Human Immunodeficiency Virus Persistence and T-Cell Activation in Blood, Rectal, and Lymph Node Tissue in Human Immunodeficiency Virus–Infected Individuals Receiving Suppressive Antiretroviral Therapy
Bibliographic record
Abstract
Background: Immune activation and inflammation remain elevated in human immunodeficiency virus (HIV)-infected individuals receiving antiretroviral therapy (ART) and may contribute to HIV persistence. Methods: Using flow cytometry expression of CD38, HLA-DR and PD-1 were measured in blood (n = 48), lymph node (LN; n = 9), and rectal tissue (n = 17) from virally suppressed individuals. Total and integrated HIV DNA, 2-LTR circles, and cell-associated unspliced HIV RNA were quantified. Results: CD4+ T cells from rectal tissue had a higher frequency of integrated HIV DNA compared with blood (4.26 fold-change in DNA; 95% confidence interval [CI] = 2.61-7.00; P < .001) and LN (2.32 fold-change in DNA; 95% CI = 1.22-4.41; P = .01). In rectal tissue, there were positive associations between integrated HIV DNA with PD-1+ CD4+ T-cells (1.44 fold-change in integrated HIV DNA per 10-unit increase in PD-1+ CD4+ T cells; 95% CI = 1.01-2.05; P = .045) and CD38+HLA-DR+ CD8+ T cells (1.40 fold-change in integrated HIV DNA per 1-unit increase in CD38+HLA-DR+ CD8+ T cells; 95% CI = 1.05-1.86; P = .02). Both associations were independent of current and nadir CD4+ T-cell counts. Conclusions: During ART, rectal tissue is an important reservoir for HIV persistence with a high frequency of activated CD4+ and CD8+ T cells. PD-1 may represent a marker of HIV persistence in rectal tissue.
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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".