Infectious Disease

Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.

Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this work, utilizing anaerobic bacteria capable of seeking out hypoxic areas for flourishing, we constructed a liposome-anchored anaerobic bacteria (Lab)-microrobot for self-driving and detachable delivery of immunity activators to tumor sites, thereby orche...

Prediction of Acute Kidney Injury in Critically ill Patients with Community-Acquired Pneumonia Using Machine Learning.

BackgroundThe incidence of acute kidney injury (AKI) is increased in patients with community-acquired pneumonia (CAP), contributing to poor outcomes in ICUs. Early identification of patients at high risk for AKI is essential for timely intervention. This study aimed to develop a machine learning model for predicting AKI in CAP patients.MethodsPatients with CAP were identified from the MIMIC-IV dat...

Morphological Profiling of Imaging Flow Cytometry Data Uncovers Heterogeneity in Infected Gephyrocapsa huxleyi Cultures.

Phytoplankton, such as the coccolitophore Gephyrocapsa huxleyi (G. huxleyi), has a major ecological impact through photosynthesis-the production of ox...

Advancing AMR Surveillance: Confluence of One Health and Big Data Integration : Converging One Health and Big Data for AMR.

Antibiotic resistance poses a critical global health threat, demanding robust surveillance systems to monitor its prevalence, patterns, and trends. Th...

Measurement, Characterization, and Mapping of COVID-19 Misinformation in Spain: Cross-Sectional Study.

BACKGROUND: The COVID-19 pandemic has been accompanied by an unprecedented infodemic characterized by the widespread dissemination of misinformation. ...

Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes.

OBJECTIVES: The early diagnosis and immunoregulatory mechanisms of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remain unclear, ...

Precision Medicine and Machine Learning to predict critical disease and death due to Coronavirus disease 2019 (COVID-19).

INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes Coronavirus Disease 2019 (COVID-19) and induces activation of in...

Improving Hepatitis B outcome prediction with ensemble machine learning: A study on predictive models and interpretability.

OBJECTIVE: Hepatitis B virus (HBV) is a significant global health threat, responsible for severe liver diseases such as liver failure, cirrhosis, and ...

A machine learning model for predicting severity-adjusted in-hospital mortality in pneumonia patients.

OBJECTIVE: This study aims to develop a customized severity adjustment tool for hospital deaths in pneumonia patients considering characteristics of K...

Chemokine-like factor-like MARVEL transmembrane domain-containing 1 identified as a novel target protein for immune dysregulation in sepsis: A machine learning and molecular dynamics framework for diagnostic biomarkers and therapeutic exploration.

BACKGROUND: Sepsis, a systemic inflammatory response syndrome precipitated by infection, involves critical immune dysregulation. Here, we aimed to eva...

Melioidosis molecular diagnostics: An update.

Melioidosis, a fatal tropical disease, presents a wide array of clinical manifestations, including abscesses, pneumonia, septic shock, bacteraemia, os...

AI-driven techniques for detection and mitigation of SARS-CoV-2 spread: a review, taxonomy, and trends.

The SARS-CoV-2 RNA virus, with its rapid spread and frequent genetic changes, has posed unparalleled obstacles for public health and treatment efforts...

LLM-Generated Multiple Choice Practice Quizzes for Pre-Clinical Medical Students; Prevalence of Item Writing Flaws.

Multiple choice questions (MCQs) are frequently used in medical education for assessment. Automated generation of MCQs in board-exam format could pote...

Analysis of disease severity and mortality prediction using machine learning during COVID-19.

This paper focuses on how machine learning (ML) algorithms and applications have been used to analyze disease severity and mortality prediction in COV...

Enzymatic carbon-fluorine bond cleavage by human gut microbes.

Fluorinated compounds are used for agrochemical, pharmaceutical, and numerous industrial applications, resulting in global contamination. In many mole...

Gut microbiota alterations are linked to COVID-19 severity in North African and European populations.

Although COVID-19 primarily affects the respiratory system, many patients experience gastrointestinal symptoms, suggesting a role for the gut microbio...

Trade-off between resistance and persistence in high cell density cultures.

Bacterial growth to high cell densities is commonly observed in infections, microbiomes, and biomanufacturing, yet there is limited understanding of h...

Fixed-bed studies and artificial neural network modeling for removal of fluoroquinolone antibiotics using a green MWCNT@E adsorbent.

Ciprofloxacin (CIP) and ofloxacin (OFL), commonly used fluoroquinolone antibiotics, have been frequently detected in water sources which can cause env...

Targeting Mycobacterial Dormancy Survival Regulator (DosR) With Generative Artificial Intelligence and Omics Methods.

Tuberculosis, driven by Mycobacterium tuberculosis, remains a global health challenge due to the pathogen's ability to enter a dormant state, evading ...

Prediction of Antibiotic Resistance Phenotypes and Minimum Inhibitory Concentrations in Using Machine Learning Analysis of Its Pan-Genome and Pan-Resistome Features.

Traditional experimental methods for determining antibiotic resistance phenotypes (ARPs) and minimum inhibitory concentrations (MICs) in bacteria are ...