Results 211 to 220 of about 8,004,238 (365)

Precise Quantification of Angiogenesis in 3D Biomaterials Using in Vitro CAM Models: Enhancing 3Rs in Research and Minimizing in Vivo Dependency

open access: yesAdvanced Functional Materials, EarlyView.
The study develops elastin–fibrin scaffolds and evaluates angiogenesis using the chorioallantoic membrane (CAM) model. Advanced imaging with confocal microscopy and Indocyanine Green dye enables precise 3D quantification of vascular networks. Findings demonstrate superior microvessel visualization compared to micro‐CT using Microfil and Optiray 350 ...
Ece Melis Er   +8 more
wiley   +1 more source

Bioinspired Shape Reconfigurable, Printable, and Conductive “E‐Skin” Patch with Robust Antibacterial Properties for Human Health Sensing

open access: yesAdvanced Functional Materials, EarlyView.
In this article, Hojin Kim, Sayan Deb Dutta, and co‐workers report a shape‐reconfigurable, 3D printable, and highly adhesive slime‐like ‘electronic skin’ or ‘E‐skin’ patch for human health sensing and tissue engineering applications. The dual reinforcement of hydrogel patch with carbon nanotubes (CNTs) and cellulose nanocrystals (CNCs) improve the ...
Hojin Kim   +6 more
wiley   +1 more source

Network Analysis of the Organic Chemistry in Patents, Literature, and Pharmaceutical Industry. [PDF]

open access: yesMol Inform
Svensson E   +7 more
europepmc   +1 more source

Unraveling Protein Networks with Power Graph Analysis

open access: gold, 2008
Loïc A. Royer   +3 more
openalex   +2 more sources

Perfusable Brain Microvascular Network‐On‐Chip Model to Study Flavivirus NS1‐Induced Endothelial Dysfunction

open access: yesAdvanced Functional Materials, EarlyView.
This study presents a microfluidic brain microvascular network‐on‐chip (BMVasChip) to investigate endothelial barrier dysfunction caused by flavivirus non‐structural protein 1 (NS1), including virus‐ and time‐dependent vascular damage, leakiness, and dysfunction.
Monika Rajput   +5 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

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