Fungal Infection

Coupling ensemble learning with multi-omics: a novel data-driven strategy for Daqu quality assessment and validation.

Daqu, a fermentation starter for traditional fermented foods, is produced by complex microbial communities; it is generally evaluated using conventional methods based on subjective sensory perception and limited physicochemical indicators. These approaches have several limitations, including poor consistency and low repeatability, making it challenging to meet industrial demands for a transition f...

Rapid assessment of pesticide toxicity in aquatic ecosystems using deep learning-based automatic duckweed counting method.

Pesticides are widely used in agriculture to control weeds, insects, and diseases that threaten crop yields. However, their extensive use raises concerns about environmental impacts, particularly in aquatic ecosystems, which are vulnerable to contamination through runoff and leaching. To assess the toxicity of pesticides to aquatic plants, we applied an optimized automated duckweed (Wolffia globos...

Next-generation strategies for PLA degradation: microbial consortia, metagenomics, enzyme engineering and AI-guided approaches.

Polylactic acid (PLA) is one of the most widely used biodegradable bioplastics; however, its slow degradation under natural conditions limits its envi...

Systematic review of prediction models and meta-analysis of risk factors for invasive fungal infection in children.

OBJECTIVES: To review the application of prediction models and risk factors identified by prediction models for invasive fungal infection (IFI) in chi...

Hybrid Modeling of Cercospora Leaf Spot Epidemiology: Integrating Mechanistic and Machine Learning Approaches Using Remote-Sensing and Environmental Data.

Despite advances in modeling and sensing, no study has previously integrated mechanistic, meteorological, and uncrewed aerial vehicle (UAV) data into ...

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts.

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resi...

Advances in the laboratory diagnosis of non-viral microbial keratitis.

Infectious keratitis remains a leading cause of corneal blindness and visual impairment worldwide, with bacterial, fungal, amoebic and viral pathogens...

A collaborative strategy of multi-technology integration for mycotoxin risk assessment and early warning in edible and medicinal plants.

BACKGROUND: Mycotoxins are toxic secondary metabolites of toxigenic fungi, posing a significant threat to human health due to their widespread contami...

Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology.

PURPOSE: Standard supervised learning assumes deterministic labels (e.g., positive or negative, present or absent), neglecting the diagnostic uncertai...

The essential role of methylation in maize (Zea mays) defense against the seed-colonizing fungus Aspergillus flavus.

UNLABELLED: The interaction between maize (Zea mays) and Aspergillus species poses a huge threat to global food safety due to the production of aflato...

Artificial intelligence-Driven detection and decision support system for precision management of maize downy mildew.

Artificial intelligence (AI) enables rapid and precise plant disease detection, offering transformative potential for crop protection. Maize downy mil...

Graph data science in fungal biotechnology: Opportunities and applications.

Fungal biotechnology is crucial for generating high-value enzymes and fermentation products. Despite its industrial importance, major knowledge gaps i...

A Gradient-Based Machine-Learning Inspired Inverse Modeling Approach for Characterization of Nonlinear Tissue Properties.

PURPOSE: Characterization of anisotropic nonlinear material properties along with fiber directions for soft tissues based on known deformations (strai...

Phenogenomics reveals the ecology and evolution of Trichoderma fungi for sustainable agriculture.

Trichoderma fungi support sustainable agriculture by suppressing plant diseases and improving crop performance. However, emerging pathogenicity of Tri...

AI Algorithms in the Pharmaceutical Environment: Poster presented at PDA Microbiology Conference 2025.

In the pharmaceutical industry, image analysis plays a crucial role in microbial identification. Traditional parametric algorithms, while effective fo...

Identification of Aspergillus at section and species levels by artificial intelligence-based microscopic morphology image recognition.

Rapid and accurate identification of Aspergillus species in clinical microbiology laboratories is crucial for aspergillosis diagnosis and antifungal t...

Bacterial laccases for green remediation of contaminants of emerging concern: from molecular cloning to metagenomic and computational insights.

Contaminants of emerging concern (CECs) are increasingly recognized for their persistence, widespread occurrence, and potential risks to environmental...

Microbial fermentation of cereals: nutritional, techno-functional, and compositional transformations toward data-driven process optimization.

Cereal fermentation represents a cornerstone of food bioprocessing that transforms staple grains into nutrient-dense, functionally enhanced ingredient...

A novel transformer-based platform for the prediction and design of biosynthetic gene clusters for (un)natural products.

Biosynthetic gene clusters (BGCs), comprising sets of functionally related genes responsible for synthesizing complex natural products, are a rich sou...

Real-time identification and quantification of apple scab on fruit in preharvest and postharvest conditions using YOLO11: a deep learning approach.

BACKGROUND: Apple scab (AS), caused by the fungal pathogen Venturia inaequalis, is a major disease of apple that manifests as lesions on leaves and fr...