Comparison of DNA Extraction Feasibility from Menstrual Blood and Endometrial Tissue in Reproductive-Aged Women
Bibliographic record
Abstract
ABSTRACT The endometrium is a highly vascularized tissue composed of numerous blood vessels, with cells that are formed and destroyed during each menstrual cycle. Menstrual blood, which is shed cyclically from the endometrium in women of reproductive age, contains endometrial tissue or cells. Both deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) are the primary nucleic acids present in cells with nuclei. In this study, 20 samples of menstrual blood and endometrial tissue were collected from women of reproductive age. Menstrual blood was gathered using specially designed filter paper, and DNA was extracted using the QIAamp DNA Mini Kit (Qiagen, Cat No.: 51304). Endometrial tissue was obtained via biopsy, and DNA was extracted using the Geneaid DNA Isolation Kit (Geneaid, New Taipei, Taiwan). DNA purity and concentration were measured using a Thermo Scientific Nano-Drop microvolume Spectrophotometer. The results indicated an average DNA purity of 1.88 ± 0.09 and a mean concentration of 116.9 ng/µL for menstrual blood, while endometrial tissue had a median DNA purity of 1.92 and a concentration of 192 ng/µL. Statistical analysis revealed no significant difference in DNA purity between menstrual blood and endometrial tissue (p = 0.083), but a significant difference in DNA concentration was observed (p = 0.002). Although there was a slight difference in DNA concentration, both menstrual blood and endometrial tissue samples were equally effective in preserving optimal purity and concentration of DNA molecules. Keywords: Deoxyribonucleic Acid, DNA, Endometrial Tissue, Menstrual Blood, Nucleic Acid.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".