HIV viral set point and host immune control in individuals with HIV-specific CD8+ T-cell responses prior to HIV acquisition
Bibliographic record
Abstract
OBJECTIVE: Vaccine-induced CD8(+) T-cell responses in primates have been associated with a reduced simian immunodeficiency virus plasma viral load and enhanced T-cell responses, but cellular vaccines have shown limited success in human trials. We previously described HIV-specific T-cell responses in two groups of highly exposed, persistently seronegative Kenyan female sex workers, and a subset of these participants have subsequently acquired HIV. We examined the impact of pre-existing CD8(+) T-cell responses on post-acquisition outcomes. DESIGN AND METHODS: HIV-specific CD8(+) T-cell responses had been examined in highly exposed, persistently seronegative participants from the Pumwani and Kibera cohorts, using a combination of virus-specific lysis, proliferation, interferon-gamma production, or all. Plasma viral load set point and HIV-specific T-cell proliferation and cytokine production were now examined post hoc by blinded investigators in the subset of participants who acquired HIV. RESULTS: Pre-acquisition cellular immune assays and post-infection viral load were available for 46 participants, and HIV-specific CD8(+) T-cell responses had been detected in 25 of 46 (54%) participants. Pre-acquisition CD8(+) T-cell responses were associated with a lower post-acquisition HIV viral load set point in both cohorts (pooled analysis, 3.1 vs. 4.1 log(10) RNA copies/ml; P=0.0002) and with enhanced post-acquisition HIV-specific CD8(+) T-cell proliferation (3.8 vs. 1.0%, P=0.03), but with a trend to reduced post-acquisition CD8(+) T-cell interferon-gamma responses. CONCLUSION: HIV-specific CD8(+) T-cell responses prior to HIV acquisition were associated with a lower HIV viral load and an altered functional profile of post-acquisition CD8(+) T-cell responses.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".