Chromosomal mosaicism throughout human preimplantation development in vitro: incidence, type, and relevance to embryo outcome
Bibliographic record
Abstract
BACKGROUND: A large percentage of in-vitro generated cleavage stage human embryos are chromosomally mosaic, consisting of both normal (diploid) and abnormal (non-diploid) cells. The present study characterized mosaicism at each stage of cleavage division and examined its effect on preimplantation development in vitro. METHODS: A total of 216 normally fertilized (two-pronucleate) embryos which were not selected for transfer to the patients were analysed for chromosomal abnormalities using multi-colour fluorescence in-situ hybridization DNA probes specific for three to five of nine different chromosomes (X, Y, 2, 7, 13, 16, 18, 21, 22). RESULTS: Overall, 48.1% of embryos were mosaic. The frequency of mosaic embryos increased from 15.2 to 49.4 to 58.1%, from the 2-4-cell to 5-8-cell to morula stages respectively, and the types of non-diploid cells detected were mostly aneuploid or chaotic. The incidence of mosaicism at the blastocyst stage was 90.9%; however, most of the mosaicism comprised diploid and polyploid cells. Arrested mosaic embryos had a higher incidence of chaotic abnormalities, and higher proportions of abnormal cells compared with the non-arrested group. CONCLUSIONS: Post-zygotic errors leading to mosaicism may occur, and persist throughout preimplantation development in vitro. Our results suggest that mosaicism involving multiple chromosomal imbalances and/or imbalances affecting a high proportion of cells in an embryo appear to impair development to the blastocyst stage.
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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 | 0.001 |
| 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".