Proximity of Cytomegalovirus-Specific CD8+ T Cells to Replicative Senescence in Human Immunodeficiency Virus-Infected Individuals
Bibliographic record
Abstract
Antiretroviral therapy, (ART) effectively extends the life expectancy of HIV-infected individuals, however, age-related morbidities have emerged as major clinical concerns. In this context, co-infection with cytomegalovirus (CMV) accelerates immune senescence and elevates risk for other age-related morbidities, possibly through increased inflammation. We investigated potential relationships between CMV memory inflation, immune senescence and inflammation by measuring markers of inflammation and telomere lengths of different lymphocyte subsets in HIV-infected individuals seropositive for anti-CMV antibodies. Our study cohort consists mainly of middle aged men who have sex with men (MSM) and heterosexuals who are stable under long term ART. Median levels of IL-6, TNF- and CRP were significantly higher in those co-infected with CMV. Lymphocyte telomere length in general correlated with age, but for 32/32 subjects tested, there was a consistent hierarchy of telomere lengths with CD8+ T cells’ shorter than the general lymphocyte population, CD57+CD8+ T cells’ shorter than CD8+ T cells’ and CMV-specific CD57+CD8+ T cells’ the shortest of all. Telomeres of HIV-specific CD8+ T cells were longer than those of CMV-specific CD8+ T cells in all cases tested and over 10 years, CMV-specific CD8+ T cell telomeres of 2 HIV-infected individuals eroded faster than those of HIV-specific CD8+ T cells. These data indicate that CMV-specific CD8+ T cells of HIV-infected individuals are the lymphocytes closest to telomere-imposed replicative senescence. Exhaustive proliferation of CMV-specific CD8+ T cells in HIV-infected individuals is a potential source of senescent lymphocytes affecting systemic immune function and inflammation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".