Immunosenescence is associated with altered gene expression and epigenetic regulation in primary and secondary immune organs
Bibliographic record
Abstract
Deterioration of the immune system (immunosenescence) with age is associated with an increased susceptibility to infection, autoimmune disease and cancer, and reduced responsiveness to vaccination. Immunosenescence entails a reduced supply of naïve T cells from the thymus and increased specialization of peripheral T cell clones. Both thymic involution and peripheral T cell homeostasis are thought to involve cellular senescence. In order to analyze this at the molecular level, we studied gene expression profiles, epigenetic status, and genome stability in the thymus and spleen of 1-, 4-, and 18-month-old Long Evans rats. In the thymus, altered gene expression, DNA and histone H3K9 hypomethylation, increased genome instability, and apoptosis were observed in 18-month-old animals compared to 1- and 4-month-old animals. In the spleen, alterations in gene expression and epigenetic regulation occurred already by the age of 4 months compared to 1 month and persisted in 18-month-old compared to 1-month-old rats. In both organs, these changes were accompanied by the altered composition of resident T cell populations. Our study suggests that both senescence and apoptosis may be involved in altered organ function.
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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 | 0.001 | 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".