Monocyte subpopulations exhibit distinct TNF-dependent aging signatures
Bibliographic record
Abstract
Abstract Monocytes are a key cell type contributing to age-associated inflammation or inflammaging. Since monocytes have the potential to enter circulation and differentiate into macrophages in tissues, they are capable of having a systemic effect on health. Here, we characterize the effect of aging on the transcriptional regulation of monocyte subpopulations in the bone marrow. We find that aging classical (Ly6c high) and non-classical (Ly6c low) monocytes exhibit distinct transcriptional profiles. These were associated with changes to the epigenomic landscape driven by the activity of specific TFs that often had opposing effects in monocyte subpopulations. Next, we determined that the aging signature was diminished in TNF-KO mice indicating that monocytes are altered in a TNF-dependent manner. Finally, we found that a subset of the aging signature was triggered by TNF over-expression. Together, our results implicate key factors driving age-associated changes to the transcriptional regulation of monocyte subpopulations. This study provides a better understanding of the impact of aging on monocytes and identifies targets for future investigation aiming to improve health in aging.
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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".