Results 231 to 240 of about 46,112 (290)
A new approach for neural decoding by inspiring of hyperdimensional computing for implantable intra-cortical BMIs. [PDF]
Katoozian D +2 more
europepmc +1 more source
Phylogenetic and biochemical analyses of the heme transporter CydDC reveal its functional conservation throughout bacterial evolution and demonstrate its unique asymmetric allosteric mechanism. Furthermore, impairment of CydDC function directly affects bacterial antibiotic resistance and likely compromises antibiotic efficacy through drug efflux.
Lili Yang +19 more
wiley +1 more source
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding. [PDF]
Luo DD, Giri B, Diba K, Kemere C.
europepmc +1 more source
Upon JEV infection, ZNF33B recruits METTL14 to stabilize the METTL3‐METTL14 m6A methyltransferase complex, leading to increased m6A modification of host transcripts, including Trim25 mRNA. ZNF33B selectively binds m6A‐modified sites on Trim25 mRNA and accelerates its decay, resulting in reduced TRIM25 protein abundance.
Jian Du +9 more
wiley +1 more source
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
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 +11 more
wiley +1 more source
ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding. [PDF]
Mou X +15 more
europepmc +1 more source
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
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 +4 more
wiley +1 more source
Adult stem cell therapy requires more than high in vitro potency. This review proposes a systems framework in which cell‐intrinsic programs, instructive microenvironmental cues, and pre‐/post‐delivery engineering are co‐designed under standardized translational rules.
Soo‐Rim Kim +2 more
wiley +1 more source

