3 research outputs found
Occurrence and characterization of shiga toxin-producing Escherichia coli in raw meat, raw milk, and street vended juices in Bangladesh
The major objective of this study was to investigate the prevalence of Shiga toxin (Stx)–producing Escherichia coli (STEC) in different types of food samples and to compare their genetic relatedness with STEC strains previously isolated from animal sources in Bangladesh. We investigated a total of 213 food samples, including 90 raw meat samples collected from retail butcher shops, 20 raw milk samples from domestic cattle, and 103 fresh juice samples from street vendors in Dhaka city. We found that more than 68% (n=62) of the raw meat samples were positive for the stx gene(s); 34% (n=21) of buffalo meats and 66% (n=41) of beef. Approximately 10% (n=2) of the raw milk and 8% (n=8) of the fresh juice samples were positive for stx. We isolated STEC O157 from seven meat samples (7.8%), of which two were from buffalo meats and five from beef; and no other STEC serotypes could be isolated. We could not isolate STEC from any of the stx-positive raw milk and juice samples. The STEC O157 isolates from raw meats were positive for the stx2, eae, katP, etpD, and enterohemorrhagic E. coli hly virulence genes, and they belonged to three different phage types: 8 (14.3%), 31 (42.8%), and 32 (42.8%). Pulsed-field gel electrophoresis (PFGE) typing revealed six distinct patterns among seven isolates of STEC O157, suggesting a heterogeneous clonal diversity. Of the six PFGE patterns, one was identical and the other two were =90% related to PFGE patterns of STEC O157 strains previously isolated from animal feces, indicating that raw meats are readily contaminated with fecal materials. This study represents the first survey of STEC in the food chain in Bangladesh
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High-throughput screening Raman microspectroscopy for assessment of drug-induced changes in diatom cells
High-throughput screening Raman spectroscopy (HTS-RS) with automated localization algorithms offers unsurpassed speed and sensitivity to investigate the effect of dithiothreitol on the diatom Phaedactylum tricornutum. The HTS-RS capability that was demonstrated for this model system can be transferred to unmet analytical applications such as kinetic in vivo studies of microalgal assemblages. © 2019 The Royal Society of Chemistry
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New methodology to process shifted excitation Raman difference spectroscopy data : a case study of pollen classification
Shifted excitation Raman difference spectroscopy (SERDS) is a background correction method for Raman spectroscopy. Here, the difference spectra were directly used as input for SERDS-based classification after an optimization procedure to correct for photobleaching of the autofluorescence. Further processing included a principal component analysis to compensate for the reduced signal to noise ratio of the difference spectra and subsequent classification by linear discriminant analysis. As a case study 6,028 Raman spectra of single pollen originating from plants of eight different genera and four different growth habits were automatically recorded at excitation wavelengths 784 and 786 nm using a high-throughput screening Raman system. Different pollen were distinguished according to their growth habit, i.e. tree versus non-tree with an accuracy of 95.9%. Furthermore, all pollen were separated according to their genus, providing also insight into similarities based on their families. Classification results were compared using spectra reconstructed from the differences and raw spectra after state-of-art baseline correction as input. Similar sensitivities, specificities, accuracies and precisions were found for all spectra with moderately background. Advantages of SERDS are expected in scenarios where Raman spectra are affected by variations due to detector etaloning, ambient light, and high background