Increased HIV-specific CD8+ T-cell cytotoxic potential in HIV elite controllers is associated with T-bet expression
Bibliographic record
Abstract
Recent data suggest that CD8+ T-cell effector activity is an important component in the control of HIV replication in elite controllers (ECs). One critical element of CD8+ T-cell effector function and differentiation is the T-box transcription factor T-bet. In the present study, we assessed T-bet expression, together with the effector proteins perforin, granzyme A (Grz A), granzyme B (Grz B), and granulysin, in HIV-specific CD8+ T cells from ECs (n = 20), chronically infected progressors (CPs; n = 18), and highly active antiretroviral therapy (HAART)-suppressed individuals (n = 19). Compared with the other cohort groups, HIV-specific CD8+ T cells among ECs demonstrated a superior ability to express perforin and Grz B, but with no detectable difference in the levels of Grz A or granulysin. We also observed higher levels of T-bet in HIV-specific CD8+ T cells from ECs, with an ensuing positive correlation between T-bet and levels of both perforin and Grz B. Moreover, HIV-specific CD8+ T cells in ECs up-regulated T-bet to a greater extent than CPs after in vitro expansion, with concomitant up-regulation of perforin and Grz B. These results suggest that T-bet may play an important role in driving effector function, and its modulation may lead to enhanced effector activity against HIV.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".