Universal precautions

Patient-specific modeling identifies metabolic interventions for reversing glucose use reprogramming in alcohol-associated hepatitis.

Alcoholic hepatitis (AH) is an acute form of alcohol-associated liver disease with very few treatment options. Recent studies highlighted liver metabolic reprogramming in AH as an indicator of severity. We aim at identifying new intervention points to reverse liver metabolic dysregulation across varying degrees of AH. We develop 89 personalized genome-scale metabolic models by integrating a generi...

Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on an ancient disease with persistent, unresolved problems.

Tuberculosis (TB) is prevalent in Uganda and overlaps with a high rate of HIV/TB coinfection. While nearly all hospital-based TB cases in Kampala, the capital of Uganda, show clear TB symptoms, 30% or more of undiagnosed TB cases found through active screening are asymptomatic. Additionally, the host risk factors for TB in Kampala cannot be distinguished from environmental risk factors. These TB-s...

Genomic and socioeconomic drivers of antimicrobial resistance forecast to 2050.

Antimicrobial resistance (AMR) is rising worldwide, and a better understanding of the genetic and socioeconomic determinants tied to it may establish ...

Pan-pathogen vaccine approaches: Toward broad-spectrum immunity in a One Health era.

Emerging and re-emerging infectious diseases (EIDs) represent an escalating threat to global public health, as exemplified by outbreaks of COVID-19, E...

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening c...

Early antifungal resistance prediction based on MALDI-TOF mass spectrometry and machine learning.

Antimicrobial resistance (AMR) is a significant global health threat. Recent studies have shown that combining MALDI-TOF mass spectrometry with machin...

An artificial intelligence model for prediction of hepatocellular carcinoma risk in patients with chronic hepatitis C.

Hepatocellular carcinoma (HCC) still occurs in patients with hepatitis C who achieved sustained virologic response (SVR) after direct-acting antiviral...

Harnessing Artificial Intelligence to Counter Microbial Immune Evasion Strategies.

BACKGROUND: Microbial pathogens deploy sophisticated mechanisms to evade host immune responses, complicating the development of effective therapeutics...

Host-Pathogen Network and Eco-Evolutionary Drivers of Avian Influenza Transmission in Wild Birds.

Multi-host pathogens vary in how they utilise different hosts, yet the traits determining which species occupy central positions in transmission netwo...

Non-invasive assistive framework for sign language recognition using software-defined radio sensing and deep learning.

PURPOSE: This study proposes an early-stage, non-invasive assistive framework as a proof-of-concept for American Sign Language recognition (ASLR) usin...

HAMNet: Hierarchical Multi-scale Attention Network for precise disease detection in pearl millet using spatial fusion.

Pearl millet is a vital crop in arid and semi-arid regions, but its productivity is significantly impacted by fungal and bacterial diseases. Tradition...

Field-based and close-range multispectral imaging dataset for Huanglongbing (HLB) detection in orange trees: A resource for machine learning and digital agriculture.

This article presents a multispectral imaging dataset dedicated to training a machine learning algorithm for the in situ detection of Huanglongbing (H...

AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding.

The ability to reliably predict protective immunity against infectious diseases remains a central challenge in immunology, vaccine development, and pu...

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space.

BACKGROUND: Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens i...

Advances in rapid microbiological testing for animal diseases: A review.

Animal pathogenic microorganisms destabilize livestock economies and jeopardize human health through zoonotic transmission and foodborne illness. Trad...

AI-microbial hybrid biosensors: the next generation of intelligent detection systems.

The convergence of artificial intelligence (AI) and microbial biosensor technology is transforming pathogen detection, environmental surveillance, ant...

Development and validation of a machine learning-based diagnostic system for 22 pediatric respiratory pathogens: a large-scale multicenter study.

Respiratory tract infections (RTIs) are a significant cause of morbidity in children, caused by a wide range of pathogens. As treatment strategies dep...

Application of artificial neural networks to solve differential equations in Zika virus dynamics with exponential kernel derivatives.

The Zika virus is a relatively new pathogen that has quickly become a major issue in virology. Infectious mosquitoes of the Aedes genus, particularly ...

Machine learning models for predicting metabolic syndrome to support clinical decision-making in ART-treated adults living with HIV.

BACKGROUND: Metabolic syndrome (MetS) is an emerging complication among people living with HIV (PLHIV) receiving long-term antiretroviral therapy (ART...

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii.

Pneumocystis jirovecii is an opportunistic fungal pathogen responsible for Pneumocystis pneumonia (PCP) in immunocompromised patients. Antifolate drug...