Results 161 to 170 of about 111,877 (248)
Unique local gradient-based functional fingerprints enable precisely identifying individual infants over ages. [PDF]
Yuan X +6 more
europepmc +1 more source
Perception in robotic manipulation improves through the cooperative and complementary operation of biologically inspired multimodal tactile sensors. Receptor‐specific contribution analysis identifies which sensing modalities are required for specific tactile tasks.
Yu‐Jin Lee +4 more
wiley +1 more source
Covert Optical Fingerprints Within Overt Structural Colors via Cascaded Cavity Resonances. [PDF]
Kim G +6 more
europepmc +1 more source
A Transformer‐based AI framework, DLINP, screens millions of compounds to identify Co68, a cobalt‐pincer organometallic complex that biases TLR4‐MD2 signaling toward antitumor interferon activation while suppressing inflammatory toxicity through an early TLR4‐SYK‐STAT1 axis.
Xuefei Guo +10 more
wiley +1 more source
Machine learning prediction of bile salt export pump inhibition with Boruta feature selection in imbalanced data. [PDF]
Liu B +10 more
europepmc +1 more source
Chronic stress drives autophagy‐mediated β2‐AR degradation, impairing antiviral immunity and promoting poxvirus lethality. Lycorine directly stabilizes β2‐AR to restore host defense, suppress excessive inflammation and improve survival. ABSTRACT Psychological stress is a pervasive yet poorly understood modulator of infectious disease outcomes. Here, we
Xin Zhang +12 more
wiley +1 more source
Count your bits: fingerprint benchmarking to assess broad chemical space representation. [PDF]
Huber F, Pollmann J.
europepmc +1 more source
Mesoporous mixed ionic‐electronic PU/PEDOT: PSS electrodes enable label‐free detection of stochastic extracellular bioelectrical dynamics in living Phaeodactylum tricornutum. Living diatoms actively modulate interfacial ionic dynamics, establishing stochastic electrochemical noise as a sensitive probe of microbial bioelectrochemical activity and a new ...
David M. S. Silva +7 more
wiley +1 more source
Predicting Chemical Stressor Effects on Conjugative Plasmid Transfer Rates Using Machine Learning. [PDF]
Rey-Sogo A +4 more
europepmc +1 more source
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu +7 more
wiley +1 more source

