Beneficial effect of microsurgical varicocelectomy on human sperm DNA integrity
Bibliographic record
Abstract
BACKGROUND: Human sperm DNA damage may adversely affect reproductive outcomes, and the spermatozoa of infertile men possess substantially more DNA damage than that of fertile men. To date, there is no available treatment for men with high levels of sperm DNA damage. The objective of this study was to examine the effect of varicocelectomy on sperm DNA denaturation (DD, an index of sperm DNA damage) in infertile men with a clinical varicocele. METHODS: We reviewed the reports of 37 men who underwent microsurgical varicocelectomy at our institution from September 2001 to July 2002. Standard semen parameters and the percentage of spermatozoa with DD (monitored by flow cytometry analysis of acridine orange-treated spermatozoa) were assessed before and 6 months after varicocelectomy. RESULTS: The percentage of spermatozoa with DD decreased following varicocelectomy compared with pre-operatively (27.7 versus 24.6%, respectively, P < 0.05). Sperm concentration and the percentages of motile sperm and normal forms (WHO criteria) increased following varicocelectomy, but the difference did not reach statistical significance. CONCLUSIONS: Our data suggest that varicocelectomy can improve human sperm DNA integrity in infertile men with varicocele. These data represent the first report of improved sperm DNA integrity after therapy and further support the beneficial effect of varicocelectomy on human spermatogenesis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".