Results 231 to 240 of about 144,075 (292)

The impact of bias due to exponentiation in the estimation of hazard, risk, and odds ratios: an empirical investigation from 1,495,059 effect sizes from MEDLINE/PubMed abstracts. [PDF]

BMC Med Res Methodol
Košuta T, Heinze G, Kastrin A, Kosmidis I, Blagus R.   +4 more
europepmc   +1 more source

SiCmiR Atlas: Single‐Cell miRNA Landscape Reveals Hub‐miRNA and Network Signatures in Human Cancers

Advanced Science, EarlyView.
SiCmiR predicts mature miRNA activity at single‐cell resolution using only 977 landmark genes, enabling scalable reconstruction of miRNA landscapes across diverse tissues and disease contexts. The SiCmiR Atlas integrates 9.36 million cells with analytical tools for hub‐miRNA discovery, biomarker prioritization, and regulatory network interrogation ...
Xiao‐Xuan Cai, Jing‐Shan Liao, Jia‐Jun Ma, Yu‐Xuan Pang, Yi‐Gang Chen, Yang‐Chi‐Dung Lin, Yi‐Dan Chen, Xin Cao, Yi‐Cheng Zhang, Tao‐Sheng Xu, Tzong‐Yi Lee, Hsi‐Yuan Huang, Hsien‐Da Huang   +12 more
wiley   +1 more source

Surface Chemistry and Particle Morphology Changes in Pine Biomass under Indirect Thermal Gradients: Implications for Feed Screw Design. [PDF]

ACS Omega
Zeng Y, Gruber J, Dunning T, Rowland S, Carpenter D, Donohoe BS.   +5 more
europepmc   +1 more source

Decoding Triphenotypic Neutrophils in Cervical Cancer Evolution and Targeting SPP1+/GBP1+/ELOVL5+ Tumor‐Associated Neutrophils to Sensitize Immunotherapy

Advanced Science, EarlyView.
The functional schematic diagram of tumor associated neutrophils. Abstract Enhancing cervical cancer (CC) immunotherapy requires deciphering the heterogeneous tumor immune microenvironment (TIME), particularly neutrophil phenotypic dynamics. Here, 1) we collected 543 CC cases to find that patients with elevated neutrophil levels have a higher incidence
Xingyu Chang, Xinyu Qu, Tingting Ren, Tong Wu, Weiyong Gu, Jingxin Ding, Keqin Hua, Junjun Qiu   +7 more
wiley   +1 more source

Macroscopic and Microscopic Performance Study of Filling-Type Large-Size Cement-Stabilized Macadam. [PDF]

Materials (Basel)
Ran J, Wang H, Tang D, Zhang N, Li M, Jia Y, Ma L, Zhang Y.   +7 more
europepmc   +1 more source

A Novel 10‐Protein Score for Liver Fat Content Predicts Cardiovascular‐Kidney‐Metabolic Disease Risk

Advanced Science, EarlyView.
A novel 10‐protein plasma score precisely quantifies liver fat, outperforming the fatty liver index. It robustly predicts the risk of numerous cardiovascular‐kidney‐metabolic diseases and integrates with genetic data for precision prevention, offering a practical alternative to magnetic resonance imaging (MRI). Abstract Liver fat content (LFC) is a key
Xiaoqin Gan, Yuanxiu Wei, Yiting Wu, Xinyue Su, Gangling Wang, Sisi Yang, Ziliang Ye, Yanjun Zhang, Hao Xiang, Yu Huang, Yiwei Zhang, Yuanyuan Zhang, Xianhui Qin   +12 more
wiley   +1 more source

James-Stein Estimator Improves Accuracy and Sample Efficiency in Human Kinematic and Metabolic Data. [PDF]

Ann Biomed Eng
Alwan A, Srinivasan M.
europepmc   +1 more source

Stimuli‐Responsive Supramolecular Biomaterials for Cancer Theranostics

Advanced Science, EarlyView.
The ultimate goal of cancer theranostics is to get imaging agents and therapeutic cargo to tumor sites when and where they are required. “Smart” systems should be developed. This review discusses the characteristics of physiological stimuli, types and action modes of external stimuli, construction approaches and working principles, as well as ...
Wenting Hu, Binglin Ye, Guocan Yu, Feihe Huang, Zhengwei Mao   +4 more
wiley   +1 more source

Transfer-learning on federated observational healthcare data for prediction models using Bayesian sparse logistic regression with informed priors. [PDF]

J Am Med Inform Assoc
Li KM, Reps JM, Nishimura A, Schuemie MJ, Suchard MA.   +4 more
europepmc   +1 more source

Pathomics Signature for Prognosis and CA19‐9 Interception in Pancreatic Ductal Adenocarcinoma: A Real‐Life, Multi‐Center Study

Advanced Science, EarlyView.
This study develops a deep learning‐based pathomics model to predict survival outcomes in pancreatic cancer patients. The CrossFormer architecture analyzes routine H&E‐stained tissue slides, identifying key prognostic features including stromal patterns, cellular characteristics, and immune infiltration.
Qiangda Chen, Zhihang Xu, Yiping Zou, Zhenlai Jiang, Yecheng Li, Taochen He, Hanlin Yin, Jiali Li, Yanfei An, Jiande Han, Yuqi Xie, Wei Gan, Yaolin Xu, Wenquan Wang, Junyi He, Haibo Wang, Wenchuan Wu, Zhenyu Ye, Wenhui Lou, Jihui Hao, Liang Liu, Jun Yu, Ning Pu   +22 more
wiley   +1 more source