HIV Nef Expression Favors the Relative Preservation of CD4+ T Regulatory Cells That Retain Some Important Suppressive Functions
Bibliographic record
Abstract
HIV-1 infection causes depletion and/or dysfunction of distinct CD4(+) T cell subsets and may affect these differently. Using the CD4C/HIV-1(Nef) transgenic (Tg) mice as a model, we report that HIV-1 Nef causes depletion of total CD4(+) T cells, but preserves and relatively enriches CD4(+) regulatory T cells (Treg). We found that Nef-mediated CD4(+) Treg enrichment is the direct result of Nef expression in CD4(+) T cells, occurs independently of Nef-induced lymphopenia, and most likely results from multiple mechanisms: lower apoptosis, enhanced cell division, and increased generation from precursors. Interestingly, Tg Treg relative enrichment could be reversed by enhancing Lck activity. Most importantly, we show that, in contrast to Tg helper CD4(+) T cells that have lost their function, Nef-expressing CD4(+) Treg retain their regulatory function in vitro and also in vivo, under some settings. In particular, we found that Treg prevent expansion of Tg B and non-Treg T cells in vivo. Our study reveals that Nef affects distinct CD4(+) T cell subsets differently and uncovers the high proliferative potential of B and non-Treg T cells in this mouse model.
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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 | 0.000 | 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) | 0.001 | 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".