Scientific library

1. Plating validation easySpiral/easyeasySpiral Pro in decreasing exponential mode
   1. Aim: To study the reliability of easySpiral/easySpiral Pro plating in decreasing exponential mode (known as the Spiral method) by carrying out a comparative study with the reference method "manual surface plating" (known as the classic technique).
   2. Conclusion: Our results show a strong correlation (R2 ≥ 0.982) between plating in Spiral mode using the easySpiral and the conventional method. Also, the average difference in log CFU/mL between the two methods is 12 times less than the maximum difference, and therefore not significant.
2. Cleaning efficiency of easySpiral/easyeasySpiral Pro
   1. Aim: Ensure that the easySpiral/easySpiral Pro stylus is cleaned between each sample run. Check the effectiveness of stylus disinfection by inoculating with sterile diluent.
   2. Conclusion: The study shows that for all six bacterial strains, cleaning in either long or short mode enables disinfection of the stylus and avoids contamination between samples. Three disinfectants were tested: ethanol 70%, bleach 1% and a formulation based on hydrogen peroxide (3%) + peracetic acid (0.08%). Other formulations with slightly different concentrations of H2O2 and APA may also be effective.

Aim: The aim of this study was to evaluate the performance of the Scan 1200 by comparing manual and automatic counting. For optimal comparison, Petri dishes were plated and incubated in our R&D laboratory, using standard methods to reproduce normal laboratory conditions. The same technician then counted the colonies with a Scan 1200 and manually to obtain results for evaluating the accuracy of the Scan. This document also contains a study of the analysis time per dish and an estimate of the time spent by the laboratories.

Conclusion: Tests show in a variety of ways (regression line, correlation coefficient, average Log value difference, and ISO 7218:2007) that Scan 1200:
— Enables faster counting (up to 80% time saving).
— Counts as well as another user (strong relationship between the 2 methods, with an average difference of 2.35% per dish).

The Scan 1200 is an excellent tool for laboratories needing to count large numbers of dishes accurately and without wasting time. All results can be saved in specific files (called sessions) which contain all dish photos and counts, guaranteeing analysis quality and perfect traceability.

Aim: The aim of this study was to evaluate the performance of the ScanStation 100 by comparing the manual and automatic methods for food and milk payment analysis. For an optimal comparison, 1238 food samples, in duplicate, were carried out on a multitude of micro-organisms according to the laboratory’s reference methods. This document also contains curves showing the evolution of bacterial load over time.

Conclusion: Interpretation of these curves shows that the number of CFUs evolves up to 15 h of incubation. Thereafter, the number of CFU remains constant. Real-time counting during incubation enables us to quickly determine the presence of contamination, for example, and thus to define corrective actions before the end of incubation.

Aim: The aim of this study was to evaluate the performance of the ScanStation (ISS) by comparing manual and automatic counting on the analysis of samples seeded on Symphony and TBX media.

Conclusion: The difference in the majority of counts does not exceed the 0.3 log CFU limit. These results show no significant difference. By reading the "Time to Result" of the various microorganisms grown on Symphony and TBX media, it is possible to anticipate count results, enabling the user to define corrective action more quickly.

Aim: The aim of this study was to evaluate the performance of the ScanStation (ISS) by comparing manual and automatic decomposition of pure cultures of Salmonella typhimurium and Listeria monocytogenes.

Conclusion: The difference in the majority of counts does not exceed the 0.3 log CFU limit. These results show no significant difference. Reading the "Time to Result" for Salmonella typhimurium and Listeria monocytogenes makes it possible to anticipate count results, enabling the user to define corrective action more quickly.

Aim: ScanStation’s performance is evaluated by comparing actual manual enumeration with automatic counting of pure cultures of five microorganisms tested for environmental control in the pharmaceutical field (Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Candida albicans and Aspergillus brasiliensis).

Conclusion: In light of the results discussed in this study study, which show a strong and significant correlation between automatic ScanStation with the actual count verified by a human verified by a human operator of the set photos taken during the incubation incubation cycle, we confidently recommend confidently recommend the ScanStation for environmental environmental monitoring or analyses. In addition, time-to-result studies studies give us an insight into the growth kinetics growth kinetics of the five main pharmacopoeia strains which, if replicated and validated in the replicated and validated in the laboratory where ScanStation can be installed, to shorten the detection time for environmental and thus reduce production costs production costs in the pharmaceutical industry.

Aim: The objective of this study is to evaluate the ScanStation 100’s performances vs. manual method for the analysis of any matrices in beauty care from pure strains. For an optimal interpretation, the graph, contained in this file, is realized from 109 samples, the average of every duplicate. The maximum difference chosen in absolute value is 0.3 log

Conclusion: The different graphs show that manual counting and counting with the ScanStation do not present significant differences except where explicable. We see that the ScanStation tends to overestimate the counting compared to manual counting; the cosmetic matrices present many colony-resembling particles, which the ScanStation differentiates better than the human eye.

Aim: The objective of this study was to evaluate the performance of the ScanStation to count in real time colonies on membrane filtration. Enumeration was performed on waterborne pathogens that have been linked to healthcare-associated infections (HAIs). Bacterial suspensions were passed through filtration membranes that were deposited on Petri dish. Colonies were manually counted and results were compared with automatic counts performed by the ScanStation.

Conclusion: ScanStation performs well in counting colonies on filtration membranes in real time. For the seven strains tested, the automatic and manual counts are similar when bacterial suspensions are filtered on white polycarbonate membranes (without grids). For best automatic counts in this case, the recommended light configuration is white background (light from below). This study shows that bacterial colonies can be efficiently counted with ScanStation.

Aim: The aim of this study is to evaluate the performance of ScanStation (ISS) by comparing manual and automatic counting of plated samples for robustness counting assessment.

Conclusion: ScanStation’s robustness tests showed reproducible data under both intra- and inter-machine conditions.

Aim: Environmental monitoring is an important part of the microbiological quality control in diverse industrial production fields (pharmaceutical, cosmetic or food). This quality control includes surfaces, air and water testing. While surface testing is mainly carried out using contact agar, air and water testing requires the use of filtration membranes to filter out microorganisms and reveal their presence. The aim of this applicative note is to assess the performance of colony counting on different types of filtration membranes.

Conclusion: The ScanStation counting assessment results highlight that colonies are automatically detected on white membranes with correct accuracy. The ScanStation enumerates on filtration membrane with an accuracy as follow:

• PVDF = 99%
• MCE = 97%
• CA = 91%
• PES = 90%

Aim: The performance of the ScanStation is evaluated by comparing actual manual counting with automatic counting on selective media commonly used in the food industry (Baird Parker, VRBL, Symphony, and TBX). This study also shows that real-time colony reading by the ScanStation leads to earlier results.

Conclusion: In light of the results discussed in this study, which show a significantly high correlation between the ScanStation automatic CFU count and the “true count” as verified by a human operator with all the pictures taken during the incubation cycle, we confidently recommend the use of the ScanStation for production quality control.

Furthermore, the Time to Result study gives insights into the growth kinetics of each strain which can be used, if replicated and validated in the lab where it would be intended to be installed, to shorten the detection time to reduce production costs in the food industry.

The ScanStation is particularly fit for regulated laboratories, as the 21 CFR part 11-compliant software offers full data integrity and traceability to the user.

On our end, further research is planned to assess monotemperature in the ScanStation in such as the Food, Pharmaceutical or Cosmetics industries.