Bacterial Infection

Machine-Learning Single-Stranded DNA Nanoparticles for Bacterial Analysis.

A two-dimensional nanoparticle-single-stranded DNA (ssDNA) array has been assembled for the detection of bacterial species using machine-learning (ML) algorithms. Out of 60 unknowns prepared from bacterial lysates, 54 unknowns were predicted correctly. Furthermore, the nanosensor array, supported by ML algorithms, was able to distinguish wild-type from its mutant by a single gene difference. In a...

Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine.

The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source tracking of fecal contamination. The performances of classification models on predicting the fecal source of geographical local and foreign samples were examined herein, by applying support vector machine (SVM) algorithm. Random forest (RF) and Adaboost ...

Deep learning for sensitive detection of Helicobacter Pylori in gastric biopsies.

BACKGROUND: Helicobacter pylori, a 2 × 1 μm spiral-shaped bacterium, is the most common risk factor for gastric cancer worldwide. Clinically, patients...

A scaffold hopping strategy to generate new aryl-2-amino pyrimidine MRSA biofilm inhibitors.

Infections that stem from bacterial biofilms are difficult to eradicate. Within a biofilm state, bacteria are upwards of 1000-fold more resistant to c...

An Exploratory Study of a New Vancomycin Eye Drops Formulation for Extemporaneous Compounding.

PURPOSE: Compounded eye drop solutions of vancomycin hydrochloride have important clinical applications, such as postoperative antimicrobial prophylax...

Pre-Trained Deep Convolutional Neural Network for Clostridioides Difficile Bacteria Cytotoxicity Classification Based on Fluorescence Images.

infection (CDI) is an enteric bacterial disease that is increasing in incidence worldwide. Symptoms of CDI range from mild diarrhea to severe life-th...

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases.

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotatio...

-Related Infections and their Significance: A 9-Year Retrospective Study.

INTRODUCTION: is a Gram-positive, catalase- and oxidase-negative, microaerophilic, nonmotile bacteria species rarely associated with human infections...

Degradation of poly(butylene adipate-co-terephthalate) by Stenotrophomonas sp. YCJ1 isolated from farmland soil.

In recent years, poly (butylene adipate-co-terephthalate) (PBAT) has been widely used. However, PBAT-degrading bacteria have rarely been reported. PBA...

Deep-Learning Resources for Studying Glycan-Mediated Host-Microbe Interactions.

Glycans, the most diverse biopolymer, are shaped by evolutionary pressures stemming from host-microbe interactions. Here, we present machine learning ...

Temporal variation and sharing of antibiotic resistance genes between water and wild fish gut in a peri-urban river.

Antibiotic resistance genes (ARGs) as emergence contaminations have spread widely in the water environment. Wild fish may be recipients and communicat...

Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing.

Rapid antimicrobial susceptibility testing (AST) is an integral tool to mitigate the unnecessary use of powerful and broad-spectrum antibiotics that l...

Infusion of short chain fatty acids in the ileum improves the carcass traits, meat quality and lipid metabolism of growing pigs.

Short chain fatty acids (SCFA) are the main products of indigestible carbohydrates undergoing bacterial fermentation in the hindgut, which are related...

Weissella cibaria EIR/P2-derived exopolysaccharide: A novel alternative to conventional biomaterials targeting periodontal regeneration.

Healing and regeneration of periodontium are considered as a complex physiological process. Therefore, treatments need to be addressed with highly eff...

Predicting antimicrobial resistance using conserved genes.

A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence ...

Anaerobic condition induces a viable but nonculturable state of the PCB-degrading Bacteria Rhodococcus biphenylivorans TG9.

Significant microbial removal of highly chlorinated polychlorinated biphenyls (PCBs) requires the cooperation of anaerobic and aerobic bacteria. Durin...

DeeplyEssential: a deep neural network for predicting essential genes in microbes.

BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provi...

Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our rec...

A Study of the Chemistries, Growth Mechanisms, and Antibacterial Properties of Cerium- and Yttrium-Containing Nanoparticles.

Under the current climate, physicians prescribe antibiotics for treating bacterial infections, and such a limitation to a single class of drugs is dis...

Machine learning-driven electronic identifications of single pathogenic bacteria.

A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report o...