Infectious Disease

First-line combination therapy of immunotherapy plus anti-angiogenic drug for thoracic SMARCA4-deficient undifferentiated tumors in AIDS: a case report and review of the literature.

BACKGROUND: Thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT) exhibit a notably aggressive phenotype, which is associated with poor patient survival outcomes. These tumors are generally resistant to conventional cytotoxic chemotherapy, thereby limiting the availability of effective treatment options.

Phenotypic antibiotic resistance prediction using antibiotic resistance genes and machine learning models in Mannheimia haemolytica.

Mannheimia haemolytica is one of the most common causative agents of bovine respiratory disease (BRD); however, antibiotic resistance in this species is increasing, making treatment more difficult. Integrative-conjugative elements (ICE), a subset of mobile genetic elements (MGE), encoding up to 100 genes have been reported in Mannheimia haemolytica genomes to confer multidrug resistance, including...

Open-set deep learning-enabled single-cell Raman spectroscopy for rapid identification of airborne pathogens in real-world environments.

Pathogenic bioaerosols are critical for outbreaks of airborne disease; however, rapidly and accurately identifying pathogens directly from complex air...

Virtual Gram staining of label-free bacteria using dark-field microscopy and deep learning.

Gram staining has been a frequently used staining protocol in microbiology. It is vulnerable to staining artifacts due to, e.g., operator errors and c...

Enhanced swin transformer based tuberculosis classification with segmentation using chest X-ray.

BACKGROUND:: Tuberculosis disease is the disease that causes significant morbidity and mortality worldwide. Thus, early detection of the disease is cr...

Interpretable machine learning-based prediction of 28-day mortality in ICU patients with sepsis: a multicenter retrospective study.

BACKGROUND: Sepsis is a major cause of mortality in intensive care units (ICUs) and continues to pose a significant global health challenge, with seps...

NRGCNMDA: Microbe-Drug Association Prediction Based on Residual Graph Convolutional Networks and Conditional Random Fields.

The process of discovering new drugs related to microbes through traditional biological methods is lengthy and costly. In response to these issues, a ...

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...

ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer.

The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational ...

ProPr54 web server: predicting σ promoters and regulon with a hybrid convolutional and recurrent deep neural network.

σ serves as an unconventional sigma factor with a distinct mechanism of transcription initiation, which depends on the involvement of a transcription ...

SProtFP: a machine learning-based method for functional classification of small ORFs in prokaryotes.

Small proteins (≤100 amino acids) play important roles across all life forms, ranging from unicellular bacteria to higher organisms. In this study, we...

Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence.

Antimicrobial resistance refers to the ability of pathogens to develop resistance to drugs designed to eliminate them, making the infections they caus...

MO-GCN: A multi-omics graph convolutional network for discriminative analysis of schizophrenia.

The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these s...

High-throughput, rapid, and non-destructive detection of common foodborne pathogens via hyperspectral imaging coupled with deep neural networks and support vector machines.

Foodborne pathogens such as Bacillus cereus, Staphylococcus aureus, and Escherichia coli are major causes of gastrointestinal diseases worldwide and f...

Enhanced Sampling Simulations of RNA-Peptide Binding Using Deep Learning Collective Variables.

Enhanced sampling (ES) simulations of biomolecular recognition, such as binding small molecules to proteins and nucleic acid targets, protein-protein ...

Acoustic COVID-19 Detection Using Multiple Instance Learning.

In the COVID-19 pandemic, a rigorous testing scheme was crucial. However, tests can be time-consuming and expensive. A machine learning-based diagnost...

An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia.

BACKGROUND: Ventilator-associated pneumonia (VAP) is a common nosocomial infection in ICU, significantly associated with poor outcomes. However, there...

Effects of antibiotic therapy on the early development of gut microbiota and butyrate-producers in early infants.

BACKGROUND: Antibiotics, as the most commonly prescribed class of drugs in neonatal intensive care units, have an important impact on the developing n...

Isolation, identification and characteristics of from diseased rainbow trout ().

is an opportunistic pathogen that can infect humans, animals and aquatic species, which is widely distributed in different aquatic environments and p...

Plasma Epstein-Barr Virus DNA load for diagnostic and prognostic assessment in intestinal Epstein-Barr Virus infection.

BACKGROUND: The prospective application of plasma Epstein-Barr virus (EBV) DNA load as a noninvasive measure of intestinal EBV infection remains unexp...