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Yan WZ, Xiang XX, Cui GH, Hu Y, Lyu B, Zhang X, Peng HL. [Analysis and reflections on the current status of diagnosis and treatment of marginal zone lymphoma]. ZHONGHUA YI XUE ZA ZHI 2024; 104:4360-4365. [PMID: 39690529 DOI: 10.3760/cma.j.cn112137-20241012-02311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/19/2024]
Abstract
The current study aimed to understand the current status and problems of marginal zone lymphoma (MZL) in the diagnosis and treatment of hospitals at all levels in China. A multi-center questionnaire survey was conducted in a number of medical institutions across the country. A combination of online questionnaire survey and face-to-face interview was adopted. (1)Pathologists paid more attention than clinicians to distinguish MALT from chronic inflammation (86.3% vs 32.1%, P<0.01) and plasma cell tumor (51.8% vs 23.1%, P<0.01). A total of 21% pathologists never performed B-cell gene rearrangement, 67.6% of clinicians and 69.0% of pathologists would not recommend splenic puncture to diagnose SMZL.(2)In terms of treatment indications, 40.0% of clinicians mistakenly believed that stage Ⅲ-Ⅳ was also a treatment indication. Seventy percent of clinicians reported confusion about treatment indications. (3) In staging and efficacy evaluation, 63.3% of physicians performed PET-CT testing for patients, mainly for resolving clinical staging (89.0%), identifying histologically transformation (79.6%), and determining the site of radiotherapy or biopsy (66.2%). (4) In terms of treatment choice, only 32.2% of patients with indications were recommended for radiotherapy, and the proportion of hematologists choosing radiotherapy was significantly lower than that of oncologists (42.6% vs 71.7%, P<0.01); In the anti-HP indications, 53.1% of physicians will perform anti-HP therapy regardless of Hp positive or not; For advanced MZL, first-line immunochemotherapy was selected by 62.7% of clinicians, compared with 37.3% for targeted therapy. (5)15.3% of clinicians believed that the current prognostic evaluation system could not guide the selection of treatment options after initial treatment and recurrence. At present, there are still some cognitive deviations in the disease cognition and treatment indication of MZL among clinicians at all levels of hospitals in China. Likewise, there are still many unmet needs in MZL staging, efficacy evaluation, treatment selection and prognosis evaluation.
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Ma Y, Hu Y, Dong W, Wang Q, Wang J, Wu W, Shi B. Design, Synthesis of Dienthiazole Derivatives, and Evaluation of Aphicidal Activity. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024. [PMID: 39698997 DOI: 10.1021/acs.jafc.4c06060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2024]
Abstract
Nitrogen-containing heterocycles have attracted attention for the development of chemicals because of their many types, high physiological activities, and ease of synthesis. Aphids are severe pests found worldwide that cause serious losses in crop yield and quality every year. In this study, a series of novel dienolone thiazole derivatives were synthesized using dienolone acetate as the parent molecule. The synthesis involved bromination, Hantzsch reaction, esterification, deprotection, and other reactions. The structure of the compounds was determined using proton and carbon-13 nuclear magnetic resonance, high-resolution mass spectrometry, and single-crystal diffraction. The synthesized compounds exhibited excellent insecticidal activities against five species of aphids, including Schizaphis graminum, Brevicoryne brassicae, Aphis gossypii, Aphis citricola Van der, and Myzus persicae. The median lethal concentration values of the compound H-13 for S. graminum, B. brassicae, A. gossypii, A. citricola Van der, and M. persicae were 8.72, 13.77, 14.17, 12.96, and 12.35 μg/mL, respectively. The mode of action test results indicated that compound H-13 had superior contact and systemic activity against M. persicae, similar to the positive control flonicamid. Furthermore, a field trial showed that the control effect of compound H-13 at 100 μg/mL concentration was comparable to that of flonicamid against M. persicae. The mortality was 85.6% and 90.3% after 7 and 14 days, respectively. Finally, to further explore the action mechanism of these compounds, the insecticidal activity of compounds H-13 (strong) and H-24 (weak) on aphid protease was determined. Compound H-13 was found to have a significant inhibitory effect on the strong alkaline tryptase activity. Compound H-13 might cause aphid poisoning and death by inhibiting the trypsin activity. This study provided important insights for the discovery and development of new insecticides.
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Ablikim M, Achasov MN, Adlarson P, Ai XC, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Balossino I, Ban Y, Batozskaya V, Begzsuren K, Berger N, Berlowski M, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang TT, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Coen SC, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding B, Ding XX, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Fu JL, Fu Y, 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, H XT, Han TT, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Holtmann T, Hong PC, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang LL, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kui X, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuessner MK, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li JW, Li KL, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QX, Li SX, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZJ, Li ZX, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu LC, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma JL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JL, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su YJ, Sun GB, Sun GX, Sun H, Sun HK, Sun JF, Sun K, Sun L, Sun SS, Sun T, Sun WY, Sun Y, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian WH, Tian Y, Tian ZF, Uman I, Wang SJ, Wang B, Wang BL, Wang B, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang JP, Wang K, Wang LL, Wang M, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang W, Wang WP, Wang X, Wang XF, Wang XJ, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YN, Wang YQ, Wang Y, Wang Y, Wang Z, Wang ZL, Wang ZY, Wang Z, Wei D, Wei DH, Weidner F, Wen SP, Wenzel CW, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu C, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xian XM, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu YC, Xu ZP, Xu ZS, Yan F, Yan L, Yan WB, Yan WC, Yan XQ, Yang HJ, Yang HL, Yang HX, Yang T, Yang Y, Yang YF, Yang YX, Yang Y, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JJ, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu L, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. R(3780) Resonance Interpreted as the 1^{3}D_{1}-Wave Dominant State of Charmonium from Precise Measurements of the Cross Section of e^{+}e^{-}→Hadrons. PHYSICAL REVIEW LETTERS 2024; 133:241902. [PMID: 39750337 DOI: 10.1103/physrevlett.133.241902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 10/24/2024] [Accepted: 10/31/2024] [Indexed: 01/04/2025]
Abstract
We report the precise measurements of the cross section of e^{+}e^{-}→hadrons at center-of-mass energies from 3.645 to 3.871 GeV. We thereby perform the most precise study of the cross sections and find a complex system composed of three resonances of R(3760), R(3780), and R(3810). For the first time, we measure the R(3810) electronic width to be (19.4±7.4±12.1) eV. For the R(3760) resonance, we measure the mass to be (3751.9±3.8±2.8) MeV/c^{2}, the total width to be (32.8±5.8±8.7) MeV, and the electronic width to be (184±75±86) eV. For the R(3780) resonance, we measure its mass to be (3778.7±0.5±0.3) MeV/c^{2}, total width to be (20.3±0.8±1.7) MeV, and electronic width to be (265±67±83) eV. Forty-seven years ago, the ψ(3770) resonance was discovered, and was subsequently interpreted as the 1^{3}D_{1}-wave dominant state of charmonium. However, our analysis of the total-hadron cross sections indicates that the ψ(3770) is not a single state, but a complex system composed of the R(3760), R(3780), and R(3810) resonances. Among these, we interpret the R(3780) is a resonance dominated by the 1^{3}D_{1} charmonium state.
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Huang J, Li T, Tang L, Hu Y, Hu Y, Gu Y. Development and Validation of an 18F-FDG PET/CT-based Radiomics Nomogram for Predicting the Prognosis of Patients with Esophageal Squamous Cell Carcinoma. Acad Radiol 2024; 31:5066-5077. [PMID: 38845294 DOI: 10.1016/j.acra.2024.05.029] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/02/2024] [Accepted: 05/16/2024] [Indexed: 11/30/2024]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to develop and validate a nomogram, integrating clinical factors and radiomics features, capable of predicting overall survival (OS) in patients diagnosed with esophageal squamous cell carcinoma (ESCC). METHODS In this study, we retrospectively analyzed the case data of 130 patients with ESCC who underwent 18F-FDG PET/CT before treatment. Radiomics features associated with OS were screened by univariate Cox regression (p < 0.05). Further selection was performed by applying the least absolute shrinkage and selection operator Cox regression to generate the weighted Radiomics-score (Rad-score). Independent clinical risk factors were obtained by multivariate Cox regression, and a nomogram was constructed by combining Rad-score and independent risk factors. The predictive performance of the model for OS was assessed using the time-dependent receiver operating characteristic curve, concordance index (C-index), calibration curve, and decision curve analysis. RESULTS Five radiomics features associated with prognosis were finally screened, and a Rad-score was established. Multivariate Cox regression analysis revealed that surgery and clinical M stage were identified as independent risk factors for OS in ESCC. The combined clinical-radiomics nomogram exhibited C-index values of 0.768 (95% CI: 0.699-0.837) and 0.809 (95% CI: 0.695-0.923) in the training and validation cohorts, respectively. Ultimately, calibration curves and decision curves for the 1-, 2-, and 3-year OS demonstrated the satisfactory prognostic prediction and clinical utility of the nomogram. CONCLUSION The developed nomogram, leveraging 18F-FDG PET/CT radiomics and clinically independent risk factors, demonstrates a reliable prognostic prediction for patients with ESCC, potentially serving as a valuable tool for guiding and optimizing clinical treatment decisions in the future.
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Hu Y, Li YJ, Mu YM. [Glucokinase activators: the first step in regulating intracellular glucose metabolism]. ZHONGHUA NEI KE ZA ZHI 2024; 63:1170-1174. [PMID: 39622719 DOI: 10.3760/cma.j.cn112138-20240713-00448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/13/2024]
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Hu Y, Zhou G, Jiang S, Gao L, Yu Y, Wang Q, Chen J, Zhang J. Impact of risk factors on atrial fibrillation types via epicardial adipose tissue computed tomography-based radiomics analysis. Clin Radiol 2024; 80:106753. [PMID: 39689621 DOI: 10.1016/j.crad.2024.106753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 10/19/2024] [Accepted: 11/14/2024] [Indexed: 12/19/2024]
Abstract
AIM To analyze epicardial adipose tissue (EAT) radiomics and assess the impact of risk factors on different types of atrial fibrillation (AF). MATERIALS AND METHODS We included AF patients undergoing radiofrequency ablation from June 2018 to December 2020. Propensity score matching (PSM) was employed to limit the differences in risk factors between patients with different types of AF. The nnU-Net model was utilized to segment EAT. After extracting radiomic features, a generalized linear model was used to examine the epicardial adipose tissue (EAT) radiomic features associated with risk factors, and logistic regression analysis was conducted to identify the features differentiating the two AF groups. Hierarchical clustering was utilized to identify clusters among significant features. RESULTS After PSM, 794 patients (median age 67, 547 males) were selected, with 397 having paroxysmal and 397 persistent AF. In univariate analysis, 15.11% of the features were significantly associated with the type of AF (P<.000005). 39.29% of all features were significantly correlated with at least one risk factor, with 141 features being significantly related to both risk factors and the type of AF. Three independent clusters were successfully identified among the 141 features. The biggest cluster is dominated by hypertension and hyperlipidemia factors, exhibiting a high overlap in their effects on EAT. Following closely in influence are gender, age, and diabetes clusters, collectively covering 59 out of the 141 features. CONCLUSION Our study identifies distinct differences in EAT characteristics between paroxysmal and persistent AF, with persistent cases showing higher EAT gray values and a more disordered texture.
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Liu G, Xu F, Ren H, Zhang CM, Li Y, Cheng YB, Chen YP, Duan HN, Liu CF, Jin YP, Chen S, Wang XM, Sun JY, Dang HX, Xu XZ, Zhu QJ, Wang XD, Liu XH, Liu Y, Hu Y, Wang W, Ai Q, Gao HM, Fan CN, Qian SY. [A multicenter retrospective study on clinical features and pathogenic composition of septic shock in children]. ZHONGHUA ER KE ZA ZHI = CHINESE JOURNAL OF PEDIATRICS 2024; 62:1083-1089. [PMID: 39429081 DOI: 10.3760/cma.j.cn112140-20240518-00340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Objective: To investigate the clinical features, pathogen composition, and prognosis of septic shock in pediatric intensive care units (PICU) in China. Methods: A multicenter retrospective cohort study. A retrospective analysis was conducted on the clinical data of children with septic shock from 10 hospitals in China between January 2018 and December 2021. The clinical features, pathogen composition, and outcomes were collected. Patients were categorized into malignant tumor and non-malignant tumor groups, as well as survival and mortality groups. T test, Mann Whitney U test or Chi square test were used respectively for comparing clinical characteristics and prognosis between 2 groups. Multiple Logistic regression was used to identify risk factors for mortality. Results: A total of 1 247 children with septic shock were included, with 748 males (59.9%) and the age of 3.1 (0.9, 8.8) years. The in-patient mortality rate was 23.2% (289 cases). The overall pathogen positive rate was 68.2% (851 cases), with 1 229 pathogens identified. Bacterial accounted for 61.4% (754 strains) and virus for 24.8% (305 strains). Among all bacterium, Gram negative bacteria constituted 64.2% (484 strains), with Pseudomonas aeruginosa and Enterobacter being the most common; Gram positive bacteria comprised 35.8% (270 strains), primarily Streptococcus and Staphylococcus species. Influenza virus (86 strains (28.2%)), Epstein-Barr virus (53 strains (17.4%)), and respiratory syncytial virus (46 strains (17.1%)) were the top three viruses. Children with malignant tumors were older and had higher pediatric risk of mortality (PRISM) Ⅲ score, paediatric sequential organ failure assessment (pSOFA) score (7.9 (4.3, 11.8) vs. 2.3 (0.8, 7.5) years old, 22 (16, 26) vs. 16 (10, 24) points, 10 (5, 14) vs. 8 (4, 12) points, Z=11.32, 0.87, 4.00, all P<0.05), and higher pathogen positive rate, and in-hospital mortality (77.7% (240/309) vs. 65.1% (611/938), 29.7% (92/309) vs. 21.0% (197/938), χ2=16.84, 10.04, both P<0.05) compared to the non-tumor group. In the death group, the score of PRISM Ⅲ, pSOFA (16 (22, 29) vs. 14 (10, 20) points, 8 (12, 15) vs. 6 (3, 9) points, Z=4.92, 11.88, both P<0.05) were all higher, and presence of neoplastic disease, positive rate of pathogen and proportion of invasive mechanical ventilation in death group were also all higher than those in survival group (29.7% (87/289) vs. 23.2% (222/958), 77.8% (225/289) vs. 65.4% (626/958), 73.7% (213/289) vs. 50.6% (485/958), χ2=5.72, 16.03, 49.98, all P<0.05). Multiple Logistic regression showed that PRISM Ⅲ, pSOFA, and malignant tumor were the independent risk factors for mortality (OR=1.04, 1.09, 0.67, 95%CI 1.01-1.05, 1.04-1.12, 0.47-0.94, all P<0.05). Conclusions: Bacterial infection are predominant in pediatric septic shock, but viral infection are also significant. Children with malignancies are more severe and resource consumptive. The overall mortality rate for pediatric septic shock remains high, and mortality are associated with malignant tumor, PRISM Ⅲ and pSOFA scores.
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Hu Y, Wang L, Yao K, Wang Q. Atypical surge of hospitalized and severe cases of pertussis: A single center 19-years study from China. Pulmonology 2024; 30:636-638. [PMID: 39003188 DOI: 10.1016/j.pulmoe.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 07/15/2024] Open
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Jin B, Huang L, Liu S, Lyu B, Hu Y. [Effect of an artificial intelligence-assisted recognition system on colonoscopy quality]. ZHONGHUA NEI KE ZA ZHI 2024; 63:1111-1115. [PMID: 39482075 DOI: 10.3760/cma.j.cn112138-20240216-00109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Objective: To explore the value of the artificial intelligence (AI)-assisted recognition system in the detection quality of colonoscopy. Methods: From January 2023, the data on 700 patients who underwent colonoscopy in the Digestive Endoscopy Center of the First Affiliated Hospital of Zhejiang Chinese Medical University were collected prospectively. Based on a computerized number method, patients were divided into the AI assistance group and control group. The detection rate of adenomas (ADR) and polyps, number and size of adenomas, Boston bowel preparation scale (BBPS), intubation time, withdrawal time, and cecal intubation rate were compared between groups. Normally distributed data were analyzed with the t-test for independent samples. Non-normally distributed data were analyzed with the Rank sum test. Categorical data were analyzed with the Chi-square test. Results: In total, 691 patients were included in the analysis. According to the intention to treat (ITT) analysis and per-protocol (PP) analysis, the withdrawal time of the AI group was higher than that of the control group (ITT:436 (305, 620) vs 368 (265, 510) s, Z=-4.24, P<0.001;PP:439 (306, 618) vs 364 (262, 500) s,t=-4.50, P<0.001); however, there were no significant differences in the ADR (ITT:123(35.5%) vs 111(32.2%), χ2=0.88, P=0.349;PP:108(34.2%) vs 99(31.1%), χ2=0.67, P=0.414), the number of adenomas (ITT:0(0, 1) vs 0(0, 1),Z=-1.08, P=0.282;PP:0(0, 1) vs 0(0, 1),Z=-0.87, P=0.387), the polyp detection rate (ITT:85(24.6%) vs 85(24.6%),χ2=0.001, P=0.983;PP:79(25.0%) vs 77(24.2%),χ2=0.05, P=0.818), BBPS (ITT:6.5±0.9 vs 6.5±0.7,t=-0.59, P=0.555;PP:6.7±0.6 vs 6.6±0.6,t=-1.83, P=0.068), and cecal intubation rate (ITT:346(100.0%) vs 343(99.4%), χ2=0.50, P=0.478) between these two groups. After excluding inadequate bowel preparation and failed cecal intubation cases, the AI-assisted system was found to significantly improve the detection rate of small adenomas (≤5 mm) (PP:27.8%(88/316)vs 21.1%(67/318), χ2=3.94, P=0.047). Conclusions: The application of an AI-assisted system in colonoscopy can increase the withdrawal time and improve the detection rate of small adenomas.
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Lin H, Chen J, Hu Y, Li W. Embracing technological revolution: A panorama of machine learning in dentistry. Med Oral Patol Oral Cir Bucal 2024; 29:e742-e749. [PMID: 39418127 PMCID: PMC11584966 DOI: 10.4317/medoral.26679] [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: 04/17/2024] [Accepted: 09/25/2024] [Indexed: 10/19/2024] Open
Abstract
BACKGROUND The overarching aim of this study is to furnish dental experts and researchers with a comprehensive understanding of the role of machine learning in dentistry. This entails a nuanced understanding of prevailing technologies, discerning emerging trends, and providing strategic guidance for future research endeavors and practical implementations. MATERIAL AND METHODS We assessed the literature by looking for papers related to the issue after 2019 in the Pubmed, Web of Science, and Google Scholar databases. A narrative review of 29 papers satisfying the search criteria was undertaken, with an emphasis on the application of machine learning in dentistry. RESULTS A review was conducted, including 29 publications. The advent of emerging technologies holds promise for enhancing the accuracy and efficiency of dental diagnosis, treatment, and prognosis. Nevertheless, the intricate nature of oral disease diagnosis and outcome prediction mandates acknowledgment of variables such as individual idiosyncrasies, lifestyle, genetics, image quality, and tooth morphology. These factors may impact the precision of machine learning models. Dental professionals should not rely solely on AI-based results but rather use them as references. Integrating these findings with clinical examinations, assessing the patient's overall health, and oral condition is crucial for informed decision-making. CONCLUSIONS This review explores the clinical applications of machine learning in dentistry, encompassing disciplines like cariology, endodontics, periodontology, oral medicine, oral and maxillofacial surgery, prosthodontics and orthodontics. It serves as a valuable resource for dental practitioners and scholars in understanding the computer algorithms employed in each study, facilitating the clinical translation of machine learning research outcomes.
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Abdulhamid MI, Aboona BE, Adam J, Adams JR, Agakishiev G, Aggarwal I, Aggarwal MM, Ahammed Z, Aitbaev A, Alekseev I, Alpatov E, Aparin A, Aslam S, Atchison J, Averichev GS, Bairathi V, Cap JGB, Barish K, Bhagat P, Bhasin A, Bhatta S, Bhosale SR, Bordyuzhin IG, Brandenburg JD, Brandin AV, Broodo C, Cai XZ, Caines H, Calderón de la Barca Sánchez M, Cebra D, Ceska J, Chakaberia I, Chan BK, Chang Z, Chatterjee A, Chen D, Chen J, Chen JH, Chen Z, Cheng J, Cheng Y, Christie W, Chu X, Crawford HJ, Csanád M, Dale-Gau G, Das A, Dedovich TG, Deppner IM, Derevschikov AA, Dhamija A, Dixit P, Dong X, Drachenberg JL, Duckworth E, Dunlop JC, Engelage J, Eppley G, Esumi S, Evdokimov O, Eyser O, Fatemi R, Fazio S, Feng CJ, Feng Y, Finch E, Fisyak Y, Flor FA, Fu C, Gao T, Geurts F, Ghimire N, Gibson A, Gopal K, Gou X, Grosnick D, Gupta A, Hamed A, Han Y, Harasty MD, Harris JW, Harrison-Smith H, He W, He XH, He Y, Hu C, Hu Q, Hu Y, Huang H, Huang HZ, Huang SL, Huang T, Huang Y, Huang Y, Humanic TJ, Isshiki M, Jacobs WW, Jalotra A, Jena C, Ji Y, Jia J, Jin C, Ju X, Judd EG, Kabana S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Keane D, Kechechyan A, Khanal A, Kiselev A, Knospe AG, Ko HS, Kochenda L, Korobitsin AA, Yu. Kraeva A, Kravtsov P, Kumar L, Labonte MC, Lacey R, Landgraf JM, Lebedev A, Lednicky R, Lee JH, Leung YH, Li C, Li D, Li HS, Li H, Li W, Li X, Li Y, Li Y, Li Z, Liang X, Liang Y, Lin T, Lin Y, Liu C, Liu G, Liu H, Liu L, Liu T, Liu X, Liu Y, Liu Z, Ljubicic T, Lomicky O, Longacre RS, Loyd EM, Lu T, Luo J, Luo XF, Luong VB, Ma L, Ma R, Ma YG, Magdy N, Manikandhan R, Margetis S, Matonoha O, McNamara G, Mezhanska O, Mi K, Minaev NG, Mohanty B, Mondal B, Mondal MM, Mooney I, Morozov DA, Mudrokh A, Nagy MI, Nain AS, Nam JD, Nasim M, Nedorezov E, Neff D, Nelson JM, Nie M, Nigmatkulov G, Niida T, Nogach LV, Nonaka T, Odyniec G, Ogawa A, Oh S, Okorokov VA, Okubo K, Page BS, Pal S, Pandav A, Panday A, Panebratsev Y, Pani T, Parfenov P, Paul A, Perkins C, Pokhrel BR, Posik M, Povarov A, Protzman T, Pruthi NK, Putschke J, Qin Z, Qiu H, Racz C, Radhakrishnan SK, Rana A, Ray RL, Robertson CW, Rogachevsky OV, Rosales Aguilar MA, Roy D, Ruan L, Sahoo AK, Sahoo NR, Sako H, Salur S, Samigullin E, Sato S, Schaefer BC, Schmidke WB, Schmitz N, Seger J, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao T, Sharma M, Sharma N, Sharma R, Sharma SR, Sheikh AI, Shen D, Shen DY, Shen K, Shi SS, Shi Y, Shou QY, Si F, Singh J, Singha S, Sinha P, Skoby MJ, Söhngen Y, Song Y, Srivastava B, Stanislaus TDS, Stewart DJ, Strikhanov M, Su Y, Sun C, Sun X, Sun Y, Sun Y, Surrow B, Svirida DN, Sweger ZW, Tamis AC, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Tlusty D, Todoroki T, Tokarev MV, Trentalange S, Tribedy P, Tsai OD, Tsang CY, Tu Z, Tyler J, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vasiliev AN, Verkest V, Videbæk F, Vokal S, Voloshin SA, Wang G, Wang JS, Wang J, Wang K, Wang X, Wang Y, Wang Y, Wang Y, Wang Z, Webb JC, Weidenkaff PC, Westfall GD, Wieman H, Wilks G, Wissink SW, Wu J, Wu J, Wu X, Wu X, Xi B, Xiao ZG, Xie G, Xie W, Xu H, Xu N, Xu QH, Xu Y, Xu Y, Xu Z, Xu Z, Yan G, Yan Z, Yang C, Yang Q, Yang S, Yang Y, Ye Z, Ye Z, Yi L, Yu Y, Zha W, Zhang C, Zhang D, Zhang J, Zhang S, Zhang W, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang ZJ, Zhang Z, Zhang Z, Zhao F, Zhao J, Zhao M, Zhou S, Zhou Y, Zhu X, Zurek M, Zyzak M. Imaging shapes of atomic nuclei in high-energy nuclear collisions. Nature 2024; 635:67-72. [PMID: 39506156 PMCID: PMC11541211 DOI: 10.1038/s41586-024-08097-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 09/23/2024] [Indexed: 11/08/2024]
Abstract
Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes1-3, traditionally explored using non-invasive spectroscopic techniques at low energies4,5. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors6,7. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.
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Zheng H, Zhao D, Gu M, Wang QH, Li CH, Li X, Li J, Che NY, Hu Y. [Clinical characteristics and prognostic factors of epidermal growth factor receptor-mutated non-small cell lung cancer transformed into small-cell lung cancer after treatment]. ZHONGHUA YI XUE ZA ZHI 2024; 104:3751-3756. [PMID: 39463369 DOI: 10.3760/cma.j.cn112137-20240422-00952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Objective: To analyze the clinical characteristics and prognostic factors of non-small cell lung cancer (NSCLC) patients with sensitive epidermal growth factor receptor (EGFR) mutations who developed small cell lung cancer (SCLC) transformation after treatment with EGFR tyrosine kinase inhibitors (TKI). Methods: We conducted a retrospective collection of clinical data for 21 patients with advanced EGFR mutant NSCLC who developed SCLC transformation after EGFR-TKI treatment at Beijing Chest Hospital, Capital Medical University from January 2015 to December 2021. The clinical characteristics were summarized and the prognosis analysis was conducted. Patients were followed up until February 2024. The efficacy was evaluated using Solid Tumor Response Evaluation Criteria, and survival curves were plotted using the Kaplan-Meier method, and the log-rank test was used to compare the differences in survival time (OS) between limited stage and extensive stage in transformed SCLC patients. Cox proportional hazards model was used to analyze the influencing factors of survival after SCLC transformation. Results: Among the 21 patients, there were 5 males and 16 females, with an age range of 33-74 years old [(58.9±2.6) years old]. All 21 patients were adenocarcinoma with sensitive EGFR mutations. There were 18 cases (85.7%) with EGFR gene 19del mutation, including 1 case of 19del+anaplastic lymphoma kinase (ALK) mutation, and 3 cases of L858R mutation. Among the transformed SCLC, there were 11 cases of pure SCLC and 10 cases of mixed SCLC (coexisting of adenocarcinoma and small cell carcinoma components). The median time from diagnosis of NSCLC to SCLC transformation was 12.0 months (95%CI: 7.6-16.3 months). Among the 21 cases of SCLC transformation, there were 13 cases with the extensive stage and 8 cases with the limited stage. Among them, 16 patients received systemic chemotherapy based on etoposide, of which 13 cases could be evaluated for efficacy, 11 cases could be calculated for PFS. Five cases had partial remission, 5 cases were stable, 3 cases had disease progression, and 3 cases cloud not be evaluated. The median progression free survival time (PFS) was 4.8 months (95%CI: 2.8-6.8 months). The median survival time (OS) after SCLC transformation in 21 patients was 10.6 months (95%CI: 7.0-14.2 months), with a median OS of 8.8 months (95%CI: 6.3-11.4 months) for patients with the extensive stage and 27.5 months (95%CI: 9.6-34.4 months) for patients with the limited stage, with statistically significant differences (P=0.002). Cox proportional hazards model analysis showed that the limited stage after SCLC transformation was a protective factor for OS (HR=0.32, 95%CI: 0.12-0.73, P=0.010). The median OS of 21 patients from the diagnosis of lung cancer was 24.9 months (95%CI: 13.0-36.7 months). Conclusions: NSCLC patients with SCLC transformation are all adenocarcinomas, and the proportion of EGFR19del mutations is relatively high. After SCLC transformation, the standard chemotherapy regimen for SCLC is generally used for treatment. The OS after SCLC transformation is related to the stage, and the prognosis is better in the limited stage.
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Ablikim M, Achasov MN, Adlarson P, Afedulidis O, Ai XC, Aliberti R, Amoroso A, 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, Chai XY, Chang JF, Che GR, Che YZ, Chelkov G, Chen C, Chen CH, Chen C, Chen G, Chen HS, Chen HY, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Chen ZY, Choi SK, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng CQ, 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 YY, Duan ZH, Egorov P, Fan YH, Fang J, Fang J, Fang SS, Fang WX, Fang Y, Fang YQ, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Feng YT, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao XB, Gao YN, Gao Y, Garbolino S, Garzia I, Ge L, 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, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Gutierrez J, Han KL, Han TT, Hanisch F, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, 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 SL, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang YS, Hussain T, Hölzken F, Hüsken N, In der Wiesche N, Jackson J, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji W, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang D, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao JK, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, 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, Kui X, Kumar N, Kupsc A, Kühn W, Lane JJ, Lavezzi L, Lei TT, Lei ZH, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li K, Li KL, Li LJ, Li LK, Li L, Li MH, Li PR, Li QM, Li QX, Li R, Li SX, Li T, Li WD, Li WG, Li X, Li XH, Li XL, Li XY, Li XZ, Li YG, Li ZJ, Li ZY, Liang C, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao YP, Libby J, Limphirat A, Lin CC, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu F, Liu FH, Liu F, Liu GM, Liu H, Liu HB, Liu HH, Liu HM, 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 X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZD, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo JR, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma LR, Ma MM, Ma QM, Ma RQ, Ma T, Ma XT, Ma XY, Ma YM, Maas FE, MacKay I, Maggiora M, Malde S, 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, Nie LS, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, 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, Qiao XK, Qin JJ, Qin LQ, Qin LY, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu ZH, Redmer CF, Ren KJ, Rivetti A, Rolo M, Rong G, Rosner C, Ruan MQ, Ruan SN, Salone N, Sarantsev A, Schelhaas Y, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shang ZJ, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi H, Shi HC, Shi JL, Shi JY, Shi QQ, Shi SY, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su SS, 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 ZQ, Sun ZT, Tang CJ, Tang GY, Tang J, Tang M, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, Wang DY, Wang F, Wang HJ, Wang HP, Wang JJ, Wang JP, Wang K, Wang LL, 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 XN, 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 DH, Weidner F, Wen SP, Wen YR, 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 BH, 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 M, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu Y, Xu YC, 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 YF, Yang YX, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, Yin J, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu MC, Yu T, Yu XD, Yu YC, Yuan CZ, Yuan J, Yuan J, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HR, Zhang HY, Zhang J, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JS, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang L, Zhang P, Zhang QY, Zhang RY, Zhang SH, Zhang S, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang YM, Zhang Y, Zhang ZD, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhang ZZ, Zhao G, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao N, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng BM, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou JY, Zhou LP, Zhou S, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhou ZC, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu KS, Zhu L, Zhu LX, Zhu SH, Zhu TJ, Zhu WD, Zhu YC, Zhu ZA, Zou JH, Zu J. Study of the Decay and Production Properties of D_{s1}(2536) and D_{s2}^{*}(2573). PHYSICAL REVIEW LETTERS 2024; 133:171903. [PMID: 39530816 DOI: 10.1103/physrevlett.133.171903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 08/28/2024] [Accepted: 09/27/2024] [Indexed: 11/16/2024]
Abstract
The e^{+}e^{-}→D_{s}^{+}D_{s1}(2536)^{-} and e^{+}e^{-}→D_{s}^{+}D_{s2}^{*}(2573)^{-} processes are studied using data samples collected with the BESIII detector at center-of-mass energies from 4.530 to 4.946 GeV. The absolute branching fractions of D_{s1}(2536)^{-}→D[over ¯]^{*0}K^{-} and D_{s2}^{*}(2573)^{-}→D[over ¯]^{0}K^{-} are measured for the first time to be (35.9±4.8±3.5)% and (37.4±3.1±4.6)%, respectively. The e^{+}e^{-}→D_{s}^{+}D_{s1}(2536)^{-} and e^{+}e^{-}→D_{s}^{+}D_{s2}^{*}(2573)^{-} cross sections are measured, and a resonant structure at around 4.6 GeV with a width of 50 MeV is observed in both processes with a statistical significance of 7.2σ and 15σ, respectively. The state is observed for the first time in e^{+}e^{-}→D_{s}^{+}D_{s2}^{*}(2573)^{-} and could be the Y(4626) found by the Belle oration in the D_{s}^{+}D_{s1}(2536)^{-} final state, since they have similar masses and widths. There is also evidence for a structure at around 4.75 GeV in both processes.
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Zeng X, Hu Y, Qiao S, Cao X, Dai Y, Wu F, Wei Z. ADORA3 activation promotes goblet cell differentiation via enhancing HMGCS2-mediated ketogenesis in ulcerative colitis. Int Immunopharmacol 2024; 140:112729. [PMID: 39098229 DOI: 10.1016/j.intimp.2024.112729] [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: 05/15/2024] [Revised: 06/28/2024] [Accepted: 07/17/2024] [Indexed: 08/06/2024]
Abstract
ADORA3 is mainly expressed in intestinal tract, and has the potential to promote the expression of mucin 2 (MUC2), the function-related factor of goblet cells, under asthma conditions. This study aims to confirm the induction and mechanisms of ADORA3 activation on goblet cells in ulcerative colitis (UC). A significant decrease in ADORA3 expression was found in mucosal biopsies from UC patients and in the colons of colitis mice. This reduction correlated negatively with disease severity and positively with goblet cell number. ADORA3 activation mitigated dextran sulfate sodium (DSS)-induced colitis and facilitated ATOH1-mediated goblet cell differentiation in both in vivo and in vitro. Metabolomics analysis unveiled that ADORA3 activation bolstered ketogenesis, leading to elevated levels of the metabolite BHB. Subsequently, BHB heightened the activity of HDAC1/2, augmenting histone acetylation at the H3K9ac site within the promoter region of the ATOH1 gene. Furthermore, the reason for ADORA3 activation to enhance ketogenesis was attributed to controlling the competitive binding among β-arrestin2, SHP1 and PPARγ. This results in the non-ligand-dependent activation of PPARγ, thereby promoting the transcription of HMGCS2. The exact mechanisms by which ADORA3 promoted goblet cell differentiation and alleviated UC were elucidated using MRS1191 and shHMGCS2 plasmid. Collectively, ADORA3 activation promoted goblet cell differentiation and alleviated UC by enhancing ketogenesis via the "BHB-HDAC1/2-H3K9ac" pathway.
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Ablikim M, Achasov MN, Adlarson P, Albrecht M, Aliberti R, Amoroso A, An MR, An Q, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Batozskaya V, Becker D, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bianco E, Bloms J, Bortone A, Boyko I, Briere RA, Brueggemann A, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Che GR, Chelkov G, Chen C, Chen C, Chen G, Chen HS, Chen ML, Chen SJ, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen ZJ, Cheng WS, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Duan ZH, Egorov P, Fan YL, Fang J, Fang SS, Fang WX, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Fischer K, Fritsch M, Fritzsch C, Fu CD, Gao H, Gao YN, Gao Y, Garbolino S, Garzia I, Ge PT, Ge ZW, Geng C, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han WY, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, Heinz CH, Heng YK, Herold C, Hou GY, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang Z, Hussain T, Hüsken N, Imoehl W, Irshad M, Jackson J, Jaeger S, Janchiv S, Jang E, Jeong JH, Ji Q, Ji QP, Ji XB, Ji XL, Ji YY, Jia ZK, Jiang PC, Jiang SS, Jiang XS, Jiang Y, Jiao JB, Jiao Z, Jin S, Jin Y, Jing MQ, Johansson T, Kabana S, Kalantar-Nayestanaki N, Kang XL, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiuchi R, Kliemt R, Koch L, Kolcu OB, Kopf B, Kuemmel M, Kuessner M, Kupsc A, Kühn W, Lane JJ, Lange JS, Larin P, Lavania A, Lavezzi L, Lei TT, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li H, Li HB, Li HJ, Li HN, Li JQ, Li JS, Li JW, Li K, Li LJ, Li LK, Li L, Li MH, Li PR, Li SX, Li SY, Li T, Li WD, Li WG, Li XH, Li XL, Li X, Li YG, Li ZX, Li ZY, Liang C, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Lin CX, Lin DX, Lin T, Liu BJ, Liu C, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu GM, Liu H, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JL, Liu JY, Liu K, Liu KY, Liu K, Liu L, Liu L, Liu MH, Liu PL, Liu Q, Liu SB, Liu T, Liu WK, Liu WM, Liu X, Liu Y, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XY, Ma Y, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Pei YP, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Plura S, Pogodin S, Prasad V, Qi FZ, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qian Z, Qiao CF, Qin JJ, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Extracting the femtometer structure of strange baryons using the vacuum polarization effect. Nat Commun 2024; 15:8812. [PMID: 39394218 PMCID: PMC11470094 DOI: 10.1038/s41467-024-51802-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 08/19/2024] [Indexed: 10/13/2024] Open
Abstract
One of the fundamental goals of particle physics is to gain a microscopic understanding of the strong interaction. Electromagnetic form factors quantify the structure of hadrons in terms of charge and magnetization distributions. While the nucleon structure has been investigated extensively, data on hyperons are still scarce. It has recently been demonstrated that electron-positron annihilations into hyperon-antihyperon pairs provide a powerful tool to investigate their inner structure. We present a method useful for hyperon-antihyperon pairs of different types which exploits the cross section enhancement due to the effect of vacuum polarization at the J/ψ resonance. Using the 10 billion J/ψ events collected with the BESIII detector, this allows a precise determination of the hyperon structure function. The result is essentially a precise snapshot of theΛ ¯ Σ 0 ( Λ Σ ¯ 0 ) transition process, encoded in the transition form factor ratio and phase. Their values are measured to be R = 0.860 ± 0.029(stat.) ± 0.015(syst.), Δ Φ Λ ¯ Σ 0 = ( 1.011 ± 0.094 ( stat. ) ± 0.010 ( syst. ) ) r a d and Δ Φ Λ Σ ¯ 0 = ( 2.128 ± 0.094 ( stat. ) ± 0.010 ( syst. ) ) r a d . Furthermore, charge-parity (CP) breaking is investigated in this reaction and found to be consistent with CP symmetry.
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Grants
- The BESIII collaboration thanks the staff of BEPCII and the IHEP computing center for their strong support. This work is supported in part by National Key R&D Program of China under Contracts Nos. 2020YFA0406300, 2020YFA0406400; National Natural Science Foundation of China (NSFC) under Contracts Nos. 11635010, 11735014, 11835012, 11875115, 11935015, 11935016, 11935018, 11961141012, 12022510, 12025502, 12035009, 12035013, 12075250, 12165022, 12192260, 12192261, 12192262, 12192263, 12192264, 12192265, 12225509; the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; Joint Large-Scale Scientific Facility Funds of the NSFC and CAS under Contract No. U1832207; the CAS Center for Excellence in Particle Physics (CCEPP); 100 Talents Program of CAS; The Institute of Nuclear and Particle Physics (INPAC) and Shanghai Key Laboratory for Particle Physics and Cosmology; Yunnan Fundamental Research Project under Contract No. 202301AT070162; ERC under Contract No. 758462; European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement under Contract No. 894790; German Research Foundation DFG under Contracts Nos. 443159800, 455635585, Collaborative Research Center CRC 1044, FOR5327, GRK 2149; Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey under Contract No. DPT2006K-120470; National Science and Technology fund; National Science Research and Innovation Fund (NSRF) via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation under Contract No. B16F640076; Olle Engkvist Foundation under Contract No. 200-0605; STFC (United Kingdom); Suranaree University of Technology (SUT), Thailand Science Research and Innovation (TSRI), and National Science Research and Innovation Fund (NSRF) under Contract No. 160355; Polish National Science Centre under Contract 2019/35/O/ST2/02907; The Royal Society, UK under Contracts Nos. DH140054, DH160214; The Knut and Alice Wallenberg Foundation (Sweden); The Swedish Research Council; The Swedish Foundation for International Cooperation in Research and Higher Education (STINT); U. S. Department of Energy under Contract No. DE-FG02-05ER41374.
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Hu Y, Li Q, Shi X, Yan J, Chen Y. Domain knowledge-enhanced multi-spatial multi-temporal PM 2.5 forecasting with integrated monitoring and reanalysis data. ENVIRONMENT INTERNATIONAL 2024; 192:108997. [PMID: 39293234 DOI: 10.1016/j.envint.2024.108997] [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: 02/17/2024] [Revised: 07/31/2024] [Accepted: 09/02/2024] [Indexed: 09/20/2024]
Abstract
Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize multi-scale information, both spatially and temporally. There is a lack of integration between individual monitoring stations and city-wide scales. Temporally, the periodic nature of air quality variations is often overlooked or inadequately considered. To overcome these limitations, we conduct a thorough analysis of the data and tasks, integrating spatio-temporal multi-scale domain knowledge. We present a novel Multi-spatial Multi-temporal air quality forecasting method based on Graph Convolutional Networks and Gated Recurrent Units (M2G2), bridging the gap in air quality forecasting across spatial and temporal scales. The proposed framework consists of two modules: Multi-scale Spatial GCN (MS-GCN) for spatial information fusion and Multi-scale Temporal GRU (MT-GRU) for temporal information integration. In the spatial dimension, the MS-GCN module employs a bidirectional learnable structure and a residual structure, enabling comprehensive information exchange between individual monitoring stations and the city-scale graph. Regarding the temporal dimension, the MT-GRU module adaptively combines information from different temporal scales through parallel hidden states. Leveraging meteorological indicators and four air quality indicators, we present comprehensive comparative analyses and ablation experiments, showcasing the higher accuracy of M2G2 in comparison to nine currently available advanced approaches across all aspects. The improvements of M2G2 over the second-best method on RMSE of 72-h future predictions are as follows: PM2.5: 6%∼10%; PM10: 5%∼7%; NO2: 5%∼16%; O3: 6%∼9%. Furthermore, we demonstrate the effectiveness of each module of M2G2 by ablation study. We conduct a sensitivity analysis of air quality and meteorological data, finding that the introduction of O3 adversely impacts the prediction accuracy of PM2.5.
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Lu S, Wang J, Yu Y, Yu X, Hu Y, Ma Z, Li X, He W, Bao Y, Wang M. Tislelizumab plus chemotherapy as first-line treatment of locally advanced or metastatic nonsquamous non-small-cell lung cancer (final analysis of RATIONALE-304: a randomized phase III trial). ESMO Open 2024; 9:103728. [PMID: 39461773 PMCID: PMC11549519 DOI: 10.1016/j.esmoop.2024.103728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 08/14/2024] [Accepted: 08/27/2024] [Indexed: 10/29/2024] Open
Abstract
BACKGROUND The purpose of this study was to report an updated, final analysis with longer follow-up for the open-label phase III RATIONALE-304 study of first-line tislelizumab plus chemotherapy versus chemotherapy alone for advanced nonsquamous non-small-cell lung cancer (nsq-NSCLC). MATERIALS AND METHODS Patients with histologically confirmed stage IIIB/IV nsq-NSCLC were randomized (2 : 1) to 4-6 cycles of tislelizumab plus platinum-based chemotherapy and pemetrexed every 3 weeks, followed by maintenance tislelizumab and pemetrexed, or platinum-based chemotherapy and pemetrexed alone every 3 weeks followed by maintenance pemetrexed. The primary endpoint was independent review committee (IRC)-assessed progression-free survival (PFSIRC). Overall survival (OS), safety, and tolerability were secondary endpoints. RESULTS Overall, 334 patients were randomized (tislelizumab plus chemotherapy: n = 223; chemotherapy: n = 111). At final analysis (median follow-up 16.1 months), safety/tolerability profiles in both arms were consistent with the interim analysis. Tislelizumab plus chemotherapy continued to demonstrate prolongation of PFSIRC versus chemotherapy alone {stratified hazard ratio (HR) 0.63 [95% confidence interval (CI) 0.47-0.86]; median PFSIRC 9.8 months (95% CI 8.9-11.7 months) versus 7.6 months (95% CI 5.6-8.0 months), respectively}. OS stratified HR for tislelizumab plus chemotherapy versus chemotherapy was 0.90 (95% CI 0.63-1.28), with median OS of 21.4 months (95% CI 17.7 months-not estimable) versus 21.3 months (95% CI 15.6 months-not estimable), respectively. At a subsequent ad hoc analysis (median follow-up 19.3 months), OS HR between arms was 0.85 (95% CI 0.63-1.14); when adjusted for crossover using the two-stage method, the OS HR was 0.68 (95% CI 0.48-0.96). CONCLUSIONS After longer follow-up, first-line tislelizumab plus chemotherapy continued to demonstrate a manageable safety profile and a favorable PFS benefit over chemotherapy alone in patients with advanced/metastatic nsq-NSCLC.
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You R, Liu Y, Deng X, Hu Y, Ouyang S, Chen L, Xiang W, He H. Variations in water use efficiency and carbon and nitrogen concentrations in red heart Chinese fir. PLANT BIOLOGY (STUTTGART, GERMANY) 2024; 26:1088-1097. [PMID: 39011596 DOI: 10.1111/plb.13694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 06/24/2024] [Indexed: 07/17/2024]
Abstract
Temperature can significantly (P < 0.05) affect plant growth by modifying water use strategies, which are determined by intrinsic water use efficiency (WUE i). Red Heart Chinese Fir (Cunninghamia lanceolata) is one of the most important ecological and economic plantation species in China. However, the C. lanceolata water use strategy in response to increased temperatures and uneven temporal distribution of precipitation during the growing season is rarely reported. In a 7-year-old C. lanceolata plantation, differences in WUEi and C and N concentrations in different organs were analysed by anova, and the δ13C stable isotope, C, and N concentrations in stems determined at different tree heights. Stepwise regression and variance inflation factor were used to remove autocorrelated factors, and structural equation modelling was then used to explore relationships between WUEi and climate and biological factors. WUEi differed significantly between leaf and branch at different standardized precipitation evapotranspiration indices (SPEI). WUEi and N concentration decreased with age. The highest WUEi in branches and leaves were 92.7 and 88.4 μmol·mol-1 in 2020 (SPEI = 0.00), respectively. δ13C increased with relative tree height but N concentration and C/N ratio were not affected. Air temperatures has increased in between 2014 and 2020. WUEi and N concentration decreased with increasing branch and leaf age, but C concentration increased. SPEI significantly positively affected WUEi (P < 0.05), and WUE i was significantly negatively related to C concentration, which is consistent with the trade-off between C and water.
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Wang J, Lu S, Yu X, Hu Y, Zhao J, Sun M, Yu Y, Hu C, Yang K, Song Y, Lin X, Liang L, Leaw S, Zheng W. Tislelizumab plus chemotherapy versus chemotherapy alone as first-line treatment for advanced squamous non-small-cell lung cancer: final analysis of the randomized, phase III RATIONALE-307 trial. ESMO Open 2024; 9:103727. [PMID: 39461775 PMCID: PMC11549530 DOI: 10.1016/j.esmoop.2024.103727] [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: 03/18/2024] [Revised: 08/14/2024] [Accepted: 08/27/2024] [Indexed: 10/29/2024] Open
Abstract
PURPOSE First-line tislelizumab plus chemotherapy significantly improved progression-free survival (PFS) versus chemotherapy alone in advanced squamous non-small-cell lung cancer (sq-NSCLC) at the interim analysis of the phase III RATIONALE-307 trial. We present the final analysis of this trial. PATIENTS AND METHODS Patients with treatment-naive, stage IIIB/IV, sq-NSCLC were randomized (1 : 1: 1) to 21-day cycles of i.v.: tislelizumab plus paclitaxel and carboplatin (arm A); tislelizumab plus nab-paclitaxel and carboplatin (arm B); or paclitaxel and carboplatin (arm C). The primary endpoint was independent review committee-assessed PFS; overall survival was a secondary endpoint. RESULTS In total, 360 patients were randomized; 355 received treatment. At the final analysis (median study follow-up: 16.7 months), tislelizumab plus chemotherapy had a manageable safety profile, consistent with that at the interim analysis. Improvement in PFS was maintained for arms A and B versus C {hazard ratio (HR) 0.45 [95% confidence interval (CI) 0.33-0.62] and 0.43 (95% CI 0.31-0.60), respectively}. Overall survival HRs for arms A and B versus C were 0.68 (95% CI 0.46-1.01) and 0.75 (95% CI 0.50-1.12), respectively. CONCLUSIONS The RATIONALE-307 final analysis demonstrated superior clinical benefit with addition of tislelizumab to chemotherapy, and a manageable safety profile, as first-line treatment of advanced sq-NSCLC.
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Ablikim M, Achasov MN, Adlarson P, Afedulidis O, Ai XC, Aliberti R, Amoroso A, 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 CH, 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, Chen ZY, Choi SK, Chu X, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng CQ, 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 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, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, 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, Huang ZY, Hussain T, Hölzken F, Hüsken N, In der Wiesche N, Irshad M, Jackson J, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji W, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang D, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao JK, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, 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, Kui X, 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 K, Li LJ, Li LK, Li L, Li MH, Li PR, Li QM, Li QX, Li R, Li SX, Li T, Li WD, Li WG, Li X, 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 X, Liu XY, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZD, 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 XT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Miao H, Min TJ, Mitchell RE, Mo XH, 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, Qu ZH, 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 SY, 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 ZQ, Sun ZT, Tang CJ, Tang GY, Tang J, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, 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 XN, 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, Wen YR, 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 BH, 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 J, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, 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 L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang YM, 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 JY, 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. Search for Rare Decays of D_{s}^{+} to Final States π^{+}e^{+}e^{-}, ρ^{+}e^{+}e^{-}, π^{+}π^{0}e^{+}e^{-}, K^{+}π^{0}e^{+}e^{-}, and K_{S}^{0}π^{+}e^{+}e^{-}. PHYSICAL REVIEW LETTERS 2024; 133:121801. [PMID: 39373421 DOI: 10.1103/physrevlett.133.121801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/21/2024] [Indexed: 10/08/2024]
Abstract
Using 7.33 fb^{-1} of e^{+}e^{-} collision data collected by the BESIII detector at center-of-mass energies in the range of sqrt[s]=4.128-4.226 GeV, we search for the rare decays D_{s}^{+}→h^{+}(h^{0})e^{+}e^{-}, where h represents a kaon or pion. By requiring the e^{+}e^{-} invariant mass to be consistent with a ϕ(1020), 0.98
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Ablikim M, Achasov MN, Adlarson P, Afedulidis O, Ai XC, Aliberti R, Amoroso A, 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, Che GR, Chelkov G, Chen C, Chen CH, Chen C, Chen G, Chen HS, Chen HY, Chen ML, Chen SJ, Chen SL, Chen SM, Chen T, Chen XR, Chen XT, Chen YB, Chen YQ, Chen ZJ, Chen ZY, Choi SK, Cibinetto G, Cossio F, Cui JJ, Dai HL, Dai JP, Dbeyssi A, de Boer RE, Dedovich D, Deng CQ, 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 YY, Duan ZH, Egorov P, Fan YH, Fang J, Fang J, Fang SS, Fang WX, Fang Y, Fang YQ, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Feng JH, Feng YT, Fritsch M, Fu CD, Fu JL, Fu YW, Gao H, Gao XB, Gao YN, Gao Y, Garbolino S, Garzia I, Ge L, 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, Guo AQ, Guo LB, Guo MJ, Guo RP, Guo YP, Guskov A, Gutierrez J, Han KL, Han TT, Hanisch F, Hao XQ, Harris FA, He KK, He KL, Heinsius FH, 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 SL, Hu T, Hu Y, Hu ZM, Huang GS, Huang KX, Huang LQ, Huang XT, Huang YP, Huang YS, Hussain T, Hölzken F, Hüsken N, In der Wiesche N, Jackson J, Janchiv S, Jeong JH, Ji Q, Ji QP, Ji W, Ji XB, Ji XL, Ji YY, Jia XQ, Jia ZK, Jiang D, Jiang HB, Jiang PC, Jiang SS, Jiang TJ, Jiang XS, Jiang Y, Jiao JB, Jiao JK, Jiao Z, Jin S, Jin Y, Jing MQ, Jing XM, Johansson T, 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, Kui X, Kumar N, Kupsc A, Kühn W, Lane JJ, Lavezzi L, Lei TT, Lei ZH, Lellmann M, Lenz T, Li C, Li C, Li CH, Li C, Li DM, Li F, Li G, Li HB, Li HJ, Li HN, Li H, Li JR, Li JS, Li K, Li KL, Li LJ, Li LK, Li L, Li MH, Li PR, Li QM, Li QX, Li R, Li SX, Li T, Li WD, Li WG, Li X, Li XH, Li XL, Li XY, Li XZ, Li YG, Li ZJ, Li ZY, Liang C, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao YP, Libby J, Limphirat A, Lin CC, Lin DX, Lin T, Liu BJ, Liu BX, Liu C, Liu CX, Liu F, Liu FH, Liu F, Liu GM, Liu H, Liu HB, Liu HH, Liu HM, 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 X, Liu Y, Liu Y, Liu YB, Liu ZA, Liu ZD, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JG, Lu XL, Lu Y, Lu YP, Lu ZH, Luo CL, Luo JR, Luo MX, Luo T, Luo XL, Lyu XR, Lyu YF, Ma FC, Ma H, Ma HL, Ma JL, Ma LL, Ma LR, Ma MM, Ma QM, Ma RQ, Ma T, Ma XT, Ma XY, Ma Y, Ma YM, Maas FE, Maggiora M, Malde S, Malik QA, 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, Nie LS, Nikolaev IB, Ning Z, Nisar S, Niu QL, Niu WD, Niu Y, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, 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, Qiao XK, Qin JJ, Qin LQ, Qin LY, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu ZH, 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, Shang ZJ, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi H, Shi HC, Shi JL, Shi JY, Shi QQ, Shi SY, Shi X, Song JJ, Song TZ, Song WM, Song YJ, Song YX, Sosio S, Spataro S, Stieler F, Su SS, 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 ZQ, Sun ZT, Tang CJ, Tang GY, Tang J, Tang M, Tang YA, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Tian ZF, Uman I, Wan Y, Wang SJ, Wang B, Wang BL, Wang B, Wang DY, Wang F, Wang HJ, Wang JJ, Wang JP, Wang K, Wang LL, 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 XN, 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 DH, Weidner F, Wen SP, Wen YR, 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 BH, 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 M, Xu QJ, Xu QN, Xu W, Xu WL, Xu XP, Xu Y, Xu YC, 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 YF, Yang YX, Yang ZW, Yao ZP, Ye M, Ye MH, Yin JH, Yin J, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu MC, Yu T, Yu XD, Yu YC, Yuan CZ, Yuan J, Yuan J, Yuan L, Yuan SC, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng SH, Zeng X, Zeng Y, Zeng YJ, Zeng YJ, Zhai XY, Zhai YC, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang H, Zhang HC, Zhang HH, Zhang HH, Zhang HQ, Zhang HR, Zhang HY, Zhang J, Zhang J, Zhang JJ, Zhang JL, Zhang JQ, Zhang JS, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang LM, Zhang L, Zhang P, Zhang QY, Zhang RY, Zhang SH, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang Y, Zhang YT, Zhang YH, Zhang YM, Zhang Y, Zhang ZD, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhang ZZ, Zhao G, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao N, Zhao RP, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng BM, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong X, Zhou H, Zhou JY, Zhou LP, Zhou S, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhou ZC, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu KS, Zhu L, Zhu LX, Zhu SH, Zhu TJ, Zhu WD, Zhu YC, Zhu ZA, Zou JH, Zu J. Strong and Weak CP Tests in Sequential Decays of Polarized Σ^{0} Hyperons. PHYSICAL REVIEW LETTERS 2024; 133:101902. [PMID: 39303247 DOI: 10.1103/physrevlett.133.101902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/16/2024] [Accepted: 08/07/2024] [Indexed: 09/22/2024]
Abstract
The J/ψ, ψ(3686)→Σ^{0}Σ[over ¯]^{0} processes and subsequent decays are studied using the world's largest J/ψ and ψ(3686) data samples collected with the BESIII detector. The parity-violating decay parameters of the decays Σ^{0}→Λγ and Σ[over ¯]^{0}→Λ[over ¯]γ, α_{Σ^{0}}=-0.0017±0.0021±0.0018 and α[over ¯]_{Σ^{0}}=0.0021±0.0020±0.0022, are measured for the first time. The strong CP symmetry is tested in the decays of the Σ^{0} hyperons for the first time by measuring the asymmetry A_{CP}^{Σ}=α_{Σ^{0}}+α[over ¯]_{Σ^{0}}=(0.4±2.9±1.3)×10^{-3}. The weak CP test is performed in the subsequent decays of their daughter particles Λ and Λ[over ¯]. Also for the first time, the transverse polarizations of the Σ^{0} hyperons in J/ψ and ψ(3686) decays are observed with opposite directions, and the ratios between the S-wave and D-wave contributions of the J/ψ, ψ(3686)→Σ^{0}Σ[over ¯]^{0} decays are obtained. These results are crucial to understand the decay dynamics of the charmonium states and the production mechanism of the Σ^{0}-Σ[over ¯]^{0} pairs.
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Ranti D, Yu H, Wang YA, Bieber C, Strandgaard T, Salomé B, Houghton S, Kim J, Ravichandran H, Okulate I, Merritt E, Bang S, Demetriou A, Li Z, Lindskrog SV, Ruan DF, Daza J, Rai R, Hegewisch-Solloa E, Mace EM, Fernandez-Rodriguez R, Izadmehr S, Doherty G, Narasimhan A, Farkas AM, Cruz-Encarnacion P, Shroff S, Patel F, Tran M, Park SJ, Qi J, Patel M, Geanon D, Kelly G, de Real RM, Lee B, Nie K, Miake-Iye S, Angeliadis K, Radkevich E, Thin TH, Garcia-Barros M, Brown H, Martin B, Mateo A, Soto A, Sussman R, Shiwlani S, Francisco-Simon S, Beaumont KG, Hu Y, Wang YC, Wang L, Sebra RP, Smith S, Skobe M, Clancy-Thompson E, Palmer D, Hammond S, Hopkins BD, Wiklund P, Zhu J, Bravo-Cordero JJ, Brody R, Hopkins B, Chen Z, Kim-Schulze S, Dyrskjøt L, Elemento O, Tocheva A, Song WM, Bhardwaj N, Galsky MD, Sfakianos JP, Horowitz A. HLA-E and NKG2A Mediate Resistance to M. bovis BCG Immunotherapy in Non-Muscle-Invasive Bladder Cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.02.610816. [PMID: 39282294 PMCID: PMC11398371 DOI: 10.1101/2024.09.02.610816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Mycobacterium bovis Bacillus Calmette-Guerin (BCG) is the primary treatment for non-muscle-invasive bladder cancer (NMIBC), known to stimulate inflammatory cytokines, notably interferon (IFN)-γ. We observed that prolonged IFN-γ exposure fosters adaptive resistance in recurrent tumors, aiding immune evasion and tumor proliferation. We identify HLA-E and NKG2A, part of a novel NK and T cell checkpoint pathway, as key mediators of resistance in BCG-unresponsive NMIBC. IFN-γ enhances HLA-E and PD-L1 expression in recurrent tumors, with an enrichment of intra-tumoral NKG2A-expressing NK and CD8 T cells. CXCL9+ macrophages and dendritic cells and CXCL12-expressing stromal cells likely recruit CXCR3/CXCR4-expressing NK and T cells and CXCR7+ HLA-EHIGH tumor cells. NK and CD8 T cells remain functional within BCG-unresponsive tumors but are inhibited by HLA-E and PD-L1, providing a framework for combined NKG2A and PD-L1 blockade strategy for bladder-sparing treatment of BCG-unresponsive NMIBC.
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Hoang LN, Dinh LT, Tai S, Nguyen D, Pooh RK, Shiozaki A, Zheng M, Hu Y, Ma R, Kusuma RA, Yapan P, Gosavi D, Kaneko M, Luewan S, Chang T, Chaiyasit N, Nanthakomon T, Liu H, Shaw S, Leung W, Mahdy ZA, Aguilar AS, Leung H, Lee N, Lau S, Wah Y, Lu X, Sahota DS, Chong K, Poon LC. Abstracts of the 34th World Congress on Ultrasound in Obstetrics and Gynecology, 15-18 September 2024, Budapest, Hungary. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 64 Suppl 1:33-34. [PMID: 39249221 DOI: 10.1002/uog.27809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/10/2024]
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Chen Y, Papastefanou I, Hoang LN, Dinh LT, Tai S, Nguyen D, Pooh RK, Shiozaki A, Zheng M, Hu Y, Li B, Kusuma RA, Yapan P, Choolani M, Tokunaka M, Luewan S, Chang T, Chaiyasit N, Nanthakomon T, Liu H, Shaw S, Leung W, Mahdy ZA, Aguilar AS, Leung H, Lee N, Lau S, Lu X, Sahota DS, Chong K, Poon LC. Abstracts of the 34th World Congress on Ultrasound in Obstetrics and Gynecology, 15-18 September 2024, Budapest, Hungary. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 64 Suppl 1:35. [PMID: 39249193 DOI: 10.1002/uog.27813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/10/2024]
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Huang Y, Chen T, Hu Y, Li Z. Muscular MRI and magnetic resonance neurography in spinal muscular atrophy. Clin Radiol 2024; 79:673-680. [PMID: 38945793 DOI: 10.1016/j.crad.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 04/08/2024] [Accepted: 06/03/2024] [Indexed: 07/02/2024]
Abstract
Spinal muscular atrophy (SMA) is an autosomal recessive genetic disease caused by the degeneration of the α-motor neurons in the anterior horn of the spinal cord. SMA is clinically characterized by progressive and symmetrical muscle weakness and muscle atrophy and ends up with systemic multisystem abnormalities. Quantitative MRI (qMRI) has the advantages of non-invasiveness, objective sensitivity, and high reproducibility, and has important clinical value in evaluating the severity of neuromuscular diseases and monitoring the efficacy of treatment. This article summarizes the clinical use of muscular MRI and magnetic resonance neurography in assessing the progress of SMA.
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