Results 151 to 160 of about 70,842 (213)

The Use of Research Findings on Self-Regulated Learning by Teachers and Students in an Australian High School. [PDF]

open access: yesBehav Sci (Basel)
Lawson MJ   +13 more
europepmc   +1 more source

Microglia‐Targeted Biomimetic Tetrahedral Framework Nucleic Acid Nanovesicles for Synergistic Treatment of Sepsis‐Associated Encephalopathy

open access: yesAdvanced Science, EarlyView.
Sepsis‐associated encephalopathy (SAE) lacks effective therapies. We developed ME@FDsi, a biomimetic nanodrug using a tetrahedral framework nucleic acid to deliver disulfiram and siTNFα. It crosses the blood‐brain barrier, targets M1 microglia, inhibits pyroptosis and inflammation, and scavenges ROS.
Huimin Shi   +15 more
wiley   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

open access: yesAdvanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu   +5 more
wiley   +1 more source

Toward Prostate Cancer Early Warning with a Self‐Powered Wearable Biosensing Platform Integrated with Machine Learning

open access: yesAdvanced Science, EarlyView.
ABSTRACT Current prostate cancer detection methods remain limited in non‐invasiveness and specificity, prompting interest in urinary biomarkers such as sarcosine. Here, we report a urine‐powered wearable platform for non‐invasive sarcosine detection as a proof‐of‐concept for decentralized early warning.
Jing Xu   +10 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

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