Fungal Infection

Correction: Machine learning-assisted SERS detection of pyrethroid pesticides in edible fungi using a magnetic nanosensor.

Intracellular acidification by microbiota-derived valeric acid facilitates trans-kingdom ecology limiting Candida parapsilosis colonization.

In hematopoietic cell transplant (HCT) patients, intestinal Candida parapsilosis expansion and translocation can cause life-threatening candidemia, yet whether commensal intestinal bacteria prevent Candida expansion remains incompletely defined. Here, we trained a machine learning model on supernatant metabolomic profiles of Lachnospiraceae to identify bacteria-derived inhibitors of fungal growth,...

MeDiCNet: Integrating Multi-scale Dynamic Convolution and Enhanced Position-Aware Transformer for DNA Methylation Site Prediction.

DNA methylation is a covalent modification of cytosine and adenine bases that regulates gene expression and underlies diverse biological processes and...

Learning continuous activation fields from microscopic SEM images of lycoperdioid fungi via CNN-guided neural operator modeling.

Accurate interpretation of microscopic morphological features is critical for resolving taxonomic boundaries in morphologically similar fungal taxa, y...

Pan-pathogen vaccine approaches: Toward broad-spectrum immunity in a One Health era.

Emerging and re-emerging infectious diseases (EIDs) represent an escalating threat to global public health, as exemplified by outbreaks of COVID-19, E...

Hybrid Modeling for Industrial Fermentation Processes with an 'Intra-Batch Experimental Design'.

Successful development of a predictive digital twin or digital shadow enabling improved batch planning and process optimization of industrial fungal f...

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 machin...

Attention-enhanced GNN model for fungal disease classification in spinach leaves using monospectral imaging.

Plant leaf diseases must be detected and treated early to improve crop yield and reduce agricultural losses. However, pixel-level representations and ...

Visualisation and Prediction of Phosphate Deficiency via Auto-Glowing Plant Bioluminescent Sensors.

This study introduces BioLumiPi, a novel, low‐cost, and non‐invasive biosensor plant, engineered by combining a phosphate (Pi) deficiency‐induced prom...

Integrated Network Pharmacology, Molecular Docking, and Experimental Validation for Uncovering the Pharmacodynamic Basis of Sanghuang against Human Pulmonary Fibrosis.

INTRODUCTION/OBJECTIVE: Sanghuang, a traditional Chinese medicinal fungus, exhibits well-documented anti-inflammatory, antioxidant, and antitumor acti...

HAMNet: Hierarchical Multi-scale Attention Network for precise disease detection in pearl millet using spatial fusion.

Pearl millet is a vital crop in arid and semi-arid regions, but its productivity is significantly impacted by fungal and bacterial diseases. Tradition...

Multikingdom microbiome-based machine learning enables multiple sclerosis diagnosis.

Emerging evidence suggests a role for the gut bacteria in the pathogenesis of multiple sclerosis (MS); however, the role of other microorganisms and t...

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...

Predicting the antifungal effects of ethanolic propolis and geopropolis extracts on Aspergillus flavus growth using mechanistic and machine-learning models.

This study evaluated the antifungal potential of ethanolic propolis (EEP) and geopropolis (EEG) extracts against Aspergillus flavus, integrating mecha...

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii.

Pneumocystis jirovecii is an opportunistic fungal pathogen responsible for Pneumocystis pneumonia (PCP) in immunocompromised patients. Antifolate drug...

Genome-wide analysis of the invasive fungal pathogen Neopestalotiopsis reveals high genomic diversity, effector repertoires, and the assessment of fungicide resistance risks.

Neopestalotiopsis species (spp.) have recently emerged as major pathogens worldwide, causing leaf spot, fruit rot, and crown rot of strawberry, result...

Artificial intelligence in drug discovery for fungal diseases: a scoping review.

BACKGROUND: Fungal diseases represent a global health threat, with high mortality rates and growing antifungal resistance demanding new therapeutic st...

Advancing One Health: Innovations and Future Directions in Mycotoxin Detection, Management, and Prevention-Narrative Review.

Mycotoxins, toxic secondary metabolites generated by fungi such as Aspergillus, Fusarium, and Penicillium species pose substantial concerns to food sa...

A hybrid deep learning model with adaptive feature fusion for automated rice leaf disease detection and classification.

Many countries greatly rely on agriculture as a means of livelihood and economic growth. Even the most industrialized countries need food, medicine, c...

Artificial intelligence in antimicrobial drug discovery: predictive and generative strategies.

INTRODUCTION: The slow pipeline of antimicrobial drug development stands in stark contrast to the continued expansion of microbial infections, which p...