Assessment of the sensitivity of current standard procedures for the isolation of Yersinia enterocolitica from pork mince : a dissertation presented in partial fulfilment (25%) of the requirements for the degree of Master of Veterinary Studies in Veterinary Public Health at Massey University

Y. enterocolitica and related species have been isolated from many types of food. The majority of isolates differ in biochemical and serological characteristics from typical pathogenic strains and are termed non-pathogenic or environmental strains. Usually the number of Y. enterocolitica organisms present in food products is low compared with the dominant background flora. The ability of current enrichment procedures to recover pathogenic strains of Y. enterocolitica from different foods is often inadequate probably because different strains require different conditions for optimum growth (De Boer 1992). An efficient enrichment procedure should confer some selective advantage to the desired type of microorganism by promoting its growth relative to the competing microflora. At present, there is no single ideal isolation procedure available for the recovery of pathogenic strains of Y. enterocolitica from foods. The aim of this study was to determine the recovery rate of Y. enterocolitica biotype 4/serotype 0:3 from samples of pork mince inoculated with known numbers of the microorganism using different enrichment parameters (Time, temperature and pH) and Cefsulodin-Irgasan-Novobiocin (CIN) agar as the selective medium. The experiment was conducted in two trials using different bacterial dilutions. Three pork mince samples in duplicate were inoculated with known quantities of Y. enterocolitica biotype 4/serotype 0:3 organisms and subjected to cold enrichment in phosphate buffered saline (PBS) with a pH of 7.6, 6.6 and 5.5 at 25°C for 2 days, 10°C for 7 days and 4°C for 21 days. CIN agar was used as the selective medium. Pre-inoculation control samples were selected and plated in CIN on day O and on day 21 after PBS enrichment at 4°C. In Trial one Y. enterocolitica organisms were recovered from all 3 samples incubated at 25°C for 2 days and from 1 out of 3 inoculated samples incubated at 4°C for 21 days. There were no organisms recovered from other inoculated samples. The control sample did not show any environmental contamination with Yersinia species. In Trial two, Y. enterocolitica was recovered from 1 out of 3 duplicate samples enriched in PBS with pH 6.6 and incubated at 25°C for two days. Y. enterocolitica was not recovered from other inoculated samples. Y. intermedia was isolated from all pH, temperature and time combinations and also from control samples. The following conclusions can be drawn from this experiment. Incubation at high temperature (25°C) and short duration (48 hours) can be used as an efficient method for isolating Y. enterocolitica from pork samples. The standard incubation period of 21 days required for cold enrichment at 4°C is too long for the isolation of pathogenic strains, because of possible growth of environmental microorganisms. A pH of 6.6 is less efficient than 7.6 for enrichment although occasional isolation can be made using this pH. Enrichment in PBS with a pH of 5.5 with any time as well as temperature combinations and incubation at 10°C for 7 days are not ideal for isolation of pathogenic Yersinia enterocolitica strains. Of the three enrichments (PBS 7.6, 6.6, 5.5) used in this experiment, PBS with pH 7.6 was found to be most efficient to others

Novel graph based algorithms for transcriptome sequence analysis

RNA-sequencing (RNA-seq) is one of the most-widely used techniques in molecular biology. A key bioinformatics task in any RNA-seq workflow is the assembling the reads. As the size of transcriptomics data sets is constantly increasing, scalable and accurate assembly approaches have to be developed.Here, we propose several approaches to improve assembling of RNA-seq data generated by second-generation sequencing technologies. We demonstrated that the systematic removal of irrelevant reads from a high coverage dataset prior to assembly, reduces runtime and improves the quality of the assembly. Further, we propose a novel RNA-seq assembly work- flow comprised of read error correction, normalization, assembly with informed parameter selection and transcript-level expression computation. In recent years, the popularity of third-generation sequencing technologies in- creased as long reads allow for accurate isoform quantification and gene-fusion detection, which is essential for biomedical research. We present a sequence-to-graph alignment method to detect and to quantify transcripts for third-generation sequencing data. Also, we propose the first gene-fusion prediction tool which is specifically tailored towards long-read data and hence achieves accurate expression estimation even on complex data sets. Moreover, our method predicted experimentally verified fusion events along with some novel events, which can be validated in the future

Accuracy of activity quantitation of F-18 fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging using simulated malignant tumors

This thesis involves a procedure, which calculated and compared the sum of all the pixel counts, threshold pixel counts sum of a 3D PET image and mean and maximum pixel count of one single transaxial slice (2D) of simulated tumors for a chosen region of interest (ROI). A calibration factor was multiplied by the sum of the pixel counts, threshold pixel counts sum of all the transaxial slices, and the mean, and maximum pixel counts of one single transaxial slice in an ROI to calculate for the activity of the tumor. This activity calculated was compared with the real activity values. The results showed that the sum of all the pixel counts with applied threshold is better to calculate the activity of tumor with greater accuracy. These findings suggest that a 3D distribution of sum of all the pixel counts was able to calculate the activity of malignant tumors and lung lesions with better accuracy

Marxist thought in Tamil Novels

Marxism, which produced the theory of communism, is very extensive. This field that originated in the West and grew up in Tamil novel literature, and Karl Marx and Friedrich Engels are the founders of Marxism, which has the principle of equality for the working class. The theory of reflection is the theory that is primarily in the literary theories advanced by Marxism. That is, the class conflicts in society cause crises in human lives. The economic inequality in society is the primary cause of social contradiction. Struggles erupt when the bourgeoisie exploits the working people. This article seeks to examine the struggles in Tamil novels published in the 21st century

Validation of LRINEC scoring system for diagnosis of Necrotizing fasciitis in patients presenting with soft Tissue infections

INTRODUCTION: Necrotising fasciitis is one the highly lethal infections that causes rapidly spreading necrosis of fascia and subcutaneous tissue which leads to high morbidity and mortality. With early diagnosis, outcome can be much improved so that long term disability can be significantly reduced or prevented. AIM OF THE STUDY: To validate the LRINEC scoring system for the diagnosis of necrotizing fasciitis among patients with soft tissue infections. METHOD: This was a prospective study which included patients who were admitted with soft tissue infections in Govt. Rajaji hospital, Madurai for a period of one year. These patients were subjected to LRINEC scoring system and results were interpreted. RESULTS: The present study comprised of 76 cases who were presented with necrotizing soft tissue infections as per the inclusion and exclusion criteria. Male gender, older age group predominantly in soft tissue infections.Present study showed that LRINEC score is capable of detecting early cases of necrotizing fasciitis among patients with severe soft tissue infections. Positive predictive value for the LRINEC scoring system was 94.7% with a sensitivity value of 95.6% in the present study. 51 patients with soft tissue infections were debrided based on LRINEC scoring system. CONCLUSION: Early operative debridement was demonstrated to reduce mortality among patients with this condition. The LRINEC score is a robust index that is capable of detecting early cases of necrotizing fasciitis and is simple enough for routine use. LRINEC scoring system is an important adjunctive tool in diagnosing necrotizing soft tissue infections

Logarithmic Mean Labeling of Some Ladder Related Graphs

In general, the logarithmic mean of two positive integers need not be an integer. Hence, the logarithmic mean is to be an integer; we use either flooring or ceiling function. The logarithmic mean labeling of graphs have been defined in which the edge labels may be assigned by either flooring function or ceiling function. In this, we establish the logarithmic mean labeling on graphs by considering the edge labels obtained only from the flooring function. A logarithmic mean labeling of a graph G with q edges is an injective function from the vertex set of G to 1, 2, 3,..., q+1 such that the edge labels obtained from the flooring function of logarithmic mean of the vertex labels of the end vertices of each edge are all distinct, and the set of edge labels is 1, 2, 3,..., q. A graph is said to be a logarithmic mean graph if it admits a logarithmic mean labeling. In this paper, we study the logarithmic meanness of some ladder related graphs

k mer

Motivation: De novo transcriptome assembly is an integral part for many RNA-seq workflows. Common applications include sequencing of non-model organisms, cancer or meta transcriptomes. Most de novo transcriptome assemblers use the de Bruijn graph (DBG) as the underlying data structure. The quality of the assemblies produced by such assemblers is highly influenced by the exact word length k. As such no single kmer value leads to optimal results. Instead, DBGs over different kmer values are built and the assemblies are merged to improve sensitivity. However, no studies have investigated thoroughly the problem of automatically learning at which kmer value to stop the assembly. Instead a suboptimal selection of kmer values is often used in practice. Results: Here we investigate the contribution of a single kmer value in a multi-kmer based assembly approach. We find that a comparative clustering of related assemblies can be used to estimate the importance of an additional kmer assembly. Using a model fit based algorithm we predict the kmer value at which no further assemblies are necessary. Our approach is tested with different de novo assemblers for datasets with different coverage values and read lengths. Further, we suggest a simple post processing step that significantly improves the quality of multi-kmer assemblies. Conclusion: We provide an automatic method for limiting the number of kmer values without a significant loss in assembly quality but with savings in assembly time. This is a step forward to making multi-kmer methods more reliable and easier to use. Availability and Implementation:A general implementation of our approach can be found under: https://github.com/SchulzLab/KREATION. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected]