Bacterial Infection

Real-time 3D tracking of swimming microbes using digital holographic microscopy and deep learning.

The three-dimensional swimming tracks of motile microorganisms can be used to identify their species, which holds promise for the rapid identification of bacterial pathogens. The tracks also provide detailed information on the cells' responses to external stimuli such as chemical gradients and physical objects. Digital holographic microscopy (DHM) is a well-established, but computationally intensi...

Paper-based fluorescence sensor array with functionalized carbon quantum dots for bacterial discrimination using a machine learning algorithm.

The rapid discrimination of bacteria is currently an emerging trend in the fields of food safety, medical detection, and environmental observation. Traditional methods often require lengthy culturing processes, specialized analytical equipment, and bacterial recognition receptors. In response to this need, we have developed a paper-based fluorescence sensor array platform for identifying different...

Combining deep learning and droplet microfluidics for rapid and label-free antimicrobial susceptibility testing of colistin.

Efficient tools for rapid antibiotic susceptibility testing (AST) are crucial for appropriate use of antibiotics, especially colistin, which is now of...

Nucleic Acid Plate Culture: Label-Free and Naked-Eye-Based Digital Loop-Mediated Isothermal Amplification in Hydrogel with Machine Learning.

Digital nucleic acid amplification enables the absolute quantification of single molecules. However, due to the ultrasmall reaction volume in the digi...

KEGG orthology prediction of bacterial proteins using natural language processing.

BACKGROUND: The advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing t...

Cardiovascular disease risk assessment through sensing the circulating microbiome with perovskite quantum dots leveraging deep learning models for bacterial species selection.

Perovskite quantum dots (PQDs) are novel nanomaterials wherein perovskites are used to formulate quantum dots (QDs). The present study utilizes the ex...

Dynamic Bayesian network structure learning based on an improved bacterial foraging optimization algorithm.

With the rapid development of artificial intelligence and data science, Dynamic Bayesian Network (DBN), as an effective probabilistic graphical model,...

Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.

BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) a...

Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.

In clinical bacteriology laboratories, reading and processing of sterile plates remain a significant part of the routine workload (30%-40% of the plat...

Multiplex Detection of Foodborne Pathogens using 3D Nanostructure Swab and Deep Learning-Based Classification of Raman Spectra.

Proactive management of foodborne illness requires routine surveillance of foodborne pathogens, which requires developing simple, rapid, and sensitive...

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspec...

Going to extremes: progress in exploring new environments for novel antibiotics.

The discoveries of penicillin and streptomycin were pivotal for infection control with the knowledge subsequently being used to enable the discovery o...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional m...

Biodegradation of ciprofloxacin using machine learning tools: Kinetics and modelling.

Recently, the rampant administration of antibiotics and their synthetic organic constitutes have exacerbated adverse effects on ecosystems, affecting ...

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbi...

Addressing the Research and Development Gaps in Modern Phage Therapy.

Antimicrobial resistance is on the rise globally, prompting increased research and development (R&D) of phage therapy as a strategy to address difficu...

Between Centralization and Fragmentation: The Past, Present, and Future of Phage Collections.

Despite over a century of collecting bacteriophages, there has been a persistent lack of interest in systematically cataloging resulting phage banks. ...

Nonionic surfactant Tween 80-facilitated bacterial transport in porous media: A nonmonotonic concentration-dependent performance, mechanism, and machine learning prediction.

The surfactant-enhanced bioremediation (SEBR) of organic-contaminated soil is a promising soil remediation technology, in which surfactants not only m...

Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due t...

Waste to resource: Mining antimicrobial peptides in sludge from metagenomes using machine learning.

The emergence of antibiotic-resistant bacteria poses a huge threat to the treatment of infections. Antimicrobial peptides are a class of short peptide...