Size-scaling promotes senescence-like changes in proteome and organelle content
Bibliographic record
Abstract
Abstract Senescent cells typically have an enlarged cell size but the reason for this has not been fully elucidated. As abnormal cell size may alter protein concentrations and cellular functionality, we used proteomic data from 59 unperturbed human cell lines to systematically characterize cell-size dependent changes in intracellular protein concentrations and organelle content. Increase in cell size leads to ubiquitous transcriptionally and post-transcriptionally regulated reorganization and dilution of the proteome. Many known senescence proteins display disproportionate size-scaling consistent with their altered expression in senescent cells, while lysosomes and the endoplasmic reticulum expand in larger cells contributing to the senescence phenotype. Analysis of organelle proteome expression identifies p53 and retinoblastoma pathways as mediators of size-scaling, consistent with their role in senescence. Taken together, cell size can alter cellular fitness and function through cumulative reorganization of the proteome and organelle content. An extreme consequence of this pervasive size-scaling appears to be senescence.
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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) | 0.002 | 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".