Infectious Disease

OLink proteomic biomarker to predict clinical efficacy of Macaranga sinensis Müll.Arg: A nested case-control study.

ETHNOPHARMACOLOGICAL RELEVANCE: Despite the fact that herbal medicine has been used for a long time,...

Integrating GC-MS, high-throughput sequencing, and machine learning to elucidate flavor development and microbial succession in Italian-style dry-cured ham.

This study investigated effects of ripening on physicochemical, aroma profiles, and microbial succes...

Personalized Antibiogram: A Novel Multi-Task Machine Learning Framework for Simultaneous Prediction of Antimicrobial Resistance Profile with Enhanced Detection of Carbapenem Resistance in Enterobacteriaceae.

BACKGROUND: Conventional hospital antibiograms summarize aggregated resistance rates, limiting their...

Machine learning-assisted SERS detection of pyrethroid pesticides in edible fungi using a magnetic nanosensor.

Pyrethroid pesticide residues pose a significant global public health challenge, particularly in com...

Whole-genome sequencing and comparative genomics reveal antimicrobial potential and adaptive traits of Bacillus velezensis AM12.

The global rise of antimicrobial resistance has intensified the demand for novel antimicrobial agent...

Deep learning on meta-analytic data for therapeutic decision-making in central nervous system aspergillosis.

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite...

Innovative application of a traffic-prediction spatio-temporal graph convolutional network for dengue disease forecasting.

A novel hypothetical protein (SAUSA300_1684) confers excellent protection against multi-drug-resistant Staphylococcus aureus infection in the murine model.

Staphylococcus aureus is a leading cause of nosocomial infections, including sepsis, bacteraemia, pn...

Construction of a diagnostic model for tuberculosis based on long non-coding RNA.

BACKGROUND: The World Health Organization encourages the development of novel diagnostic tools based...

Substrate-mediated trade-offs between pollutant removal efficiency and ecological risks in constructed wetlands treating multi-antibiotic wastewater.

The environmental dissemination of antibiotic resistance genes (ARGs) is a cornerstone of the One He...

Deconstruction by C. thermocellum-from microbe mediated to dynamic redistribution of cellulosomes.

Clostridium thermocellum is one of the most efficient microorganisms for the deconstruction of cellu...

Predicting epistasis across proteins by structural logic.

Accurately predicting the phenotypic consequences of genetic variation is a major challenge for prec...

Stratification of viral shedding patterns in saliva of COVID-19 patients.

Living with COVID-19 requires continued vigilance against the spread and emergence of variants of co...

AI-Assisted Multiplex SYBR Green I-Based qPCR for the Identification and Quantitative Analysis of Oral Microbiota.

Conventional multiplex qPCR faces challenges in quantitative multipathogen detection due to limited ...

Grape expectations: disentangling environmental drivers of microbiome establishment in winegrowing ecosystems.

Microbial communities play a central role in viticulture, influencing wine characteristics (a concep...

Plasma glutamic acid predicts myelosuppression and mortality in septic patients using machine learning.

Myelosuppression is a common secondary manifestation of sepsis and is associated with increased morb...

Foundation models enable wearable signal screening for cardiovascular disease among people living with HIV.

BACKGROUND: Cardiovascular disease screening faces significant challenges in resource-limited settin...

An interpretable machine learning model for prediction of significant liver fibrosis in comorbid chronic hepatitis B and nonalcoholic fatty liver disease: a retrospective development and validation study.

Ai derivation and exploration of antibiotic class spaces.

PURPOSE: The rapid evolution of antibiotic-resistant bacteria poses an urgent global health crisis. ...

Predictive modeling and spatiotemporal analysis of TB in Argentina: Advancing control efforts through machine learning.

OBJECTIVES: To improve prediction and understanding of TB dynamics in Argentina, identifying key ris...