Dual-Color PRINS for <i>In Situ</i> Detection of Fetal Cells in Maternal Blood
Bibliographic record
Abstract
Fetal nucleated cells circulating in the peripheral blood during pregnancy are potential targets for noninvasive genetic testing. Fluorescence in situ hybridization (FISH) frequently is used to quantify the total number of fetal cells in peripheral blood of pregnant women. We describe an alternative molecular cytogenetic procedure that is the primed in situ labeling (PRINS). This technique consists of annealing oligonucleotides specific to individual chromosome targets and in situ elongation using Taq DNA polymerase to incorporate labeled dUTPs. The sites of the newly synthesized DNA sequences were revealed as fluorescent signals using an immunochemical reaction. The dual-color PRINS was specifically performed for simultaneous detection of two chromosome targets, X and Y. The fluorescent signals corresponding to chromosomes X and Y were displayed as red and green color spots, respectively. The sensitivity and specificity of PRINS are similar to FISH and allow us to efficiently and reliably detect fetal cells in maternal blood. Moreover, dual-color PRINS is faster and more cost-effective than FISH.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".