The diagnosis is an important factor in healthcare care, and it is essential to identify microorganisms that cause infections and diseases. The application of artificial intelligence (AI) systems can improve disease management, drug development, antibiotic resistance prediction, and epidemiological monitoring in the field of microbial diagnosis. AI systems can quickly and accurately detect infections, including new and drug-resistant strains, and enable early detection of antibiotic resistance and improved diagnostic techniques. The application of AI in bacterial diagnosis focuses on the speed, precision, and identification of pathogens and the ability to predict antibiotic resistance.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10749263 | PMC |
http://dx.doi.org/10.7759/cureus.49366 | DOI Listing |
Microb Cell Fact
January 2025
Human Microbiology Institute, New York, NY, 10014, USA.
Our previous studies revealed the existence of a Universal Receptive System that regulates interactions between cells and their environment. This system is composed of DNA- and RNA-based Teazeled receptors (TezRs) found on the surface of prokaryotic and eukaryotic cells, as well as integrases and recombinases. In the current study, we aimed to provide further insight into the regulatory role of TezR and its loss in Staphylococcus aureus gene transcription.
View Article and Find Full Text PDFCurr Microbiol
January 2025
Department of Clinical Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Bovine mastitis is the most widespread disease that causes financial loss in the dairy industry. Staphylococcus aureus is a well-researched multidrug-resistant opportunistic bacterium that is frequently linked to subclinical mastitis and causes significant economic losses. A further problem in the management of S.
View Article and Find Full Text PDFBiosens Bioelectron
December 2024
Department of Pharmaceutical Analysis, School of Pharmacy, Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Ningxia Medical University, Yinchuan, 750004, China. Electronic address:
Efficient analysis of active ingredient in complex natural products is crucial for drug discovery, but developing a simple method for this is challenging. The discovery of drugs against bacterial resistance is urgent because drug-resistant bacteria produce β-lactamases, which inactivate antibiotics and increase infection risks, particularly the AmpC β-lactamase. Here, an integrated analytical model based on colorimetric sensing and magnetic nanoparticles (MNPs) affinity chromatography was developed for screening AmpC β-lactamase inhibitors.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:
The dissemination of antibiotic resistance genes (ARGs) in activated sludge (AS) systems poses significant environmental and public health challenges. The role of viruses, primarily bacteriophages, in storing and spreading ARGs in AS systems remains largely unexplored. This study characterized the viral community, virus-associated ARGs (vir_ARGs), and mobile genetic elements (MGEs) of aerobic AS viromes from eight wastewater treatment plants (WWTPs) in eastern China.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; International Joint Laboratory on Food Safety, Institute of Analytical Food Safety, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, China. Electronic address:
Antibiotic resistance genes (ARGs) are markers of drug-resistant pathogens, monitoring them contributes to prevent resistance to drugs. The detection methods for ARGs including PCR and isothermal amplification are sensitive and selective. However, it may take several hours or cannot be used on spot.
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