Content of exDNA in rooster’s seminal plasma as a potential biomarker of sperm viability
Bibliographic record
Abstract
Searching biomarkers, that have an early prognostic trait and determinate functional status of male gametes Gallus Gallus is a promising direction for improving ejaculate’s quality reproductive characteristics. In context of a decreasing reproductive performance due to breeding selection of birds aimed to improving economically useful traits, this approach to selecting males, based on their sperm quality production will make it possible to evaluate sperm in a short time and identify potentially the best producers at early stages. The study determined possibility of using exDNA as a potential biomarker that determines quality indicators of native sperm obtained from roosters. Significant correlations were revealed between exDNA and proportion of cells with damaged plasma membrane (r = 0.35, p<0.05), which indicates a possible connection of this biomarker with necrotic and apoptotic processes occurring in cells. Variation coefficient of exDNA indicator was 30.28 %, demonstrating the possibility of using the proposed biomarker (exDNA concentration in the seminal fluid of Gallus Gallus) as a predictive criterion for assessing quality of male gametes. Significant correlations (r = 0.51, p<0.05) were established between proportion of cells exposed to oxidative stress, proportion of cells with damaged plasma membrane and high mitochondrial activity, which indicates negative impact of reactive oxygen species on the plasma membrane integrity and relationship increased generation of reactive oxygen species with functional status of mitochondria. On the basis of the analysis of research results, the indicator “exDNA content in seminal fluid” should be considered as a preventive non-invasive biomarker of the functional state of male gamete Gallus Gallus.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".