Tetraploidy causes chromosomal instability in acentriolar mouse embryos
Bibliographic record
Abstract
Tetraploidisation is considered a common event in the evolution of chromosomal instability (CIN) in cancer cells. The current model for how tetraploidy drives CIN in mammalian cells is that a doubling of the number of centrioles that accompany the genome doubling event leads to multipolar spindle formation and chromosome segregation errors. By exploiting the unusual scenario of mouse blastomeres, which lack centrioles until the ~64-cell stage, we show that tetraploidy can drive CIN by an entirely distinct mechanism. Tetraploid blastomeres assemble bipolar spindles dictated by microtubule organising centres, and multipolar spindles are rare. Rather, kinetochore-microtubule turnover is altered, leading to microtubule attachment defects and anaphase chromosome segregation errors. The resulting blastomeres become chromosomally unstable and exhibit a dramatic increase in whole chromosome aneuploidies. Our results thus reveal an unexpected mechanism by which tetraploidy drives CIN, in which the acquisition of chromosomally-unstable microtubule dynamics contributes to chromosome segregation errors following tetraploidisation.
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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 | 0.001 | 0.001 |
| 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".