Evaluation of potential protein biomarkers in patients with high sperm DNA damage
Bibliographic record
Abstract
The laboratory evaluation of male infertility remains an essential area of research as 40-60% of infertility cases are attributable to male-related factors. Current sperm analysis methods add only partial information on sperm quality and fertility outcomes. The specific underlying cause of infertility in most cases is unknown, while a proportion of male infertility could be caused by molecular factors such as the absence or abnormal expression of some essential sperm proteins. The objective of this study was to screen for associations between sperm protein profiles and sperm concentration, motility, and DNA fragmentation index in patients undergoing fertility evaluation in a clinical setting. Based on those parameters, semen samples were categorized as either normal or abnormal. We screened 34 semen samples with various abnormal parameters and compared them to 24 normal control samples by using one dimensional (1-D) gel electrophoresis and mass-spectrometry. In this study, we anticipated to establish a normal sperm parameter profile which would be compared to abnormal sperm samples and reveal candidate proteins. Our preliminary results indicate that no normal uniform profile could be established, which affirms the complexity of male fertility and confirms the limitations of standard semen analysis. Four main protein groups were identified in correlation with abnormal DNA fragmentation and/or motility. The first group included sperm nuclear proteins such as the SPANX (sperm protein associated with the nucleus on the X chromosome) isoforms and several types of histones. The second group contained mitochondria-related functions and oxidative stress proteins including Mitochondrial Ferritin, Mitochondrial Single-Stranded DNA Binding Protein, and several isoforms of Peroxiredoxins. Two other protein groups were related to sperm motility such as microtubule-based flagellum and spindle microtubule as well as proteins related to the ubiquitin-proteasome pathway. Further research is required in order to characterize these potential biomarkers of male fertility potential.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".