Maintenance of CD4+ T-cell memory and HIV persistence: keeping memory, keeping HIV
Bibliographic record
Abstract
PURPOSE OF REVIEW: The present review summarizes the current challenges for the design of new therapeutic strategies toward HIV eradication in individuals receiving suppressive highly active antiretroviral therapy (HAART). We will focus on the experimental evidence suggesting that immunological mechanisms involved in the generation and maintenance of memory CD4+ T cells are also responsible for the establishment and persistence of a stable reservoir for HIV. RECENT FINDINGS: Recent studies performed on clinical samples obtained from virally suppressed HIV-infected individuals indicate that T-cell survival and homeostatic proliferation, two major mechanisms involved in the maintenance of immunological memory, contribute to the persistence of latently infected memory CD4+ T cells. Thus, the long lifespan characteristic of the HIV reservoir is likely a consequence of the capacity of the immune system to generate and maintain memory CD4+ T cells for a long period. SUMMARY: These findings suggest that strategies aimed at reducing the pool of latently infected cells should interfere with the survival pathways responsible for the long-term maintenance of memory CD4+ T cells. Because memory CD4+ T cells are critical for appropriate immune defense, targeted approaches are needed to interfere only with the long-term survival of discrete fractions of memory T cells carrying proviral DNA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".