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AbstractExposure to microbial contamination through drinking water is a major global health concern. Effective management of microbial drinking water quality requires rapid detection equipment. Currently, microbial quality is monitored using time‐consuming laboratory methods, which delay any response. This study demonstrates the development of an automated and high‐throughput method for the measurement of viable biomass in water through the quantification of cellular adenosine triphosphate (ATP). The developed method was able to efficiently and accurately quantify cellular ATP in multiple water samples simultaneously. In addition, it proved to be 5× faster and as accurate as the Standard Test Method for Adenosine Triphosphate (ATP) Content of Microorganisms in Water (ASTM D4012). The developed method has the potential to represent a significant advancement for microbial monitoring and could benefit utilities interested in measuring viable biomass in water to monitor the health of biofilters and the effectiveness of disinfection strategies.

BACKGROUND: The large amount of data produced by high-throughput sequencing poses new computational challenges. In the last decade, several tools have been developed for the identification of transcription and splicing factor binding sites. RESULTS: Here, we introduce the SeAMotE (Sequence Analysis of Motifs Enrichment) algorithm for discovery of regulatory regions in nucleic acid sequences. SeAMotE provides (i) a robust analysis of high-throughput sequence sets, (ii) a motif search based on pattern occurrences and (iii) an easy-to-use web-server interface. We applied our method to recently published data including 351 chromatin immunoprecipitation (ChIP) and 13 crosslinking immunoprecipitation (CLIP) experiments and compared our results with those of other well-established motif discovery tools. SeAMotE shows an average accuracy of 80% in finding discriminative motifs and outperforms other methods available in literature. CONCLUSIONS: /nSeAMotE is a fast, accurate and flexible algorithm for the identification of sequence patterns involved in protein-DNA and protein-RNA recognition. The server can be freely accessed at http://s.tartaglialab.com/new_submission/seamote. ; The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013), through the European Research Council, under grant agreement RIBOMYLOME_309545, and from the Spanish Ministry of Economy and Competitiveness/n(SAF2011-26211). We also acknowledge support from the Spanish Ministry of Economy and Competitiveness, 'Centro de Excelencia Severo Ochoa 2013–2017' (SEV-2012-0208)

12 páginas, 3 figuras, 1 tabla ; A rapid and high throughput protocol to measure the catalase activity in vitro has been designed. Catalase is an enzyme with unusual kinetic properties because it does not follow the standard Michaelis–Menten model and is inactivated by H2O2. This makes the analysis of the two rate equations of the second‐ordered reactions of the kinetic model rather complex. A two‐degree polynomial fitting of the experimental data is proposed after transforming the exponential form of the integrated rate equation of the [H2O2] into a polynomial using the Taylor series. The fitting is validated by establishing an experimental linear relationship between the initial rate of the H2O2 decomposition and the protein concentration, regardless of the suicide inactivation that catalase might undergo beyond t > 0. In addition, experimental considerations are taken into account to avoid statistical bias in the analysis of the catalase activity. ANOVA analyses show that the proposed protocol can be utilized to measure the initial rate of the H2O2 decomposition by catalase in 32 samples in triplicates if kept below 8 mM min−1 in the microplate wells. These kinetic and statistical analyses can pave the way for other antioxidant enzyme activity assays in microplate readers at small scale and low cost. ; This research was funded by the Spanish national plan for Scientific and Technical Research and Innovation, grant number AGL2016-79589-R, and the regional government of Castilla y León, grant number CSI260P20. The Project "CLU-2019-05—IRNASA/CSIC Unit of Excellence" funded by the Junta de Castilla y León and co-financed by the European Union (ERDF "Europe drives our growth") is also acknowledged ; Peer reviewed

4.4 Malicious Contamination of FoodReferences; Chapter 5: Multiresidual Determination of 295 Pesticides and Chemical Pollutants in Animal Fat by Gel Permeation Chromatography (GPC) Cleanup Coupled with GC-MS/MS, GC-NCI-MS, and LC-MS/MS; 5.1 Introduction; 5.2 Experiment; 5.3 Results and Discussion; 5.4 Conclusions; References; Chapter 6: Ultrahigh-Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry: A Reliable Tool for Analysis of Veterinary Drugs in Food; 6.1 Introduction; 6.2 Veterinary Drug Legislation; 6.3 Analytical Techniques for VD Residue Analysis.