Universal precautions

Nanotrap-AI Integration Enables Ultra-Sensitive Point-of-Care HIV Testing.

Early HIV detection using noninvasive samples remains challenging because oral fluid contains extremely low antibody levels and enzymatic inhibitors that limit the sensitivity of lateral-flow assays (LFAs). We introduce BE-SMART-HIV, a diagnostic platform that integrates a BEETLES2-inspired bioengineered enrichment (BE) nanotrap with a smartphone-based deep-learning reader (SMART). The BE nanotrap...

Tuberculosis Disease Severity Assessment Using Clinical Variables and Radiology Enabled by Artificial Intelligence.

BACKGROUND: Chest X-ray (CXR) can assess pulmonary tuberculosis (TB) severity and may guide duration of treatment. However, the optimal radiological metric and its integration with clinical variables for predicting treatment outcomes remains unclear. METHODS: We used logistic regression to associate human-read and commercial artificial intelligence-generated CXR metrics with unfavorable outcome in...

A review of traditional uses, phytoconstituents, bioactivities, and therapeutic potential of Hypecoum erectum L. and Hypecoum leptocarpum Hook.f. & Thomson.

ETHNOPHARMACOLOGICAL RELEVANCE: Hypecoi Erecti Herba, derived from plants of the genus Hypecoum (Papaveraceae), includes two source species: Hypecoum ...

AI-enabled autonomous UV-C device pathogen reduction within clinically relevant parameters.

Wall-mounted UV-C disinfection systems present a promising alternative to robotic approaches for pathogen reduction. We sought to determine the pathog...

Deep Learning-Enhanced DNAzyme-Driven Rolling-Circle Amplification Encoding for Multibacterial Detection.

Food-borne outbreaks are frequently caused by multiple live pathogens that conventional methods cannot process simultaneously. We report a DNAzyme-dri...

Machine-Learning Microfluidic Minute-Scale Microorganism Metrics Monitoring(M6).

On-site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion,...

Assessing ChatGPT's capability in understanding and reporting antiretroviral therapy drug-drug interactions (ACCURATE-DDI).

OBJECTIVES: Artificial intelligence tools are transforming access to medication information. However, their ability to accurately identify antiretrovi...

Novel machine learning-based approach to identify viral biomarkers of human respiratory emissions from oral and nasal metagenomes.

Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental samp...

Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.

BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...

Region guided mask R-CNN with Haralick ResNet fusion for accurate coronary artery disease detection in computed tomography angiography images.

Coronary Computed Tomography Angiography (CCTA) is a non-invasive imaging technique used to visualize the coronary arteries and diagnose coronary arte...

Bridging Artificial Intelligence, Machine Learning with Green Nanotechnology: A Visionary Framework for Smart Fungal Disease Management in Plants.

Fungal diseases in plants pose significant threats to global food security and sustainable agriculture, yet current management methods remain limited ...

Deep learning analysis of soybean cyst nematode effectors to proven soybean resistance genes and homolog identification in the sugar beet-sugar beet root maggot plant pathosystem.

Sugar beet (Beta vulgaris ssp. vulgaris) is one of two plants from which sugar is broadly produced, accounting for 55% of U.S. sugar ($1B, U.S.) and 3...

Microbiome and multi-omics insights into sustainable aquaculture: A triennial systematic review.

Aquaculture is the fastest-growing food production sector, yet intensive practices drive disease outbreaks, antibiotic resistance, and environmental d...

AI-driven fungicide design: From target identification to field application.

Plant pathogenic fungi severely threaten global agriculture, causing substantial yield losses in staple crops and endangering food safety through myco...

Multidimensional Trends and AI-Based Forecasts of HIV Incidence in Korea, 1985-2024.

Predicting hepatocellular carcinoma in people with hepatitis B: a comparison between Cox proportional hazard and machine learning models.

BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, with chronic hepatitis B virus (HBV) infectio...

Deep learning analysis of sugar beet (Beta vulgaris ssp vulgaris) protease inhibitors interacting with identified trypsins from its primary pathogen, the sugar beet root maggot Tetanops myopaeformis.

Beta vulgaris ssp. vulgaris (sugar beet) is one of two plants globally from which sugar is widely produced, accounting for 55% of U.S. sugar $1B (U.S....

irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.

BACKGROUND: Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation ac...

SDS-CRISPR for Single-Nucleotide Variant Detection.

The CRISPR-Cas12a system offers a promising platform for simple and sensitive nucleic acid diagnostics, including tumor-associated variant detection a...

Publicly available multimodal large language models for ocular surface infections: benchmarking against corneal specialists in triage, diagnosis and treatment.

BACKGROUND/AIMS: Ocular surface infections remain a major cause of visual loss worldwide, yet diagnosis often relies on slow or insensitive microbiolo...