Infectious Disease

Engineering of soluble bacteriorhodopsin.

Studies and applications of membrane proteins remain challenging due to the requirement of maintaining them in a lipid membrane or a membrane mimic. Modern machine learning-based protein engineering methods offer a possibility of generating soluble analogs of membrane proteins that retain the active site structure and ligand-binding properties; however, clear examples are currently missing. Here, ...

Prediction of bacterial and fungal bloodstream infections using machine learning in patients undergoing chemotherapy.

PURPOSE: This study aimed to develop a machine learning (ML) model to predict bloodstream infection (BSI) in chemotherapy patients.

Improving wastewater-based epidemiology through strategic placement of samplers

Wastewater-based epidemiology (WBE) is a fast emerging method for passively monitoring diseases in a population. By measuring the concentrations of ...

Microbial dysbiosis and its diagnostic potential in androgenetic alopecia: insights from multi-kingdom sequencing and machine learning.

Androgenetic alopecia (AGA), the most common form of hair loss, has been linked to dysbiosis of the scalp microbiome. In this study, we collected micr...

FOAM: A General Frequency-Optimized Anti-Overlapping Framework for Overlapping Object Perception

Overlapping object perception aims to decouple the randomly overlapping foreground-background features, extracting foreground features while suppres...

Antimicrobial peptide developed with machine learning sequence optimization targets drug resistant Staphylococcus aureus in mice.

As antimicrobial resistance rises, new antibacterial candidates are urgently needed. Using sequence space information from over 14,743 functional anti...

Clinical correlations of plasma sphingosine-1-phosphate and sphingolipid key enzymes in severe dengue using laboratory and machine learning approach.

BACKGROUND: Sphingolipids are crucial for vascular integrity and cellular homeostasis, with recent studies highlighting their role in viral diseases.

Accelerating antimicrobial stewardship: An AI-CDSS approach to combating multidrug-resistant pathogens in the era of increasing resistance.

OBJECTIVES: The World Health Organization has identified Klebsiella pneumoniae (KP) and Pseudomonas aeruginosa (PA) as significant public health threa...

Discovery of naturally inspired antimicrobial peptides using deep learning.

Non-ribosomal peptides (NRPs) are promising lead compounds for novel antibiotics. Bioinformatic mining of silent microbial NRPS gene clusters provide ...

Active capture-directed bimetallic nanosubstrate for enhanced SERS detection of Staphylococcus aureus by combining strand exchange amplification and wavelength-selective machine learning.

Staphylococcus aureus (S. aureus) is the leading risk factor for food safety and human health. Herein, a novel wavelength-selective machine learning -...

Artificial intelligence (AI) in point-of-care testing.

The integration of artificial intelligence (AI) into point-of-care testing (POCT) represents a transformative leap in modern healthcare, addressing cr...

Artificial Intelligence and Machine Learning in the Development of Vaccines and Immunotherapeutics Yesterday, Today, and Tomorrow

In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error experimentation and extensive in vivo testing, oft...

A Lightweight IDS for Early APT Detection Using a Novel Feature Selection Method

An Advanced Persistent Threat (APT) is a multistage, highly sophisticated, and covert form of cyber threat that gains unauthorized access to network...

Viral Dark Matter: Illuminating Protein Function, Ecology, and Biotechnological Promises

Viruses are the most abundant biological entities on Earth and play central roles in shaping microbiomes and influencing ecosystem functions. Yet, m...

Beyond True or False: Retrieval-Augmented Hierarchical Analysis of Nuanced Claims

Claims made by individuals or entities are oftentimes nuanced and cannot be clearly labeled as entirely "true" or "false" -- as is frequently the ca...

Machine Learning Accelerated Discovery of Antimicrobial Inorganic Nanomaterials.

The growing prevalence of infectious diseases and the increasing threat of bacterial resistance have drawn widespread attention to antimicrobial inorg...

Evolutionary accumulation modeling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance.

Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potent...

[Advances in the application of machine learning-related combined models in infectious disease prediction].

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture ...

Improving Bovine Brucellosis Diagnostics: Rapid, Accurate Detection via Blood Serum Infrared Spectroscopy and Machine Learning.

Diagnosing bovine brucellosis is a major challenge due to its significant economic impact, causing losses in meat and dairy production and its potenti...

SHAP-Driven Feature Analysis Approach for Epileptic Seizure Prediction.

Predicting epileptic seizures presents a substantial difficulty in healthcare, with considerable implications for enhancing patient outcomes and quali...