1. Biospeckle laser digital image processing for quantitative and statistical evaluation of the activity of ciprofloxacin onEscherichia coliK-12
- Author
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Jesús E. Andrades-Grassi, Hilda C. Grassi, Efrén D. J. Andrades, Ana Velásquez, Olga M. Belandria, Humberto Cabrera, and María Lorena Lobo-Sulbarán
- Subjects
Heteroscedasticity ,Veterinary medicine ,Serial dilution ,biology ,medicine.drug_class ,Antibiotics ,Condensed Matter Physics ,biology.organism_classification ,Industrial and Manufacturing Engineering ,Atomic and Molecular Physics, and Optics ,Ciprofloxacin ,Minimum inhibitory concentration ,Linear regression ,medicine ,Autoregressive integrated moving average ,Instrumentation ,Bacteria ,medicine.drug ,Mathematics - Abstract
Antibiotic susceptibility testing is a necessary step prior to the treatment of clinical infections. A major concern is the time required to obtain a fast and reliable result. The aim of this work is to use Biospeckle laser in a 15min assay for an antimicrobial susceptibility test of Ciprofloxacin in serial two-fold dilutions on Escherichia coli K-12 using Venereal Disease Research Laboratory (VDRL) plates. Analysis of images by video edition is performed on a quantitatively selected region of interest, and processed with ImageJ-ImageDP; and by the construction of time series and analysis with either statistical diagnostics tests or Autoregressive Integrated Moving Average (ARIMA) models. Antimicrobial susceptibility tests are also performed for the purpose of quantitative comparison, showing a profile that is comparable to the result obtained with ImageJ-ImageDP processing after 15min of antibiotic action. Only the time series of the least affected bacteria (low Ciprofloxacin concentration) behaves in an expected manner, being non-independent and mainly non-linear, non-normal, and heteroscedastic. The most affected bacteria (higher Ciprofloxacin concentration) are non-independent and tend to be linear, normal and heteroscedastic. Adjustment to a linear regression identifies both, the culture medium without bacteria and the most affected bacteria, normality identifies the most affected bacteria and heteroscedasticity-homoscedasticity distinguishes the presence-absence of bacteria, respectively. ARIMA models (1,1,1)(1,0,1)11 and (4,1,1)(1,1,1)11 fit the time series of the most affected bacteria while the latter also fits the culture medium without bacteria. The time series of the least affected bacteria are identified by a (7,1,2)(1,0,1)11 model. The non-linear, non-normal and heteroscedastic behavior of this group is probably responsible for its adjustment to a model with a relatively high parameter. The four methods: diagnostic statistical tests, fitting of ARIMA models, ImageJ-ImageDP and antimicrobial susceptibility tests, show similar results, being able to distinguish among the groups of assays with bacteria and Ciprofloxacin below and above the Minimal Inhibitory Concentration.
- Published
- 2019