Results 141 to 150 of about 273,497 (278)

Intrinsic PPG–ECG Coupling for Accurate and Low‐Power Blood Pressure Monitoring

open access: yesAdvanced Science, EarlyView.
A PPG–ECG coupling strategy for continuous blood pressure monitoring that intrinsically synchronizes signals within a single waveform is demonstrated, minimizing synchronization errors and hardware complexity. This approach halves power consumption while maintaining high accuracy, enabling compact, energy‐efficient wearable devices for personalized ...
Sitong Chen   +5 more
wiley   +1 more source

No One is Illegal Between City and Nation

open access: yesStudies in Social Justice, 2010
By challenging the state's prerogative to distinguish between insiders and outsiders, citizens and non-citizens, political movements by and in support of migrants and refugees are forcing questions about what criteria, if any, can and should be used to ...
Peter Nyers
doaj  

Asymmetric Cu─N─Ru Bridgedsite Nanozyme‐Loaded Injectable Thermogel Boosts Cuproptosis‐Like Death for Multidrug‐Resistant Urinary Tract Infections

open access: yesAdvanced Science, EarlyView.
To address multidrug‐resistant urinary tract infections (MDR‐UTIs), we developed Cu‐ZIF8‐Ru nanozyme featuring an asymmetric Cu─N─Ru catalytic site. This unique structure enhances multienzyme‐mimetic activity, eradicating resistant bacteria by inducing a cuproptosis‐like death pathway through intracellular Cu2+ accumulation and energy depletion.
Guanlin Li   +9 more
wiley   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao   +11 more
wiley   +1 more source

Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Individual responses to food vary dramatically, challenging traditional dietary advice. This review explores how the unique genetic makeup, gut microbiome, and brain activity shape host metabolic health. We examine how artificial intelligence integrates these multimodal data to predict individualized dietary needs, moving beyond one‐size‐fits‐all ...
Yuanqing Fu   +5 more
wiley   +1 more source

Regular Hæmodialysis [PDF]

open access: yesProceedings of the Royal Society of Medicine, 1967
openaire   +2 more sources

Multi‐Scale Mapping of Gene Expression from Whole‐slide Images for Identifying Phenotype‐Associated Subpopulations

open access: yesAdvanced Science, EarlyView.
BiSCALE: A pathology‐driven deep learning framework for multi‐scale gene expression prediction from whole‐slide images. It accurately infers bulk and near‐cellular spot‐level expression, links predictions to clinical phenotypes, identifies disease‐associated niches, and enables applications in risk stratification and cell‐identity annotation, providing
Hailong Zheng   +8 more
wiley   +1 more source

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

open access: yesAdvanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi   +4 more
wiley   +1 more source

In Situ Quantization with Memory‐Transistor Transfer Unit Based on Electrochemical Random‐Access Memory for Edge Applications

open access: yesAdvanced Science, EarlyView.
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang   +9 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

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