Results 171 to 180 of about 1,092,620 (284)

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

Advanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin, Zijie Chen, Yurong Li, Meijing Fang, Longji Shen, Yilong Su, Odin Zhang, Qinghan Wang, Qun Su, Jike Wang, Tingjun Hou, Yu Kang   +11 more
wiley   +1 more source

Caveolin‐1 Stabilizes SERCA2 to Counteract Acute Kidney Injury via Suppression of Ca2+‐Dependent Endoplasmic Reticulum Stress in Distal Tubules

Advanced Science, EarlyView.
In AKI, initial kidney injury upregulates the expression of Cav‐1, which subsequently binds to and stabilizes SERCA2 via its scaffolding domain and through deubiquitination, thereby regulating Ca2+ homeostasis and ER stress. Conversely, Cav‐1 deficiency accelerates SERCA2 degradation, triggering Ca2+ overload and ER stress, and ultimately exacerbating ...
Yan Zhang, Xin He, Hao Huang, Rong Lu, Xin Lv, Shenglan Li, Sijue Zou, Jiawei Cheng, Yiwei Xiong, Zhenghao Deng, Qiongjing Yuan, Yanyun Xie, Ling Huang, Jiaxi Pu, Shao Liu, Qianbin Li, Jie Meng, Huixiang Yang, Lijian Tao, Zhangzhe Peng   +19 more
wiley   +1 more source

Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity. [PDF]

Biom J
Wiederkehr C, Heumann C, Schomaker M.
europepmc   +1 more source

Triple‐Mode Ferroelectric Thin‐Film Transistor for Hybrid Electrical–Optical Reservoir Computing

Advanced Science, EarlyView.
A triple‐mode ferroelectric thin‐film transistor is developed by integrating Si3N4/HZO/IGZO layers to realize three independent memory modes: electric long‐term, electric short‐term, and optical short‐term. This single‐device architecture functions as both a reservoir and readout layer, achieving 92.43% MNIST accuracy. It offers a fully hardware‐based,
Hyeonho Lee, Seungjun Lee, Tae‐Hyeon Kim, Yonghee Jeong, Gwangmin An, Minsu Ko, Junsu Yu, Heung Soo Kim, Yang Chai, Sungjun Kim   +9 more
wiley   +1 more source

Causally Informative Entropic Inequalities within Families of Distributions with Shared Marginals. [PDF]

Entropy (Basel)
Chicharro D.
europepmc   +1 more source

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

Advanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar, Yannaël Bossard, Rachel Sava, Tobias Gänswein, Lorenca Sadiraj, Jean‐Samuel Dupré, Manuel Schröter, J. Gray Camp, Fernando Cardes, Julian Bartram, Andreas Hierlemann   +10 more
wiley   +1 more source

A Generalization of the DMC. [PDF]

Entropy (Basel)
Tridenski S, Somekh-Baruch A.
europepmc   +1 more source

Marginal and Conditional Distribution Estimation from Double-Sampled Semi-Competing Risks Data. [PDF]

Scand Stat Theory Appl, 2015
Yu M, Yiannoutsos CT.
europepmc   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source