Compartmentalization of the gut viral reservoir in HIV-1 infected patients
Bibliographic record
Abstract
BACKGROUND: Recently there has been an increasing interest and appreciation for the gut as both a viral reservoir as well as an important host-pathogen interface in human immunodefiency virus type 1 (HIV-1) infection. The gut associated lymphoid tissue (GALT) is the largest lymphoid organ infected by HIV-1. In this study we examined if different HIV-1 quasispecies are found in different parts of the gut of HIV-1 infected individuals. RESULTS: Gut biopsies (esophagus, stomach, duodenum and colorectum) were obtained from eight HIV-1 infected preHAART (highly active antiretroviral therapy) patients. HIV-1 Nef and Reverse transcriptase (RT) encoding sequences were obtained through nested PCR amplification from DNA isolated from the gut biopsy tissues. The PCR fragments were cloned and sequenced. The resulting sequences were subjected to various phylogenetic analyses. Expression of the nef gene and viral RNA in the different gut tissues was determined using real-time RT-PCR. Phylogenetic analysis of the Nef protein-encoding region revealed compartmentalization of viral replication in the gut within patients. Viral diversity in both the Nef and RT encoding region varied in different parts of the gut. Moreover, increased nef gene expression (p < 0.05) and higher levels of viral genome were observed in the colorectum (p < 0.05). These differences could reflect an adaptation of HIV-1 to the various tissues. CONCLUSION: Our results indicated that different HIV-1 quasispecies populate different parts of the gut, and that viral replication in the gut is compartmentalized. These observations underscore the importance of the gut as a host-pathogen interface in HIV-1 infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".