Results 211 to 220 of about 23,915,049 (293)
Tian et al. reveal that FH K112 lactylation is elevated after TBI, leading to fumarate accumulation, mitochondrial damage, mtDNA release and amplified neuroinflammation. AARS2 and SIRT3 act as the “writer” and “eraser” for FH K112 lactylation. The peptide Pep‐K112 targeting this site alleviates brain injury, highlighting a potential therapeutic target.
Yang Tian +21 more
wiley +1 more source
Pathological tissue rigidity mechanoprimes microglia by enhancing actin cytoskeleton–nucleus coupling and chromatin opening at rigidity‐responsive cis‐regulatory elements (mechanoCREs). Subsequent NF‐κB/p65 signaling converges on this permissive regulatory state to amplify inflammatory gene expression and microglial activation.
Yu Xuan Meng +15 more
wiley +1 more source
Lightweight and robust image steganography method for secure communication. [PDF]
Kang W, Pan Y.
europepmc +1 more source
Recent advances in metasurface‐enabled low‐observable technologies are reviewed from the perspective of cross‐scale material–structure synergy. Electromagnetic, thermal, optical, and acoustic stealth are highlighted together with dynamic tuning, programmable coding, data‐driven inverse design, artificial intelligence, multispectral compatibility, and ...
Shuhao Wang +5 more
wiley +1 more source
From Pixel Modification to Generative Synthesis: A Survey of Deep Learning for Image Data Hiding. [PDF]
Janok M, Forgáč R, Hluchý L.
europepmc +1 more source
An ATP‐driven molecular switch, comprising viral nucleocapsid (N) protein and host helicase DDX21, dynamically modulates SARS‐CoV‐2 RNA G‐quadruplex (G4) heterogeneity. These viral G4s feature non‐canonical ion‐dependence and act as energy‐sensitive structural checkpoints.
Ya‐Ting Zheng +8 more
wiley +1 more source
Correction: Bai et al. A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network. <i>Sensors</i> 2023, <i>23,</i> 5360. [PDF]
Bai Y, Li L, Lu J, Zhang S, Chu N.
europepmc +1 more source
Predicting Enzyme Turnover Numbers and Enabling Rational Enzyme Evolution
MCKcat, a deep learning framework combining multi‐scale convolution and cross‐attention, accurately predicts enzyme turnover number (kcat) by fusing sequence and reaction representations. It couples with rational design in a two‐step strategy for Bacillus aryabhattai laccase engineering, achieving a 75% positive rate with synergistically enhanced ...
Fengya Ge +6 more
wiley +1 more source

