The development of preimplantation genetic diagnosis for myotonic dystrophy using multiplex fluorescent polymerase chain reaction and its clinical application
Bibliographic record
Abstract
Preimplantation genetic diagnoses (PGD) for single gene defects require considerable time and resources for the standardization of polymerase chain reactions that are rapid, sensitive and reliable. Developing tests for the trinucleotide repeat diseases, where the expansion of unstable repeats produces the phenotypes, are particularly complex. One of these disorders is myotonic dystrophy where, at present, diagnosis at the single cell level relies on the detection of the normal alleles from both the affected and unaffected parent. The incorporation of short tandem repeat polymorphisms in the assay can give additional information to improve the accuracy of diagnosis. We have developed a multiplex fluorescent reaction for myotonic dystrophy and one of two closely mapped, highly heterozygous, short tandem repeats (D19S219 and D19S559) on chromosome 19 to reduce the possibility of misdiagnosis due to contamination, act as a control for allelic drop-out and maximize the number of embryos genotyped. This protocol was designed as a general diagnosis for myotonic dystrophy, using the most informative of the two polymorphisms for each couple. Subsequently this approach was used in a PGD treatment cycle.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".