Major depression, physical health and molecular senescence markers abnormalities
Bibliographic record
Abstract
Previous studies suggested the role of cellular senescence in late-life depression (LLD). However, it is unclear how this finding relates to common features of LLD, such as medical and cognitive problems. We applied factor analyses to an extensive battery of clinical variables in 426 individuals with LLD. Here we tested the relationship between these factors, age and sex, with an index of cellular senescence based on 22 senescence-associated secretory phenotype proteins. We found four factors: 'depression and anxiety severity', 'cognitive functioning', 'cardiovascular and cardiometabolic health' and 'blood pressure'. A higher senescence-associated secretory phenotype index was associated with poorer 'cognitive functioning' and 'cardiovascular and cardiometabolic health' but not with 'depression and anxiety severity'. These findings highlight the role of cellular senescence in poorer physical and cognitive health in LLD. They are consonant with the viewpoint that co-occurring medical burdens and their associated disabilities are part of a phenotype of accelerated ageing in LLD.
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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 | 0.000 | 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".