Bacterial Infection

Machine learning at the edge for AI-enabled multiplexed pathogen detection.

Multiplexed detection of biomarkers in real-time is crucial for sensitive and accurate diagnosis at the point of use. This scenario poses tremendous challenges for detection and identification of signals of varying shape and quality at the edge of the signal-to-noise limit. Here, we demonstrate a robust target identification scheme that utilizes a Deep Neural Network (DNN) for multiplex detection ...

GutBug: A Tool for Prediction of Human Gut Bacteria Mediated Biotransformation of Biotic and Xenobiotic Molecules Using Machine Learning.

Dietary components and bioactive molecules present in functional foods and nutraceuticals provide various beneficial effects including modulation of host gut microbiome. These metabolites along with orally administered drugs can be potentially bio-transformed by gut microbiome, which can alter their bioavailability and intended biological or pharmacological activity resulting in individual or popu...

Bacteria-Specific Feature Selection for Enhanced Antimicrobial Peptide Activity Predictions Using Machine-Learning Methods.

There are several classes of short peptide molecules, known as antimicrobial peptides (AMPs), which are produced during the immune responses of living...

Cracking the code of cellular protein-protein interactions: Alphafold and whole-cell crosslinking to the rescue.

Integration of experimental and computational methods is crucial to better understanding protein-protein interactions (PPIs), ideally in their cellula...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large...

Protein complexes in cells by AI-assisted structural proteomics.

Accurately modeling the structures of proteins and their complexes using artificial intelligence is revolutionizing molecular biology. Experimental da...

Rational design of stapled antimicrobial peptides.

The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antib...

CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first-line imaging technique for...

Artificial Intelligence-Driven Image Analysis of Bacterial Cells and Biofilms.

The current study explores an artificial intelligence framework for measuring the structural features from microscopy images of the bacterial biofilms...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive bacterial infection (IBI) in febrile infants compare...

Artificial intelligence as a smart approach to develop antimicrobial drug molecules: A paradigm to combat drug-resistant infections.

Antimicrobial resistance (AMR) is a silent pandemic with the third highest global mortality. The antibiotic development pipeline is scarce even though...

Classification of pathogenic bacteria by Raman spectroscopy combined with variational auto-encoder and deep learning.

Rapid and early identification of pathogens is critical to guide antibiotic therapy. Raman spectroscopy as a noninvasive diagnostic technique provides...

Identifying Bacteria Species on Microscopic Polyculture Images Using Deep Learning.

Preliminary microbiological diagnosis usually relies on microscopic examination and, due to the routine culture and bacteriological examination, lasts...

Newest perspectives of glycopeptide antibiotics: biosynthetic cascades, novel derivatives, and new appealing antimicrobial applications.

Glycopeptide antibiotics (GPAs) are a family of non-ribosomal peptide natural products with polypeptide skeleton characteristics, which are considered...

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria.

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Mu...

Deep learning-based ensemble modeling of Vibrio parahaemolyticus concentration in marine environment.

Vibrio parahaemolyticus (V.p) is a marine pathogenic bacterium that poses a high risk to human health and shellfish industry, yet an effective regiona...

Chestnut-Tannin-Crosslinked, Antibacterial, Antifreezing, Conductive Organohydrogel as a Strain Sensor for Motion Monitoring, Flexible Keyboards, and Velocity Monitoring.

Flexible sensing devices (FSDs) fabricated using conductive hydrogels have attracted researchers' extensive enthusiasm in recent years due to their ve...

Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging.

In assessing food microbial safety, the presence of Escherichia coli is a critical indicator of fecal contamination. However, conventional detection m...

BCM3D 2.0: accurate segmentation of single bacterial cells in dense biofilms using computationally generated intermediate image representations.

Accurate detection and segmentation of single cells in three-dimensional (3D) fluorescence time-lapse images is essential for observing individual cel...

RMSCNN: A Random Multi-Scale Convolutional Neural Network for Marine Microbial Bacteriocins Identification.

The abuse of traditional antibiotics has led to an increase in the resistance of bacteria and viruses. Similar to the function of antibacterial peptid...