Effect of IL-7 Therapy on Phospho-Ribosomal Protein S6 and TRAF1 Expression in HIV-Specific CD8 T Cells in Patients Receiving Antiretroviral Therapy
Bibliographic record
Abstract
Abstract IL-7 therapy has been evaluated in patients who do not regain normal CD4 T cell counts after virologically successful antiretroviral therapy. IL-7 increases total circulating CD4 and CD8 T cell counts; however, its effect on HIV-specific CD8 T cells has not been fully examined. TRAF1, a prosurvival signaling adaptor required for 4-1BB–mediated costimulation, is lost from chronically stimulated virus-specific CD8 T cells with progression of HIV infection in humans and during chronic lymphocytic choriomeningitis infection in mice. Previous results showed that IL-7 can restore TRAF1 expression in virus-specific CD8 T cells in mice, rendering them sensitive to anti–4-1BB agonist therapy. In this article, we show that IL-7 therapy in humans increases the number of circulating HIV-specific CD8 T cells. For a subset of patients, we also observed an increased frequency of TRAF1+ HIV-specific CD8 T cells 10 wk after completion of IL-7 treatment. IL-7 treatment increased levels of phospho-ribosomal protein S6 in HIV-specific CD8 T cells, suggesting increased activation of the metabolic checkpoint kinase mTORC1. Thus, IL-7 therapy in antiretroviral therapy–treated patients induces sustained changes in the number and phenotype of HIV-specific T cells.
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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) | 0.001 | 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".