MiRNA-103 downmodulates CCR5 expression reducing human immunodeficiency virus type-1 entry and impacting latency establishment in CD4+ T cells
Bibliographic record
Abstract
Activated-to-memory transitioning CD4 + T cells display elevated expression of the HIV-1 co-receptor CCR5 and are more prone to HIV-1 latent infection. Here, we show that p53-regulated miRNA-103 downmodulates CCR5 levels in CD4 + T lymphocytes. We reveal that miRNA-103 mimics, as well as Nutlin-3, an inhibitor of Mdm2-mediated p53 degradation, decrease CCR5-dependent HIV-1 infection. Using a dual-reporter virus, we subsequently validate that in transitioning CD4 + T cells, Nutlin-3 treatment decreases the frequency of both productively and latently infected cells via upregulation of miRNA-103. Importantly, we provide evidence that CD4 + T cells from HIV-1 elite controllers express less CCR5 than those from antiretroviral therapy-naïve progressors, an effect linked to a significant increase in miRNA-103 levels. By contributing to the control of CCR5 expression in CD4 + T cells, miRNA-103 is likely to play a key role in countering the establishment of latent HIV-1 reservoirs in vivo .
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".