Unique features of memory T cells in HIV elite controllers: a systems biology perspective
Bibliographic record
Abstract
PURPOSE OF REVIEW: Elite controllers constitute a rare group of HIV-infected individuals who control HIV replication and maintain normal CD4 cell counts without antiretroviral therapy (ART). The mechanisms involved in the control of infection are poorly understood. This review will focus on the identification of signaling pathways upregulated or downregulated in different memory T-cell subsets in elite controllers by using systems biology approaches. Features of memory T cells in simian immunodeficiency virus (SIV) natural hosts will be also highlighted. Finally, we will discuss how these approaches will guide the development of new vaccines and therapeutic interventions. RECENT FINDINGS: Studies by our group identified the FOXO3a, STAT5, and Wnt/beta-catenin pathways as unique molecular signatures associated with survival of memory T cells in elite controllers. These discoveries open the path for the design of new strategies to prevent T-cell depletion in HIV-infected individuals. SUMMARY: The use of systems biology to identify molecular pathways involved in the survival of memory T cells is a powerful tool toward the understanding of mechanisms of HIV control in elite controllers. This will help to identify correlates of immune protection leading to the design of effective HIV vaccines and new targeted therapeutic interventions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".