Fungal Infection

Machine learning models for predicting indoor airborne fungal concentrations in public facilities utilizing environmental variables.

Airborne fungi are major contributors to substandard indoor air quality, with potential implications for public health, especially in public facilities. The risk of chronic exposure can be significantly reduced by accurately predicting airborne fungal concentrations. To manage indoor air quality, we developed machine learning (ML) models that predict airborne fungal concentrations in public facili...

Characterizing the microbiome recruited by the endangered plant in phosphorus-deficient acidic soil.

Phosphorus (P)-deficient soils serve as crucial habitats for endangered plant species. Microbiomes play pivotal roles in soil element cycling and in determining a plant's adaptability to the environment. However, the relationship between the endangered plant, microbiome, and soil stoichiometric traits, and how it affects plant adaption to P-deficient habitats remain largely unexplored. In this stu...

Understanding the impacts of drought on peanuts L.): exploring physio-genetic mechanisms to develop drought-resilient peanut cultivars.

Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production oc...

Prediction of Deoxynivalenol contamination in wheat kernels and flour based on visible near-infrared spectroscopy, feature selection and machine learning modelling.

Contamination of wheat by the mycotoxin Deoxynivalenol (DON), produced by Fusarium fungi, poses significant challenges to the quality of crop yield an...

Optimizing Corn Tar Spot Measurement: A Deep Learning Approach Using Red-Green-Blue Imaging and the Stromata Contour Detection Algorithm for Leaf-Level Disease Severity Analysis.

Visual detection of stromata (brown-black, elevated fungal fruiting bodies) is the primary method for quantifying tar spot early in the season because...

Fungal keratitis caused by : a case report.

BACKGROUND: We report a rare case of fungal keratitis caused by , a filamentous fungus that is widely distributed in soil and graminaceous plants.

Antimicrobial Activity of Tea and Agarwood Leaf Extracts Against Multidrug-Resistant Microbes.

Emerging multidrug-resistant (MDR) strains are the main challenges to the progression of new drug discovery. To diminish infectious disease-causing pa...

Isolation and screening of wood-decaying fungi for lignocellulolytic enzyme production and bioremediation processes.

The growing demand for novel enzyme producers to meet industrial and environmental needs has driven interest in lignocellulose-degrading fungi. In thi...

Antimicrobial Peptides as Broad-Spectrum Therapeutics: Computational Analysis to Identify Universal Physical-Chemical Features Responsible for Multitarget Activity.

Antimicrobial peptides (AMPs) hold significant potential as broad-spectrum therapeutics due to their ability to target a variety of different pathogen...

Prevalence of fungal colonization among patients with psoriasis in difficult-to-treat areas: impact of apremilast on mycotic burden and clinical outcomes.

INTRODUCTION: Fungi, including , may be a trigger or exacerbate psoriasis, especially in difficult to treat (DTT) areas, through the activation of IL-...

Antimycobacterial and Antifungal Activities of Leaf Extracts From .

The global problem of infectious and deadly diseases caused by microbes such as candida and mycobacteria presents major scientific and medical challen...

Polyketides and alkaloids from the fungus YB4-17 and -Fumiquinazoline J induce apoptosis, paraptosis in human hepatoma HepG2 cells.

Hepatocellular carcinoma (HCC) is one of the most common malignancies. The currently available clinical drugs for HCC frequently cause serious side ef...

Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning.

Huanglongbing (HLB), also known as citrus greening disease, is a devastating disease of citrus. However, there is no known cure so far. Recently, unde...

Integrating machine learning and multitargeted drug design to combat antimicrobial resistance: a systematic review.

Antimicrobial resistance (AMR) is a critical global health challenge, undermining the efficacy of antimicrobial drugs against microorganisms like bact...

Targeted isolation and AI-based analysis of edible fungal polysaccharides: Emphasizing tumor immunological mechanisms and future prospects as mycomedicines.

Edible fungal polysaccharides have emerged as significant bioactive compounds with diverse therapeutic potentials, including notable anti-tumor effect...

A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa).

Quantitative structure-activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving ac...

AI-assisted diagnosis of vulvovaginal candidiasis using cascaded neural networks.

UNLABELLED: Vulvovaginal candidiasis (VVC) is a prevalent fungal ailment affecting women globally. Timely and accurate diagnosis is crucial. Tradition...

Deep learning pipeline for accelerating virtual screening in drug discovery.

In the race to combat ever-evolving diseases, the drug discovery process often faces the hurdles of high-cost and time-consuming procedures. To tackle...

Deep Learning-Based Classification of Macrofungi: Comparative Analysis of Advanced Models for Accurate Fungi Identification.

This study focuses on the classification of six different macrofungi species using advanced deep learning techniques. Fungi species, such as , , , , ...

Enabling Demonstrated Consent for Biobanking with Blockchain and Generative AI.

Participation in research is supposed to be voluntary and informed. Yet it is difficult to ensure people are adequately informed about the potential u...