Results 261 to 270 of about 4,991,757 (343)

Comparative GMM and GQL logistic regression models on hierarchical data

, 2017
Bei Wang, Jeffrey R. Wilson
openalex   +2 more sources

Polystyrene Microplastics Exposure Aggravates Clear Cell Renal Cell Carcinoma Progression via the NF‐κB and TGF‐β Signaling Pathways

Advanced Science, EarlyView.
This research provides the first comprehensive evidence that PS‐MPs exacerbate ccRCC progression by activating the NF‐κB and TGF‐β pathways. These findings establish PS‐MPs as an environmental risk factor for ccRCC progression and identify the NF‐κB and TGF‐β signaling as potential therapeutic targets to mitigate the adverse effects of ‐PS‐MPs exposure.
Shiqi Ye, Jianfeng Xiang, Siqi Zhou, Qintao Ge, Aihetaimujiang Anwaier, Kun Chang, Gang Wei, Jiahe Lu, Xi Tian, Shuxuan Zhu, Yuchen Jiang, Wei Zhang, Tingting Cai, Moran Xu, Dingwei Ye, Danfeng Xu, Tao Wang, Hailiang Zhang, Wenhao Xu   +18 more
wiley   +1 more source

Research on Olympic medal prediction based on GA-BP and logistic regression model. [PDF]

F1000Res
Zhao S, Cao J, Lu K, Steve J.
europepmc   +1 more source

Macrophagic Sclerostin Loop2‐ApoER2 Interaction Required by Sclerostin for Cardiovascular Protective Action

Advanced Science, EarlyView.
Sclerostin loop2‐ApoER2 interaction in macrophages is required by sclerostin to suppress NF‐κB nuclear translocation and phosphorylation, to promote macrophage conversion into anti‐inflammatory subtypes in atherosclerotic aortas, as well as to prevent atherosclerosis and aortic aneurysm development in ApoE−/− mice. Abstract Therapeutic antibody against
Luyao Wang, Xiaohui Tao, Ning Zhang, Xin Yang, Hewen Jiang, Xiaofei Li, Shenghang Wang, Shijian Ding, Sifan Yu, Huarui Zhang, Yihao Zhang, Nanxi Li, Haitian Li, Zhanghao Li, Xiaoxin Wen, Meiheng Sun, Chuanxin Zhong, Jin Liu, Yuanyuan Yu, Xianghang Luo, Tao Zhang, Shu Zhang, Péter Ferdinandy, Yu Huang, Daqing Ma, Aiping Lu, Baoting Zhang, Ge Zhang   +27 more
wiley   +1 more source

Construction and efficacy evaluation of a model for early diagnosis of pediatric sepsis based on LASSO-logistic regression. [PDF]

Front Pediatr
Jiang Y, Wang W, Xu R, Wang C, Wang Z, Wang X, Zhang J, Wang Y.   +7 more
europepmc   +1 more source

Effectiveness of Pre‐Transplant Dual GLP‐1 Receptor Agonist and SGLT2 Inhibitor Therapy on All‐Cause Mortality in Organ Transplantation Candidates with Obesity and Type 2 Diabetes: a Target‐Trial Emulation

Advanced Science, EarlyView.
This target trial emulation in solid organ transplant candidates with obesity and type 2 diabetes evaluates whether pre‐transplant dual therapy with GLP‐1 receptor agonists plus SGLT2 inhibitors is associated with post‐transplant mortality and kidney graft outcomes compared with monotherapy or usual care, using multinational electronic health records ...
Yu‐Nan Huang, Min‐Yu Tsou, Pin‐Hung Li, Jo‐Ching Chen, Yen‐Liang Liu, Gideon Meyerowitz‐Katz, Tsung‐Hsun Tsai, Pen‐Hua Su   +7 more
wiley   +1 more source

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Advanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
wiley   +1 more source

Correlation between systemic inflammatory response index and post-stroke epilepsy based on multiple logistic regression analysis. [PDF]

Front Neurol
Hu YM, Huang H, Chen YT, Wang WJ, Zhang BH.   +4 more
europepmc   +1 more source

LANDSLIDE SUSCEPTIBILITY ASSESSMENT USING GEOGRAPHICAL INFORMATION SYSTEM BASED LOGISTIC REGRESSION SYSTEM BETWEEN ÇUBUK-KALECİK (ANKARA) AND ŞABANÖZÜ (ÇANKIRI) REGIONS

, 2017
Hasan Elmacı, Senem Tekin, Nail Ünsal
openalex   +2 more sources

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source