Sigmoid Th17 populations, the HIV latent reservoir, and microbial translocation in men on long-term antiretroviral therapy
Bibliographic record
Abstract
OBJECTIVE: Th17 cells play an important role in mucosal defence and repair and are highly susceptible to infection by HIV. Antiretroviral therapy (ART) suppresses HIV viremia and can restore CD4(+) numbers in the blood and gastrointestinal mucosa, but the resolution of systemic inflammation and gut microbial translocation is often incomplete. We hypothesized that this might relate to persistent dysregulation of gut CD4(+) Th17 subsets. METHODS: Blood and sigmoid biopsies were collected from HIV-uninfected men, chronically HIV-infected, ART-naive men, and men on effective ART for more than 4 years. Sigmoid provirus levels were assayed blind to participant status, as were CD4(+) Th17 subsets, systemic markers of microbial translocation, and cellular immune activation. RESULTS: There was minimal CD4(+) Th17 dysregulation in the blood until later stage HIV infection, but gastrointestinal Th17 depletion was apparent much earlier, along with increased plasma markers of microbial translocation. Plasma lipopolysaccharide (LPS) remained elevated despite overall normalization of sigmoid Th17 populations on long-term ART, although there was considerable interindividual variability in Th17 reconstitution. An inverse correlation was observed between plasma LPS levels and gut Th17 frequencies, and higher plasma LPS levels correlated with an increased gut HIV proviral reservoir. CONCLUSION: Sigmoid Th17 populations were preferentially depleted during HIV infection. Despite overall CD4(+) T-cell reconstitution, sigmoid Th17 frequencies after long-term ART were heterogeneous and higher frequencies were correlated with reduced microbial translocation.
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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 | 0.001 | 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".