Characterization of CD8<sup>+</sup> T‐cell responses in HIV‐1‐exposed seronegative commercial sex workers from Nairobi, Kenya
Bibliographic record
Abstract
CD8+ T-lymphocyte responses are crucial to the control of HIV-1; therefore, studying the CD8+ immune response in a naturally resistant population could provide valuable insights into an effective anti-HIV response in healthy uninfected individuals. Approximately 5-10% of the women in the Pumwani Commercial Sex Worker cohort in Nairobi, Kenya, have been highly exposed to HIV-1 yet remain HIV-IgG-seronegative and HIV-PCR negative (HIV(ES)). As IFN-gamma production correlates to cytotoxic function, the CD8+ T-lymphocyte IFN-gamma response to HIV p24 peptides was compared in HIV(ES) and HIV-infected (HIV+) individuals. Almost 40% of the HIV(ES) had a CD8+ IFN-gamma+ response that was five times lower in magnitude than that of the HIV+ group. The breadth of the response in HIV(ES) was very narrow and focused primarily on one peptide that is similar to the protective KK10 peptide. In the HIV+ group, low peripheral CD4+ counts negatively influenced the number of CD8+ cells producing IFN-gamma, which may undermine the ability to control HIV. Overall, many of the HIV(ES) women possess a HIV-1 p24-specific CD8+ IFN-gamma response, providing evidence to the specificity needed for an effective HIV vaccine.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".