A zombie <i>LIF</i> gene in elephants is up-regulated by TP53 to induce apoptosis in response to DNA damage
Bibliographic record
Abstract
Abstract Large bodied organisms have more cells that can potentially turn cancerous than smallbodied organisms with fewer cells, imposing an increased risk of developing cancer. This expectation predicts a positive correlation between body size and cancer risk, however, there is no correlation between body size and cancer risk across species (‘Peto’s Paradox’). Here we show that elephants and their extinct relatives (Proboscideans) may have resolved Peto’s Paradox in part through re-functionalizing a leukemia inhibitory factor pseudogene ( LIF6 ) with pro-apoptotic functions. The LIF6 gene is transcriptionally up-regulated by TP53 in response to DNA damage, and translocates to the mitochondria where it induces apoptosis. Phylogenetic analyses of living and extinct Proboscidean LIF6 genes indicates its TP53 response element evolved coincident with the evolution of large body sizes in the Proboscidean stem-lineage. These results suggest that re-functionalizing of a pro-apoptotic LIF pseudogene may have been permissive (though not sufficient) for the evolution of large body sizes in Proboscideans.
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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".