Effect of Alcohol Consumption on the Sperm DNA Integrity: A Systematic Review
Bibliographic record
Abstract
There is no solid conclusion on the conventional sperm parameters in association with alcohol consumption, evaluation of sperm DNA integrity thus become a more reliable parameter. Hereby, this literature search was performed to summarize alcohol consumption on the sperm DNA integrity. A computerized database search was done through MEDLINE via Ovid (since 1946 until August 2017) and Cochrane was used. The following set of keywords: ‘alcohol consumption OR alcohol intake OR alcohol diet OR drinking alcohol OR ethanol diet’ AND ‘sperm DNA OR sperm chromatin OR sperm genome OR sperm histone OR sperm protamine’ were utilised. 24 articles were retrieved where only five studies conform to the inclusion criteria All studies demonstrated a negative effect of alcohol consumption on sperm DNA integrity, regardless of various range of alcohol doses and duration of alcohol consumption. Out of five studies reviewed, four studies were using a different approach to measure the sperm DNA damage. Hereby, this review identified a need to use a single approach of DNA damage test by having various method of alcohol administration and/or vice versa so that the extension of sperm DNA damage to alcohol consumption will have a better conclusion. On the same note, a few studies have reported the reversibility on conventional semen parameters, none has been done on the sperm DNA damage upon alcohol withdrawal. Therefore, the role of alcohol withdrawal on the reversibility of sperm DNA damage needs to be as well investigated further.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".