Results 191 to 200 of about 411,514 (294)

Single‐Cell Morphomechanics of Prostate Cancer‐Associated Fibroblasts Identifies Distinct Features Associated with Patient Outcome

open access: yesAdvanced Science, EarlyView.
Cancer‐associated fibroblasts (CAFs) in prostate tumors exhibit distinct morphomechanical traits vs normal fibroblasts, including greater stiffness and volume, more elongated stress fibres, and larger and more elongated nuclei. These features, quantified through imaging and real‐time deformability cytometry, correlate with patient outcomes and can be ...
Antje Garside   +11 more
wiley   +1 more source

Redefining the Health Risk of Battery Materials Through a Biologically Transformed Metal Mixture

open access: yesAdvanced Science, EarlyView.
Inhaled NCM particles undergo lysosomal degradation, releasing complex ion mixtures that induce systemic impact. The impact is determined by a critical balance between antagonistic Ni‐Co interactions and synergistic Mn effects. To capture these complexities in risk assessment, we develop an IAI model, ensuring a more accurate quantitative risk ...
Ze Zhang   +11 more
wiley   +1 more source

Implicit neural representations for accurate estimation of the Standard Model of white matter. [PDF]

open access: yesCommun Biol
Hendriks T   +5 more
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Machine‐Learning‐Guided Design of Incommensurate Antiferroelectrics via Field‐Driven Phase Engineering

open access: yesAdvanced Science, EarlyView.
The key to enhancing the energy storage performance of antiferroelectrics lies in regulating the phase transition and reverse phase transition. A phase‐field‐machine learning framework is employed to predict the energy storage performance of Pb‐based incommensurate antiferroelectrics with multi‐scale regulation strategy, thereby revealing the dynamic ...
Ke Xu   +9 more
wiley   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

open access: yesAdvanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang   +15 more
wiley   +1 more source

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