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Statin, aspirin and metformin use and risk of hepatocellular carcinoma related outcomes following liver transplantation: A retrospective study

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World Journal of Transplantation 2024年第3期14卷 120-131页

作者： William Chung Kevin Wong Noel Ravindranayagam Lauren Tang Josephine Grace Darren Wong danny con Marie Sinclair Avik Majumdar Numan Kutaiba Samuel Hui Paul Gow Vijayaragavan Muralidharan Alexander Dobrovic Adam Testro Department of Gastroenterology Austin HealthHeidelberg 3084VictoriaAustralia Victorian Liver Transplant Unit Austin HealthHeidelberg 3084VictoriaAustralia Department of Radiology Austin HealthHeidelberg 3084VictoriaAustralia Department of Gastroenterology Monash HealthClayton 3168VictoriaAustralia Department of Surgery University of MelbourneAustin HealthHeidelberg 3048VictoriaAustralia Department of Surgery Beacon LaboratoryAustin PrecinctThe University of MelbourneAustin HospitalHeidelberg 3048VictoriaAustralia

BACKGROUND Liver transplantation(LT)is a potentially curative therapy for patients with hepatocellular carcinoma(HCC).HCC-recurrence following LT is associated with reduced *** is increasing interest in chemoprophylaxis to improve HCC-related outcomes *** To investigate whether there is any benefit for the use of drugs with proposed chemoprophylactic properties against HCC,and patient outcomes following *** This was a retrospective study of adult patients who received Deceased Donor LT for HCC from 2005-2022,from a single Australian *** use was defined as statin,aspirin or metformin therapy for≥29 days,within 24 months post-LT.A cox proportional-hazards model with time-dependent covariates was used for survival *** measures were the composite-endpoint of HCC-recurrence and all-cause mortality,HCC-recurrence and HCC-related *** analysis was performed to account for immortality time bias and statin *** Three hundred and five patients were included in this study,with 253(82.95%)males with a median age of 58.90 *** of liver disease were 150(49.18%)hepatitis C,73(23.93%)hepatitis B(HBV)and 33(10.82%)non-alcoholic fatty liver disease(NAFLD).56(18.36%)took statins,51(16.72%)aspirin and 50(16.39%)*** a median follow-up time of 59.90 months,34(11.15%)developed HCC-recurrence,48(15.74%)died,17(5.57%)from HCC-related ***,aspirin or metformin use was not associated with statistically significant differences in the composite endpoint of HCC-recurrence or all-cause mortality[hazard ratio(HR):1.16,95%CI:0.58-2.30;HR:1.21,95%CI:0.28-5.27;HR:0.61,95%CI:0.27-1.36],HCC-recurrence(HR:0.52,95%CI:0.20-1.35;HR:0.51,95%CI:0.14-1.93;HR 1.00,95%CI:0.37-2.72),or HCC-related mortality(HR:0.32,95%CI:0.033-3.09;HR:0.71,95%CI:0.14-3.73;HR:1.57,95%CI:0.61-4.04)*** dosing was not associated with statist-ically significant differences in HCC-related ***

关键词： Liver transplantation Hepatocellular carcinoma Transplant oncology Statins HMG-Co-A reductase Aspirin Metformin Mammalian target of rapamycin

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Deep learning vs conventional learning algorithms for clinical prediction in Crohn's disease: A proof-of-concept study

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World Journal of Gastroenterology 2021年第38期27卷 6476-6488页

作者： danny con Daniel R van Langenberg Abhinav Vasudevan Department of Gastroenterology and Hepatology Eastern HealthBox Hill 3128VictoriaAustralia Faculty of Medicine Nursing and Health SciencesMonash UniversityBox Hill 3128VictoriaAustralia

BACKGROUND Traditional methods of developing predictive models in inflammatory bowel diseases(IBD)rely on using statistical regression approaches to deriving clinical scores such as the Crohn's disease(CD)activity ***,traditional approaches are unable to take advantage of more complex data structures such as repeated *** learning methods have the potential ability to automatically find and learn complex,hidden relationships between predictive markers and outcomes,but their application to clinical prediction in CD and IBD has not been explored *** To determine and compare the utility of deep learning with conventional algorithms in predicting response to anti-tumor necrosis factor(anti-TNF)therapy in *** This was a retrospective single-center cohort study of all CD patients who commenced anti-TNF therapy(either adalimumab or infliximab)from January 1,2010 to December 31,*** was defined as a C-reactive protein(CRP)conventional statistical learning algorithm using multivariable logistic regression on baseline data only;(2)A deep learning algorithm using a feed-forward artificial neural network on baseline data only;and(3)A deep learning algorithm using a recurrent neural network on repeated *** performance was assessed using area under the receiver operator characteristic curve(AUC)after 10×repeated 5-fold *** A total of 146 patients were included(median age 36 years,48%male).concomitant therapy at anti-TNF commencement included thiopurines(68%),methotrexate(18%),corticosteroids(44%)and aminosalicylates(33%).After 12 mo,64%had CRPconventional learning algorithm selected the following baseline variables for the predictive model:Complex disease behavior,albumin,monocytes,lymphocytes,mean corpuscular hemoglobin concentration and gamma-glutamyl transferase,and had a cross-valid

关键词： Machine learning Artificial intelligence Precision medicine Personalized medicine Deep learning

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Effects of Two Isometric Strength Training Methods on Jump and Sprint Performances:A Randomized controlled Trial

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Journal of Science in Sport and Exercise 2021年第2期3卷 115-124页

作者： danny Lum Tiago M.Barbosa Ranald Joseph Govindasamy Balasekaran Sport Science and Sport Medicine Singapore Sport Institute3 Stadium DriveSingapore 397630Singapore Physical Education and Sports Science National Institute of EducationNanyang Technological UniversitySingaporeSingapore Polytechnic Institute of Braganca BragançaPortugal Research Centre in Sports Health and Human Development(CIDESD)Vila RealPortugal

Purpose Isometric strength training (IST) with rapid non-sustained contraction (RIST) is effective in improving the ability to generate force ***,the neuromuscular adaptation of IST with sustained contraction (SIST) and RIST is not ***,the aim of the study was to compare the neuromuscular adaptations of RIST with *** Thirty-three national floorball players (23.9 ± 3.1 years old;1.69± 0.08 m;64.6± 11.1 kg) were recruited for this ***-and post-test included countermovement jump (CMJ),30-m sprint (TT30),isometric squat at 90° (ISqT90) and 120° (ISqT120) knee *** were randomly assigned to either control (con) (n =9),RIST (n =12) or SIST (n =12)group and performed 12 sessions of intervention *** groups performed the same sets of exercises,but RIST and SIST had to perform ISqT with and without sustained contraction,*** Time × group effect for CMJ height (P =0.01,η2p=0.25),peak force (PF) (P =0.03,η2p =0.22) and rate of force development (RFD) (P =0.02,η2p =0.22) obtained from ISqT 120 were noted.A main effect for time was observed in CMJ height,PF obtained from ISqT90 and ISqT120,and RFD obtained from ISqT90 (P con *** SIST was more effective in improving strength and dynamic performance as compared to RIST,making it a viable training method to enhance dynamic performances.

关键词： Countermovement jump Isometric squat Peak force Rate of force development

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Metabolomic Profiling in Selaginella lepidophylla at Various Hydration States Provides New Insights into the Mechanistic Basis of Desiccation Tolerance

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Molecular Plant 2013年第2期6卷 369-385页

作者： Abou Yobi Bernard W.M. Wone Wenxin Xu danny C. Alexander Lining Guo John A. Ryals Melvin J. Oliver John C. Cushman Department of Biochemistry and Molecular Biology University of Nevada Reno NV 89557-0330 USA Department of Biological Sciences University of Nevada Reno NV 89557-0314 USA Metabolon Inc. 800 Capitola Drive Suite 1 Durham NC 27713 USA US Department of Agriculture-Agricultural Research Service Plant Genetic Research Unit University of Missouri Columbia MI 65211 USA

Selaginella lepidophylla is one of only a few species of spike mosses （Selaginellaceae） that have evolved des-iccation tolerance （DT） or the ability to ＇resurrect＇ from an air-dried state. In order to understand the metabolic basis of DT, S, lepidophylla was subjected to a five-stage, rehydration/dehydration cycle, then analyzed using non-biased, global metabolomics profiling technology based on GC/MS and UHLC/MS/MS2 platforms. A total of 251 metabolites including 167 named （66.5%） and 84 （33.4%） unnamed compounds were characterized. Only 42 （16.7%） and 74 （29.5%） of compounds showed significantly increased or decreased abundance, respectively, indicating that most compounds were produced con-stitutively, including highly abundant trehalose, sucrose, and glucose. Several glycolysis/gluconeogenesis and tricarboxylic acid （TCA） cycle intermediates showed increased abundance at 100% relative water content （RWC） and 50% RWC. Vanillate, a potent antioxidant, was also more abundant in the hydrated state. Many different sugar alcohols and sugar acids were more abundant in the hydrated state. These polyols likely decelerate the rate of water loss during the drying process as well as slow water absorption during rehydration, stabilize proteins, and scavenge reactive oxygen species （ROS）. In contrast, nitrogen-rich and y-glutamyl amino acids, citrulline, and nucleotide catabolism products （e.g. allantoin） were more abundant in the dry states, suggesting that these compounds might play important roles in nitrogen remobilization during rehydration or in ROS scavenging. UV-protective compounds such as 3-（3-hydroxyphenyl）propionate, apigenin, and naringenin, were more abundant in the dry states. Most lipids were produced constitutively, with the exception of choline phosphate, which was more abundant in dry states and likely plays a role in membrane hydration and stabilization. In contrast, several poly- unsaturated fatty acids were more abundant in the hydrated states, suggestin

关键词： abiotic/environmental stress mass spectrometry metabolomics oxidative/photooxidative stress desiccationtolerance Selaginella.

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