Infectious Disease

Machine Learning Model Predicts Recurrent Clostridioides difficile Infection in Patients With Inflammatory Bowel Disease (Recur CDI-IBD).

INTRODUCTION: Clostridioides difficile infection (CDI) present a significant challenge in patients with inflammatory bowel disease (IBD), with high recurrence rates and complications. Predicting recurrent CDI (rCDI) in IBD patients is crucial for implementing targeted interventions to improve patient outcomes. This study aimed to develop and validate a predictive model (RecurCDI-IBD) using supervi...

A Smartphone-Read, Machine Learning-Enhanced Lanthanide Hydrogel Sensor for Multimodal and On-Site Detection of Kanamycin in Food Safety.

Residual kanamycin from veterinary use poses a persistent threat to environmental safety and public health, as its accumulation in water systems and animal-derived foods can foster antibiotic resistance and induce toxic effects. To address the urgent need for on-site monitoring, we developed mechanically robust, self-healing, dual-network hydrogels (Gel-1 and Gel-2) coordinated with lanthanide ion...

Vancomycin resistance in gram-positive infections: evolutionary strategies of survival.

Vancomycin is a critical glycopeptide antibiotic for treating severe infections caused by Gram-positive bacteria, particularly MRSA and Clostridioides...

Elucidating the link between NS-SNP-Induced protein conformational changes and drug resistance in Klebsiella pneumoniae.

The escalating drug-resistance of Klebsiella pneumoniae (K. pneumoniae), a leading cause of both community-acquired and nosocomial infections, poses a...

Investigation on the Molecular Mechanism of ORF7a Suppressing BST-2 Antiviral Activity through Structural Modeling of Their Protein-Protein Interface.

In the present work, a structural model for the protein-protein interface of bone marrow stromal cell antigen 2 (BST-2) and severe acute respiratory s...

CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2.

The third Critical Assessment of Computational Hit-finding Experiments (CACHE) challenged computational teams to identify chemically novel ligands tar...

Enhanced language models for predicting and understanding HIV care disengagement: a case study in Tanzania.

Sustained engagement in HIV care and adherence to ART are crucial for meeting the UNAIDS "95-95-95" targets. Disengagement from care remains a signifi...

Multidimensional analysis of clinical pharmacist intervention impact on hospital length of stay in pulmonary tuberculosis: a random forest-driven retrospective study.

Diagnosis and classification of infective endocarditis via efficient serum metabolic fingerprint analysis.

Infective endocarditis (IE) continues to pose significant clinical challenges as a life-threatening condition associated with 30 % mortality. The curr...

Classification and detection of Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes using Fourier-transform near infrared spectroscopy coupled with machine learning.

This study was conducted to investigate the potential use of Fourier-transform near-infrared (FT-NIR) spectroscopy combined with machine learning (ML)...

Noncanonical genetic markers resolve the pre-GOE emergence of aerobic bacteria in Earth's history.

The transition from anaerobic to aerobic life was a pivotal adaptation in Earth's history, yet the timing and genomic drivers remain poorly resolved. ...

Microclimates, land cover, and socioeconomic vulnerability shape Anopheles hotspots in Maryland, USA.

BACKGROUND: Anopheles mosquitoes pose notable public health concerns as competent vectors of malaria and other diseases. Although malaria is no longer...

Lifespan Pancreas Morphology for Control Versus Type 2 Diabetes Using AI on Largescale Clinical Imaging.

Understanding how pancreas size and shape change with normal aging is critical for establishing a baseline to detect deviations in type 2 diabetes and...

Mapping Antibiotic Photocatalytic Transformation and Resistance Risks with a DFT-Informed Machine Learning Workflow.

The photocatalytic degradation of antibiotics is effective but may yield transformation products (TPs) that sustain or amplify ecological risks, inclu...

Artificial intelligence in lung scintigraphy.

Lung scintigraphy is a common nuclear medicine procedure for evaluating pulmonary perfusion and ventilation, particularly in the diagnosis of pulmonar...

Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba Networks.

Sepsis-associated acute kidney injury (SA-AKI) is a heterogeneous clinical syndrome and a leading cause of mortality in intensive care units (ICUs). I...

One-Step Design of Potent and Nonhemolytic Antimicrobial Peptides by Using a Database-Guided, Nonmachine Learning Approach.

The search for antibiotics is urgent because of the global antibiotic resistance problem. While a variety of strategies are actively sought, interest ...

Large-scale serum N-glycomics tracks N-glycosylation dynamics in hepatocellular carcinoma progression and enables early diagnosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, yet the role of N-glycosylation in its pathogenesis remains unclear. We applied...

Cha-PO and CVNet: a hybrid approach for automated cataract detection using adaptive feature selection and deep learning for high accuracy and efficiency.

Early detection of cataract is crucial for thwarting visual impairment worldwide, and the utilization of automated cataract detection through medical ...

An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study.

Sepsis is a major global health crisis where early recognition and effective management remain significant challenges for healthcare systems. As part ...