Results 81 to 90 of about 3,246,502 (304)
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao +6 more
wiley +1 more source
The accelerated decline of Arctic sea ice is profoundly reshaping regional climate regimes. Sea ice thickness (SIT), particularly under thin-ice conditions, is an important indicator for assessing early-season Arctic sea ice variability, and accurate ...
Jikun Liu +11 more
doaj +1 more source
Interaction‐Driven Assembly Pathways in Heterogeneous Active Microrobotic Systems
Peanut‐ and cube‐shaped light‐powered microrobots exhibit distinct magnetic and photocatalytic responses that determine their heterogeneous self‐assembly. In the dark, magnetic dipole interactions drive colloidal copolymerization with cubes acting as nucleation centers, whereas under light irradiation, phoretic interactions compete with magnetic ...
Domenico Calabrò +5 more
wiley +1 more source
The ionospheric total electron content (TEC) has complex spatiotemporal variations, making its spatiotemporal prediction challenging. Capturing long-range spatial dependencies is of great significance for improving the spatiotemporal prediction accuracy ...
Yalan Li +6 more
doaj +1 more source
A 3D Human Neuron‐on‐Chip Platform to Monitor Neuronal Injury Responses
This study presents a novel 3D Neuron‐on‐Chip model that can maintain human PSC‐derived excitatory prefrontal cortex neurons in 3D hydrogels and can be used to monitor neuronal injury responses over time. Results show injury‐induced acute neuronal excitotoxicity, declining neuronal connectivity, and the activation of a neurodegenerative, SASP‐like ...
Ruiping Tang +16 more
wiley +1 more source
Prediction of PM2.5 Concentration on the Basis of Multitemporal Spatial Scale Fusion
While machine learning methods have been successful in predicting air pollution, current deep learning models usually focus only on the time-based connection of air quality monitoring stations or the complex link between PM2.5 levels and explanatory ...
Sihan Li, Yu Sun, Pengying Wang
doaj +1 more source
This study presents a bioengineered assembloid (ASM) system combining glioblastoma (GBM) cells in oxidized alginate (OA) microgels with dorsal organoids (DOs). This model simulates brain tumor‐host interactions, revealing enhanced GBM invasion, altered gene expression, and aggressive infiltration patterns, demonstrating ASM as a valuable platform for ...
Chao Liang +17 more
wiley +1 more source
A migration‐permissive bioink composed of methacrylated collagen type I and thiolated hyaluronic acid enables 3D bioprinting of breast cancer‐stroma models. Single‐cell tracking reveals that adipose stromal cells enhance tumor cell motility and stromal invasion, accompanied by collagen remodeling, and a shift in tumor cell morphology.
Sabrina Stecher +19 more
wiley +1 more source
Spatiotemporal prediction of gas extraction-induced seismicity is a key challenge in regional seismic risk management, hindered by heterogeneous spatial coupling among reservoir blocks and extreme class imbalance in seismicity records.
Hanfeng Zhang +7 more
doaj +1 more source
We developed a patient‐derived, functional microfluidic model of the diffuse midline glioma (DMG) blood–brain–tumor barrier (BBTB) comprised of endothelial cells, astrocytes, pericytes, and tumor cells. The system forms perfusable microvasculature, reveals the BBTB retains vascular integrity, identifies DMG‐specific transcriptomic changes distinct from
Kimberly R. Bennett +7 more
wiley +1 more source

