Results 171 to 180 of about 14,032,665 (282)

Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis

open access: yesAdvanced Science, EarlyView.
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko   +8 more
wiley   +1 more source

Socially motivated bedtime procrastination impairs sleep and wellbeing in residential college students. [PDF]

open access: yesSleep
Kok VJT   +7 more
europepmc   +1 more source

A Dual‐Mode In Situ EV‐miRNA Profiling Platform for Machine‐Learning‐Assisted Gastric Cancer Liquid Biopsy

open access: yesAdvanced Science, EarlyView.
An in situ dual‐mode platform integrates fusogenic liposomes with localized autocatalytic DNA circuits for plasma‐derived extracellular vesicle microRNA analysis. Following membrane fusion, target miRNAs trigger feedback‐assisted LECHA amplification inside intact vesicles, generating fluorescence and electrochemical outputs. Machine learning integrates
Wenbin Li   +15 more
wiley   +1 more source

The Interplay of Curvature, Geometry, and Topology Shapes Tissue Organisation in Epithelial Shells

open access: yesAdvanced Science, EarlyView.
Purely geometric 3D Voronoi models predict the organisation of epithelial shells. The interplay of curvature, geometry, and topology enriches the number of pentagons in shells with lower number of cells. Small MDCK cysts and Mouse embryos match the top polygonal configurations in a compactness‐based ranking derived from the Voronoi model. In conclusion,
Laura Morato   +9 more
wiley   +1 more source

Sublattice‐Resolved Magnetoelastic Coupling and Opposing Pressure Responses in the Frustrated Magnetocaloric GdMn2O5

open access: yesAdvanced Science, EarlyView.
In GdMn2O5, sublattice‐resolved EXAFS and diffraction analysis reveal pronounced spin‐phonon coupling and an unexpected opposing pressure response: the Mn‐driven Néel temperature slightly decreases while the Gd‐sublattice ordering temperature rises under pressures up to 0.86 GPa.
Romualdo S. Silva Jr.   +9 more
wiley   +1 more source

DyProL: Dynamic Ensemble Representation Learning for Protein–Nucleic Acid Binding Site Prediction

open access: yesAdvanced Science, EarlyView.
Protein function is represented as a dynamic conformational ensemble rather than a single static structure. A multi‐conformation geometric attention framework aligns, clusters, and learns representative states to capture residue‐ and ensemble‐level signals. Integrating structural dynamics improves interpretable protein‐NA binding prediction and reveals
Pengpai Li   +3 more
wiley   +1 more source

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