Characterization of a Human Cervical CD4+ T Cell Subset Coexpressing Multiple Markers of HIV Susceptibility
Bibliographic record
Abstract
The HIV pandemic disproportionately affects women, with most infections acquired through receptive vaginal sex. Although the target cells by which HIV establishes infection in the female genital tract remain poorly defined, it is known that immune activation results in CD4(+) T cells with enhanced susceptibility, as does expression of the mucosal integrin α4β7 and the HIV coreceptor CCR5. Blood and cervical cytobrush specimens were collected from female sex workers (FSWs) in Nairobi, Kenya. Genital infection diagnostics were performed, T cell populations were defined by multiparameter flow cytometry based on their expression of surface receptors relevant to mucosal homing and/or HIV acquisition, and cytokine production was assayed by intracellular cytokine staining. The integrin α4β7 was expressed on 26.0% of cervical CD4(+) T cells, and these cells were more likely to express both the HIV coreceptor CCR5 (p < 0.0001) and the early activation marker CD69 (p < 0.0001) but not CXCR4 (p = 0.34). Cervical Th17 frequencies were enhanced compared with blood (7.02 versus 1.24%; p < 0.0001), and cervical IL-17A(+) CD4(+) T cells preferentially coexpressed α4β7 and CCR5. Expression of IFN-γ and IL-22 was greater in cervical Th17 cells than in blood Th17 cells. In keeping with the hypothesis that these cells are preferential HIV targets, gp120 preferentially bound CCR5(+) cervical T cells, and cervical Th17 cells were almost completely depleted in HIV(+) FSWs compared with HIV(-) FSWs. In summary, a subset of Th17 CD4(+) T cells in the cervical mucosa coexpresses multiple HIV susceptibility markers; their dramatic depletion after HIV infection suggests that these may serve as key target cells during HIV transmission.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".