Results 201 to 210 of about 55,372 (282)

Targeting a Myeloid–Regulatory B Cell Network Reverses Immune Paralysis in Periprosthetic Joint Infections

open access: yesAdvanced Science, EarlyView.
Periprosthetic joint infection establishes a sophisticated immunosuppressive network between CXCR4+ PMN‐MDSCs and Bregs, inducing profound CD8+ T cell paralysis. Alendronate effectively disrupts this CXCR4+ PMN‐MDSC–Breg axis by targeting STAT3, thereby restoring local immune surveillance.
Jintao Wu   +9 more
wiley   +1 more source

Tandem Duplication‐Driven Neofunctionalization of UDP‐Glycosyltransferases Shapes the Diversification of Triterpenoid Saponins in the Cucurbitaceae

open access: yesAdvanced Science, EarlyView.
We present a chromosome‐level genome assembly of Siraitia grosvenorii and, through comparative genomics, uncover a conserved UGT73 tandem array driving triterpenoid saponin diversification in Cucurbitaceae. Crystalized SgUGT73AM30 further reveals the regioselectivity mechanism underlying its catalytic activity.
Guangyi Wang   +13 more
wiley   +1 more source

Pericentrosomal Redistribution of the Endoplasmic Reticulum Ensures Organelle Symmetric Inheritance and Mitotic Progression

open access: yesAdvanced Science, EarlyView.
Upon mitotic entry, RTN4 relocalizes to the pericentrosomal region, forming a more tubular ER network around centrosomes. CDK1‐mediated phosphorylation of RTN4 increases its interaction with Rab11 GTPase, facilitating dynein‐dependent transport of RTN4 to the pericentrosomal region.
Xiangyu Xu   +9 more
wiley   +1 more source

Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami

open access: yesAdvanced Science, EarlyView.
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning   +3 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

open access: yesAdvanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai   +3 more
wiley   +1 more source

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