Results 81 to 90 of about 206 (178)

Targeting ANGPTL3 and IL‐33/ST2 Ameliorates Diabetic Kidney Disease by Reducing Lipotoxicity, Alleviating Inflammation and Inhibiting Fibrosis

open access: yesAdvanced Science, EarlyView.
Dual targeting of ANGPTL3 and IL‐33/ST2 attenuates diabetic kidney disease by reprogramming lipid–inflammatory crosstalk. This strategy reduces renal lipotoxicity, suppresses inflammatory activation, and limits fibrotic remodeling, thereby preserving kidney structure and function and highlighting a mechanism‐guided therapeutic approach for metabolic ...
Zhuojin Li   +8 more
wiley   +1 more source

Single‐Cell Annotation and Localization via Integrating Spatial Transcriptomics Maps the Mouse Ocular Atlas and RAO Dynamics

open access: yesAdvanced Science, EarlyView.
We developed the ASCAL pipeline, integrating complementary spatial transcriptomics, to construct a high‐fidelity mouse whole‐eye single‐cell atlas. Applying ASCAL to a retinal artery occlusion (RAO) model revealed spatially restricted immune activation localized to the ganglion cell layer and the selective depletion of a translationally active, outer ...
Chen Du   +11 more
wiley   +1 more source

Text encryption using Sosemanuk and Harris Hawks optimization by laser communication. [PDF]

open access: yesSci Rep
Mahdi MS   +6 more
europepmc   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

open access: yesAdvanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh   +8 more
wiley   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

open access: yesAdvanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li   +9 more
wiley   +1 more source

Home - About - Disclaimer - Privacy