The Colocalization Potential of HIV-Specific CD8+ and CD4+ T-Cells is Mediated by Integrin β7 but Not CCR6 and Regulated by Retinoic Acid
Bibliographic record
Abstract
CD4(+) T-cells from gut-associated lymphoid tissues (GALT) are major targets for HIV-1 infection. Recruitment of excess effector CD8(+) T-cells in the proximity of target cells is critical for the control of viral replication. Here, we investigated the colocalization potential of HIV-specific CD8(+) and CD4(+) T-cells into the GALT and explored the role of retinoic acid (RA) in regulating this process in a cohort of HIV-infected subjects with slow disease progression. The expression of the gut-homing molecules integrin β7, CCR6, and CXCR3 was identified as a "signature" for HIV-specific but not CMV-specific CD4(+) T-cells thus providing a new explanation for their enhanced permissiveness to infection in vivo. HIV-specific CD8(+) T-cells also expressed high levels of integrin β7 and CXCR3; however CCR6 was detected at superior levels on HIV-specific CD4(+) versus CD8(+) T-cells. All trans RA (ATRA) upregulated the expression of integrin β7 but not CCR6 on HIV-specific T-cells. Together, these results suggest that HIV-specific CD8(+) T-cells may colocalize in excess with CD4(+) T-cells into the GALT via integrin β7 and CXCR3, but not via CCR6. Considering our previous findings that CCR6(+)CD4(+) T-cells are major cellular targets for HIV-DNA integration in vivo, a limited ability of CD8(+) T-cells to migrate in the vicinity of CCR6(+)CD4(+) T-cells may facilitate HIV replication and dissemination at mucosal sites.
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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 | 0.000 |
| 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) | 0.002 | 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".