ArticleMolecular biology reports2017
A new look at the drug-resistance investigation of uropathogenic E. coli strains.
Article in Molecular biology reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Effect of β - hydroxy - γ -aminophosphonate (β - HPC) on the hydrolytic activity ofFrontiers in microbiology · 2023Article
- Current and Emerging Treatment Options for Multidrug ResistantAntibiotics (Basel, Switzerland) · 2022Review
- Extrinsic role of gibberellin mitigating salinity effect in different rice genotypes.Frontiers in plant science · 2022Article
- Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (FTIR) and Artificial Neural Networks Applied to Investigate Quantitative Changes of Selected Soluble Biomarkers, Correlated withJournal of clinical medicine · 2020Article
- Antimicrobial Stewardship for Respiratory Pathogens in Swine.Antibiotics (Basel, Switzerland) · 2020Article
- Ciprofloxacin, amoxicillin, and aminoglycosides stimulate genetic and phenotypic changes in uropathogenic Escherichia coli strains.Virulence · 2019Article
- Fourier transform infrared spectroscopy: unlocking fundamentals and prospects for bacterial strain typing.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019Review
- The genetic background of antibiotic resistance among clinical uropathogenic Escherichia coli strains.Molecular biology reports · 2018Article
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Authors and funding
6 authors.
Funding
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Abstract
Bacterial drug resistance and uropathogenic tract infections are among the most important issues of current medicine. Uropathogenic Escherichia coli strains are the primary factor of this issue. This article is the continuation of the previous study, where we used Kohonen relations to predict the direction of drug resistance. The characterized collection of uropathogenic E. coli strains was used for microbiological (the disc diffusion method for antimicrobial susceptibility testing), chemical (ATR/FT-IR) and mathematical (artificial neural networks, Ward's hierarchical clustering method, the analysis of distributions of inhibition zone diameters for antibiotics, Cohen's kappa measure of agreement) analysis. This study presents other potential tools for the epidemiological differentiation of E. coli strains. It is noteworthy that ATR/FT-IR technique has turned out to be useful for the quick and simple identification of MDR strains. Also, diameter zones of resistance of this E. coli population were compared to the population of E. coli strains published by EUCAST. We observed the bacterial behaviors toward particular antibiotics in comparison to EUCAST bacterial collections. Additionally, we used Cohen's kappa to show which antibiotics from the same class are closely related to each other and which are not. The presented associations between antibiotics may be helpful in selecting the proper therapy directions. Here we present an adaptation of interdisciplinary studies of drug resistance of E. coli strains for epidemiological and clinical investigations. The obtained results may be some indication in deciding on antibiotic therapy.
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