Antibiotics Susceptibility Pattern of Pseudomonas aeruginosa Isolated from Wounds in Patients Attending Ahmadu Bello University Teaching Hospital, Zaria, Nigeria

This work investigated the prevalence and antibiotics sensitivity of Pseudomonas aeruginosa isolated from wounds of patients attending Ahmadu Bello University Teaching Hospital (ABUTH), Zaria-Nigeria. One hundred Isolates were characterized and identified from the specimens using standard microbiological methods. The results of the isolation and identification showed that 55(55%) were Gram-negative organisms and 44 (44%) were Gram-positive. Klebsiella species and Pseudomonas aeruginosa accounted for 25% of the Gramnegative organisms, followed by Proteus species 19%, Klebsiella species 14% and Escherichia coli accounts for 11%, while Staphylococcus aureus 44% was the predominant Gram-positive organism. Antibiotic susceptibility pattern was determined using the disc diffusion method where the susceptibility of Pseudomonas aeruginosa isolated in wounds was observed. The highest sensitivity was observed for ofloxacin, moderate susceptibility was observed for ampicillin, cefuroxime and ceftriazone. The results obtained indicated strong resistance to cotrimoxazole, amoxicillin tetracycline and augmentin. There is the need for routine antibiotic sensitivity check

Analysis of gene expression data from non-small celllung carcinoma cell lines reveals distinct sub-classesfrom those identified at the phenotype level

Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that subclasses were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC

Boletín de Segovia: Número 107 - 1873 agosto 20

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