Results 151 to 160 of about 28,711,041 (283)

Integrated Team-Based Learning in a UK Undergraduate Medical Programme. [PDF]

Clin Teach
Drovandi A, Sheader E, Kingston M.
europepmc   +1 more source

Highly Sensitive Spatial Host‐Microbiome Transcriptomics in FFPE Tissues via Iterative Hydrogel Expansion

Advanced Science, EarlyView.
Ex‐spRandom is a spatial transcriptomics platform that synergizes random‐primed chemistry with iterative hydrogel expansion. By physically decrowding the dense FFPE matrix, this scalable technology shatters the traditional resolution‐sensitivity barrier.
Shunji Zhang, Mengyuan Wang, Jiaye Chen, Yuyi Zhu, Bin Zhu, Ziye Xu, Yuan Liao, Yongcheng Wang   +7 more
wiley   +1 more source

Team learning behaviors: Supporting team-based learning in a first-year design and communications course

, 2016
Team learning behaviors: Supporting team-based learning in a first-year design and communications ...
M Eggermont (13478491), Nicole Larson (13087596), WD Rosehart (15824123), G Hoffart (13478485), T O'Neill (7742537)   +4 more
core  

Uncoupling Type I Interferon Benefits From Inflammatory Toxicity: Transformer‐Prioritized Precision Agonists for Potent and Safer Cancer Immunotherapy

Advanced Science, EarlyView.
A Transformer‐based AI framework, DLINP, screens millions of compounds to identify Co68, a cobalt‐pincer organometallic complex that biases TLR4‐MD2 signaling toward antitumor interferon activation while suppressing inflammatory toxicity through an early TLR4‐SYK‐STAT1 axis.
Xuefei Guo, Yang Zhao, Xianle Rong, Xingyu Chen, Xiao Wang, Tianyi Liu, Yunfei Xie, Yushu Zou, Pingsen Zhao, Qiang Liu, Fuping You   +10 more
wiley   +1 more source

Examination of the Interaction of Team Learning Variables Within a Systems Focus on Organizational Learning and the Learning Organization: A Study of a Nursing Team at a Large Southeastern Teaching Hospital

, 2003
The purpose of this study is twofold. First, this study takes an exploratory approach into examining the interaction of the team learning variables contained in the Team Learning Survey developed by Dechant and Marsick (1993).
Corpening, James L. Jr.
core  

Recommendations for Training Faculty in Generative AI Use: Crafting Higher-Order Application Exercises in Team-Based Learning. [PDF]

Clin Teach
Dalmeida D, Gomaa N, Prabhakar E.
europepmc   +1 more source

NICE: A Two‐Step Non‐Invasive Framework for Embryo cfDNA Read Enrichment and Quality Assessment

Advanced Science, EarlyView.
The non‐invasive NICE framework, built on an ensemble stacking machine learning model, prioritizes embryos by analyzing cell‐free DNA from spent culture medium. By integrating multimodal signals, including genomic and epigenetic profiles, this automated approach standardizes morphological assessment without human bias, paving the way for more precise ...
Xueya Zhou, Shu Ding, Zhenyi Zhang, Qiaoling Shangguan, Jie Qiao, Peijie Zhou, Yidong Chen   +6 more
wiley   +1 more source

A Unified Hierarchical Multiscale Fusion Framework for Drug–Target Affinity Prediction: From Benchmark Performance to Nanomolar Inhibitor Discovery

Advanced Science, EarlyView.
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu, Xiang Zhang, Haixia Feng, Yuquan Li, Xiaoqing Gong, Yong Liang, Xiaojun Yao, Huanxiang Liu   +7 more
wiley   +1 more source

Teaching clinical reasoning skills using an online team-based learning method. [PDF]

BMC Med Educ
Shah SDBA, Ahmed F, Sethi A, Kashif L, Hamid SM.   +4 more
europepmc   +1 more source

Low Latency Global Carbon Budget Reveals Late 2024 Carbon Losses and Contrasting Early 2025 Land Sink Recovery Signals

Advanced Science, EarlyView.
Low latency carbon budget estimates for July 2024–June 2025 combine atmospheric CO2 growth rates, fossil emissions, ocean uptake, DGVM land fluxes, and OCO‐2 inversions. The budget shows that late‐2024 land carbon losses dominate the annual anomaly, while early‐2025 recovery differs between bottom‐up models and top‐down inversions, especially in ...
Piyu Ke, Philippe Ciais, Yitong Yao, Stephen Sitch, Wei Li, Xiaomeng Du, Xiaofan Gui, Ben Poulter, Thomas Colligan, Auke M. van der Woude, Joram Hooghiem, Wouter Peters, Zhu Liu, Zhu Deng, Zhe Jin, Xiangjun Tian, Yilong Wang, Junjie Liu, Sudhanshu Pandey, Chris O'Dell, Jiang Bian, John Miller, Xin Lan, Jefferson Goncalves De Souza, Michael O'Sullivan, Pierre Friedlingstein, Julien Alléon, Yi Xi, Daniel S. Goll, Lei Zhu, Guido R. van der Werf, Shilong Piao, Frédéric Chevallier   +32 more
wiley   +1 more source