Results 151 to 160 of about 48,760 (297)

Pharmacological Inhibition of FKBP51 Mitigates Early Life Adversity‐Induced Social Deficits in Male Mice

Advanced Science, EarlyView.
Early life adversity triggers persistent social subordination and brain‐wide molecular dysregulation. Pharmacological inhibition of the stress‐mediator FKBP51 during the adversity period prevents these long‐term deficits and restores normative social hierarchy.
Joeri Bordes, Xiuqi Ji, Serena Gasperoni, Choham Sudre‐Chinsky, Amirali Kalbasi, Daniela Harbich, Cornelia Flachskamm, Paula Fontanet, Sowmya Narayan, Manfred Uhr, Christian Namendorf, Camilla Bellone, Alon Chen, Felix Hausch, Juan Pablo Lopez, Mathias V. Schmidt   +15 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer

Advanced Science, EarlyView.
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu, Xia Ling, Xianhe Zhang, Chuanjiang Jian, Leilei Shi, Wentao Song, Xiaonan Wang, Bin Liu   +7 more
wiley   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

CHCHD10 Mitigates Alzheimer's Disease‐Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons

Advanced Science, EarlyView.
CHCHD10 loss in Alzheimer's disease is associated with mitochondrial dysfunction, epigenomic disruption, and tau pathology. Restoration of CHCHD10 shifts DNA methylation toward a non‐disease state and reduces tau and amyloid pathology, with KATNAL2 acting as a downstream effector.
Teresa M. Thomas, Ching‐Yao Yang, Kexin Zhang, Liam Wetzel, Dina Bugybayeva, Julia Ferguson, Md Mahmudul Hasan, William Samsa, Nandita Patil, Anshul Dash, Tarini Gowda, Xiongwei Zhu, Feixiong Cheng, Tian Liu   +13 more
wiley   +1 more source

Non‐Noble Metal Nanocatalysts for Hydrogen Evolution

Advanced Science, EarlyView.
Recent overviews and latest developments of diverse classes of non‐noble catalysts for application toward high‐performance photocatalysis, thermocatalytic steam reforming, and electrocatalysis. Toward sustainability objectives, several advanced characterization tools in combination with the latest breakthroughs in machine learning for material ...
Lina Jaya Diguna, Gede Herry Arum Wijaya, Md Abdul Kuddus Sheikh, Tobias Haposan, Fidelis Stefanus Hubertson Simanjuntak, Arramel Arramel, Muhammad Danang Birowosuto, Konstantin Sergeevich Novoselov   +7 more
wiley   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

RHINO: An Integrative Multi‐Omics Framework Linking Circadian Physiology to Precision Medicine

Advanced Science, EarlyView.
RHINO (RHythmic Interacting Network for multi‐Omics) is an integrative framework that maps circadian regulation across diverse genetic and disease contexts and prioritizes druggable circadian targets. Released as an AI‐powered interactive web portal, RHINO unifies genetic, regulatory, disease, and drug–target information, enabling context‐specific ...
Ying Chen, Chengxuan Chen, Dishu Zhou, Panpan Liu, Roberto E. López‐Valiente, Yuan Liu, Cam Mong La, Isabella Beraldo Xavier, Sean M. Hartig, Pradip Saha, Zheng Sun, Leng Han, Dongyin Guan   +12 more
wiley   +1 more source

Study on direction and strength of relation based on knowledge graph

大数据, 2019
In current popular ideas for knowledge graph construction,the relations in graphs were described by words,it is difficult to calculate the relations in graphs.To this issue,concepts of the direction,intensive factors,temporal factors of relations were ...
Genlin ZANG, Yaqiang WANG, Qingrong WU, Chunli ZHAN, Xinyang XIE   +4 more
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