Bacterial Infection

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 machine learning algorithms can accelerate AMR determination. However, these efforts have predominantly focused on bacterial pathogens. The significant morbidity, mortality, and healthcare costs associated with fungal infections highlight the need for accu...

Identification of Key Microbial Signatures Associated With Breast Cancer: Machine Learning-Based Approaches Using Gut Microbiome Data.

BACKGROUND: Breast cancer (BC) is one of the most common types of cancer incidence and mortality rates among women all over the world. Limitations in existing diagnostic methods, especially in low- and middle-income countries, require novel, noninvasive biomarkers. A complex and modifiable ecosystem, the gut microbiome has become a potential origin of such biomarkers because it has a systemic infl...

Data-Driven Prediction of Microbiological Quality in Oregano-Active Packaged Gilthead Sea Bream Fillets using Non-Invasive Spectroscopy and Machine Learning.

This study investigated the potential of FTIR spectroscopy and multispectral imaging (MSI) combined with machine learning to monitor microbiological q...

Overcoming resolution constraints in automated colony counting via a high-performance deep learning framework using SAHI.

Lightweight models perform poorly in bacterial colony counting when high-resolution Petri dish images are downscaled to 640 × 640 pixels. This study a...

Predicting Bacterial Radiation Resistance Through Identifying Novel Genomic Features.

Radiation resistance in bacteria is a critical trait with implications for biotechnology, medicine and environmental science. Deinococcus species poss...

Machine learning-based discovery of GW3965 as a therapeutic compound against invasive emm92-type group A Streptococcus.

A multi-drug resistant emm92-type strain of group A Streptococcus (GAS) has emerged as an important causative agent of invasive infections-particularl...

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...

Investigating Infection and Clinical Data to Predict Effective Antibiotic Therapy and Monitor Resistance Trends.

BACKGROUND: Data-driven approaches to effectively select antibiotics are crucial to improving patient outcomes and reducing antibiotic resistance. Thi...

Application of surface-enhanced Raman spectroscopy in the diagnosis of infectious diseases.

Surface-enhanced Raman spectroscopy (SERS) is increasingly emerging as a pivotal analytical technique in the field of clinical diagnostics. The diagno...

Gut microbiome composition and functional potential associate with incident type 2 diabetes in 4,685 adults from a Swedish prospective cohort.

Cross-sectional studies link gut microbiome alterations to type 2 diabetes (T2D), but prospective evidence remains limited. We aim to identify taxonom...

Stage-Associated Subgingival Dysbiosis Across the Periodontal Disease Spectrum in a Thai Cohort.

AIMS: This cross-sectional study aimed to investigate the subgingival microbiota and predict functional profiles across the 2018 EFP/AAP periodontal d...

Advancing poultry health: A meta-analysis of epitope-based and peptide-based vaccines against Avian Pathogenic E. coli with machine learning insights.

INTRODUCTION: Avian Pathogenic Escherichia coli (APEC) causes colibacillosis in poultry, which leads to tremendous economic losses. Traditional contro...

Diagnostic value of integrated albumin-to-leukocyte ratio risk modeling stratification and machine learning approaches for prediction of spontaneous bacterial peritonitis in cirrhotic patients.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) remains a life-threatening complication of liver cirrhosis, requiring accurate and rapid predictio...

Prediction of antimicrobial minimum inhibitory concentration from bacterial genomes using a scalable and interpretable machine learning approach.

Although machine learning models can predict antimicrobial susceptibility from bacterial whole genome sequencing (WGS), state-of-the-art approaches ar...

Overcoming LPS-mediated resistance in gram-negative pathogens: a review of LL-37 analogs and computational design strategies.

The increasing incidence of antimicrobial resistance (AMR) in Gram-negative bacteria has become a significant global health issue, driven primarily by...

Optimization of an improved chemically defined medium for high-efficiency expression of glucokinase in Escherichia coli.

BACKGROUND: Recombinant glucokinase (GLK), an important enzyme for blood glucose diagnostics, is commonly prepared in Escherichia coli (E.coli )for la...

Metagenomic polymorphic toxin effector and immunity profiling predicts microbiome development and disease-related dysbiosis.

Bacteria use antagonistic interbacterial weapons, such as polymorphic toxin secretion systems (TSS), to compete for niches in the human gut microbiome...

An Applied Framework of CLSM and Rheology for Controlling Foodborne Biofilms and Their Cleaning Agents and Disinfectants Resistance: A Review.

Biofilms formed by foodborne pathogens pose a significant threat to food safety, as they enhance microbial resistance to disinfectants and environment...

Improved Prediction of Invasive Bacterial Infections in Febrile Infants Using Machine Learning.

BACKGROUND: Existing guidelines for febrile infants aged 8 to 60 days use clinical appearance, age, and laboratory test results to assess the risk of ...

AI-designed OpenCRISPR-1 enables efficient targeted mutagenesis and prime editing in rice.

Recent advances in generative artificial intelligence (AI) have enabled the de novo design of genome-editing nucleases. For example, OpenCRISPR-1 offe...