Results 171 to 180 of about 163,662 (260)

HNRNPU K181 Lactylation Drives Cervical Cancer Growth by Upregulating PHGDH and Reprogramming Serine Metabolism

Advanced Science, EarlyView.
Lactate in cervical cancer induces HNRNPU K181 lactylation, opposed by NAA50‐mediated acetylation and suppressed by Pazopanib. This lactylation enhances HNRNPU binding to PHGDH pre‐mRNA exon 1, maintaining exon 1‐containing transcripts and mRNA stability, thereby activating serine metabolism.
Chang Zhang, Qingfei Meng, Hui Jiao, Huixin Liu, Xiangchao Wang, Honglan Zhou, Yishu Wang   +6 more
wiley   +1 more source

An improved control strategy of power-frequency characteristics of virtual synchronous generator. [PDF]

PLoS One
Zheng W, Su M, Gao C.
europepmc   +1 more source

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

Advanced Science, EarlyView.
When a master transcription factor (TF) is lost, bacteria can rapidly rewire gene regulatory networks by co‐opting related regulators. Using experimental evolution in Pseudomonas fluorescens, we show that TF promiscuity (low‐level, non‐cognate binding) provides the raw material for rewiring. Successful co‐option follows a predictable hierarchy governed
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Assessing the importance of sex and disease-specific anatomy in electrophysiology and mechanical simulations with a newly developed public virtual cohort of four-chamber heart models. [PDF]

PLoS Comput Biol
Solís-Lemus JA, Barrows RK, Rodero C, Strocchi M, Montarello N, Lahoti N, Corrado C, Qayyum A, Rahmani S, Roney C, Plank G, Augustin C, Xu H, Young A, Pathmanathan P, Rajani R, Niederer SA.   +16 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Virtual Bioequivalence Assessment of Long-Acting Injectable Suspensions Using PBPK Modeling: Part 2. Type I Error and Safe Space Analyses. [PDF]

AAPS J
Morris NM, Jamei M, Alam K, Tsakalozou E, Donnelly M, Feng K, Bois FY.   +6 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Integrated ADRC and Consensus Control for Anti-Disturbance Formation Tracking Control of Multiple Biomimetic Underwater Spherical Robots. [PDF]

Biomimetics (Basel)
Hou X, Xu M, Wei L, Li H, Li Z, Xing H, Guo S.   +6 more
europepmc   +1 more source

Two‐Dimensional Triferroics: From Fundamental Couplings to Multifunctional Applications

Advanced Science, EarlyView.
This graphic summarizes the three main types of currently reported 2D triferroic couplings. From the structural perspective, existing systems can be broadly classified into two categories, which exhibit distinct symmetry features and coupling behaviors. Beyond the lattice difference, a third type involves the interplay among ferroelectricity, magnetism,
Yang Li, Jialin Gong, Zhiqing Li
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source