Bacterial Infection

Living Inorganic Nanomaterials: Design, Preparation, and Biomedical Applications.

Living inorganic nanomaterials are defined as inorganic nanostructures that are integrated with living bacteria, cells, or biologically active cell-derived components. This unique integration addresses key limitations of traditional inorganic nanomaterials in biomedical applications, including poor biocompatibility and limited ability to cross physiological barriers. This review outlines the devel...

Spectroscopic discrimination of bacterial species of variable pathogenicity through explainable machine learning.

Rapid and accurate identification of bacterial pathogens and their degree of pathogenicity is essential for guiding antimicrobial therapy. Current culture-based methods require a timeframe of at least 24-48 h for species-level identification alone, which often leads to substantial disease progression and increases the propensity of antimicrobial resistance (AMR). Surface-Enhanced Raman Spectroscop...

Machine Learning to Identify Bacteremia and Meningitis in Febrile Infants: A Systematic Review.

CONTEXT: The accurate identification of febrile infants who are at risk for invasive bacterial infections (IBIs), ie, bacteremia and meningitis, is es...

Development and validation of a novel multimodal deep neural network model based on CBC digit parameters and scattergrams for rapid hematolymphoid malignancy classification: a multicenter cohort study.

BACKGROUND: Rapid screening of hematolymphoid malignancies (HMs) by complete blood cell count (CBC) is crucial for choosing the next appropriate worku...

Machine learning-enabled label-free SERS for microbial sensing: Toward robust, generalizable, and deployable workflows.

Label-free surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) provides a rapid, reagent-light approach to microbial detect...

TACTIC: A transfer learning framework to predict drug interactions in emerging pathogens.

Machine learning (ML) is necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However,...

Machine learning-guided discovery of spirocyclic inhibitors targeting Mycobacterium tuberculosis FtsZ.

Tuberculosis continues to pose serious threats to global public health and calls for the design of new drugs that can target key bacterial proteins. T...

Explainable machine learning deciphers and quantifies material-microbe-methane pathways in zero-valent iron-enhanced anaerobic digestion.

Zero-valent iron (ZVI) has been widely applied to enhance methane recovery in anaerobic digestion (AD), but how ZVI material properties and operating ...

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission event...

Conserved 3' stem-loop structures enable comprehensive analysis of bacterial transcription termination in metagenomes.

BACKGROUND: Bacterial transcription termination is a critical yet underexplored layer of gene regulation in microbial ecosystems. Existing computation...

Artificial intelligence and CRISPR-based approaches for targeted delivery of bacteriophages.

The rapid emergence of multidrug-resistant (MDR) bacteria has increased interest in bacteriophage therapy as a promising alternative to conventional a...

Machine learning-based prediction of E. coli infection in hospitalized patients using a no-code analytical framework.

Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs....

Spatiotemporal temperature trajectories underpin predictive modeling of microbial succession in single-batch high-temperature daqu solid-state fermentation.

Spontaneous solid-state fermentation (SSF) efficiency and product quality depend on microbial consortia regulation under dynamic temperature regimes, ...

Strain-Level Food Surveillance of Escherichia coli Using a Specific-Nonspecific Hybrid Sensor Array Strategy.

Array-based sensing platforms have advanced rapidly in recent years, offering strong potential for high-throughout and multiplexed detection. However,...

Antimicrobial Peptides and Biofilms: From Molecular Interactions to Therapeutic Control.

The rising problem of antimicrobial resistance (AMR), further complicated by the resilience of bacterial biofilms, calls for the discovery of new ther...

The Role of Intracellular ROS in the Development of Antimicrobial Resistance:A Convergent Mediator Linking Mutations and Horizontal Gene Transfer.

The development of antimicrobial resistance (AMR) is a major threat to global public health and environmental security. While antibiotics are known dr...

A review of bloodstream infections-pathogens, pathogenesis, diagnostic strategies, treatment methods-challenges and future aspects.

PURPOSE: Bloodstream infections (BSIs) remain a major cause of morbidity and mortality worldwide and continue to represent a substantial challenge to ...

BanglaRiceLeaf: A benchmark dataset for automated rice leaf disease detection and health classification in Bangladesh.

Rice leaf diseases pose a major challenge to crop health and agricultural productivity, particularly when timely and accurate diagnosis is required un...

Microbially driven microplastic degradation: From mining functional microbiota to enhancing remediation potential in diverse environments.

Microplastic (MPs) pollution poses a global threat to ecosystems and human health. Traditional physicochemical methods face limitations like high cost...

Spatial distribution and determinants of antimicrobial resistance in livestock across pathogen types, animal species and antimicrobial classes.

Antimicrobial resistance (AMR) in livestock is a growing global health concern with important implications for food security, human and animal health....