Evolution of HIV-1 in the Gut
Bibliographic record
Abstract
The high mutation rate of Human Immunodeficiency Virus (HIV) is a significant contributor to its ability to develop drug resistance. While much research has been directed towards developing new drugs and treatments in response to resistance, it is also critical to gain a better understanding of the nature of the virus’s replication. Previous studies (van Marle et al., 2007; van Marle et al., 2010) have demonstrated that viral replication and evolution are compartmentalized in different gut tissues. However, these studies focused on the reverse transcriptase (rt) region of the proviral DNA. This project examined whether the same patterns of viral evolution would be found in the n ef (negative factor) encoding region. The Nef protein contributes to the infectivity and pathogenicity of the virus and is therefore under different selection pressures than reverse transcriptase. For this project, gut biopsy samples were taken from a patient cohort at the Southern Alberta HIV Clinic from 1993-1996 and again from 2007-2010. Proviral DNA was isolated and the nef region was subsequently sequenced and analyzed using Molecular Evolutionary Genetic Analysis (MEGA) software. The results indicated that evolution of the nef region over time is consistent with compartmentalization of the gut in each patient. Overall diversity of the Nef protein encoding region is similar among all tissue types. Finally, the majority of mutations suggest that HIV-1 is under neutral or purifying selection. These observations are consistent with the observations of the rt region, suggesting a similar evolutionary pattern for the nef region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".