HIV persists in CCR6+CD4+ T cells from colon and blood during antiretroviral therapy
Bibliographic record
Abstract
OBJECTIVES: The objective of this article is to investigate the contribution of colon and blood CD4 T-cell subsets expressing the chemokine receptor CCR6 to HIV persistence during antiretroviral therapy. DESIGN: Matched sigmoid biopsies and blood samples (n = 13) as well as leukapheresis (n = 20) were collected from chronically HIV-infected individuals receiving antiretroviral therapy. Subsets of CD4 T cells with distinct differentiation/polarization profiles were identified using surface markers as follows: memory (TM, CD45RA), central memory (TCM; CD45RACCR7), effector (TEM/TM; CD45RACCR7), Th17 (CCR6CCR4), Th1Th17 (CCR6CXCR3), Th1 (CCR6CXCR3), and Th2 (CCR6CCR4). METHODS: We used polychromatic flow cytometry for cell sorting, nested real-time PCR for HIV DNA quantification, ELISA and flow cytometry for HIV p24 quantification. HIV reactivation was induced by TCR triggering in the presence/absence of all-trans retinoic acid. RESULTS: Compared with blood, the frequency of CCR6 TM was higher in the colon. In both colon and blood compartments, CCR6 TM were significantly enriched in HIV DNA when compared with their CCR6 counterparts (n = 13). In blood, integrated HIV DNA levels were significantly enriched in CCR6 versus CCR6 TCM of four of five individuals and CCR6 versus CCR6 TEM of three of five individuals. Among blood TCM, Th17 and Th1Th17 contributed the most to the pool of cells harboring integrated HIV DNA despite their reduced frequency compared with Th2, which were infected the least. HIV reactivation was induced by TCR triggering and/or retinoic acid exposure at higher levels in CCR6 versus CCR6 TM, TCM, and TEM. CONCLUSION: CCR6 is a marker for colon and blood CD4 T cells enriched for replication-competent HIV DNA. Novel eradication strategies should target HIV persistence in CCR6CD4 T cells from various anatomic sites.
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 | 0.001 |
| 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".