HIV-Specific CD8+ Lymphocytes in Semen Are Not Associated with Reduced HIV Shedding
Bibliographic record
Abstract
Sexual contact with HIV-infected semen is a major driving force behind the global HIV pandemic. Little is known regarding the immune correlates of virus shedding in this compartment, although HIV-1-specific CD8+ T cells are present in semen. We collected blood and semen from 27 chronically HIV-infected, therapy-naive men without common sexually transmitted infections or urethral inflammation and measured HIV-1 RNA viral load and cytokine/chemokine levels in both compartments. HIV-1 RNA levels were 10-fold higher in blood than semen, but discordantly high semen shedding was associated with higher semen levels of the proinflammatory cytokines IL-6, IL-8, IL-12, and IFN-gamma. Virus-specific CD8+ T cell epitopes were mapped in blood by IFN-gamma ELISPOT, using an overlapping HIV-1 clade B peptide matrix, and blood and semen CD8+ T cell responses were then assayed ex vivo using intracellular IFN-gamma staining. HIV-specific CD8+ responses were detected in 70% of semen samples, and their frequency was similar to or higher than blood. There was no correlation between the presence of virus-specific CD8+ T cells in semen and levels of HIV-1 RNA shedding. Among participants with detectable CD8+ IFN-gamma semen responses, their relative frequency was not associated with reduced HIV-1 RNA shedding, and their absolute number was correlated with higher levels of HIV-1 RNA semen shedding (r = 0.6; p = 0.03) and of several proinflammatory cytokines. Neither the presence nor the frequency of semen HIV-specific CD8+ T cell IFN-gamma responses in semen correlated with reduced levels of HIV RNA in semen.
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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) | 0.003 | 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".