Bacterial Infection

A deep learning feature extraction-based hybrid approach for detecting pediatric pneumonia in chest X-ray images.

Pneumonia is a disease caused by bacteria, viruses, and fungi that settle in the alveolar sacs of the lungs and can lead to serious health complications in humans. Early detection of pneumonia is necessary for early treatment to manage and cure the disease. Recently, machine learning-based pneumonia detection methods have focused on pneumonia in adults. Machine learning relies on manual feature en...

Mechanism of Synergistic Photoinactivation Utilizing Curcumin and Lauric Arginate Ethyl Ester against and .

This study investigated the mechanism of how lauric arginate ethyl ester (LAE) improves the photoinactivation of bacteria by curcumin after diluting the 100 µmol/L stock curcumin-LAE micelle solution to the concentration used during the treatment based on the curcumin concentration. The photoinactivation of bacteria was conducted by irradiating the 1 µmol/L curcumin-LAE solution containing cocktai...

Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study.

: While Enterobacteriaceae bacteria are commonly found in the healthy human gut, their colonization of other body parts can potentially evolve into se...

Seasonal dynamics of bulk milk somatic cell count in grazing Norwegian dairy goats.

Somatic cell count (SCC) is a widely used indicator of milk quality in the dairy industry. It is a relatively good indicator of udder health in dairy ...

Deep learning enhanced multiplex detection of viable foodborne pathogens in digital microfluidic chip.

Culture plating is worldwide accepted as the gold standard for quantifying viable foodborne pathogens. However, it is time-consuming (1-2 days) and re...

Co-occurrence of heavy metals and antibiotics resistance in bacteria isolated from metal-polluted soil.

The indiscriminate deposition of metal-containing substances into the environment contributes significantly to high concentrations of metals in the so...

Deep learning and single-cell phenotyping for rapid antimicrobial susceptibility detection in Escherichia coli.

The rise of antimicrobial resistance (AMR) is one of the greatest public health challenges, already causing up to 1.2 million deaths annually and risi...

Optimization of laccase from Stenotrophomonas maltophilia E1 by submerge fermentation using coconut husk with its detoxification and biodecolorization ability of synthetic dyes.

Enzymatic degradation of synthetic dyes holds an immense promise for addressing the environmental concerns associated with the textile and dye industr...

Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy.

Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safegua...

Identifying ARG-carrying bacteriophages in a lake replenished by reclaimed water using deep learning techniques.

As important mobile genetic elements, phages support the spread of antibiotic resistance genes (ARGs). Previous analyses of metaviromes or metagenome-...

Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides.

Bioactive peptides are key molecules in health and medicine. Deep learning holds a big promise for the discovery and design of bioactive peptides. Yet...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 vaccine candidates identified by an artificial intel...

Methyl cellulose/okra mucilage composite films, functionalized with Hypericum perforatum oil and gentamicin, as a potential wound dressing.

There is a growing demand for the development of functional wound dressings enriched with bioactive natural compounds to improve the quality of life o...

Bacterial colony size growth estimation by deep learning.

The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide importan...

MACI: A machine learning-based approach to identify drug classes of antibiotic resistance genes from metagenomic data.

Novel methodologies are now essential for identification of antibiotic resistant pathogens in order to resist them. Here, we are presenting a model, M...

Open roads and bridge: Preservation of fresh beef by a packaging film constructed from photosensitizing bacterial cellulose.

Food packaging is now widely used in everyday life to protect food from certain environmental factors. In this work, we have successfully prepared a b...

Localization and phenotyping of tuberculosis bacteria using a combination of deep learning and SVMs.

Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fa...

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous ...

Enhanced detection of Listeria monocytogenes using tetraethylenepentamine-functionalized magnetic nanoparticles and LAMP-CRISPR/Cas12a-based biosensor.

BACKGROUND: Listeria monocytogenes is a pathogenic bacterium that can lead to severe illnesses, especially among vulnerable populations. Therefore, th...

Bacterial metabolism-triggered-chemiluminescence-based point-of-care testing platform for sensitive detection and photothermal inactivation of Staphylococcus aureus.

Post-operative pathogenic infections in liver transplantation seriously threaten human health. It is essential to develop novel methods for the highly...