Molecular control of mitochondrial function in preimplantation mouse embryos
Bibliographic record
Abstract
Mitochondria play a key role in a number of physiological events during all stages of life, including the very first stages following fertilization. It is, therefore, important to understand the mechanisms controlling mitochondrial activity during early embryogenesis to determine their role in development outcome. The objective of this study was to investigate the molecular control of mitochondrial transcription and mitochondrial DNA (mtDNA) replication in mouse preimplantation embryos. We estimated the mtDNA copy number and characterized the expression patterns of two mitochondrial genes and several nuclear genes that encode mitochondrial transcription and replication factors throughout preimplantation development. Mitochondrial gene transcripts were present in larger quantities in morula and blastocyst stage embryos relative to other stages. A significant increase in the amount of mRNA for nuclear genes encoding mtDNA transcription factors was observed in eight-cell stage embryos. Although a similar increase in the mRNA levels of nuclear genes encoding mtDNA replication factors was observed in morula and blastocyst stage embryos, the number of mtDNA molecules remained stable during preimplantation stages, suggesting that nuclear-encoded mitochondrial transcription factors are involved in the regulation of mtDNA transcription during early development. Although transcripts of replication factors are abundant at the morula and blastocyst stage, mtDNA replication did not occur until the blastocyst stage, suggesting that the inhibition of mtDNA replication is controlled at the post-transcriptional level during early embryogenesis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".