Bacterial Infection

High-fidelity machine learning models for predicting antibacterial effects of cerium oxide nanoparticles across bacterial strains.

The primary objective of this study is to develop and validate robust data-driven models for accurately predicting bacterial growth inhibition induced by cerium oxide nanoparticles across different bacterial strains and experimental conditions. This study aims to develop and validate data-driven predictive models to quantify bacterial growth inhibition induced by cerium oxide nanoparticles under d...

Role of Ambler Position 104 in Defining Substrate Specificity in the KPC Family of β-Lactamases.

Carbapenem-resistant Gram-negative bacteria pose a critical clinical challenge, largely due to the dissemination of class A Klebsiella pneumoniae carbapenemases (KPCs). Residue 104 in the α3-α4 loop of KPC enzymes forms part of a hydrophobic node influencing active-site architecture and substrate specificity. We systematically evaluated 19 amino acid substitutions at position 104 in KPC-3 to deter...

OCTN1 variants shape innate immunity and predict individual response to anti-TNFα in ulcerative colitis patients: An exploratory study.

BACKGROUND: Ulcerative colitis (UC) exhibits substantial heterogeneity in inflammatory pathways and therapeutic response. The organic cation transport...

Cost-effectiveness of infection prevention and control measures for carbapenem-resistant Gram-negative bacilli: A systematic review protocol.

INTRODUCTION: Multidrug-resistant organisms, including carbapenem-resistant Gram-negative bacilli (CRGNB), have a heavy health and economic burden in ...

Deep Learning-Based Protein Half-Life Prediction for Identifying Rate-Limiting Enzymes in Metabolic Pathways to Alleviate Bottleneck Reactions.

In synthetic metabolic pathways, the intracellular level of enzymes is a critical determinant of pathway efficiency and, thus, short-lived enzymes cre...

Gram staining decipherment using an artificial intelligence-powered smartphone-based application.

Gram staining provides rapid microbiological information that may assist in empirical antimicrobial selection; however, the results are often interpre...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...

Machine Learning-Guided Synthetic Microbial Communities Enable Functional and Sustainable Degradation of Persistent Environmental Pollutants.

Persistent environmental pollutants require diverse microbial metabolic capabilities for effective degradation. While naturally occurring consortia or...

Antibiotic resistance prediction with an attention-based bi-LSTM clinical decision support system.

BACKGROUND AND OBJECTIVE: Antimicrobial resistance is recognized by the World Health Organization as a significant global health threat. In clinical p...

Machine learning-empowered smartphone platforms for sustainable point-of-care bacterial detection.

Smartphone-based biosensing has rapidly evolved into a practical route for decentralized bacterial detection, enabled by advances in miniaturized opti...

Herbal extracts as antibiotic adjuvants against ESKAPE pathogens: mechanisms and therapeutic potential.

The escalating crisis of antimicrobial resistance, particularly driven by ESKAPE pathogens, poses a serious threat to global public health. With the s...

A robotic wound care patient for evidence-based surgical site infection research.

BACKGROUND: Surgical site infections (SSIs) are among the most common and preventable postoperative complications, yet existing preclinical models lac...

Polyhydroxyalkanoates production by yeasts - Still possible?

Synthetic polymers have become ubiquitous in modern life due to their versatility, durability and low production costs, leading to a significant incre...

Analytical validation of a highly accurate and reliable next-generation sequencing-based urine assay.

Urinary tract infections (UTIs) are diagnosed based on symptoms and confirmed by urine culture, despite its limitations in sensitivity. False-negative...

Whole genome sequencing precision medicine strategy to shorten treatment for rifampicin-resistant tuberculosis (SMARTT): a pragmatic, randomised, single-blind phase 4 trial.

BACKGROUND: All patients with rifampicin-resistant tuberculosis should receive a short course of effective treatment. We aimed to evaluate the effecti...

Distinct signatures in the human gut and oral microbiomes of gastric cancer.

Microbiome dysbiosis is increasingly recognized as a hallmark of gastric cancer (GC). Here, we analyzed gut and oral shotgun metagenomic data from 317...

An Integrated Wasserstein GAN-Transformer Deep Learning Framework for Accurate Raman Spectral Identification of Escherichia coli Strains.

Rapid and precise discrimination of Escherichia coli strains─including both pathogenic and nonpathogenic variants─is essential for clinical diagnosis ...

Copper stress responses in Scenedesmus obliquus-Bacillus subtilis Consortia: Machine Learning-Based prediction of copper removal.

Copper pollution in wastewater is an environmental issue that requires efficient and sustainable waste treatment methods. To improve the efficiency of...

Robust prediction of Listeria monocytogenes, Listeria innocua and aerobic spoilage bacteria growth in food systems using Multilayer Perceptron Artificial Neural Networks.

Spoilage microorganisms and pathogenic bacteria can negatively impact food safety and stability, leading to potential health risks and economic losses...

Circulating Neutrophils Exhibit an Altered Immune Response in Chronic LUTS: An Image-Based Deep Learning Analysis.

INTRODUCTION AND HYPOTHESIS: Chronic lower urinary tract symptoms (LUTS) are characterised by persistent symptoms and elevated urinary leukocyte count...