Validation of a New Protocol to Collect and Isolate Plasma from Pregnant Women for Noninvasive Prenatal Testing (NIPT)
Bibliographic record
Abstract
BACKGROUND: Most laboratories use specialized tubes (e.g., Streck) to recover circulating cell-free DNA (ccfDNA) for noninvasive prenatal testing (NIPT). We validated a low cost, simple procedure for collecting NIPT samples in remote laboratories that avoids highspeed centrifugation. EDTA gel blood sampling tube allows simple separation of plasma from blood cells. Decanted plasma is filtered to remove cell debris. The procedure can be performed within a few minutes after the blood centrifugation step, and ccfDNA-grade plasma can be frozen for transportation. METHODS: We recruited 51 pregnant women and collected blood in one EDTA-gel Greiner tube and two Streck tubes. All tubes were centrifuged at 1600 g x 10 min within 6 h of sample collection. Plasma from EDTA tubes was poured into a syringe cylinder and filtered through a 0.45 µm Millipore filter. Plasma from Streck tubes was recovered with a pipette and one was filtered as above while the second was centrifuged at 16 000 g. The ccfDNA was isolated and NGS sequencing libraries were prepared and sequenced on an Illumina system. Fetal fractions were estimated using SeqFF. This study had a power of 79% to detect a decrease of 1% in fetal fractions with the new method. RESULTS: We did not observe any significant difference between the three procedures for the fetal fraction nor for the quality or quantity of libraries produced. CONCLUSION: EDTA-gel tubes with filtration provide high quality plasma for ccfDNA analysis and can be sent frozen to the NIPT laboratory. This is economical and it frees the laboratory of time-consuming steps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".