The impact of sperm protamine deficiency and sperm DNA damage on human male fertility: a systematic review and meta-analysis
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Bibliographic record
Abstract
Existing literature suggests evidence that protamine deficiency is related to DNA damage and male fertility. In this meta-analysis, we analyzed the relationship between the ratio of protamine-1 and protamine-2 with male fertility and the association of protamine deficiency with sperm DNA damage. Quality of available cohort studies was evaluated using the Newcastle-Ottawa Scale checklist. Summary effect estimates with 95% confidence intervals (CI) were derived using a random effects model. The effect of the protamine ratio on male fertility was analyzed in nine studies demonstrating a significantly higher value of the protamine ratio in subfertile men (n = 633) when compared with controls (n = 453, SMD = 0.46, 95% CI 0.25-0.66, Z = 4.42, p < 0.00001). Both protamine mRNA (SMD = 0.45, 95% CI 0.11-0.79, Z = 2.63, p = 0.009) and protein ratio (SMD = 0.46, 95% CI 0.25-0.68, Z = 4.22, p < 0.0001) showed significantly increased values in subfertile patients. The association between protamine deficiency and DNA damage was analyzed in 12 studies (n = 845) exhibiting a combined overall correlation coefficient (COR) of 0.53 (95% CI 0.28-0.71, Z = 3.87, p < 0.001). Protamine deficiency measured by CMA3 staining was significantly associated with sperm DNA damage (COR = 0.71, 95% CI 0.48-0.85, Z = 4.87, p < 0.001), whereas the P1/P2 ratio was not (COR = 0.17, 95% CI -0.16 to 0.46, Z = 0.99, p = 0.33). It is concluded that the protamine ratio represents a suitable biomarker for the assessment of sperm quality and protamine deficiency is closely related with sperm DNA damage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| 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) | 0.001 | 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 it