Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues
Bibliographic record
Abstract
Hydatidiform mole (HM) is an abnormal human pregnancy characterized by excessive trophoblastic proliferation and abnormal embryonic development. There are two types of HM based on microscopic morphological evaluation, complete HM (CHM) and partial HM (PHM). These can be further subdivided based on the parental contribution to the molar genomes. Such characterization of HM, by morphology and genotype analyses, is crucial for patient management and for the fundamental understanding of this intriguing pathology. It is well documented that morphological analysis of HM is subject to wide interobserver variability and is not sufficient on its own to accurately classify HM into CHM and PHM and distinguish them from hydropic non-molar abortions. Genotyping analysis is mostly performed on DNA and tissues from formalin-fixed paraffin-embedded (FFPE) products of conception, which have less than optimal quality and may consequently lead to wrong conclusions. In this article, detailed protocols for multiplex genotyping and flow cytometry analyses of FFPE molar tissues are provided, along with the interpretation of the results of these methods, their troubleshooting, and integration with the morphological evaluation, p57KIP2 immunohistochemistry, and fluorescence in situ hybridization (FISH) to reach a correct and robust diagnosis. Here, the authors share the methods and lessons learned in the past 10 years from the analysis of approximately 400 products of conception.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".