Aneuploidy and DNA fragmentation in morphologically abnormal sperm
Bibliographic record
Abstract
In light of the relative success of ICSI in the treatment of male infertility, much importance has been made to the selection of morphologically viable sperm. However, correlation between specific sperm morphology and chromosomal abnormalities is still relatively limited and less is known about the connection between sperm morphology and DNA integrity. Sperm obtained from isolated teratozoospermic men (n = 10) and control men (n = 9) were analysed using FISH (for chromosomes 13, 18, 21, X and Y) and TUNEL assays to determine the level of aneuploidy and DNA fragmentation. Sperm morphology was evaluated on its ability to identify the level of chromosomal abnormalities or fragmented DNA in sperm. Sperm from teratozoospermic men, compared with fertile men, had higher rates of total chromosomal abnormality (p < 0.05), total aneuploidy (p < 0.01) and chromosome 13 disomy (p < 0.01). Associations between particular types of sperm morphology and chromosomal abnormalities were observed in both control (tapered heads) and teratozoospermic (amorphous heads and tail abnormalities) samples. Levels of DNA fragmented sperm were higher in teratozoospermic men than in the control men (60.28 +/- 21.40% vs. 32.40 +/- 17.20%, p < 0.05) and positively correlated to sperm with bent necks in control samples and round heads in teratozoospermic samples (p < 0.05). Sperm of isolated teratozoospermic men have higher rates of chromosomal abnormalities and DNA fragmentation than that of the fertile controls. Specific abnormal sperm morphology can be correlated to chromosomal abnormalities and level of DNA fragmentation in sperm.
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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 | 0.002 | 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".