INVOLVEMENT OF GENOTYPING AND PHYLOGENETIC ANALYSIS OF HCV AND HIV ISOLATES IN THE MONITORING OF THE DISEASE PROGRESSION AMONG HIV/HCV CO-INFECTED INDIVIDUALS IN CAMEROON
Bibliographic record
Abstract
Background: RNA virus infections represent a significant cause of illness and death in vertebrates. Specifically in humans, RNA viruses are responsible for a wide range of acute, chronic, emerging and re-emerging infections. HIV and HCV rank as some of the RNA viruses infections facing Africa. Methods: To perform genotyping and phylogenetic analysis using HCV specific genes in order to monitor the disease progression, RNA was isolated from HIV/HCV co-infected patients, in a town with heterogeneous population in Cameroon, Douala. From 2005 to 2006, a total of 36 HIV/HCV co-infected isolates (22 from volunteer blood donors and 14 from people living with HIV/AIDS and naive of treatment) were analyzed using molecular biology techniques and bioinformatics tools. Molecular biology techniques (RT-PCR, gene/TOPO cloning and DNA sequencing) and bioinformatics tools were performed at the J. Craig Venter Institute, MD, USA. Results: The results obtained show that HCV isolates from Cameroon belong to genotypes 1, 2, and 4. The corresponding subtypes investigated were 1a, 1b, 1c, 2a, 2c, 2k, and 4a. Phylogenetic analysis of the NS5B gene showed that Cameroonian strains cluster with Gabonese, French and Martinique strains, whereas they differ from Ghanaian and Canadian strains. Subtypes 1a and 1b that are mostly found in developed countries also circulate in Cameroon, indicating that HCV infection represents a serious threat in infected people. Results also show that the majority of HIV strains belong to the circulating recombinant forms, CRF_02_AG. Epidemiologic data show that HCV infected individuals are older than HIV mono-infected patients. Conclusions: These results show evidence of genetic diversity of HIV and HCV; virulent hepatitis C virus in Cameroon, and therefore a great need for further investigation of quasi-species using different clones from the same strain. Besides, there is an imperative need for monitoring the disease progression in the sub-region, using genomics and bioinformatic approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".