Distinct classes of lagging chromosome underpin age-related oocyte aneuploidy in mouse
Bibliographic record
Abstract
SUMMARY Chromosome segregation errors that cause oocyte aneuploidy increase in frequency with maternal age and are considered a major contributing factor of age-related fertility decline in females. A common age-associated chromosome segregation phenomenon in oocytes is the lagging anaphase chromosome, but whether anaphase laggards actually missegregate and cause aneuploidy is unclear. Here we show unexpectedly that lagging chromosomes in mouse oocytes comprise two mechanistically distinct classes of motion that we refer to as ‘Class-I’ and ‘Class-II’. We use imaging approaches and mechanistic interventions to dissociate the two classes, and find that whereas Class-II laggards are benign, Class-I laggards can directly cause aneuploidy. Most notably, a controlled prolongation of meiosis-I specifically lessens Class-I lagging to prevent aneuploidy. Our data thus reveal lagging chromosomes to be a cause of age-related aneuploidy in mouse oocytes and suggest that manipulating the cell cycle could increase the yield of useful oocytes in some contexts.
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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) | 0.003 | 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".