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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Fang YQ, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Feng YT, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Gutierrez J, Han KL, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu BY, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khachatryan V, Khoukaz A, Kiuchi R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Moses B, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang NY, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YL, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZD, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Determination of Spin-Parity Quantum Numbers of X(2370) as 0^{-+} from J/ψ→γK_{S}^{0}K_{S}^{0}η^{'}. PHYSICAL REVIEW LETTERS 2024; 132:181901. [PMID: 38759175 DOI: 10.1103/physrevlett.132.181901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/05/2024] [Accepted: 03/28/2024] [Indexed: 05/19/2024]
Abstract
Based on (10087±44)×10^{6} J/ψ events collected with the BESIII detector, a partial wave analysis of the decay J/ψ→γK_{S}^{0}K_{S}^{0}η^{'} is performed. The mass and width of the X(2370) are measured to be 2395±11(stat)_{-94}^{+26}(syst) MeV/c^{2} and 188_{-17}^{+18}(stat)_{-33}^{+124}(syst) MeV, respectively. The corresponding product branching fraction is B[J/ψ→γX(2370)]×B[X(2370)→f_{0}(980)η^{'}]×B[f_{0}(980)→K_{S}^{0}K_{S}^{0}]=(1.31±0.22(stat)_{-0.84}^{+2.85}(syst))×10^{-5}. The statistical significance of the X(2370) is greater than 11.7σ and the spin parity is determined to be 0^{-+} for the first time. The measured mass and spin parity of the X(2370) are consistent with the predictions of the lightest pseudoscalar glueball.
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Cui Y, Zhou Y, Gao Y, Ma X, Wang Y, Zhang X, Zhou T, Chen S, Lu L, Zhang Y, Chang X, Tong A, Li Y. Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction. J Endocrinol Invest 2024; 47:1191-1203. [PMID: 38206552 DOI: 10.1007/s40618-023-02239-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 11/02/2023] [Indexed: 01/12/2024]
Abstract
OBJECTIVE The existing prediction models for metastasis in pheochromocytomas/paragangliomas (PPGLs) showed high heterogeneity in different centers. Therefore, this study aimed to establish new prediction models integrating multiple variables based on different algorithms. DESIGN AND METHODS Data of patients with PPGLs undergoing surgical resection at the Peking Union Medical College Hospital from 2007 to 2022 were collected retrospectively. Patients were randomly divided into the training and testing sets in a ratio of 7:3. Subsequently, decision trees, random forest, and logistic models were constructed for metastasis prediction with the training set and Cox models for metastasis-free survival (MFS) prediction with the total population. Additionally, Ki-67 index and tumor size were transformed into categorical variables for adjusting models. The testing set was used to assess the discrimination and calibration of models and the optimal models were visualized as nomograms. Clinical characteristics and MFS were compared between patients with and without risk factors. RESULTS A total of 198 patients with 59 cases of metastasis were included and classified into the training set (n = 138) and testing set (n = 60). Among all models, the logistic regression model showed the best discrimination for metastasis prediction with an AUC of 0.891 (95% CI, 0.793-0.990), integrating SDHB germline mutations [OR: 96.72 (95% CI, 16.61-940.79)], S-100 (-) [OR: 11.22 (95% CI, 3.04-58.51)], ATRX (-) [OR: 8.42 (95% CI, 2.73-29.24)] and Ki-67 ≥ 3% [OR: 7.98 (95% CI, 2.27-32.24)] evaluated through immunohistochemistry (IHC), and tumor size ≥ 5 cm [OR: 4.59 (95% CI, 1.34-19.13)]. The multivariate Cox model including the above risk factors also showed a high C-index of 0.860 (95% CI, 0.810-0.911) in predicting MFS after surgery. Furthermore, patients with the above risk factors showed a significantly poorer MFS (P ≤ 0.001). CONCLUSIONS Models established in this study provided alternative and reliable tools for clinicians to predict PPGLs patients' metastasis and MFS. More importantly, this study revealed for the first time that IHC of ATRX could act as an independent predictor of metastasis in PPGLs.
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Liu N, Lv L, Jiao J, Zhang Y, Zuo XL. Reply Letter to Chiavarini et al - "Association between nutritional indices and mortality after hip fracture: a systematic review and meta-analysis". EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2024; 28:3295-3296. [PMID: 38766785 DOI: 10.26355/eurrev_202405_36174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
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Li X, Zhang S, Zhang Y, Zhou X. Visualization of intracellular ice formation and growth in mouse oocytes. CRYO LETTERS 2024; 45:185-193. [PMID: 38709190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
BACKGROUND Characterization of intracellular ice formation (IIF) in oocytes during the freezing and thawing processes will contribute to optimizing their cryopreservation. However, the observation of the ice formation process in oocytes is limited by the spatiotemporal resolution of the cryomicroscope systems. OBJECTIVE To observe the intracellular icing of oocytes during cooling and rewarming, and to study the mechanism of formation and growth of intracellular ice in oocytes. MATERIALS AND METHODS Mouse oocytes were frozen at different cooling rates to induce intracellular ice formation using a cryomicroscopy system consisting of a microscope equipped with a cryogenic cold stage, an automatic cooling system, a temperature control system, and a high-speed camera. The growth patterns of intracellular ice in oocytes were analyzed from the images recorded. Finally, the growth rate of intracellular ice formation in oocytes was calculated using an automatic intracellular ice tracking method. RESULTS The IIF temperature decreased gradually with the increase in cooling rate. Initiation sites of IIF could be classified into three categories: marginal type, internal type and coexisting type. There was a strong predominance for ice crystal initiation site in the oocytes, with up to 80% of the initiation sites located in the marginal region. The intracellular ice growth modes of darkening and twitching cells were characterized by "spreading" and "clustering", respectively. In addition, twitching cells started to recrystallize during rewarming, while darkening cells did not. The instantaneous maximal growth rate of ice crystals in twitching cells was about 10 times higher than that in darkening cells. CONCLUSION By visualising the growth of ice crystals in mouse oocytes during cooling and rewarming, we obtained valuable information on the kinetics of ice formation and melting in these cells. This information can help us understand how ice formation and melting affect the viability and quality of oocytes after cryopreservation. Doi.org/10.54680/fr24310110412.
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Cao B, Li Q, Xu P, Zhang Y, Cai S, Rao S, Zeng M, Dai Y, Jiang S, Zhou J. Vesical Imaging-Reporting and Data System (VI-RADS) as a grouping imaging biomarker combined with a decision-tree mode to preoperatively predict the pathological grade of bladder cancer. Clin Radiol 2024; 79:e725-e735. [PMID: 38360514 DOI: 10.1016/j.crad.2024.01.031] [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: 09/15/2023] [Revised: 01/12/2024] [Accepted: 01/22/2024] [Indexed: 02/17/2024]
Abstract
AIM To investigate whether the Vesical Imaging-Reporting and Data System (VI-RADS) could be used to develop a new non-invasive preoperative grade-prediction system to partially predict high-grade bladder cancer (HG-BC). MATERIALS AND METHODS The present study enrolled 89 primary BC patients prospectively from March 2022 to June 2023. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of VI-RADS for predicting HG-BC and muscle-invasive bladder cancer (MIBC) in the entire group. In the low VI-RADS (≤2) group, the decision tree-based method was used to obtain significant predictors and construct the decision-tree model (DT model). The performance of the DT model and low VI-RADS scores for predicting HG-BC was determined using ROC, calibration, and decision curve analyses. RESULTS At a cut-off of ≥3, the specificity and positive predictive value of VI-RADS for predicting HG-BC in the entire group was 100%, and the area under the ROC curve (AUC) was 0.697. Among 65 patients with low VI-RADS scores, the DT model showed an AUC of 0.884 in predicting HG-BC compared to 0.506 for low VI-RADS scores. Calibration and decision curve analyses showed that the DT model performed better than the low VI-RADS scores. CONCLUSION Most VI-RADS scores ≥3 correspond to HG-BCs. VI-RADS could be used as a grouping imaging biomarker for a pathological grade-prediction procedure, which in combination with the DT model for low VI-RADS (≤2) populations, would provide a potential preoperative non-invasive method of predicting HG-BC.
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Abeyratne WMLK, Zhang Y, Brewer CE, Nirmalakhandan N. Domestic wastewater sludge valorization: Multi-criteria evaluation of anaerobic digestion vs. hydrothermal liquefaction. BIORESOURCE TECHNOLOGY 2024; 400:130655. [PMID: 38580168 DOI: 10.1016/j.biortech.2024.130655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 03/13/2024] [Accepted: 04/03/2024] [Indexed: 04/07/2024]
Abstract
The emerging hydrothermal liquefaction (HTL) process is evaluated against the classical anaerobic digestion (AD) processes for stabilizing wastewater sludges and recovering their energy- and nutrient-contents. Although HTL affords faster stabilization, better process stability, and liquid fuel and sterile fertilizer recovery, it suffers from higher energy demand and lower technology readiness level. For a rational comparison of these pathways, a multi-criteria evaluation is conducted considering 21 technical, environmental, economic, and social criteria. Criteria values for the HTL-pathway were derived from laboratory tests while those for the AD-pathway were compiled from literature. Of the 16 process alternatives evaluated, the AD-pathway including nitrogen-recovery by air-stripping and phosphorus recovery by the MEPHREC® process ranked first followed by the HTL-pathway. This multi-criteria study suggests that the HTL-pathway could be engineered as a superior alternative for sludge stabilization and resource recovery if phosphorus recovery and its technology readiness level could be improved.
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Meng Z, Guo Y, Deng S, Xiang Q, Cao J, Zhang Y, Zhang K, Ma K, Xie S, Kang Z. Improving image quality of triple-low-protocol renal artery CT angiography with deep-learning image reconstruction: a comparative study with standard-dose single-energy and dual-energy CT with adaptive statistical iterative reconstruction. Clin Radiol 2024; 79:e651-e658. [PMID: 38433041 DOI: 10.1016/j.crad.2024.01.008] [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: 08/22/2023] [Revised: 01/03/2024] [Accepted: 01/09/2024] [Indexed: 03/05/2024]
Abstract
AIM To investigate the improvement in image quality of triple-low-protocol (low radiation, low contrast medium dose, low injection speed) renal artery computed tomography (CT) angiography (RACTA) using deep-learning image reconstruction (DLIR), in comparison with standard-dose single- and dual-energy CT (DECT) using adaptive statistical iterative reconstruction-Veo (ASIR-V) algorithm. MATERIALS AND METHODS Ninety patients for RACTA were divided into different groups: standard-dose single-energy CT (S group) using ASIR-V at 60% strength (60%ASIR-V), DECT (DE group) with 60%ASIR-V including virtual monochromatic images at 40 keV (DE40 group) and 70 keV (DE70 group), and the triple-low protocol single-energy CT (L group) with DLIR at high level (DLIR-H). The effective dose (ED), contrast medium dose, injection speed, standard deviation (SD), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal aorta (AA), and left/right renal artery (LRA, RRA), and subjective scores were compared among the different groups. RESULTS The L group significantly reduced ED by 37.6% and 31.2%, contrast medium dose by 33.9% and 30.5%, and injection speed by 30% and 30%, respectively, compared to the S and DE groups. The L group had the lowest SD values for all arteries compared to the other groups (p<0.001). The SNR of RRA and LRA in the L group, and the CNR of all arteries in the DE40 group had highest value compared to others (p<0.05). The L group had the best comprehensive score with good consistency (p<0.05). CONCLUSIONS The triple-low protocol RACTA with DLIR-H significantly reduces the ED, contrast medium doses, and injection speed, while providing good comprehensive image quality.
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Liu N, Lv L, Jiao J, Zhang Y, Zuo XL. Author Correction: Association between nutritional indices and mortality after hip fracture: a systematic review and meta-analysis. EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES 2024; 28:3475. [PMID: 38856146 DOI: 10.26355/eurrev_202405_36275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Eur Rev Med Pharmacol Sci 2023; 27 (6): 2297-2304-DOI: 10.26355/eurrev_202303_31763-PMID: 37013747-published online on March 30, 2023. This erratum corrects Figure 4, which presents some mistakes. The authors have substituted the unadjusted OR of 11.16 (95% CI: 3.78-32.91) with 4.37 (95% CI: 1.77-10.80). The amended Figure 4 now has a pooled ratio of OR: 3.00 95% CI: 1.60, 5.64 I2=79% p=0.006 instead of OR: 3.61 95% CI: 1.70, 7.70 I2=85% p=0.0009 presented in the article. The corrected version of Figure 4 is as follows: There are amendments to this paper. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/31763.
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You A, Gu J, Wang J, Li J, Zhang Y, Rao G, Ge X, Zhang K, Gao X, Wang D. Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma. Neurologia 2024; 39:353-360. [PMID: 38616063 DOI: 10.1016/j.nrleng.2021.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 06/11/2021] [Indexed: 04/16/2024] Open
Abstract
BACKGROUND Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. METHODS The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. RESULTS HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. CONCLUSIONS Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.
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Zhang H, Ouyang Y, Zhang H, Zhang Y, Su R, Zhou B, Yang W, Lei Y, Huang B. Sub-region based radiomics analysis for prediction of isocitrate dehydrogenase and telomerase reverse transcriptase promoter mutations in diffuse gliomas. Clin Radiol 2024; 79:e682-e691. [PMID: 38402087 DOI: 10.1016/j.crad.2024.01.030] [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: 08/25/2023] [Revised: 01/16/2024] [Accepted: 01/21/2024] [Indexed: 02/26/2024]
Abstract
AIM To enhance the prediction of mutation status of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter, which are crucial for glioma prognostication and therapeutic decision-making, via sub-regional radiomics analysis based on multiparametric magnetic resonance imaging (MRI). MATERIALS AND METHODS A retrospective study was conducted on 401 participants with adult-type diffuse gliomas. Employing the K-means algorithm, tumours were clustered into two to four subregions. Sub-regional radiomics features were extracted and selected using the Mann-Whitney U-test, Pearson correlation analysis, and least absolute shrinkage and selection operator, forming the basis for predictive models. The performance of model combinations of different sub-regional features and classifiers (including logistic regression, support vector machines, K-nearest neighbour, light gradient boosting machine, and multilayer perceptron) was evaluated using an external test set. RESULTS The models demonstrated high predictive performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.918 to 0.994 in the training set for IDH mutation prediction and from 0.758 to 0.939 for TERT promoter mutation prediction. In the external test sets, the two-cluster radiomics features and the logistic regression model yielded the highest prediction for IDH mutation, resulting in an AUC of 0.905. Additionally, the most effective predictive performance with an AUC of 0.803 was achieved using the four-cluster radiomics features and the support vector machine model, specifically for TERT promoter mutation prediction. CONCLUSION The present study underscores the potential of sub-regional radiomics analysis in predicting IDH and TERT promoter mutations in glioma patients. These models have the capacity to refine preoperative glioma diagnosis and contribute to personalised therapeutic interventions for patients.
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Yuan XM, Xiang MQ, Ping Y, Zhang PW, Liu YT, Liu XW, Wei J, Tang Q, Zhang Y. Beneficial Effects of High-Intensity Interval Training and Dietary Changes Intervention on Hepatic Fat Accumulation in HFD-Induced Obese Rats. Physiol Res 2024; 73:273-284. [PMID: 38710057 PMCID: PMC11081183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/02/2023] [Indexed: 05/08/2024] Open
Abstract
Lifestyle intervention encompassing nutrition and physical activity are effective strategies to prevent progressive lipid deposition in the liver. This study aimed to explore the effect of dietary change, and/or high-intensity interval training (HIIT) on hepatic lipid accumulation in high fat diet (HFD)-induced obese rats. We divided lean rats into lean control (LC) or HIIT groups (LH), and obese rats into obese normal chow diet (ND) control (ONC) or HIIT groups (ONH) and obese HFD control (OHC) or HIIT groups (OHH). We found that dietary or HIIT intervention significantly decreased body weight and the risk of dyslipidemia, prevented hepatic lipid accumulation. HIIT significantly improved mitochondrial fatty acid oxidation through upregulating mitochondrial enzyme activities, mitochondrial function and AMPK/PPARalpha/CPT1alpha pathway, as well as inhibiting hepatic de novo lipogenesis in obese HFD rats. These findings indicate that dietary alone or HIIT intervention powerfully improve intrahepatic storage of fat in diet induced obese rats. Keywords: Obesity, Exercise, Diet, Mitochondrial function, Lipid deposition.
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Qu YL, Song YH, Sun RR, Ma YJ, Zhang Y. Serum Vitamin D Level in Overweight Individuals and Its Correlation With the Incidence of Non-alcoholic Fatty Liver Disease. Physiol Res 2024; 73:265-271. [PMID: 38710056 PMCID: PMC11081187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/24/2024] [Indexed: 05/08/2024] Open
Abstract
In this study, we investigated the serum vitamin D level in overweight individuals and its correlation with the incidence of nonalcoholic fatty liver disease (NAFLD). Between May 2020 and May 2021, the Department of Gastroenterology at the People's Hospital of Henan University of Traditional Chinese Medicine treated a total of 321 outpatients and inpatients with NAFLD, who were included in the NAFLD group, while 245 healthy age- and gender-matched individuals were included in the control group. All the data were collected for the relevant indices, including fasting plasma glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, alanine transaminase, and 25-hydroxy vitamin D (25[OH]D. The patients with NAFLD were divided into the normal BMI group, the overweight group, and the obese group, according to the body mass index, and the 25(OH)D levels were compared between the different groups. Spearman's correlation analysis was performed to analyze the correlation between the serum 25(OH)D level and NAFLD. Regarding the serum 25 (OH)D level, it was lower in the NAFLD group than in the control group ([18.36 + 1.41] µg/L vs [22.33 + 2.59] µg/L, t = ?5.15, P<0.001), and was lower in the overweight group than in the normal group ([18.09 ± 5.81] µg/L vs [20.60 ± 4.16] µg/L, t = 0.26, P = 0.041). The serum 25(OH)D level was thus negatively correlated with the incidence of NAFLD in overweight individuals (r = 0.625, P<0.05). In conclusion, the level of 25(OH)D decreased in patients with NAFLD with increasing BMI (normal, overweight, obese). Keywords: Nonalcoholic fatty liver disease, Vitamin D.
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Mao WW, Tang JJ, Zhang Y, Li W, Zhu Y, Wang Y, Gui JC, Qin JZ. [Evaluation of arthroscopic ATFL and CFL repair separately for chronic lateral ankle instability in conjunction with subtalar instability]. ZHONGHUA WAI KE ZA ZHI [CHINESE JOURNAL OF SURGERY] 2024; 62:565-571. [PMID: 38682628 DOI: 10.3760/cma.j.cn112139-20240229-00092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/01/2024]
Abstract
Objective: To investigate the clinical efficacy of simultaneous arthroscopic repair of anterior talofibular ligament (ATFL) and calcaneofibular ligament (CFL) for treating chronic lateral ankle instability (CLAI) in conjunction with subtalar instability (STI). Methods: This study is a retrospective case series study. The clinical data of 15 patients with ankle arthroscopic in the Department of Hand and Foot Surgery, the Second Affiliated Hospital of Soochow University from January 2019 to December 2022 were analyzed retrospectively. There were 11 male cases and 4 female cases, aged (28.6±1.5) years (range: 19 to 39 years). All the patients were evaluated by manual inversion stress X-ray and MRI before operation. Arthroscopically observing and then repairing the ATFL and CFL separately after further diagnostic confirmation. One year after operation, MRI was performed, and visual analogue (VAS) pain scores, American Orthopedic Foot and Ankle Society ankle hindfoot scale (AOFAS-AH) and Karlsson ankle functional scale(KAFS) were evaluated. Data were compared using paired sample t test. Results: The follow-up period was (22.6±2.3) months (range: 12 to 30 months). At last follow-up,the VAS decreased from 6.1±1.4 preoperatively to 1.4±1.2(t=9.482, P<0.01). The AOFAS-AH improved from 50.5±11.7 preoperatively to 94.2±6.1(t=-13.132, P<0.01), and the KAFS improved from preoperatively 44.3±10.8 to 90.8±6.4 (t=-12.510, P<0.01). There were no complications such as recurred instability or joint stiffness. Conclusions: Arthroscopically repairing the ATFL and CFL separately can effectively restore the stability of the ankle and subtalar joint with small trauma. Patients can recover quickly after surgery. It provides a new idea for the clinical treatment of CLAI combined with STI.
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Shao K, Hao Y, Xu M, Shi Z, Lin G, Xu C, Zhang Y, Song Z. Comparison of Efficacy and Safety of Different Second-line Therapies for Patients With Advanced Thymic Carcinoma. Clin Oncol (R Coll Radiol) 2024:S0936-6555(24)00170-5. [PMID: 38777703 DOI: 10.1016/j.clon.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 03/28/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024]
Abstract
AIMS Thymic carcinoma (TC) is a rare form of highly invasive tumors. Currently, the standard first-line therapy involves paclitaxel plus carboplatin treatment, while the recommended regimen for second-line therapy remains uncertain. The purpose of this study is to explore the second-line mode of TC patients. MATERIALS AND METHODS We evaluated the outcome of subjects with advanced TC between 2009 and 2023 in three medical centers, retrospectively. Tumor response was evaluated according to the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). Kaplan-Meier was used for calculating Progression-free survival (PFS) and overall survival (OS). The factors affecting survival in the real world were evaluated by Cox analysis. RESULTS Totally 136 patients were included in this study, the median PFS (mPFS) for all subjects was 5.97 months, and the median OS (mOS) was 25.03 months. According to patient's treatment modes, they are divided into monotherapy (n = 95) and combination therapy (n = 41), PFS manifested the difference between two groups (5.17 vs. 9.00 months, P = 0.043). OS also indicated a significant distinction (22.50 vs. 38.00 months, P = 0.017). Furthermore, there was a significant difference in PFS between patients using immunotherapy combined with chemotherapy and those with antivascular therapy (8.57 vs. 13.10 months, P = 0.047). CONCLUSION In the second-line therapy for advanced TC, the efficacy of combination therapy was better than monotherapy, especially for immunotherapy combined with antivascular therapy.
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Balachandran A, Pei H, Beard J, Caspi A, Cohen A, Domingue BW, Eckstein Indik C, Ferrucci L, Furuya A, Kothari M, Moffitt TE, Ryan C, Skirbekk V, Zhang Y, Belsky DW. Pace of Aging in older adults matters for healthspan and lifespan. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306359. [PMID: 38712264 PMCID: PMC11071564 DOI: 10.1101/2024.04.25.24306359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
As societies age, policy makers need tools to understand how demographic aging will affect population health and to develop programs to increase healthspan. The current metrics used for policy analysis do not distinguish differences caused by early-life factors, such as prenatal care and nutrition, from those caused by ongoing changes in people's bodies due to aging. Here we introduce an adapted Pace of Aging method designed to quantify differences between individuals and populations in the speed of aging-related health declines. The adapted Pace of Aging method, implemented in data from N=13,626 older adults in the US Health and Retirement Study, integrates longitudinal data on blood biomarkers, physical measurements, and functional tests. It reveals stark differences in rates of aging between population subgroups and demonstrates strong and consistent prospective associations with incident morbidity, disability, and mortality. Pace of Aging can advance the population science of healthy longevity.
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Acharya S, Adamová D, Aglieri Rinella G, Aglietta L, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altamura AR, Altsybeev I, Alvarado JR, Anaam MN, Andrei C, Andreou N, Andronic A, Andronov E, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arneiro JGMCA, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Baba H, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Bala R, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barile F, Barioglio L, Barlou M, Barman B, Barnaföldi GG, Barnby LS, Barreau E, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Beltran LGE, Beltran YAV, Bencedi G, Beole S, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Boi S, Bok J, Boldizsár L, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Buhler P, Burmasov N, Buthelezi Z, Bylinkin A, Bysiak SA, Cabanillas Noris JC, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Cantway SL, Carabas M, Carballo AA, Carnesecchi F, Caron R, Carvalho LAD, Castillo Castellanos J, Catalano F, Cattaruzzi S, Ceballos Sanchez C, Cerri R, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Cheng T, Cheshkov C, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Choudhury D, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cortese P, Cosentino MR, Costa F, Costanza S, Cot C, Crkovská J, Crochet P, Cruz-Torres R, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb R, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diab B, Diaz RA, Dietel T, Ding Y, Ditzel J, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eisenhut F, Ejima R, Elia D, Erazmus B, Ercolessi F, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flatland E, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Gahlaut T, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, García Chávez T, Garcia-Solis E, Gargiulo C, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghimouz A, Ghosh C, Giacalone M, Gioachin G, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, Gordeev P, Gorgon M, Goswami K, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Grunwald NA, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gündem T, Gunji T, Guo W, Gupta A, Gupta R, Gupta R, Gwizdziel K, Gyulai L, Hadjidakis C, Haider FU, Haidlova S, Haldar M, Hamagaki H, Hamdi A, Han Y, Hanley BG, Hannigan R, Hansen J, Harris JW, Harton A, Hartung MV, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hippolyte B, Hoffmann FW, Hofman B, Hong GH, Horst M, Horzyk A, Hou Y, Hristov P, Huhn P, Huhta LM, Humanic TJ, Hutson A, Hutter D, Hwang MC, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Iversen KE, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Ji S, Jia S, Jimenez AAP, Jonas F, Jones DM, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khade SS, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Khuranova Z, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Korwieser M, Koryciak SD, Kotliarov A, Kovacic N, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Krcal L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kuskov V, Kutyla M, Kweon MJ, Kwon Y, La Pointe SL, La Rocca P, Lakrathok A, Lamanna M, Landou AR, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lea R, Lee H, Legrand I, Legras G, Lehrbach J, Lelek TM, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lévai P, Li X, Liang-Gilman BE, Lien J, Lietava R, Likmeta I, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu DH, Liu J, Liveraro GSS, Lofnes IM, Loizides C, Lokos S, Lömker J, Loncar P, Lopez X, López Torres E, Lu P, Lugo FV, Luhder JR, Lunardon M, Luparello G, Ma YG, Mager M, Maire A, Majerz EM, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mallick D, Mallick N, Mandaglio G, Mandal SK, Manko V, Manso F, Manzari V, Mao Y, Marcjan RW, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martínez MI, Martínez García G, Martins MPP, Masciocchi S, Masera M, Masoni A, Massacrier L, Massen O, Mastroserio A, Matonoha O, Mattiazzo S, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Melikyan Y, Menchaca-Rocha A, Mendez JEM, Meninno E, Menon AS, Meres M, Miake Y, Micheletti L, Mihaylov DL, Mikhaylov K, Miśkowiec D, Modak A, Mohanty B, Khan MM, Molander MA, Monira S, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nekrasova E, Nellen L, Nepeivoda R, Nese S, Neskovic G, Nicassio N, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Oh S, Ohlson A, Okorokov VA, Oleniacz J, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Paisano-Guzmán S, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patley Y, Paul B, Paulino MMDM, Pei H, Peitzmann T, Peng X, Pennisi M, Perciballi S, Peresunko D, Perez GM, Pestov Y, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pozos IY, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Ragoni S, Rai A, Rakotozafindrabe A, Ramello L, Rami F, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Reetz CA, Regules-Medel HD, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Riffero AG, Ristea C, Rodriguez MV, Rodríguez Cahuantzi M, Rodríguez Ramírez SA, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Roslon K, Rossi A, Roy A, Roy S, Rubini N, Ruggiano D, Rui R, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Ryu J, Rzesa W, Saarimaki OAM, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha P, Saha SK, Saha S, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Samitz D, Sanna I, Saramela TB, Sarkar D, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Sawan S, Scapparone E, Schambach J, Scheid HS, Schiaua C, Schicker R, Schlepper F, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selina M, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Serkin L, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma B, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh K, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Sonnabend C, Sonneveld JM, Soramel F, Soto-Hernandez AB, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Sturniolo A, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Szarka I, Szymkowski M, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tavira García A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Thakur S, Thomas D, Tikhonov A, Tiltmann N, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Tomohiro K, Topilskaya N, Toppi M, Tork T, Torres PV, Torres VV, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vazquez Rueda O, Vechernin V, Vercellin E, Vergara Limón S, Verma R, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Villani A, Vinogradov A, Virgili T, Virta MMO, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wan J, Wang C, Wang D, Wang Y, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yamaguchi Y, Yang S, Yano S, Yeats ER, Yin Z, Yoo IK, Yoon JH, Yu H, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang C, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhong C, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. Emergence of Long-Range Angular Correlations in Low-Multiplicity Proton-Proton Collisions. PHYSICAL REVIEW LETTERS 2024; 132:172302. [PMID: 38728735 DOI: 10.1103/physrevlett.132.172302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/22/2024] [Accepted: 03/22/2024] [Indexed: 05/12/2024]
Abstract
This Letter presents the measurement of near-side associated per-trigger yields, denoted ridge yields, from the analysis of angular correlations of charged hadrons in proton-proton collisions at sqrt[s]=13 TeV. Long-range ridge yields are extracted for pairs of charged particles with a pseudorapidity difference of 1.4<|Δη|<1.8 and a transverse momentum of 1
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Liu XM, Duan HY, Zhang DQ, Chen C, Ji YT, Zhang YM, Feng ZW, Liu Y, Li JJ, Zhang Y, Li CY, Zhang YC, Yang L, Lyu ZY, Song FF, Song FJ, Huang YB. [Exploration and validation of optimal cut-off values for tPSA and fPSA/tPSA screening of prostate cancer at different ages]. ZHONGHUA ZHONG LIU ZA ZHI [CHINESE JOURNAL OF ONCOLOGY] 2024; 46:354-364. [PMID: 38644271 DOI: 10.3760/cma.j.cn112152-20230805-00062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Objective: To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China. Methods: Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (<60, 60-<70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values. Results: A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening. Conclusion: To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.
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Li Y, Yang J, Zhang Y, Zhang C, Wei Y, Wang Y, Wu N, Sun J, Wu Z. [The Miao medicine Sidaxue alleviates rheumatoid arthritis in rats possibly by downregulating matrix metalloproteinases]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024; 44:739-747. [PMID: 38708508 DOI: 10.12122/j.issn.1673-4254.2024.04.16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
OBJECTIVE To explore the inhibitory effect of Sidaxue, a traditional Miao herbal medicine formula, on articular bone and cartilage destruction and synovial neovascularization in rats with collagen-induced arthritis (CIA). METHODS In a SD rat model of CIA, we tested the effects of daily gavage of Sidaxue at low, moderate and high doses (10, 20, and 40 g/kg, respectively) for 21 days, with Tripterygium glycosides (GTW) as the positive control, on swelling in the hind limb plantar regions by arthritis index scoring. Pathologies in joint synovial membrane of the rats were observed with HE staining, and serum TNF-α and IL-1β levels were detected with ELISA. The expressions of NF-κB p65, matrix metalloproteinase 1 (MMP1), MMP2 and MMP9 at the mRNA and protein levels in the synovial tissues were detected using real-time PCR and Western blotting. Network pharmacology analysis was conducted to identify the important target proteins in the pathways correlated with the therapeutic effects of topical Sidaxue treatment for RA, and the core target proteins were screened by topological analysis. RESULTS Treatment with GTW and Sidaxue at the 3 doses all significantly alleviated plantar swelling, lowered arthritis index scores, improved cartilage and bone damage and reduced neovascularization in CIA rats (P<0.05), and the effects of Sidaxue showed a dose dependence. Both GTW and Sidaxue treatments significantly lowered TNF-α, IL-1β, NF-κB p65, MMP1, MMP2, and MMP9 mRNA and protein expressions in the synovial tissues of CIA rats (P<0.05). Network pharmacological analysis identified MMPs as the core proteins associated with topical Sidaxue treatment of RA. CONCLUSION Sidaxue alleviates articular bone and cartilage damages and reduces synovial neovascularization in CIA rats possibly by downregulating MMPs via the TNF-α/IL-1β/NF-κB-MMP1, 2, 9 signaling pathway, and MMPs probably plays a key role in mediating the effect of Sidaxue though the therapeutic pathways other than oral administration.
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Guo ZK, Zhang YT, Zhang Y, Weng YL, Li HY, Wu SY. [Microglia differential genes and their functions in paraquat-induced Parkinson's disease-like in mice's brains based on single-cell RNA sequencing]. ZHONGHUA LAO DONG WEI SHENG ZHI YE BING ZA ZHI = ZHONGHUA LAODONG WEISHENG ZHIYEBING ZAZHI = CHINESE JOURNAL OF INDUSTRIAL HYGIENE AND OCCUPATIONAL DISEASES 2024; 42:248-257. [PMID: 38677987 DOI: 10.3760/cma.j.cn121094-20230524-00184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
Abstract
Objective: To analyze the differential genes and related signaling pathways of microglia subpopulations in Parkinson's disease (PD) -like mouse brains induced by paraquat (PQ) based on single-cell RNA sequencing, and provide clues to elucidate the mechanism of PQ-induced PD-like changes in the brain of animals. Methods: In September 2021, six male 6-week-old C57BL/6 mice were randomly divided into control group and experimental group (three mice in each group) . The mice were injected with saline, 10.0 mg/kg PQ intraperitoneally, once every three days, and 10 consecutive injections were used for modeling. After infection, the brains of mice were taken and 10×Genomics single-cell RNA sequencing was performed. Microglia subpopulations were screened based on gene expression characteristics, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The differential genes of microglia subpopulations between the experimental group and control group were further screened, and functional enrichment analysis was performed using bioinformatics tools. Mouse microglia (BV2 cells) were treated with 0, 60, 90 μmol/L PQ solution, respectively. And real-time fluorescence quantitative PCR experiments were conducted to validate the expressions of differential genes hexokinase 2 (Hk2) , ATPase H+ Transporting V0 Subunit B (Atp6v0b) and Neuregulin 1 (Nrg1) . Results: Cluster 7 and Cluster 20 were identified as microglia subpopulations based on the signature genes inositol polyphosphate-5-phosphatase d, Inpp5d (Inpp5d) and transforming growth factor beta receptor 1 (Tgfbr1) , and they reflected the microglia-activated M2 phenotype. The bioinformatics analysis showed that the characteristic genes of identified microglia subpopulations were enriched in endocytosis. In terms of molecular function, it mainly enriched in transmembrane receptor protein kinase activity and cytokine binding. The up-regulated genes of Cluster 7 were mainly enriched in lysosomal pathway, endocytosis pathway, and down-regulated genes were mainly enriched in neurodegenerative disease and other signaling pathways. The up-regulated genes of Cluster 20 were mainly enriched in signaling pathways related to PD, and down-regulated genes were mainly enriched in cyclic adenosine 3', 5'-monophosphate (cAMP) signaling pathways, neurological development, synaptic function and other signaling pathways. The results of real-time fluorescence quantitative PCR showed that the expressions of Hk2 mRNA and Atp6v0b mRNA increased and the expression of Nrg1 mRNA decreased in the 90 μmol/L PQ-treated BV2 cells compared with the 0 μmol/L, and the differences were statistically significant (P<0.05) . Conclusion: Microglia are activated in the PQ-induced PD-like mouse model and polarized toward the M2 phenotype. And their functions are associated with lysosomal (endocytosis) , synaptic functions and the regulation of PD-related pathways.
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Acharya S, Adamová D, Adler A, Aglieri Rinella G, Agnello M, Agrawal N, Ahammed Z, Ahmad S, Ahn SU, Ahuja I, Akindinov A, Al-Turany M, Aleksandrov D, Alessandro B, Alfanda HM, Alfaro Molina R, Ali B, Alici A, Alizadehvandchali N, Alkin A, Alme J, Alocco G, Alt T, Altamura AR, Altsybeev I, Alvarado JR, Anaam MN, Andrei C, Andronic A, Anguelov V, Antinori F, Antonioli P, Apadula N, Aphecetche L, Appelshäuser H, Arata C, Arcelli S, Aresti M, Arnaldi R, Arneiro JGMCA, Arsene IC, Arslandok M, Augustinus A, Averbeck R, Azmi MD, Baba H, Badalà A, Bae J, Baek YW, Bai X, Bailhache R, Bailung Y, Balbino A, Baldisseri A, Balis B, Banerjee D, Banoo Z, Barbera R, Barile F, Barioglio L, Barlou M, Barnaföldi GG, Barnby LS, Barret V, Barreto L, Bartels C, Barth K, Bartsch E, Bastid N, Basu S, Batigne G, Battistini D, Batyunya B, Bauri D, Bazo Alba JL, Bearden IG, Beattie C, Becht P, Behera D, Belikov I, Bell Hechavarria ADC, Bellini F, Bellwied R, Belokurova S, Bencedi G, Beole S, Bercuci A, Berdnikov Y, Berdnikova A, Bergmann L, Besoiu MG, Betev L, Bhaduri PP, Bhasin A, Bhat MA, Bhattacharjee B, Bianchi L, Bianchi N, Bielčík J, Bielčíková J, Biernat J, Bigot AP, Bilandzic A, Biro G, Biswas S, Bize N, Blair JT, Blau D, Blidaru MB, Bluhme N, Blume C, Boca G, Bock F, Bodova T, Bogdanov A, Boi S, Bok J, Boldizsár L, Bombara M, Bond PM, Bonomi G, Borel H, Borissov A, Borquez Carcamo AG, Bossi H, Botta E, Bouziani YEM, Bratrud L, Braun-Munzinger P, Bregant M, Broz M, Bruno GE, Buckland MD, Budnikov D, Buesching H, Bufalino S, Buhler P, Burmasov N, Buthelezi Z, Bylinkin A, Bysiak SA, Cai M, Caines H, Caliva A, Calvo Villar E, Camacho JMM, Camerini P, Canedo FDM, Cantway SL, Carabas M, Carballo AA, Carnesecchi F, Caron R, Carvalho LAD, Castillo Castellanos J, Catalano F, Ceballos Sanchez C, Chakaberia I, Chakraborty P, Chandra S, Chapeland S, Chartier M, Chattopadhyay S, Chattopadhyay S, Cheng T, Cheshkov C, Cheynis B, Chibante Barroso V, Chinellato DD, Chizzali ES, Cho J, Cho S, Chochula P, Christakoglou P, Christensen CH, Christiansen P, Chujo T, Ciacco M, Cicalo C, Cindolo F, Ciupek MR, Clai G, Colamaria F, Colburn JS, Colella D, Colocci M, Concas M, Conesa Balbastre G, Conesa Del Valle Z, Contin G, Contreras JG, Coquet ML, Cortese P, Cosentino MR, Costa F, Costanza S, Cot C, Crkovská J, Crochet P, Cruz-Torres R, Cui P, Dainese A, Danisch MC, Danu A, Das P, Das P, Das S, Dash AR, Dash S, De Caro A, de Cataldo G, de Cuveland J, De Falco A, De Gruttola D, De Marco N, De Martin C, De Pasquale S, Deb R, Deb S, Del Grande R, Dello Stritto L, Deng W, Dhankher P, Di Bari D, Di Mauro A, Diab B, Diaz RA, Dietel T, Ding Y, Divià R, Dixit DU, Djuvsland Ø, Dmitrieva U, Dobrin A, Dönigus B, Dubinski JM, Dubla A, Dudi S, Dupieux P, Durkac M, Dzalaiova N, Eder TM, Ehlers RJ, Eisenhut F, Ejima R, Elia D, Erazmus B, Ercolessi F, Erhardt F, Ersdal MR, Espagnon B, Eulisse G, Evans D, Evdokimov S, Fabbietti L, Faggin M, Faivre J, Fan F, Fan W, Fantoni A, Fasel M, Fecchio P, Feliciello A, Feofilov G, Fernández Téllez A, Ferrandi L, Ferrer MB, Ferrero A, Ferrero C, Ferretti A, Feuillard VJG, Filova V, Finogeev D, Fionda FM, Flor F, Flores AN, Foertsch S, Fokin I, Fokin S, Fragiacomo E, Frajna E, Fuchs U, Funicello N, Furget C, Furs A, Fusayasu T, Gaardhøje JJ, Gagliardi M, Gago AM, Gahlaut T, Galvan CD, Gangadharan DR, Ganoti P, Garabatos C, Garcia AT, García Chávez T, Garcia-Solis E, Gargiulo C, Garner K, Gasik P, Gautam A, Gay Ducati MB, Germain M, Ghimouz A, Ghosh C, Giacalone M, Giubellino P, Giubilato P, Glaenzer AMC, Glässel P, Glimos E, Goh DJQ, Gonzalez V, Gorgon M, Goswami K, Gotovac S, Grabski V, Graczykowski LK, Grecka E, Grelli A, Grigoras C, Grigoriev V, Grigoryan S, Grosa F, Grosse-Oetringhaus JF, Grosso R, Grund D, Guardiano GG, Guernane R, Guilbaud M, Gulbrandsen K, Gündem T, Gunji T, Guo W, Gupta A, Gupta R, Gupta R, Gwizdziel K, Gyulai L, Habib MK, Hadjidakis C, Haider FU, Hamagaki H, Hamdi A, Hamid M, Han Y, Hanley BG, Hannigan R, Hansen J, Haque MR, Harris JW, Harton A, Hassan H, Hatzifotiadou D, Hauer P, Havener LB, Heckel ST, Hellbär E, Helstrup H, Hemmer M, Herman T, Herrera Corral G, Herrmann F, Herrmann S, Hetland KF, Heybeck B, Hillemanns H, Hippolyte B, Hoffmann FW, Hofman B, Hohlweger B, Hong GH, Horst M, Horzyk A, Hou Y, Hristov P, Hughes C, Huhn P, Huhta LM, Humanic TJ, Hutson A, Hutter D, Ilkaev R, Ilyas H, Inaba M, Innocenti GM, Ippolitov M, Isakov A, Isidori T, Islam MS, Ivanov M, Ivanov M, Ivanov V, Iversen KE, Jablonski M, Jacak B, Jacazio N, Jacobs PM, Jadlovska S, Jadlovsky J, Jaelani S, Jahnke C, Jakubowska MJ, Janik MA, Janson T, Jercic M, Ji S, Jia S, Jimenez AAP, Jonas F, Jones DM, Jowett JM, Jung J, Jung M, Junique A, Jusko A, Kabus MJ, Kaewjai J, Kalinak P, Kalteyer AS, Kalweit A, Kaplin V, Karasu Uysal A, Karatovic D, Karavichev O, Karavicheva T, Karczmarczyk P, Karpechev E, Kebschull U, Keidel R, Keijdener DLD, Keil M, Ketzer B, Khade SS, Khan AM, Khan S, Khanzadeev A, Kharlov Y, Khatun A, Khuntia A, Kidson MB, Kileng B, Kim B, Kim C, Kim DJ, Kim EJ, Kim J, Kim JS, Kim J, Kim J, Kim M, Kim S, Kim T, Kimura K, Kirsch S, Kisel I, Kiselev S, Kisiel A, Kitowski JP, Klay JL, Klein J, Klein S, Klein-Bösing C, Kleiner M, Klemenz T, Kluge A, Knospe AG, Kobdaj C, Kollegger T, Kondratyev A, Kondratyeva N, Kondratyuk E, Konig J, Konigstorfer SA, Konopka PJ, Kornakov G, Korwieser M, Koryciak SD, Kotliarov A, Kovalenko V, Kowalski M, Kozhuharov V, Králik I, Kravčáková A, Krcal L, Krivda M, Krizek F, Krizkova Gajdosova K, Kroesen M, Krüger M, Krupova DM, Kryshen E, Kučera V, Kuhn C, Kuijer PG, Kumaoka T, Kumar D, Kumar L, Kumar N, Kumar S, Kundu S, Kurashvili P, Kurepin A, Kurepin AB, Kuryakin A, Kushpil S, Kweon MJ, Kwon Y, La Pointe SL, La Rocca P, Lakrathok A, Lamanna M, Landou AR, Langoy R, Larionov P, Laudi E, Lautner L, Lavicka R, Lea R, Lee H, Legrand I, Legras G, Lehrbach J, Lelek TM, Lemmon RC, León Monzón I, Lesch MM, Lesser ED, Lévai P, Li X, Li XL, Lien J, Lietava R, Likmeta I, Lim B, Lim SH, Lindenstruth V, Lindner A, Lippmann C, Liu A, Liu DH, Liu J, Liveraro GSS, Lofnes IM, Loizides C, Lokos S, Lomker J, Loncar P, Lopez JA, Lopez X, López Torres E, Lu P, Luhder JR, Lunardon M, Luparello G, Ma YG, Mager M, Maire A, Majerz EM, Makariev MV, Malaev M, Malfattore G, Malik NM, Malik QW, Malik SK, Malinina L, Mallick D, Mallick N, Mandaglio G, Mandal SK, Manko V, Manso F, Manzari V, Mao Y, Marcjan RW, Margagliotti GV, Margotti A, Marín A, Markert C, Martinengo P, Martínez MI, Martínez García G, Martins MPP, Masciocchi S, Masera M, Masoni A, Massacrier L, Mastroserio A, Matonoha O, Mattiazzo S, Matuoka PFT, Matyja A, Mayer C, Mazuecos AL, Mazzaschi F, Mazzilli M, Mdhluli JE, Mechler AF, Melikyan Y, Menchaca-Rocha A, Meninno E, Menon AS, Meres M, Mhlanga S, Miake Y, Micheletti L, Migliorin LC, Mihaylov DL, Mikhaylov K, Mishra AN, Miśkowiec D, Modak A, Mohanty AP, Mohanty B, Mohisin Khan M, Molander MA, Monira S, Moravcova Z, Mordasini C, Moreira De Godoy DA, Morozov I, Morsch A, Mrnjavac T, Muccifora V, Muhuri S, Mulligan JD, Mulliri A, Munhoz MG, Munzer RH, Murakami H, Murray S, Musa L, Musinsky J, Myrcha JW, Naik B, Nambrath AI, Nandi BK, Nania R, Nappi E, Nassirpour AF, Nath A, Nattrass C, Naydenov MN, Neagu A, Negru A, Nellen L, Nepeivoda R, Nese S, Neskovic G, Nielsen BS, Nielsen EG, Nikolaev S, Nikulin S, Nikulin V, Noferini F, Noh S, Nomokonov P, Norman J, Novitzky N, Nowakowski P, Nyanin A, Nystrand J, Ogino M, Oh S, Ohlson A, Okorokov VA, Oleniacz J, Oliveira Da Silva AC, Oliver MH, Onnerstad A, Oppedisano C, Ortiz Velasquez A, Otwinowski J, Oya M, Oyama K, Pachmayer Y, Padhan S, Pagano D, Paić G, Paisano-Guzmán S, Palasciano A, Panebianco S, Park H, Park H, Park J, Parkkila JE, Patley Y, Patra RN, Paul B, Pei H, Peitzmann T, Peng X, Pennisi M, Peresunko D, Perez GM, Pestov Y, Petrov V, Petrovici M, Pezzi RP, Piano S, Pikna M, Pillot P, Pinazza O, Pinsky L, Pinto C, Pisano S, Płoskoń M, Planinic M, Pliquett F, Poghosyan MG, Polichtchouk B, Politano S, Poljak N, Pop A, Porteboeuf-Houssais S, Pozdniakov V, Pozos IY, Pradhan KK, Prasad SK, Prasad S, Preghenella R, Prino F, Pruneau CA, Pshenichnov I, Puccio M, Pucillo S, Pugelova Z, Qiu S, Quaglia L, Quishpe RE, Ragoni S, Rakotozafindrabe A, Ramello L, Rami F, Rancien TA, Rasa M, Räsänen SS, Rath R, Rauch MP, Ravasenga I, Read KF, Reckziegel C, Redelbach AR, Redlich K, Reetz CA, Regules-Medel HD, Rehman A, Reidt F, Reme-Ness HA, Rescakova Z, Reygers K, Riabov A, Riabov V, Ricci R, Richter M, Riedel AA, Riegler W, Ristea C, Rodriguez MV, Rodríguez Cahuantzi M, Rodríguez Ramírez SA, Røed K, Rogalev R, Rogochaya E, Rogoschinski TS, Rohr D, Röhrich D, Rojas PF, Rojas Torres S, Rokita PS, Romanenko G, Ronchetti F, Rosano A, Rosas ED, Roslon K, Rossi A, Roy A, Roy S, Rubini N, Ruggiano D, Rui R, Russek PG, Russo R, Rustamov A, Ryabinkin E, Ryabov Y, Rybicki A, Rytkonen H, Ryu J, Rzesa W, Saarimaki OAM, Sadek R, Sadhu S, Sadovsky S, Saetre J, Šafařík K, Saha P, Saha SK, Saha S, Sahoo B, Sahoo B, Sahoo R, Sahoo S, Sahu D, Sahu PK, Saini J, Sajdakova K, Sakai S, Salvan MP, Sambyal S, Sanna I, Saramela TB, Sarkar D, Sarkar N, Sarma P, Sarritzu V, Sarti VM, Sas MHP, Schambach J, Scheid HS, Schiaua C, Schicker R, Schmah A, Schmidt C, Schmidt HR, Schmidt MO, Schmidt M, Schmidt NV, Schmier AR, Schotter R, Schröter A, Schukraft J, Schweda K, Scioli G, Scomparin E, Seger JE, Sekiguchi Y, Sekihata D, Selina M, Selyuzhenkov I, Senyukov S, Seo JJ, Serebryakov D, Šerkšnytė L, Sevcenco A, Shaba TJ, Shabetai A, Shahoyan R, Shangaraev A, Sharma A, Sharma B, Sharma D, Sharma H, Sharma M, Sharma S, Sharma S, Sharma U, Shatat A, Sheibani O, Shigaki K, Shimomura M, Shin J, Shirinkin S, Shou Q, Sibiriak Y, Siddhanta S, Siemiarczuk T, Silva TF, Silvermyr D, Simantathammakul T, Simeonov R, Singh B, Singh B, Singh K, Singh R, Singh R, Singh R, Singh S, Singh VK, Singhal V, Sinha T, Sitar B, Sitta M, Skaali TB, Skorodumovs G, Slupecki M, Smirnov N, Snellings RJM, Solheim EH, Song J, Songmoolnak A, Sonnabend C, Soramel F, Soto-Hernandez AB, Spijkers R, Sputowska I, Staa J, Stachel J, Stan I, Steffanic PJ, Stiefelmaier SF, Stocco D, Storehaug I, Stratmann P, Strazzi S, Stylianidis CP, Suaide AAP, Suire C, Sukhanov M, Suljic M, Sultanov R, Sumberia V, Sumowidagdo S, Swain S, Szarka I, Szymkowski M, Taghavi SF, Taillepied G, Takahashi J, Tambave GJ, Tang S, Tang Z, Tapia Takaki JD, Tapus N, Tarasovicova LA, Tarzila MG, Tassielli GF, Tauro A, Tejeda Muñoz G, Telesca A, Terlizzi L, Terrevoli C, Thakur S, Thomas D, Tikhonov A, Timmins AR, Tkacik M, Tkacik T, Toia A, Tokumoto R, Tomohiro K, Topilskaya N, Toppi M, Tork T, Torres VV, Torres Ramos AG, Trifiró A, Triolo AS, Tripathy S, Tripathy T, Trogolo S, Trubnikov V, Trzaska WH, Trzcinski TP, Tumkin A, Turrisi R, Tveter TS, Ullaland K, Ulukutlu B, Uras A, Urioni M, Usai GL, Vala M, Valle N, van Doremalen LVR, van Leeuwen M, van Veen CA, van Weelden RJG, Vande Vyvre P, Varga D, Varga Z, Vasileiou M, Vasiliev A, Vázquez Doce O, Vazquez Rueda O, Vechernin V, Vercellin E, Vergara Limón S, Verma R, Vermunt L, Vértesi R, Verweij M, Vickovic L, Vilakazi Z, Villalobos Baillie O, Villani A, Vino G, Vinogradov A, Virgili T, Virta MMO, Vislavicius V, Vodopyanov A, Volkel B, Völkl MA, Voloshin K, Voloshin SA, Volpe G, von Haller B, Vorobyev I, Vozniuk N, Vrláková J, Wan J, Wang C, Wang D, Wang Y, Wang Y, Wegrzynek A, Weiglhofer FT, Wenzel SC, Wessels JP, Wiechula J, Wikne J, Wilk G, Wilkinson J, Willems GA, Windelband B, Winn M, Wright JR, Wu W, Wu Y, Xu R, Yadav A, Yadav AK, Yalcin S, Yamaguchi Y, Yang S, Yano S, Yin Z, Yoo IK, Yoon JH, Yu H, Yuan S, Yuncu A, Zaccolo V, Zampolli C, Zanone F, Zardoshti N, Zarochentsev A, Závada P, Zaviyalov N, Zhalov M, Zhang B, Zhang C, Zhang L, Zhang S, Zhang X, Zhang Y, Zhang Z, Zhao M, Zherebchevskii V, Zhi Y, Zhou D, Zhou Y, Zhu J, Zhu Y, Zugravel SC, Zurlo N. First Measurement of the |t| Dependence of Incoherent J/ψ Photonuclear Production. PHYSICAL REVIEW LETTERS 2024; 132:162302. [PMID: 38701458 DOI: 10.1103/physrevlett.132.162302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 11/22/2023] [Accepted: 01/23/2024] [Indexed: 05/05/2024]
Abstract
The first measurement of the cross section for incoherent photonuclear production of J/ψ vector mesons as a function of the Mandelstam |t| variable is presented. The measurement was carried out with the ALICE detector at midrapidity, |y|<0.8, using ultraperipheral collisions of Pb nuclei at a center-of-mass energy per nucleon pair of sqrt[s_{NN}]=5.02 TeV. This rapidity interval corresponds to a Bjorken-x range (0.3-1.4)×10^{-3}. Cross sections are given in five |t| intervals in the range 0.04<|t|<1 GeV^{2} and compared to the predictions by different models. Models that ignore quantum fluctuations of the gluon density in the colliding hadron predict a |t| dependence of the cross section much steeper than in data. The inclusion of such fluctuations in the same models provides a better description of the data.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Bao HR, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peng YY, Peters K, Ping JL, Ping RG, Plura S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of Structures in the Processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2}. PHYSICAL REVIEW LETTERS 2024; 132:161901. [PMID: 38701481 DOI: 10.1103/physrevlett.132.161901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 03/13/2024] [Accepted: 03/22/2024] [Indexed: 05/05/2024]
Abstract
We present measurements of the Born cross sections for the processes e^{+}e^{-}→ωχ_{c1} and ωχ_{c2} at center-of-mass energies sqrt[s] from 4.308 to 4.951 GeV. The measurements are performed with data samples corresponding to an integrated luminosity of 11.0 fb^{-1} collected with the BESIII detector operating at the Beijing Electron Positron Collider storage ring. Assuming the e^{+}e^{-}→ωχ_{c2} signals come from a single resonance, the mass and width are determined to be M=(4413.6±9.0±0.8) MeV/c^{2} and Γ=(110.5±15.0±2.9) MeV, respectively, which is consistent with the parameters of the well-established resonance ψ(4415). In addition, we also use one single resonance to describe the e^{+}e^{-}→ωχ_{c1} line shape and determine the mass and width to be M=(4544.2±18.7±1.7) MeV/c^{2} and Γ=(116.1±33.5±1.7) MeV, respectively. The structure of this line shape, observed for the first time, requires further understanding.
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Zhang Y, Lo KL, Liman AN, Feng XP, Ye W. Tongue-Coating Microbial and Metabolic Characteristics in Halitosis. J Dent Res 2024:220345241230067. [PMID: 38623900 DOI: 10.1177/00220345241230067] [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: 04/17/2024] Open
Abstract
Halitosis is a common oral condition, which leads to social embarrassment and affects quality of life. Cumulative evidence has suggested the association of tongue-coating microbiome with the development of intraoral halitosis. The dynamic variations of tongue-coating microbiota and metabolites in halitosis have not been fully elucidated. Therefore, the present study aimed to determine the tongue-coating microbial and metabolic characteristics in halitosis subjects without other oral diseases using metagenomics and metabolomics analysis. The participants underwent oral examination, halitosis assessment, and tongue-coating sample collection for the microbiome and metabolome analysis. It was found that the microbiota richness and diversity were significantly elevated in the halitosis group. Furthermore, species from Actinomyces, Prevotella, Veillonella, and Solobacterium were significantly more abundant in the halitosis group. However, the Rothia and Streptococcus species exhibited opposite tendencies. Eleven Kyoto Encyclopedia of Genes and Genomes pathways were significantly enriched in the halitosis tongue coatings, including cysteine and methionine metabolism. Functional genes related to sulfur, indole, skatole, and cadaverine metabolic processes (such as serA, metH, metK and dsrAB) were identified to be more abundant in the halitosis samples. The metabolome analysis revealed that indole-3-acetic, ornithine, and L-tryptophan were significantly elevated in the halitosis samples. Furthermore, it was observed that the values of volatile sulfur compounds and indole-3-acetic abundances were positively correlated. The multiomics analysis identified the metagenomic and metabolomic characteristics to differentiate halitosis from healthy individuals using the least absolute shrinkage and selection operator logistic regression and random forest classifier. A total of 19 species and 39 metabolites were identified as features in halitosis patients, which included indole-3-acetic acid, Bacillus altitudinis, Candidatus Saccharibacteria, and Actinomyces species. In conclusion, an evident shift in microbiome and metabolome characteristics was observed in the halitosis tongue coating, which may have a potential etiological significance and provide novel insights into the mechanism for halitosis.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, K X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Coupled-Channel Analysis of the χ_{c1}(3872) Line Shape with BESIII Data. PHYSICAL REVIEW LETTERS 2024; 132:151903. [PMID: 38682963 DOI: 10.1103/physrevlett.132.151903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/03/2024] [Accepted: 03/11/2024] [Indexed: 05/01/2024]
Abstract
We perform a study of the χ_{c1}(3872) line shape using the data samples of e^{+}e^{-}→γχ_{c1}(3872), χ_{c1}(3872)→D^{0}D[over ¯]^{0}π^{0}, and π^{+}π^{-}J/ψ collected with the BESIII detector. The effects of the coupled channels and the off-shell D^{*0} are included in the parametrization of the line shape. The line shape mass parameter is obtained to be M_{X}=(3871.63±0.13_{-0.05}^{+0.06}) MeV. Two poles are found on the first and second Riemann sheets corresponding to the D^{*0}D[over ¯]^{0} branch cut. The pole location on the first sheet is much closer to the D^{*0}D[over ¯]^{0} threshold than the other, and is determined to be 7.04±0.15_{-0.08}^{+0.07} MeV above the D^{0}D[over ¯]^{0}π^{0} threshold with an imaginary part -0.19±0.08_{-0.19}^{+0.14} MeV.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du MC, Du SX, Duan ZH, Egorov P, Fan YH, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu YW, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Gramigna S, Greco M, Gu MH, Gu YT, Guan CY, Guan ZL, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou XT, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, In der Wiesche N, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang HJ, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuessner M, Kui X, Kupsc A, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Liao YP, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muskalla J, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YH, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang X, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Observation of the Anomalous Shape of X(1840) in J/ψ→γ3(π^{+}π^{-}) Indicating a Second Resonance Near pp[over ¯] Threshold. PHYSICAL REVIEW LETTERS 2024; 132:151901. [PMID: 38682972 DOI: 10.1103/physrevlett.132.151901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/16/2024] [Accepted: 02/23/2024] [Indexed: 05/01/2024]
Abstract
Using a sample of (10087±44)×10^{6} J/ψ events, which is about 45 times larger than that was previously analyzed, a further investigation on the J/ψ→γ3(π^{+}π^{-}) decay is performed. A significant distortion at 1.84 GeV/c^{2} in the line shape of the 3(π^{+}π^{-}) invariant mass spectrum is observed for the first time, which could be resolved by two overlapping resonant structures, X(1840) and X(1880). The new state X(1880) is observed with a statistical significance larger than 10σ. The mass and width of X(1880) are determined to be 1882.1±1.7±0.7 MeV/c^{2} and 30.7±5.5±2.4 MeV, respectively, which indicates the existence of a pp[over ¯] bound state.
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Zhu X, Huang X, Hu M, Sun R, Li J, Wang H, Pan X, Ma Y, Ning L, Tong T, Zhou Y, Ding J, Zhao Y, Xuan B, Fang JY, Hong J, Hon Wong JW, Zhang Y, Chen H. A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy. Cell Host Microbe 2024; 32:489-505.e5. [PMID: 38513657 DOI: 10.1016/j.chom.2024.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/15/2023] [Accepted: 03/04/2024] [Indexed: 03/23/2024]
Abstract
Immunotherapy has revolutionized cancer treatment, but inconsistent responses persist. Our study delves into the intriguing phenomenon of enhanced immunotherapy sensitivity in older individuals with cancers. Through a meta-analysis encompassing 25 small-to-mid-sized trials of immune checkpoint blockade (ICB), we demonstrate that older individuals exhibit heightened responsiveness to ICB therapy. To understand the underlying mechanism, we reanalyze single-cell RNA sequencing (scRNA-seq) data from multiple studies and unveil distinct upregulation of exhausted and cytotoxic T cell markers within the tumor microenvironment (TME) of older patients. Recognizing the potential role of gut microbiota in modulating the efficacy of immunotherapy, we identify an aging-enriched enterotype linked to improved immunotherapy outcomes in older patients. Fecal microbiota transplantation experiments in mice confirm the therapeutic potential of the aging-enriched enterotype, enhancing treatment sensitivity and reshaping the TME. Our discoveries confront the prevailing paradox and provide encouraging paths for tailoring cancer immunotherapy strategies according to an individual's gut microbiome profile.
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