Cytomegalovirus Infection Reduces Telomere Length of the Circulating T Cell Pool
Bibliographic record
Abstract
Short telomeres of circulating leukocytes are a risk factor for age-related diseases, such as atherosclerosis, but the exact mechanisms generating variations in telomere length are unknown. We hypothesized that induction of differentiated T cells during chronic CMV infection would affect T cell telomere length. To test this, we measured the amount of differentiated T cells and telomere length of lymphocytes during primary CMV infection as well as CMV-seropositive and -seronegative healthy individuals. After primary CMV infection, we observed an increase in highly differentiated cells that coincided with a steep drop in telomere length. Moreover, we found in a cohort of 159 healthy individuals that telomere shortening was more rapid in CMV-seropositive individuals and correlated with the amount of differentiated T cells in both CD4(+) T cells and CD8(+) T cells. Finally, we found that telomere length measured in blood leukocytes is correlated with lymphocyte telomere length. Thus, CMV infection induces a strong decrease in T cell telomere length, which can be explained by changes in the composition of the circulating lymphocyte pool.
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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".