Unraveling The Impact of Viral Infections on Sperm Genetic Stability: A Scoping Review.
Bibliographic record
Abstract
Despite the apparent resilience of the male reproductive system, various viruses have been found to impact male fertility by causing testicular inflammation, hormonal imbalances, and sperm abnormalities. The integrity of the genome is vital for cell function, and its instability, influenced by various factors including viral infections, may contribute to age-related conditions such as cancer and neurodegenerative disorders. This scoping review aims to investigate the relationship between viral infections and sperm genetic stability, exploring their interactions and potential impact on male reproductive health and fertility. In order to conduct this scoping review, PubMed, MEDLINE (OVID), ScienceDirect, Google Scholar, and Cochrane databases were explored to find the relevant articles using a search strategy developed in collaboration with a medical librarian. Two independent reviewers screened titles and abstracts of the relevant papers, followed by full-text screening. Studies focusing on infertile males with viral infections, compared to fertile males, examining DNA damage and sperm abnormalities were included. Thirty-four studies were included in the current review. This review will provide valuable information to healthcare professionals in addressing virusinduced sperm genetic instability and its implications for reproductive health. Furthermore, it highlights the socioeconomic and public health aspects of preventing and managing viral infections.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".