Results 211 to 220 of about 385,713 (293)

Vital signs and common blood tests improve the predictive power of the Hospital Frailty Risk Score to predict poor outcomes across all adult ages. [PDF]

PLoS One
Kutrani H, Briggs J, Prytherch D, Spice C.   +3 more
europepmc   +1 more source

A Bioinspired Three‐Dimensional High‐Curvature Nano‐Interface Integrated Microfluidic Chip for Small Extracellular Vesicles Enrichment and Machine Learning‐Assisted Prostate Cancer Precision Diagnosis

Advanced Science, EarlyView.
A biotin‐modified artificial insertion peptide functionalized three‐dimensional high‐curvature‐TiO2 nano‐interface was engineered in a microfluidic chip to improve the isolation efficiency of small extracellular vesicles (sEVs). This chip balanced affinity, releasability, and extendibility, enabling high‐throughput recovery of sEVs for downstream ...
Le Wang, Yizhong Liang, Manan Sulaiman, Jiaqi Du, Ming Jiang, Zhihua Wang, Xu Yu, Li Xu   +7 more
wiley   +1 more source

Early Prediction of Cardiac Arrest Based on Time-Series Vital Signs Using Deep Learning: Retrospective Study. [PDF]

JMIR Form Res
Li Y, Lv L, Wang X.
europepmc   +1 more source

Dose‐Dependent Reprogramming of Chromatin Accessibility by SOX4 Drives the Transcriptional Response to Iron Overload

Advanced Science, EarlyView.
This study demonstrates that iron overload triggers widespread chromatin compaction and transcriptional repression in human granulosa cells, recapitulating features of endometriosis. The epigenetic reprogramming is orchestrated by a TFEB‐SOX4‐SWI/SNF axis, with SOX4 acting as a central, dosage‐sensitive regulator.
Feifei Li, Yaoqiu Wu, Guangyu Yang, Jingyi Lai, Xiaoyue Sun, Liyan Wang, Xiaoli Li, Jing Zhang, Qingxue Zhang, Hui Chen, Haiyan Lin, Bingxiang Xu, Junfeng Zhang, Hailong Wang, Anming Meng, Chunwei Cao   +15 more
wiley   +1 more source

Vital Signs-Only Machine Learning Model for Acute Inpatient Deterioration: A Retrospective Multicenter Study. [PDF]

Mayo Clin Proc Innov Qual Outcomes
Romero-Brufau S, Smunyahirun R, Filhol T, Niederhauser L, Trakoolwilaiwan T, Singh G.   +5 more
europepmc   +1 more source

Haplotype‐Resolved 3D Genomic Landscapes and Their Impacts on Agronomic Traits in Grapevine

Advanced Science, EarlyView.
This study presents a haplotype‐resolved 3D genomic landscape of grapevine, revealing that structural variations (SVs) are closely associated with phased topologically associating domain (TAD) boundary transitions. These rearrangements coordinate with allele‐specific DNA methylation (ASM) and allele‐biased gene expression (ASE) to shape key agronomic ...
Yanling Peng, Lianzhu Zhou, Xinyue Fang, Ruoyan Zhao, Qi Xu, Mengrui Du, Ting Hou, Guizhou Huang, Yingchun Zhang, Sheng Yan, Ruo Yang, Zhongxin Jin, Yang Dong, Yanshuai Xu, Hua Xiao, Xiaodong Xu, Yi Liao, Xiping Wang, Yongfeng Zhou   +18 more
wiley   +1 more source

Vital signs as biomarkers of early clinical deterioration in pediatric emergency departments: physiology, interpretation, and innovations: a narrative review. [PDF]

Int J Emerg Med
Alsabri M, Mourid MR, Saleh AR, Oyedele TJ, Ata IM, Darawish SM, Patel A, Rouh FA, Carr LA.   +8 more
europepmc   +1 more source

Vorinostat Potentiates Chemoimmunotherapy in Immune‐Enriched Pancreatic Cancer

Advanced Science, EarlyView.
Immune‐enriched pancreatic cancer does not confer a significant survival advantage. SAHA sensitizes these “hot” tumors to chemoimmunotherapy by disrupting a FASN/PARP9‐driven “metabolic trap” and enhancing CD8+ T cell function. A CD8high/FASNhigh/PARP9high signature identifies patients who are most likely to benefit from the “gemcitabine‐nivolumab‐SAHA”
Chen Chen, Dingru Li, Yingna Liao, Zehua Wang, Chunbin Zhu, Zifeng Zhang, Liquan Jin, Yueyue Chen, Jiaoshun Chen, Junyi Xu, Miaoyan Wei, Rong Tang, Xianjun Yu, Si Shi   +13 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source