The relationship between human sperm apoptosis, morphology and the sperm deformity index
Bibliographic record
Abstract
BACKGROUND: This study aimed to assess the relationship between apoptosis in human ejaculated spermatozoa, sperm morphology and the novel sperm deformity index (SDI). METHODS: Semen specimens from 50 healthy donors were prepared by density-gradient centrifugation followed by incubating the prepared sperm with paramagnetic annexin V-conjugated microbeads and subjecting this to magnetic cell sorting (MACS). The procedure delivers two sperm fractions: annexin-negative (non-apoptotic) and annexin-positive (apoptotic). Activated caspase-3 levels and the integrity of the sperm mitochondrial membrane potential (MMP) were assessed as markers of apoptosis in the annexin-negative and -positive aliquots following MACS. Sperm morphology and the SDI scores were assessed using the strict criteria. RESULTS: Compared with the apoptotic sperm subpopulations, the non-apoptotic sperm subpopulations had an improved sperm morphology profile as demonstrated by significantly higher proportions of sperm with normal morphology and significantly lower SDI scores and percentages of sperm with acrosomal defects, midpiece defects, cytoplasmic droplet and tail defects. There was a significant correlation between sperm morphology attributes studied and the expressed apoptotic markers - caspase-3 activation and MMP integrity. CONCLUSIONS: Non-apoptotic sperm fractions have morphologically superior quality sperm compared with apoptotic fractions as reflected by significantly lower SDI scores. The study results may support abortive apoptosis, where the apoptotic mechanism of sperm is already triggered prior to ejaculation.
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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 | 0.000 |
| 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".