Fungal Infection

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 Trichoderma warrants further ecological and genetic characterization. Here we used machine learning to correlate genomic data from 37 Trichoderma strains with over 140 phenotypic traits, spanning metabolic versatility, biotic interactions, stress tolera...

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 for tracking microbial growth over time, struggle with differentiating between bacterial and fungal species due to their rigid predefined rules. Machine learning, particularly deep learning, offers a powerful alternative by learning complex patterns fr...

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...

Harnessing AMF-plant-microbe systems for heavy metal remediation.

Soil heavy metal pollution poses a global environmental threat, demanding effective and sustainable remediation strategies. Arbuscular mycorrhizal fun...

Multiharmonic imaging-based automated recognition of cutaneous T-cell lymphoma.

BACKGROUND: Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of non-Hodgkin lymphomas, with mycosis fungoides (MF) being the most common t...

Smart and Sustainable Polymers for Nanopesticides in Green Plant Protection Innovation.

Nanopesticides, fabricated by nanotechnology to stabilize pesticide active ingredients in formulations and/or dispersion systems at the nanoscale, are...

Digital decision support integrated with diagnostics and precision fungicide application for Southern Corn Leaf Blight in maize.

Molecular docking approaches in mycetoma: Toward improved patient management.

Mycetoma is a neglected tropical disease characterised by chronic, granulomatous inflammation of the subcutaneous tissues, often leading to disfigurem...

Untargeted Metabolomic and Lipidomic Profiles of Gingival Crevicular Fluid in the Context of Periodontitis.

AIM(S): This cross-sectional clinical study aimed to explore the untargeted metabolomic and lipidomic profiles in gingival crevicular fluid (GCF) obta...

Discriminating models of trait evolution.

A central challenge in comparative biology is linking present-day trait variation across species with unobserved evolutionary processes that occurred ...

Low resource federated learning for classification of nail disease by deploying cross-silo and heterogeneously dataset distributions.

Nail diseases, including such common conditions as fungus, and more serious issues like melanoma, may be important clues to the overall health and req...

Carbon-phosphorus exchange rate constrains density-speed trade-off in arbuscular mycorrhizal fungal growth.

Symbiotic nutrient exchange between arbuscular mycorrhizal (AM) fungi and their host plants varies widely depending on their physical, chemical, and b...

FungiGuard: identification of plant antifungal peptides with artificial intelligence.

Antifungal peptides (AFPs) are crucial for plant defense against biotic stress. Yet, no artificial intelligence tool specifically classifies plant AFP...

Multi-omics profiling of chronic immune-mediated skin diseases: SKINERGY protocol and strategic evaluation.

BACKGROUND: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin disease...

Semi-supervised multi-class pneumonia classification using a CNN-cascade forest framework.

Medical imaging diagnosis of pneumonia must be accurate at distinguishing between the various disease subtypes but must be resistant to sparse annotat...

iAFP-fLRM: Accurate identification of antifungal peptides via hybrid deep learning architecture and multi-modal feature fusion.

Fungal infections (mycoses) represent a significant and increasing global health concern, particularly in immunocompromised populations. The emergence...