A Five Year Review OF API20E Bacteria Identification System’s Performance at a Teaching Hospital

Objectives: To assess the performance of the API20E bacteria  identification system at a teaching hospital in Kenya.Design: Retrospective study.Setting: The microbiology laboratoryoratory of the Aga Khan University teaching Hospital.Subjects: One thousand six hundred and fifty eight API20E records.Main outcome measures: The accuracy in identifying the bacteria species.Results: One thousand four hundred and forty two (87.6%) isolates had the exact identity, 199 (12%) nearest identity, and seven (0.4%) no identity. The performance varied among the species; Acinetobacter baumanii had 140 (99.3%) isolates with the exact identity and only one (0.7%) with the nearest identity compared with Aeromonas hydrophila which had five (17.2%) with exact and 24 (82.8%) with nearest.Conclusions: The API20E system is a robust bacteria identification method which can serve small and medium clinical microbiology laboratoryoratories that may not afford automated systems. Adhering to the manufacturer’s instructions and good laboratoryoratory practice can improve the  performance of this method

HIV-1 progression links with viral genetic variability and subtype, and patient's HLA type: analysis of a Nairobi-Kenyan cohort.

In a Nairobi-Kenyan cohort of 50 HIV-1 positive patients, we analysed the prevalence of HIV-1 subtypes and human leucocyte antigen (HLA) alleles. From this cohort, 33 patients were selected for the analysis of HIV-1 infection progression markers (i.e. CD4 cell counts and viral loads) and their association with HIV-1 genetic variability and subtype, and patient's HLA type. HIV-1 gag genetic variability, analysed using bioinformatics tools, showed an inverse relationship with CD4 cell count whereas with viral load that relationship was direct. Certain HLA types and viral subtypes were also found to associate with patients' viral load. Associations between disease parameters and the genetic makeup of the host and virus may be crucial in determining the outcome of HIV-1 infection

HIV-1 progression links with viral genetic variability and subtype, and patient's HLA type: Analysis of a Nairobi-Kenyan cohort

In a Nairobi-Kenyan cohort of 50 HIV-1 positive patients, we analysed the prevalence of HIV-1 subtypes and human leucocyte antigen (HLA) alleles. From this cohort, 33 patients were selected for the analysis of HIV-1 infection progression markers (i.e. CD4 cell counts and viral loads) and their association with HIV-1 genetic variability and subtype, and patient's HLA type. HIV-1 gag genetic variability, analysed using bioinformatics tools, showed an inverse relationship with CD4 cell count whereas with viral load that relationship was direct. Certain HLA types and viral subtypes were also found to associate with patients' viral load. Associations between disease parameters and the genetic makeup of the host and virus may be crucial in determining the outcome of HIV-1 infection. © 2013 Springer-Verlag Berlin Heidelberg

HIV-1 progression links with viral genetic variability and subtype, and patient's HLA type: Analysis of a Nairobi-Kenyan cohort

In a Nairobi-Kenyan cohort of 50 HIV-1 positive patients, we analysed the prevalence of HIV-1 subtypes and human leucocyte antigen (HLA) alleles. From this cohort, 33 patients were selected for the analysis of HIV-1 infection progression markers (i.e. CD4 cell counts and viral loads) and their association with HIV-1 genetic variability and subtype, and patient's HLA type. HIV-1 gag genetic variability, analysed using bioinformatics tools, showed an inverse relationship with CD4 cell count whereas with viral load that relationship was direct. Certain HLA types and viral subtypes were also found to associate with patients' viral load. Associations between disease parameters and the genetic makeup of the host and virus may be crucial in determining the outcome of HIV-1 infection. © 2013 Springer-Verlag Berlin Heidelberg

Population-specific evolution of HIV Gag epitopes in genetically diverged patients.

BACKGROUND: Under the host selection pressure HIV evolves rapidly to override crucial steps in the antigen presentation pathway. This allows the virus to escape binding and recognition by cytotoxic T lymphocytes. Selection pressures on HIV can be unique depending on the immunogenetics of host populations. It is therefore logical to hypothesize that the virus evolving in a given population will carry signature mutations that will allow it to survive in that particular host milieu. OBJECTIVES: The aim of this study was to perform a comparative analysis of HIV-1 Gag subtype A sequences from two genetically diverged populations, namely, Kenyan and Pakistani. We analyzed unique mutations that could intercept the antigen processing pathway and potentially change the repertoire of Gag epitopes in each study group. METHODS: Twenty-nine Kenyan and 56 Pakistani samples from HIV-1 subtype A-infected patients were used in this study. The HIV-1 gag region p24 and p2p7p1p6 was sequenced and mutations affecting proteasomal degradation, TAP binding, HLA binding and CTL epitope generation, were analyzed using the in silico softwares NetChop and MAPPP, TAPPred, nHLAPred and CTLPred, respectively. RESULTS: Certain mutations unique to either Pakistani or Kenyan patients were observed to affect sites for proteasomal degradation, TAP binding, and HLA binding. As a consequence of these mutations, epitope pattern in these populations was altered. CONCLUSION: Unique selection pressures can steer the direction of viral epitope evolution in the host populations. Population-specific HIV epitopes have to be taken into account while designing treatment as well as vaccine for HIV