Bacterial Infection

Antilogic, a new supervised machine learning software for the automatic interpretation of antibiotic susceptibility testing in clinical microbiology: proof-of-concept on three frequently isolated bacterial species.

OBJECTIVE: Antibiotic susceptibility testing (AST) is necessary in order to adjust empirical antibiotic treatment, but the interpretation of results requires experience and knowledge. We have developed a machine learning software that is capable of reading AST images without any human intervention and that automatically interprets the AST, based on a database of antibiograms that have been clinica...

Collaborative Robot Precision Task in Medical Microbiology Laboratory.

This study focuses on the feasibility of collaborative robot implementation in a medical microbiology laboratory by demonstrating fine tasks using kinesthetic teaching. Fine tasks require sub-millimetre positioning accuracy. Bacterial colony picking and identification was used as a case study. Colonies were picked from Petri dishes and identified using matrix-assisted laser desorption/ionization (...

Evaluation of the Effect of Comprehensive Nursing Interventions on Plaque Control in Patients with Periodontal Disease in the Context of Artificial Intelligence.

Plaque is a bacterial biofilm that adheres to each other and exists on the tooth surface, and new plaque can continuously reform after removing it fro...

Identification of antimicrobial peptides from the human gut microbiome using deep learning.

The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but the short lengths of AMPs pose a challenge for computational pr...

Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis.

Images of laser scattering patterns generated by bacteria in urine are promising resources for deep learning. However, floating bacteria in urine prod...

Rapid and accurate identification of pathogenic bacteria at the single-cell level using laser tweezers Raman spectroscopy and deep learning.

We report a new method for the rapid identification of pathogenic bacterial species at the single-cell level that combines laser tweezers Raman spectr...

A machine learning approach-based array sensor for rapidly predicting the mechanisms of action of antibacterial compounds.

Rapid and accurate identification of the mechanisms of action (MoAs) of antibacterial compounds remains a challenge for the development of antibacteri...

Effects of Irbesartan and Amlodipine Besylate Tablets on the Intestinal Microflora of Rats With Hypertensive Renal Damage.

The present study aimed to investigate the effects of irbesartan and amlodipine besylate tablets on the intestinal microflora of rats with hypertensi...

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule...

Biotechnological Innovations and Therapeutic Application of Pediococcus and Lactic Acid Bacteria: The Next-Generation Microorganism.

Lactic acid bacteria represent a worthwhile organism within the microbial consortium for the food sector, health, and biotechnological applications. T...

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods.

Bacterial infection is one of the most important factors affecting the human life span. Elderly people are more harmed by bacterial infections due to ...

T1SEstacker: A Tri-Layer Stacking Model Effectively Predicts Bacterial Type 1 Secreted Proteins Based on C-Terminal Non-repeats-in-Toxin-Motif Sequence Features.

Type 1 secretion systems play important roles in pathogenicity of Gram-negative bacteria. However, the substrate secretion mechanism remains largely u...

Enzyme-Photocatalyst Tandem Microrobot Powered by Urea for Escherichia coli Biofilm Eradication.

Urinary-based infections affect millions of people worldwide. Such bacterial infections are mainly caused by Escherichia coli (E. coli) biofilm format...

Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets.

Deep neural networks and other machine learning models are widely applied to biomedical signal data because they can detect complex patterns and compu...

Research Note: Study on the antibacterial activity of Chinese herbal medicine against Aspergillus flavus and Aspergillus fumigatus of duck origin in laying hens.

Aspergillus flavus and Aspergillus fumigatus were derived and identified from the ducks infected with fungi. In order to investigate the effectiveness...

Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection.

We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min...

DeLUCS: Deep learning for unsupervised clustering of DNA sequences.

We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence h...

Machine learning classification of trajectories from molecular dynamics simulations of chromosome segregation.

In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation...

ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic res...

Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network.

In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibilit...