Influence of Sperm Chromatin Immaturity on Intracytoplasmic Sperm Injection Outcomes
Bibliographic record
Abstract
Background: Assisted Reproductive Techniques (ART), particularly intracytoplasmic sperm injection (ICSI), bypass natural selection processes, allowing sperm with low deoxyribonucleic acid (DNA) integrity to fertilize eggs, which may adversely affect ICSI outcomes. Routine semen analysis provides limited insight into male reproductive potential, necessitating advanced assessments of sperm chromatin maturity.Methods: Semen samples were collected from 92 patients after 1–21 days of sexual abstinence. Macroscopic and microscopic examinations were performed according to WHO standards (6th edition, 2021). A detailed questionnaire capturing history and physical examination was used. The relationship between sperm chromatin immaturity (SCI%) and ICSI outcomes, including fertilization rate and embryo quality, was evaluated.Result: A weak and non-significant negative correlation was observed between SCI% and fertilization rate (CC = -0.051; p = 0.63) and between SCI% and grade 1 embryos (CC = -0.093; p = 0.38). Weak, non-significant positive correlations were found between SCI% and abnormal division (CC = 0.05; p = 0.64). However, a weak positive association was identified between SCI% and grade 2 embryos (CC = 0.242; p = 0.02) and grade 3 embryos (CC = 0.212; p = 0.04). SCI% showed no significant correlation with seminal fluid parameters.Conclusion: This study concluded that sperm chromatin immaturity (SCI%) does not correlate with seminal fluid parameters but showed no significant correlation with fertilization rate or pregnancy rate and showed weak associations with some embryo grades.Keywords:DNA fragmentation, Sperm chromatin immaturity, Male infertility, Intracytoplasmic sperm injection (ICSI), Embryo quality
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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 | 0.002 | 0.007 |
| 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) | 0.002 | 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".