting additional treatment after initial intervention failure were analysed. RESULTS There were statistically significant differences in gestational age, hospitalization days, costs, myometrial thickness, cardiac activity, and mean sac diameter between groups (p<0.05) after grouping by eight weeks. The initial intervention success rates were 92.86%, 89.66%, and 65.22% in Group one, two, and three, respectively (p<0.05), while the complication rates were 14.29%, 6.90%, and 26.87%, respectively (p>0.05). After grouping according to eight weeks of gestational age, the difference in initial serum β-hCG between Group two and three was statistically significant (p<0.05). Mean sac diameter was a risk factor for additional treatment after initial intervention failure, with an odds ratio of 1.113 (p<0.05). A cut-off of 22.75 mm was a preferable indicator. CONCLUSIONS MTX/mifepristone followed by embryo removal is a reliable way to treat CSP. Mean sac diameter was a risk factor for additional treatment after initial intervention failure.
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He XW, Zhou Q, Xiao ZC, Xu C, Zeng HS. [Application of antegrade wire and guide wire-capture technique in transcatheter aortic valve implantation: three cases report]. ZHONGHUA XIN XUE GUAN BING ZA ZHI 2022; 50:183-185. [PMID: 35172465 DOI: 10.3760/cma.j.cn112148-20210611-00496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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Zhu JW, Xu YJ, Li YT, Zhou Q, Chen LX, Meng XJ. [Relationships between lead-induced learning and memory impairments and gut microbiota disturbance in mice]. ZHONGHUA LAO DONG WEI SHENG ZHI YE BING ZA ZHI = ZHONGHUA LAODONG WEISHENG ZHIYEBING ZAZHI = CHINESE JOURNAL OF INDUSTRIAL HYGIENE AND OCCUPATIONAL DISEASES 2022; 40:83-89. [PMID: 35255572 DOI: 10.3760/cma.j.cn121094-20210121-00041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the effect of lead exposure on the neurobehavior and gut microbiota community structure in mice. Methods: In August 2019, 64 C57BL/6 mice were randomly divided into 4 groups: control group (0 ppm) , low lead exposure group (20 mg/l) , medium lead exposure group (100 mg/l) and high lead exposure group (500 mg/l) . During the experiment, they were free to eat and drink. The drinking water of the lead exposure group was mixed with lead acetate, and sodium acetate was added in the control group. After 10 weeks of exposure, the Morris water maze was used to test the learning and memory ability of each group of mice, and then they were sacrificed for sampling. ICP-MS was used to detect lead content in whole blood and brain tissue. ELISA was used to determine the level of IL-1β in mouse serum. 16S rRNA sequencing was used to detect the structural diversity of the intestinal flora in feces, and then the correlation between the flora and behavior indicators was analyzed. Results: In the Morris water maze experiment, compared with the control group, there was no significant difference in the body weight and swimming speed of the mice in the lead exposure groups. The escape latency of the mice in the 100 mg/l and 500 mg/l dose groups was prolonged, and the number of platform crossings decreased (P<0.05) ; meanwhile, the staying time of the mice in the 500 mg/l Pb-treated group in the target quadrant was lower than that of the control group, and the difference was statistically significant (P<0.05) . Compared with the control group, the blood lead content of the mice in each lead exposure group was significantly increased, and the brain lead content of mice in the 500 mg/l dose group was significantly elevated (P<0.05) . The serum IL-1β levels of mice in each lead exposure group were higher than those of the control group (P<0.05) . At the phylum level, the relative abundance of the Proteobacteria phylum in all of Pb-treated groups was significantly increased (P<0.05) ; at the genus level, Allobaculum, Desulfovibrio, Lachnospiraceae_NK4A136_group, Turicibacter and Ureaplasma were significantly increased (P<0.05) . Among them. The relative abundance of Desuffaoibrio, Turici bacter, and Ureaplasma was negatively correlated with the residence time of mice in the quadrant of the platform (r=-0.32, -0.29, -0.44, P<0.05) . Conclusion: Lead exposure induced learning and memory impairments in mice, which may be related to the disturbance of the gut microbiota.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, 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 DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Andersson WI, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li HN, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Lin T, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu T, Liu WM, Liu X, Liu Y, 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 PW, Luo T, Luo XL, 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, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Pettersson J, Ping JL, Ping RG, Pogodin S, Poling R, Prasad V, 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, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun X, Sun YJ, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HX, Yang L, Yang SL, Yang YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng XZ, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, 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, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Measurement of the Cross Section for e^{+}e^{-}→Hadrons at Energies from 2.2324 to 3.6710 GeV. PHYSICAL REVIEW LETTERS 2022; 128:062004. [PMID: 35213186 DOI: 10.1103/physrevlett.128.062004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
Based on electron-positron collision data collected with the BESIII detector operating at the Beijing Electron-Positron Collider II storage rings, the value of R≡σ(e^{+}e^{-}→hadrons)/σ(e^{+}e^{-}→μ^{+}μ^{-}) is measured at 14 center-of-mass energies from 2.2324 to 3.6710 GeV. The resulting uncertainties are less than 3.0% and are dominated by systematic uncertainties.
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Liu S, Chen H, Wang C, Xu Q, Feng S, Wang Y, Yao J, Zhou Q, Tong C, Yang B, Chen J, Jiang H. POS-340 MAPK1 MEDIATES HIGH GLUCOSE INDUCED RENAL TUBULAR INJURY THROUGH DISRUPTING THE INTEGRITY OF MAM. Kidney Int Rep 2022. [DOI: 10.1016/j.ekir.2022.01.361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Zhou Q, Tan YL, How CH, Yang LY. Breastfeeding woes: a family physician’s approach. Singapore Med J 2022; 63:68-73. [DOI: 10.11622/smedj.2022036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Wu Z, Zhou Q, Li Y, Zhang N, Liu HS, Chen C, Pang GF, Liang QH, Hu CY, Yuan HP, Yang Z, Sun L. [Assessment of cognitive function of the elderly by serum metabolites of brain-gut axis]. ZHONGHUA YI XUE ZA ZHI 2022; 102:125-129. [PMID: 35012301 DOI: 10.3760/cma.j.cn112137-20210702-01496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To investigate the feasibility of assessing cognitive function of the elderly by serum metabolites of brain-gut axis. Methods: Convenience sampling was used to select 100 and 60 participants from the healthy population cohort and microecological balance cohort of the longevity population in Guangxi, to constitute subset of healthy population and longevity population, respectively. A questionnaire was used to investigate the demographic characteristics of the subjects, 2-5 ml of fasting venous blood was collected from the subjects, and the serum untargeted metabolomics was determined by liquid chromatography tandem mass spectrometry. The biomarkers related to the brain-gut axis were collected through literature retrieval, and the results were intersected with the untargeted metabolites and annotated. Spearman correlation analysis was used to screen serum metabolites of brain-gut axis associated with aging, and multiple linear regression method was used to construct biological age model. The mini mental status examination was used to evaluate the cognitive function of longevity population subsets. The differences of biological age and chronological age of longevity population subsets with different cognitive function were compared. Results: The M (Q1, Q3) of subset of healthy population and longevity population were 64 (38, 72) and 97 (95, 99) years old, respectively, and there were 50 (50.0%) and 44 (73.3%) females, respectively. Nine serum metabolites of brain-gut axis were obtained by initial screening, which were propionic acid, glutamic acid, γ-aminobutyric acid (GABA), lactic acid, 5-hydroxytryptamine (5-HT), tryptophan, trimethylamine oxide, dopamine and canine urea. Spearman correlation analysis showed that glutamic acid and dopamine were positively correlated with aging (r values were 0.208 and 0.524, respectively, all P values<0.05), and tryptophan, 5-HT and GABA were negatively correlated with aging (r values were -0.308, -0.533 and -0.213, respectively, all P values<0.05). The biological age model was constructed as: y=49.81-1.18×10-5× GABA-1.82×10-4×5-HT+1.99×10-3×dopamine+1.65×10-6×glutamic acid -2.04×10-6×tryptophan+2.36×gender, where y was the biological age (years), the items on the right were the intercept item, the relative concentration of each metabolite, and gender (male=1, female=2). The coefficient of determination of model was 0.50 (P<0.001). The M (Q1, Q3) of the chronological age of the subset of longevity population with poor, moderate and good cognitive function were 97 (94, 100), 97 (93, 101) and 96 (94, 101) years old, respectively, and there was no statistical significance in pairwise comparison (all P values>0.05). The M (Q1, Q3) of the biological age of the subjects with better cognitive function was 51 (38, 54) years old, which was lower than that of the subjects with poor cognitive function [57 (47, 61)] (P=0.040). Conclusion: The biological age model can be constructed based on serum metabolites of brain-gut axis and used to evaluate the cognitive function of the elderly.
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai XH, Bai Y, Bakina O, Baldini Ferroli R, 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 DY, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Cui XF, Dai HL, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fan YL, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fritsch M, Fu CD, Gao Y, Gao Y, Gao Y, Gao YG, Garzia I, Ge PT, Geng C, 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, Han WY, Hao XQ, Harris FA, He KL, Heinsius FH, Heinz CH, Held T, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jiang HB, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth MG, Kühn W, Lane JJ, Lange JS, 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 H, Li HB, Li HJ, Li JL, Li JQ, Li JS, Li K, Li LK, Li L, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li X, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Lin CX, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu PL, Liu Q, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu Y, 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 PW, Luo T, Luo XL, 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, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Mo YJ, 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, Pettersson J, Ping JL, Ping RG, Pogodin S, Poling R, Prasad V, Qi H, Qi HR, Qi KH, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang HS, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shangguan JF, Shao M, Shen CP, Shen HF, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Su KX, Su PP, Sui FF, Sun GX, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun WY, Sun X, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Tian WH, Tian YT, Uman I, Wang B, Wang CW, Wang DY, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang Y, Wang YD, Wang YF, Wang YQ, Wang YY, Wang Z, Wang ZY, Wang Z, 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 Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, 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 YX, Yang Y, Yang Z, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Yuncu A, Zafar AA, Zeng Y, Zhang AQ, Zhang BX, Zhang G, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang S, Zhang SF, Zhang S, Zhang XD, Zhang XY, Zhang Y, Zhang YH, Zhang YT, Zhang Y, Zhang Y, Zhang ZH, 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 Y, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu TJ, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. First Measurement of Polarizations in the Decay D^{0}→ωφ. PHYSICAL REVIEW LETTERS 2022; 128:011803. [PMID: 35061485 DOI: 10.1103/physrevlett.128.011803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/14/2021] [Indexed: 06/14/2023]
Abstract
Using a data sample corresponding to an integrated luminosity of 2.93 fb^{-1} collected at a center-of-mass energy sqrt[s]=3.773 GeV by the BESIII detector, the decay D^{0}→ωϕ is observed for the first time. The branching fraction is measured to be (6.48±0.96±0.40)×10^{-4} with a significance of 6.3σ, where the first and second uncertainties are statistical and systematic, respectively. An angular analysis reveals that the ϕ and ω mesons from the D^{0}→ωϕ decay are transversely polarized. The 95% confidence level upper limit on longitudinal polarization fraction is set to be less than 0.24, which is inconsistent with current theoretical expectations and challenges our understanding of the underlying dynamics in charm meson decays.
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Wang K, Zhou Q. Risk Estimates of Dementia and Alzheimer's Disease among Different Whole Grain Food Consumption Categories: A Pilot Study. J Prev Alzheimers Dis 2022; 10:133-136. [PMID: 36641618 DOI: 10.14283/jpad.2022.91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
OBJECTIVES Whole grains (WG) have been widely recognized as healthy foods but few prospective studies have examined WG foods consumption and all-cause dementia and Alzheimer's disease (AD) dementia. This pilot study aimed to investigate the relationship between WG and dementia. METHODS 2958 subjects from the Framingham Offspring cohort were included with the Food Frequency Questionnaire (FFQ) to assess their diet intake. And multivariate Cox proportional regression was conducted to examine the relations. RESULTS After an average follow-up of 12.6 years, 322 all-cause dementia were documented, including 247 AD dementia. In the fully adjusted model, participants in the highest vs. the lowest quintiles of WG consumption had lower risks of all-cause dementia (HR, 0.72; 95% CI, 0.53-0.84; P for trend <0.001) and AD dementia (HR, 0.64; 95% CI, 0.47-0.80; P for trend <0.001). CONCLUSIONS High consumption of WG foods is associated with decreased risks of all-cause dementia and AD dementia.t disease mortality. Our findings are from a preliminary study and need to be confirmed in comprehensive settings and integrated statistical methods.
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Wang K, Guo K, Ji Z, Liu Y, Chen F, Wu S, Zhang Q, Yao Y, Zhou Q. Association of Preeclampsia with Incident Dementia and Alzheimer’s Disease among Women in the Framingham Offspring Study. J Prev Alzheimers Dis 2022; 9:725-730. [DOI: 10.14283/jpad.2022.62] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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93
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Lin R, Guan Z, Zhou Q, Zhong J, Zheng C, Zhang Z. Effects of 7,12-Dimethylbenz(a)anthracene on Apoptosis of Breast Cancer Cells through Regulating Expressions of Fas Ligand and B-Cell Lymphoma 2. Indian J Pharm Sci 2022. [DOI: 10.36468/pharmaceutical-sciences.spl.443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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94
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Zhang H, Chen Y, Lin J, Jiang X, Zhou Q. A POEMS syndrome patient with idiopathic non-cirrhotic portal hypertension received the transjugular intrahepatic portosystemic shunt: a case report and literature review. Niger J Clin Pract 2022; 25:1939-1944. [DOI: 10.4103/njcp.njcp_360_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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95
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Ablikim M, Achasov M, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An M, An Q, Bai X, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere R, Cai H, Cai X, Calcaterra A, Cao G, Cao N, Cetin S, Chang J, Chang W, Chelkov G, Chen D, Chen G, Chen H, Chen M, Chen S, Chen X, Chen Y, Chen Z, Cheng W, Cibinetto G, Cossio F, Cui X, Dai H, Dai X, Dbeyssi A, de Boer R, Dedovich D, Deng Z, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong L, Dong M, Dong X, Du S, Fan Y, Fang J, Fang S, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng C, Feng J, Fritsch M, Fu C, Gao Y, Gao Y, Gao Y, Gao Y, Garzia I, Ge P, Geng C, Gersabeck E, Gilman A, Goetzen K, Gong L, Gong W, Gradl W, Greco M, Gu L, Gu M, Gu S, Gu Y, Guan C, Guo A, Guo L, Guo R, Guo Y, Guskov A, Han T, Han W, Hao X, Harris F, Hüsken N, He K, Heinsius F, Heinz C, Held T, Heng Y, Herold C, Himmelreich M, Holtmann T, Hou Y, Hou Z, Hu H, Hu J, Hu T, Hu Y, Huang G, Huang L, Huang X, Huang Y, Huang Z, Hussain T, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji Q, Ji X, Ji X, Ji Y, Jiang H, Jiang X, Jiao J, Jiao Z, Jin S, Jin Y, Johansson T, Kalantar-Nayestanaki N, Kang X, Kappert R, Kavatsyuk M, Ke B, Keshk I, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu O, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lane J, Lange J, Larin P, Lavania A, Lavezzi L, Lei Z, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li C, Li D, Li F, Li G, Li H, Li H, Li H, Li H, Li J, Li J, Li J, Li K, Li L, Li L, Li P, Li S, Li W, Li W, Li X, Li X, Li X, Li Z, Liang H, Liang H, Liang H, Liang Y, Liang Y, Liao G, Liao L, Libby J, Lin C, Liu B, Liu C, Liu D, Liu F, Liu F, Liu F, Liu H, Liu H, Liu H, Liu H, Liu J, Liu J, Liu J, Liu K, Liu K, Liu K, Liu L, Liu M, Liu P, Liu Q, Liu Q, Liu S, Liu S, Liu T, Liu W, Liu X, Liu Y, Liu Y, Liu Z, Liu Z, Lou X, Lu F, Lu F, Lu H, Lu J, Lu J, Lu X, Lu Y, Lu Y, Luo C, Luo M, Luo P, Luo T, Luo X, Lusso S, Lyu X, Ma F, Ma H, Ma L, Ma M, Ma Q, Ma R, Ma R, Ma X, Ma X, Maas F, Maggiora M, Maldaner S, Malde S, Malik Q, Mangoni A, Mao Y, Mao Z, Marcello S, Meng Z, Messchendorp J, Mezzadri G, Min T, Mitchell R, Mo X, Mo Y, Muchnoi N, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev I, Ning Z, Nisar S, Olsen S, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng H, Peters K, Pettersson J, Ping J, Ping R, Poling R, Prasad V, Qi H, Qi H, Qi K, Qi M, Qi T, Qi T, Qian S, Qian W, Qian Z, Qiao C, Qin L, Qin X, Qin X, Qin Z, Qiu J, Qu S, Rashid K, Ravindran K, Redmer C, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang H, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan D, Shan W, Shan X, Shangguan J, Shao M, Shen C, Shen P, Shen X, Shi H, Shi R, Shi X, Shi X, Song J, Song W, Song Y, Sosio S, Spataro S, Su K, Su P, Sui F, Sun G, Sun H, Sun J, Sun L, Sun S, Sun T, Sun W, Sun W, Sun X, Sun Y, Sun Y, Sun Y, Sun Z, Tan Y, Tan Y, Tang C, Tang G, Tang J, Teng J, Thoren V, Tian W, Uman I, Wang B, Wang C, Wang D, Wang H, Wang H, Wang K, Wang L, Wang M, Wang M, Wang M, Wang W, Wang W, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Wang Z, Wei D, Weidenkaff P, Weidner F, Wen S, White D, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu J, Wu L, Wu L, Wu X, Wu Z, Xia L, Xiao H, Xiao S, Xiao Z, Xie X, Xie Y, Xie Y, Xing T, Xu G, Xu Q, Xu W, Xu X, Xu Y, Yan F, Yan L, Yan W, Yan W, Yan X, Yang H, Yang H, Yang L, Yang S, Yang Y, Yang Y, Yang Z, Ye M, Ye M, Yin J, You Z, Yu B, Yu C, Yu G, Yu J, Yu T, Yuan C, Yuan L, Yuan X, Yuan Y, Yuan Z, Yue C, Yuncu A, Zafar A, Zeng Y, Zhang B, Zhang G, Zhang H, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang L, Zhang L, Zhang S, Zhang S, Zhang S, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao G, Zhao J, Zhao J, Zhao J, Zhao L, Zhao L, Zhao M, Zhao Q, Zhao S, Zhao Y, Zhao Y, Zhao Z, Zhemchugov A, Zheng B, Zheng J, Zheng Y, Zheng Y, Zhong B, Zhong C, Zhou L, Zhou Q, Zhou X, Zhou X, Zhou X, Zhu A, Zhu J, Zhu K, Zhu K, Zhu S, Zhu T, Zhu W, Zhu W, Zhu Y, Zhu Z, Zou B, Zou J. Cross sections for the reactions
e+e−→K+K−π+π−(π0)
,
K+K−K+K−(π0)
,
π+π−π+π−(π0)
,
pp¯π+π−(π0)
in the energy region between 3.773 and 4.600 GeV. Int J Clin Exp Med 2021. [DOI: 10.1103/physrevd.104.112009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Chen N, Zhou Q, Cai LB. [A case report about curing chronic hepatitis C in children by direct-acting antiviral drugs]. ZHONGHUA GAN ZANG BING ZA ZHI = ZHONGHUA GANZANGBING ZAZHI = CHINESE JOURNAL OF HEPATOLOGY 2021; 29:1196-1197. [PMID: 35045637 DOI: 10.3760/cma.j.cn501113-20200814-00455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
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Li RZ, Zhu JX, Wang YY, Zhao SY, Peng CF, Zhou Q, Sun RQ, Hao AM, Li S, Wang Y, Xia B. [Development of a deep learning based prototype artificial intelligence system for the detection of dental caries in children]. ZHONGHUA KOU QIANG YI XUE ZA ZHI = ZHONGHUA KOUQIANG YIXUE ZAZHI = CHINESE JOURNAL OF STOMATOLOGY 2021; 56:1253-1260. [PMID: 34915661 DOI: 10.3760/cma.j.cn112144-20210712-00323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To develop a prototype artificial intelligence image recognition system for detecting dental caries, especially those without cavities, in children. Methods: Seven hundred and twelve intraoral photos, which were taken by dental professionals using a digital camera from October 2013 to June 2020 in the Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology, were collected from the children who received dental treatment under general anesthesia. The well-documented post-treatment electronic dental record of each child was identified as label standard to determine whether the teeth were carious and the type of caries types such as caries that had become cavities (caries with cavities), pit and fissure caries that had not become cavities (pit and fissure caries) and proximal caries which the marginal ridge enamel had not been destroyed (proximal caries). The various teeth and caries types were labeled by pediatric dentists using VoTT software (Windows 2.1.0, Microsoft, U S A). There were five labeled groups: pit and fissure caries, approximal caries, non-carious approximal surfaces, caries with cavities and teeth without caries (including intact fillings). Each group was randomly divided into training dataset, validation dataset and test dataset at a ratio of 6.4∶1.6∶2.0 by using random number table. After using the labeled training dataset for deep learning training, a deep learning-based artificial intelligence (AI) image recognition system for detecting dental caries was established, with the caries probability greater than 50.0% as the criterion for determining caries. Sensitivity and accuracy were used as indicators of recognition specificity. Results: Seven hundred and twelve single-jaw intraoral photographs were segmented and annotated into 953 pit and fissure caries, 1 002 approximal caries, 3 008 caries with cavities, 3 189 teeth without caries and 862 non-carious approximal surfaces, totaly 9 014 labels. The sensitivities and specificities of the test set were 96.0% and 97.0% for caries with cavities, 95.8% and 99.0% for pit and fissure caries and 88.1% and 97.1% for approximal caries. Conclusions: The current AI system developed based on deep learning of the intra-oral photos in the present study showed the ability to detect dental caries. Furthermore, the AI system could accurately verify different types of dental caries such as caries with cavities, pit and fissure caries and proximal caries.
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Ablikim M, Achasov M, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An M, An Q, Bai X, Bai Y, Bakina O, Baldini Ferroli R, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere R, Cai H, Cai X, Calcaterra A, Cao G, Cao N, Cetin S, Chang J, Chang W, Chelkov G, Chen D, Chen G, Chen H, Chen M, Chen S, Chen X, Chen Y, Chen ZJ, Cheng W, Cibinetto G, Cossio F, Cui X, Dai H, Dai J, Dai X, Dbeyssi A, de Boer R, Dedovich D, Deng Z, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong C, Dong J, Dong L, Dong M, Dong X, Du S, Fan Y, Fang J, Fang S, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng C, Feng J, Fritsch M, Fu C, Gao Y, Gao Y, Gao Y, Gao Y, Garzia I, Ge P, Geng C, Gersabeck E, Gilman A, Goetzen K, Gong L, Gong W, Gradl W, Greco M, Gu L, Gu M, Gu Y, Guan CY, Guo A, Guo L, Guo R, Guo Y, Guskov A, Han T, Han W, Hao X, Harris F, He K, Heinsius F, Heinz C, Heng Y, Herold C, Himmelreich M, Holtmann T, Hou G, Hou Y, Hou Z, Hu H, Hu J, Hu T, Hu Y, Huang G, Huang L, Huang X, Huang Y, Huang Z, Hussain T, Hüsken N, Ikegami Andersson W, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji Q, Ji X, Ji X, Ji Y, Jiang H, Jiang X, Jiao J, Jiao Z, Jin S, Jin Y, Jing M, Johansson T, Kalantar-Nayestanaki N, Kang X, Kappert R, Kavatsyuk M, Ke B, Keshk I, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Koch L, Kolcu O, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kurth M, Kühn W, Lane J, Lange J, Larin P, Lavania A, Lavezzi L, Lei Z, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li C, Li D, Li F, Li G, Li H, Li H, Li H, Li H, Li J, Li J, Li J, Li K, Li L, Li L, Li P, Li S, Li W, Li W, Li X, Li X, Li X, Li Z, Liang H, Liang H, Liang H, Liang Y, Liang Y, Liao G, Liao L, Libby J, Lin C, Liu B, Liu C, Liu D, Liu F, Liu F, Liu F, Liu H, Liu H, Liu H, Liu H, Liu J, Liu J, Liu J, Liu K, Liu K, Liu K, Liu L, Liu M, Liu P, Liu Q, Liu Q, Liu S, Liu S, Liu T, Liu W, Liu X, Liu Y, Liu Y, Liu Z, Liu Z, Lou X, Lu F, Lu H, Lu J, Lu J, Lu X, Lu Y, Lu Y, Luo C, Luo M, Luo P, Luo T, Luo X, Lyu X, Ma F, Ma H, Ma L, Ma M, Ma Q, Ma R, Ma R, Ma X, Ma X, Maas F, Maggiora M, Maldaner S, Malde S, Malik Q, Mangoni A, Mao Y, Mao Z, Marcello S, Meng Z, Messchendorp J, Mezzadri G, Min T, Mitchell R, Mo X, Muchnoi N, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev I, Ning Z, Nisar S, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pathak A, Patteri P, Pelizaeus M, Peng H, Peters K, Pettersson J, Ping J, Ping R, Pogodin S, Poling R, Prasad V, Qi H, Qi H, Qi K, Qi M, Qi T, Qian S, Qian W, Qian Z, Qiao C, Qin L, Qin X, Qin X, Qin Z, Qiu J, Qu S, Rashid K, Ravindran K, Redmer C, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Rump M, Sang H, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan D, Shan W, Shan X, Shangguan J, Shao M, Shen C, Shen H, Shen P, Shen X, Shi H, Shi R, Shi X, Shi XD, Song J, Song W, Song Y, Sosio S, Spataro S, Su K, Su P, Sui F, Sun G, Sun H, Sun J, Sun L, Sun S, Sun T, Sun W, Sun W, Sun X, Sun Y, Sun Y, Sun Y, Sun Z, Tan Y, Tan Y, Tang C, Tang G, Tang J, Teng J, Thoren V, Tian W, Tian Y, Uman I, Wang B, Wang C, Wang D, Wang H, Wang H, Wang K, Wang L, Wang M, Wang M, Wang M, Wang S, Wang W, Wang W, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Y, Wang Y, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Wang Z, Wei D, Weidner F, Wen S, White D, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu J, Wu L, Wu L, Wu X, Wu Z, Xia L, Xiao H, Xiao S, Xiao Z, Xie X, Xie Y, Xie Y, Xing T, Xu C, Xu G, Xu Q, Xu W, Xu X, Xu Y, Yan F, Yan L, Yan W, Yan W, Yan X, Yang H, Yang H, Yang L, Yang S, Yang Y, Yang Y, Yang Z, Ye M, Ye M, Yin J, You Z, Yu B, Yu C, Yu G, Yu J, Yu T, Yuan C, Yuan L, Yuan X, Yuan Y, Yuan Z, Yue C, Zafar A, Zeng XZ, Zeng Y, Zhang A, Zhang B, Zhang G, Zhang H, Zhang H, Zhang H, Zhang H, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang J, Zhang L, Zhang L, Zhang L, Zhang S, Zhang S, Zhang S, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhao G, Zhao J, Zhao J, Zhao J, Zhao L, Zhao L, Zhao M, Zhao Q, Zhao S, Zhao Y, Zhao Y, Zhao Z, Zhemchugov A, Zheng B, Zheng J, Zheng Y, Zhong B, Zhong C, Zhou L, Zhou Q, Zhou X, Zhou X, Zhou X, Zhou X, Zhu A, Zhu J, Zhu K, Zhu K, Zhu S, Zhu T, Zhu W, Zhu W, Zhu Y, Zhu Z, Zou B, Zou J. Measurement of the cross section for
e+e−→ΛΛ¯
and evidence of the decay
ψ(3770)→ΛΛ¯. Int J Clin Exp Med 2021. [DOI: 10.1103/physrevd.104.l091104] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Zhou Q, Huang X, Xie Y, Liu X, Li S, Zhou J. Role of quantitative energy spectrum CT parameters in differentiating thymic epithelial tumours and thymic cysts. Clin Radiol 2021; 77:136-141. [PMID: 34857380 DOI: 10.1016/j.crad.2021.10.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 11/01/2021] [Indexed: 11/30/2022]
Abstract
AIM To explore the utility of multiple energy spectrum computed tomography (CT) parameters in distinguishing thymic epithelial tumours (TETs) from thymic cysts among lesions <5 cm in diameter. MATERIALS AND METHODS Data pertaining to 56 patients with TETs and thymic cysts <5 cm in diameter were assessed retrospectively. All patients underwent surgical resection and the diagnosis was confirmed histopathologically. Thirty-five patients with TETs (average age, 51.97 years) and 21 patients with thymic cysts (average age, 50.54 years) were included. The region of interest for the lesion on the energy spectrum CT was delineated on the post-processing workstation, and multiple parameters of the energy spectrum CT were obtained. The diagnostic efficacies of the parameters were analysed using receiver operating characteristic (ROC) curves. RESULTS To distinguish small TETs from thymic cysts, a single-energy CT value of 60 keV showed good differential diagnostic performance in the arterial phase (cut-off value = 68.42 HU; area under the curve [AUC] = 0.978), a single-energy CT value of 70 keV showed good differential diagnostic performance in the venous phase (cut-off value = 59.77 HU; AUC = 0.956). In the arterial and venous phases, effective atomic numbers of 8.065 and 8.175, respectively, were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.972 and AUC = 0.961, respectively). Iodine concentrations of 10.99 and 11.05 were used as cut-off values to distinguish small TETs from thymic cysts (AUC = 0.956 and AUC = 0.924, respectively). CONCLUSION According to the present study, energy spectrum CT parameters may have clinical value in the differential diagnosis of TETs and thymic cysts.
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Lu Y, Zhou Q, Wang LN, He T, Zhao HY, Cao XQ. [Application effects of failure mode and effect analysis on the limb posture positioning nursing of extremely severe burn patients]. ZHONGHUA SHAO SHANG ZA ZHI = ZHONGHUA SHAOSHANG ZAZHI = CHINESE JOURNAL OF BURNS 2021; 37:1078-1084. [PMID: 34794260 DOI: 10.3760/cma.j.cn501120-20210412-00126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the application effects of risk assessment method of failure mode and effect analysis (FMEA) on the limb posture positioning nursing of extremely severe burn patients. Methods: A retrospective observational study was conducted. According to the different limb posture positioning methods, 30 extremely severe burn patients who met the inclusion criteria and underwent routine limb posture positioning in the First Affiliated Hospital of Air Force Medical University from January 2018 to June 2019 were included into routine limb positioning group (19 males and 11 females, aged (40±10) years), and 30 extremely severe burn patients who met the inclusion criteria and underwent limb posture positioning with FMEA risk assessment from July 2019 to December 2020 in the department were included into FMEA limb positioning group (20 males and 10 females, aged (38±10) years). Patients in routine limb positioning group received only routine limb posture positioning by rehabilitation therapists with bare hand every day from the time when their limb wounds healed until they were discharged from hospital. Patients in FMEA limb positioning group received FMEA risk assessment by physicians, rehabilitation therapists, and nurses within 24 hours after admission to analyze the potential failure modes of limb posture positioning, and target-directed limb posture positioning measures were adopted until they were discharged. The risk priority numbers (RPNs) of six major failure modes of patients in FMEA limb positioning group before and after intervention were compared. The range of motion (ROM) of shoulder abduction, elbow extension, wrist dorsiflexion, ankle plantarflexion, total action motion of hand, and modified Barthel index scores of the patients in two groups before and after intervention were also assessed. Data were statistically analyzed with independent sample t test, chi-square test, and paired sample t test. Results: The RPNs of 6 main potential failure modes of patients in FMEA limb positioning group i.e. untimely interference of limb posture positioning, not strong awareness of limb posture positioning of nurses, inconsistent of evaluation standards of limb posture positioning, nurses' lacking knowledge about limb posture positioning, nurses' lacking active participation, unsatisfying effects of patients' limb posture positioning were respectively (146±31), (140±22), (125±34), (136±23), (110±28), and (110±5) points after intervention, which were significantly lower than (578±64), (543±57), (419±89), (269±64), (240±41), and (222±48) points before intervention (t=18.441, 23.681, 10.035, 5.362, 9.438, 7.171, P<0.01). After intervention, the ROMs of shoulder abduction, elbow extension, wrist dorsiflexion, and ankle plantarflexion of patients in FMEA limb positioning group were significantly better than those in routine limb positioning group (t=-4.250, 11.400, -15.928, 10.963, -7.470, P<0.01); the ROMs of shoulder abduction, elbow extension, wrist dorsiflexion, and ankle plantarflexion of patients in FMEA limb positioning group and routine limb positioning group were significantly better than those before intervention (t=-35.573, 33.670, -31.090, 32.902, -19.647, -14.952, 11.411, -33.462, -12.818, -13.672, P<0.01). After intervention, the Barthel index score of patients in FMEA limb positioning group (78±9) was significantly higher than 57±9 in routine limb positioning group (t=-9.055, P<0.01), and the Barthel index scores of patients in FMEA limb positioning group and routine limb positioning group were significantly higher than those before intervention (35±5 and 34±4, t=-22.964, -12.329, P<0.01). Conclusions: In the limb posture positioning nursing of extremely severe burn patients, risk assessment method of FMEA can effectively avoid the high risk factors in the limb posture positioning of patients, thus maintain the effects of limb posture positioning and improve the ROM of patients, as well as increase the daily living ability of patients in prognosis.
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