Evaluation of a novel non-invasive preimplantation genetic screening approach
Bibliographic record
Abstract
OBJECTIVE: To assess whether embryonic DNA isolated from blastocyst culture conditioned medium (BCCM) combined with blastocoel fluid (BF) could be used for blastocyst stage non-invasive preimplantation genetic testing for chromosomal aneuploidy (non-invasive preimplantation genetic screening, NIPGS). PATIENTS: 47 embryos from 35 patients undergoing IVF. INTERVENTIONS: DNA analysis of combined BCCM plus BF in comparison with trophectoderm (TE) biopsy and/or whole blastocyst (WB)using next generation sequencing (NGS). RESULTS: Embryonic DNA was successfully amplified in 47/47 NIPGS samples (28 frozen-thawed and 19 fresh culture samples) ranging from 6.3 to 44.0 ng/μl. For frozen-thawed embryos, the concordance rate for whole chromosome copy number per sample was equivalent between NIPGS vs. TE biopsy, NIPGS vs. WB and TE vs. WB samples taken from the same embryo was 87.5%; 96.4% and 91.7% respectively (P>0.05), and the rate of concordance per single chromosome was 99.3%, 99.7% and 99.7%, respectively (P>0.05). In fresh cases (Day 4 to Day 5/6 culture), the concordance rate for whole chromosome copy number per sample between NIPGS vs. TE samples taken from the same embryo was 100%, and the rate of concordance per single chromosome was 98.2% (P>0.05). CONCLUSIONS: A combination of BCCM and BF contains sufficient embryonic DNA for whole genome amplification and accurate aneuploidy screening. Our findings suggest that aneuploidy screening using BCCM combined with BF could potentially serve as a novel NIPGS approach for use in human IVF.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".