Fungal Infection

Deep learning-based quantification of arbuscular mycorrhizal fungi in plant roots.

Soil fungi establish mutualistic interactions with the roots of most vascular land plants. Arbuscular mycorrhizal (AM) fungi are among the most extensively characterised mycobionts to date. Current approaches to quantifying the extent of root colonisation and the abundance of hyphal structures in mutant roots rely on staining and human scoring involving simple yet repetitive tasks which are prone ...

Submerged fermentation improves bioactivity of mulberry fruits and leaves.

OBJECTIVE: Mulberry ( spp.) fruits and leaves have been proven to possess nutraceutical properties. Due to its fast and easy growing characteristics, mulberry fruits (MF) and leaves (ML) potentially emerge as a great source of functional foods. This study aims to enhance bioactivities (antioxidant, anti-inflammation, and hypoglycemic activity) of MF and ML via submerged fermentation using bacteria...

Chlorinated metabolites with antibacterial activities from a deep-sea-derived fungus.

Chromatographic separation of the solid cultures of a deep-sea-derived fungus (MCCC 3A00308) resulted in the isolation of eight compounds. Their stru...

A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.

Onychomycosis is common. Diagnosis can be confirmed by various methods; a commonly used method is the histological examination of nail clippings. A de...

Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network.

Direct microscopic examination with potassium hydroxide is generally used as a screening method for diagnosing superficial fungal infections. Although...

Promising antimicrobial and antibiofilm activities of reduced graphene oxide-metal oxide (RGO-NiO, RGO-AgO, and RGO-ZnO) nanocomposites.

Microbial infections are considered one of the most dangerous infections in humans due to their resistance to most antimicrobial agents. In this study...

Towards automatic airborne pollen monitoring: From commercial devices to operational by mitigating class-imbalance in a deep learning approach.

Allergic diseases have been the epidemic of the century among chronic diseases. Particularly for pollen allergies, and in the context of climate chang...

Entomopathogenic fungus (Hypocreales: Cordycipitaceae) strain IMI 268317 colonises on tomato leaf surface through conidial adhesion and general and microcycle conidiation.

The entomopathogenic fungus strain IMI 268317, previously known as and , is currently used as a microbial insecticide to protect tomatoes from seriou...

Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the inductio...

First total synthesis of chromanone A, preparation of related compounds and evaluation of their antifungal activity against , a biofilm forming agent.

A straightforward and convenient approach for the first total syntheses of chromanone A and a related 7-OMe substituted natural product is reported. T...

Fungal melanin as a biocompatible broad-spectrum sunscreen with high antioxidant activity.

Melanin is considered a bio-inspired dermo-cosmetic component due to its high UV absorption and antioxidant activity. Among various melanin sources, f...

3-Decalinoyltetramic acids from kiwi-associated fungus sp. and their antibacterial activity against .

Four rare 3-decalinoyltetramic acid derivatives, zofielliamides A-D (1-4), were obtained from cultures of kiwi-associated fungus sp. Their structures...

Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them....

Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example.

This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on c...

Deep convolutional neural network: a novel approach for the detection of Aspergillus fungi via stereomicroscopy.

Fungi of the genus Aspergillus are ubiquitously distributed in nature, and some cause invasive aspergillosis (IA) infections in immunosuppressed indiv...

A novel method for clinical risk prediction with low-quality data.

In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital readmission, and chronic disease onset) are constan...

Computational approach for identification, characterization, three-dimensional structure modelling and machine learning-based thermostability prediction of xylanases from the genome of Aspergillus fumigatus.

Identification of thermostable and alkaline xylanases from different fungal and bacterial species have gained an interest for the researchers because ...

Deep Learning for Imaging and Detection of Microorganisms.

Despite tremendous recent interest, the application of deep learning in microbiology has still not reached its full potential. To tackle the challenge...

Branching principles of animal and plant networks identified by combining extensive data, machine learning and modelling.

Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animal...

The design and application of an automated microscope developed based on deep learning for fungal detection in dermatology.

BACKGROUND: Light microscopy to study the infection of fungi in skin specimens is time-consuming and requires automation.