Fungal Infection

Portable Electrochemiluminescence Microarray Sensor for Machine Learning-Assisted Quantitative Analysis of Zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin produced by Fusarium fungi and is widely present in cereal-based foodstuffs including wheat, rice, and maize. The exposure to ZEN can cause severe endocrine disruption and reproductive disorders. Therefore, we develop a portable electrode electrochemiluminescence (ECL) platform based on a micropillar electrode design for image-based quantitative analysi...

Determination of Fungiform Papilla Number Using Deep Learning Methods.

This study aimed to develop a deep learning-based method for the automatic detection and counting of fungiform papillae (FP) on the dorsal surface of the human tongue. FP density and morphology may serve as biomarkers for taste function and systemic disease diagnosis. Manual counting is time-consuming and subjective; therefore, an objective and reproducible artificial intelligence (AI) method was ...

Fungal infections: Classification performance and detectability with machine learning models.

This study explores the use of AI-driven machine learning algorithms for the early detection of fungal diseases in tomato plants, a method that enhanc...

Microbial succession from nursery to vineyard highlights the role of beneficial and pathogenic microbes in young vineyard yield.

BACKGROUND: The grapevine microbiome plays a central role in shaping vineyard performance, yet the influence of nursery inherited microbes on vineyard...

Deep Learning-Assisted Room-Temperature Phosphorescence Sensor Array Based on Host-Guest Doping for Visual Discrimination of Triazole Fungicides.

Detection and discrimination of structurally similar triazole fungicide (TF) subtypes remain highly desirable yet challenging. This work presents a st...

Support vector Regression-Optimized Ultrasonic-Assisted alkaline extraction of Chroogomphus rutilus Polysaccharides: Enhanced yield and preservation of helical conformations.

Polysaccharides from Chroogomphus rutilus (CRPs) exhibit promising bioactivities; however, conventional alkaline extraction (CAE) often results in low...

The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases - Between Potential and Real Clinical Support.

INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associated malignancy characterized by destructive tumors i...

Investigating the toxicological impacts of thiabendazole exposure on uterine corpus endometrial carcinoma utilizing network toxicology, machine learning, and molecular docking.

Uterine corpus endometrial carcinomas (UCEC) are common cancers of the female reproductive system linked to environmental chemicals. Thiabendazole (TB...

Distinct bile mycobiome signature identifies fungal peptide panel predictive for gallbladder carcinoma.

Carcinoma of the gallbladder (CAGB) carries a poor prognosis. While alterations in the bile microbiome and lipidome have been linked to CAGB developme...

AI-driven Predictive Models in Endourological Treatment of Urolithiasis: A Systematic Review of Nomogram Applications from EAU Endourology.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical planning, risk stratification, and outcome predict...

Integrating microbial bioremediation, multi-omics, and emerging technologies for polycyclic aromatic hydrocarbon (PAHs) detoxification.

Environmental organic pollutants, identified as Polycyclic Aromatic Hydrocarbons (PAHs), are widespread and toxic. These hydrocarbons are commonly pro...

Analytical validation of a highly accurate and reliable next-generation sequencing-based urine assay.

Urinary tract infections (UTIs) are diagnosed based on symptoms and confirmed by urine culture, despite its limitations in sensitivity. False-negative...

Advances in fungal ergothioneine: from biosynthesis to AI-driven industrial biomanufacturing.

Ergothioneine (EGT), a potent natural antioxidant from edible fungi, is highly valued for its antioxidant, anti-inflammatory, and cytoprotective effec...

Multi-Crop Sclerotinia sclerotiorum Apothecia Prediction Models for Irrigated Environments are Improved by On-Site Weather Monitoring and Supervised Machine Learning.

Sclerotinia sclerotiorum causes Sclerotinia stem rot, or white mold, on multiple economically important crops in Michigan. Soybean farmers and crop co...

Deep learning-based identification of visually similar foliar diseases in field-grown barley.

BACKGROUND: Accurate segmentation of foliar diseases under field conditions is essential for large-scale phenotyping, as breeding programs rely on rel...

Small RNAs as systemic signals in plant defense: mechanisms, challenges, and future directions.

Small RNAs (sRNAs) have emerged as central regulators of gene expression, coordinating development, stress responses, and immunity across plant tissue...

Bridging Artificial Intelligence, Machine Learning with Green Nanotechnology: A Visionary Framework for Smart Fungal Disease Management in Plants.

Fungal diseases in plants pose significant threats to global food security and sustainable agriculture, yet current management methods remain limited ...

Computational identification and multi-level validation of marine fungal metabolites as potent inhibitors of Acinetobacter baumannii GuaB.

Lightweight attention enhanced YOLOv11 for accurate multi class detection of brinjal diseases.

The cultivation of brinjal is seriously affected by various pathogens which affect crop yield and quality hence the importance of automated disease de...

AI-driven fungicide design: From target identification to field application.

Plant pathogenic fungi severely threaten global agriculture, causing substantial yield losses in staple crops and endangering food safety through myco...