Bibliographic record
Abstract
Mitochondrial (mt)DNA is strictly maternally inherited in mammals; new mutations thus segregate along maternal lineages without the benefit of homologous recombination with mtDNA of paternal origin. Despite the high mtDNA copy number (approximately 100000 or more) in mature oocytes, and despite the relatively small number of cell divisions during oogenesis, mtDNA sequence variants segregate rapidly between generations. This paradoxical behaviour has been ascribed to the presence of a mtDNA 'bottleneck' in oogenesis or early embryogenesis. The nature and size of this bottleneck have been the subject of much controversy. This review argues that segregation of mtDNA sequence variants in the female germline occurs primarily during mitosis in the oocyte precursor population. Segregation is rapid because the precursor cells (primordial germ cells and oogonia) contain a relatively small number of mtDNA templates (the bottleneck) and because the replication of mtDNA is under relaxed control. For the most part, the process appears similar in mice segregating polymorphic sequence variants and in human pedigrees segregating pathogenic point mutations. In particular, there is no evidence for selection against high levels of pathogenic mtDNA point mutations in oogenesis, in early embryonic development, or in fetal development, thus suggesting that efficient respiratory chain function is not critical until post-natal life. These results have important practical implications for clinical genetics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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".