Sperm DNA Fragmentation, Determined Using the Sperm Chromatin Dispersion (SCD) Test, A Study in Republic of Kosovo Population
Bibliographic record
Abstract
Infertility is a common condition affecting one in six couples of childbearing age. In approximately 40% of these cases, a male factor is involved. Sperm DNA integrity is essential for accurate transmission of genetic information. Materials and Methods: In this study 152 patients, 64 patients it is infertility group and 88 patients are fertile males. The ejaculate samples were taken in accordance with the patient to whom the reason for the analysis of the ejaculate sample was previously explained. All patients have been in the Dukagjini Region in the Republic of Kosovo. The samples were collected from 2016/18. Sperm Chromatin Dispersion (SCD) test, analysis in the ejaculate was performed at the Biolab Zafi, Laboratory in Peja, in the Republic of Kosovo. Statistical analysis: Data are reported as mean ± SD. The comparisons between groups were tested by student's t-test, ANOVA. A p-value less than 0.05% was considered statistically significant. Results: From our research studies, we have achieved significant (p <.00001) scores among the working group and control group across all sperm parameters, and DNA fragmentation. Conclusion: In summary, we have demonstrated that there was a negative correlation between DNA fragmentation, sperm motility, and morphology in infertile males. We conclude that sperm DNA fragmentation appears to be a useful technique to predict outcome in couples undergoing IVF/ICSI. To evaluate whether DFI 23.94 ± 4.68% can be used to determine male infertility in our country by Sperm Chromatin Dispersion (SCD), it is necessary to carry out further large-scale research by other authors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".