Biology subjects

AC Marca Home Care,

Publications and source records attributed to AC Marca Home Care,.

3 recordsLinked to original sources

bioRxiv2020

Iterative Cochran's C test as a multivariate method to detect higher than expected variability: a microbiological inter-laboratory ring trial as a case-study

IntroductionAn interlaboratory calibration analysis was carried out to validate a methodology for a European standard for domestic laundry disinfection, using different doses of disinfectant and microorganisms. ISO 5725-2 and ISO 13528 form the basis of interlaboratory validations of quantitative methods, but there is a need for a simple graphical method to detect differences in laboratory behavior in terms of accuracy and variability. ObjectiveA novel multivariate method based on the classical Cochrans C test, as well as PCA and bootstrapping, which allows the inclusion of different correlated variables, was applied to identify higher variability than expected in factor (e.g. laboratories) levels, and the detection of multivariate outliers in a reduced space. MethodsThe proposed method is based on resampling, using the same sample many times but removing cases at random and performing Cochrans C test for all the variables together in a reduced space. ResultsThe method was tested by checking 7 laboratories for high variability in different parameters (logarithmic reduction (LR), cross contamination (RI), and wash water (WW)). After applying the proposed statistical analyses, no reasons were found to reject any of the participating laboratories. Multiple applications of the method are possible and we describe a case study in which the multivariant iterative Cochrans C test was used: variability detection with multiple microbiological parameters (with high variability) during an interlaboratory ring trial.

microbiology↗

bioRxiv2020

Statistical calibration of microbial suspensions in carrier controls during a textile disinfection ring trial

IntroductionThe high number of uncontrollable variables in microbiological systems increases experimental complexity and reduces accuracy, potentially leading to data misinterpretation or uncorrectable errors. During an interlaboratory calibration analysis it was observed that the microbial logarithmic reduction (LR) caused by disinfectants depends not only on the type of disinfectant but also on the initial microbial load in the fabric carriers, which can produce a misinterpretation of the results. Fabric carriers are commonly used in standard tests such as EN16616 and ASTM2274. ObjectiveA method based on statistical calibration is proposed using a regression line between N0 (initial microbial load in the carrier) and LR to eliminate the influence of one on the other. ResultsAn example with Candida albicans is presented. Once the method was applied, the influence of N0 on LR was eliminated and the new LR values can be used for factorial experiments, for example, to check the efficacy of disinfectants or detergents without depending on the microbial load placed in the carrier.

microbiology↗

bioRxiv2020

Bivariate confidence probability plots as a method to test the accuracy and variability of microbiological measures

IntroductionIn an interlaboratory calibration analysis to validate a methodology that will be proposed as a European standard for domestic laundry disinfection, tests were carried out to detect if there are different behaviors in the measurements regarding accuracies and variabilities. Interlaboratory tests using different doses of disinfectant and microorganisms were carried out. ISO 5725-2 and ISO 13528 form the basis of validations of quantitative methods, providing validation specifications for interlaboratory studies. However, a need for a simple graphical method to detect interlaboratory differences in accuracy and variability was observed. ObjectivesThe general goal of this work is to present a new exploratory methodology, graphical and easy to interpret, that can determine the accuracy and variability (precision) of a variable, and compare it to the methodology applied in ISO 5725-2 and ISO 13528. MethodsWe used confidence probability plots of the multivariate Students t-distribution to observe the accuracy and variability of microbiological measures carried out by different laboratories during a ring trial exercise. A function in R was built for this purpose: Miriam.analysis.ellipse(Y, factor_a, eel.plot = " t-Student"). The different observations of accuracy and variability are represented in the ellipses. If any of the points are outside the ellipse with 95% confidence, we can assume a deviation in accuracy and / or variability. ResultsTwo examples are provided with real microbiological data (logarithmic unit reductions (LR) for Pseudomonas aeruginosa, Escherichia coli, Staphilococcus aureus, Enterococcus hirae, Candida albicans and microbial counts in water (WW)). The proposed new method allowed us to detect possible deviations in the WWMEA variable and we believe it has future application for the rapid control of microbiological measures.

microbiology↗