Abstract Sepsis is a serious clinical condition that is characterized by a systemic inflammatory response syndrome resulting from a known or suspected infection. The major clinical symptoms involve an abnormal WBC count, elevated body temperature, respiration and pulse rate. Reported cases with high mortality rate range between 13 - 20 million. In order to treat Sepsis, the detection of bacteria in blood culture is extremely crucial. Treating patients with broad spectrum antibiotics is usually related to adverse effects, drug resistance, increased mortality, and high cost. In the past decades, researches had detected that E. coli and S. aureus are the major role players that cause sepsis. These microbes are molecularly tested by methods like MALDI TOF, FISH and Microarrays. In this analysis, DNA fluorescence in situ hybridization (FISH) assessment for the identification of S. aureus, one of the most frequent blood pathogens, was optimized in the labs of Högskolan i Skövde. As a result, the growth of S. aureus was observed very carefully, optimizing the FISH procedure for gram positive bacteria was done and the sensitivity, stability and specificity of the DNA probe were examined under variant conditions like the continuous decrease in the bacteria cells number and utilizing a mixture of different types of bacteria cells. / Data mining strategies and molecular techniques for microbial detection in severe sepsis
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-8772 |
| Date | January 2014 |
| Creators | Al-Bayati, Omar |
| Publisher | Högskolan i Skövde, Institutionen för biovetenskap, Baghdad university |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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