Fungal Infection

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 activities. Emerging preclinical evidence indicates its efficacy in ameliorating bleomycin-induced Pulmonary Fibrosis (PF) in murine models. However, the molecular mechanisms mediating its anti-fibrotic effects remain poorly elucidated. This study was de...

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. Traditional disease detection methods, including manual inspection and conventional machine learning techniques, often suffer from inefficiencies due to subjectivity, time consumption, and limited feature extraction capabilities. Deep learning-based segmentat...

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 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...

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...

Integrating deep learning and field validation into a decision support system for Northern Corn Leaf Blight management in maize.

Northern Corn Leaf Blight (NCLB; also, Turcicum Leaf Blight, TLB), caused by Exserohilum turcicum (teleomorph: Setosphaeria turcica), is one of the mo...

Divergent fates: Polystyrene microplastics alter trifloxystrobin degradation and microbial ecology differently in agricultural soil vs. river sediment.

This study investigates the effects of polystyrene microplastics (PS-MPs) on trifloxystrobin (TRI) degradation behavior and microbial community struct...

A curated dataset and lightweight deep learning framework for tea leaf disease classification.

Tea (Camellia sinensis) is the world's second most consumed beverage, enjoyed daily by more than two billion people. In Bangladesh, it serves as a cor...

Exploration of soil microbial community: a comparative study between organic and conventional systems in perennial and annual crops.

​Soil microbiota is central to agroecosystem sustainability, influencing fertility, plant health, and resilience. Agricultural practices shape these c...

Spectrally optimised YOLOv10s-SeqOpt framework for real-time UAV-based early detection of avocado foliar diseases in indian orchards.

Avocado orchards in southern India experience annual yield losses of 20-40% due to foliar pathogens, including Anthracnose (Colletotrichum Gloeosporio...

An automated workflow for fungal cell counting, cell size and data analysis: enhancing throughput and accuracy with the cell analysis and counting tool using ilastik software (caactus).

BACKGROUND: The development of filamentous fungal cells from spore to mature mycelium is influenced by a myriad of environmental conditions. Tradition...

Integrating scanning electron microscopy, explainable deep learning, and ITS sequencing for accurate identification in some species Geastrum.

The differentiation of species within the genus Geastrum remains a challenging task due to the strong morphological similarity among taxa and the limi...

WormSpot: a machine learning-powered viability scoring platform in C. elegans for Candida pathogenicity studies.

UNLABELLED: Invasive Candida infections pose a critical health challenge, exacerbated by emerging antifungal resistance. Caenorhabditis elegans (C. el...

Breaking the culture habit: Complementing culture-based veterinary diagnostics with metagenomic data -A case study of feline and canine skin infections.

BACKGROUND: Skin infections have been described as the primary cause for veterinary small animal practice visits, frequently requiring topical and sys...

Artificial intelligence-assisted diagnosis and subtype differentiation of infectious keratitis.

BACKGROUND: Infectious keratitis (IK) is a major cause of corneal blindness world-wide, and prompt identification of IK and its etiologic subtype is e...

Multimodal artificial intelligence and the persistent challenge of early mycosis fungoides diagnosis.