Results 241 to 250 of about 7,754 (304)
This study introduces a biomimetic “nanofusion” platform that integrates the biostability of threose nucleic acids (TNA) with homotypic cell‐membrane cloaking to combat drug‐resistant TNBC. By leveraging a non‐canonical membrane‐fusion pathway for direct cytosolic delivery, the platform bypasses endosomal sequestration. To achieve potent AKT2 silencing
Wei Zheng +7 more
wiley +1 more source
HC-SPA: Hyperbolic Cosine-Based Symplectic Phase Alignment for Fusion Optimization. [PDF]
Zhang W, Fang A, Li Y, Wei Y.
europepmc +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
Hyperfiniteness and Borel asymptotic dimension of boundary actions of hyperbolic groups. [PDF]
Naryshkin P, Vaccaro A.
europepmc +1 more source
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source
Nonreciprocal Negative Refraction Enabled by Photonic Time Crystals. [PDF]
Tavakol MR, Cai W.
europepmc +1 more source
Interacting Parallel Fluidic Hysterons
The parallel coupling of fluidic hysterons is introduced, establishing advanced functionalities in inflatable soft systems. A pressure–volume framework reveals how preset volumes Δv∗${\Delta }v^*$ tune nonlinear interactions between hysterons and actuation sequences without changing architecture. Experiments validate the predictions, opening new routes
Katrien Stinissen +2 more
wiley +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
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

