Results 171 to 180 of about 420,877 (265)

The Plant‐to‐Plant Circular Strategy: Coupling Photodegradation and Phytoremediation With Plant‐Based Nanomaterials for Plastic Degradation

open access: yesAdvanced Science, EarlyView.
Plant‐based nanomaterials derived from alfalfa serve as dual‐function catalysts, coupling photodegradation and phytoremediation to degrade polyethylene under UV‐A light and in soil. The nanomaterials work synergistically with alfalfa and soil microbes, achieving efficient plastic breakdown without trophic transfer.
Haoran Liu   +4 more
wiley   +1 more source

Assessing National Health Research System in a resource-limited setting: Insights from Indonesia. [PDF]

open access: yesPLoS One
Dharmawan T   +6 more
europepmc   +1 more source

Loss of SHP1 in Spinal Astrocytes Triggers T‐Lymphocyte Infiltration and Nociceptive Hypersensitivity

open access: yesAdvanced Science, EarlyView.
Astrocyte‐specific SHP1 deletion disrupts astrocyte–vascular interactions and compromises BBB integrity while enhancing STAT1‐dependent CXCL10 expression. These changes synergistically promote peripheral CD4+ and CD8+ T‐cell infiltration into the SDH. The infiltrating T cells secrete IFN‐γ, which in turn activates microglia.
Lan‐Xing Yi   +7 more
wiley   +1 more source

Advancing Clinical Research

open access: yes
Advanced Science, EarlyView.
wiley   +1 more source

A Novel Pak1 Activator Ameliorates ER Stress for HFpEF Therapy

open access: yesAdvanced Science, EarlyView.
Chronic metabolic stress is a major contributor to HFpEF progression. Under prolonged metabolic stress, Pak1 activity becomes impaired, contributing to disrupted ER proteostasis, cardiomyocyte apoptosis, fibrosis, and diastolic dysfunction. Mechanistically, Pak1 overexpression activates the ERK1/2–MNK1–eIF4E signaling axis, promotes translational ...
Honglin Xu   +17 more
wiley   +1 more source

Trustworthy Multimodal Attention Framework for Creep Rupture Life Prediction Under Data‐Scarce Conditions: A Case Study on IN718

open access: yesAdvanced Science, EarlyView.
An attention‐based multimodal deep learning framework is developed to predict the creep life of Ni‐based superalloys by fusing processing parameters with microstructural micrographs. The model achieves high accuracy (R2 = 0.92), aligns with metallurgical principles by capturing δ‐phase influence, and incorporates uncertainty quantification, offering a ...
Haopeng Lv   +10 more
wiley   +1 more source

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