The application of proteomic approaches to the study of mammalian spermatogenesis and sperm function
Bibliographic record
Abstract
Spermatogenesis is the process by which terminally differentiated sperm are produced from male germline stem cells. This complex developmental process requires the coordination of both somatic and germ cells through phases of proliferation, meiosis, and morphological differentiation, to produce the cell responsible for the delivery of the paternal genome. With infertility affecting ~ 15% of all couples, furthering our understanding of spermatogenesis and sperm function is vital for improving the diagnosis and treatment of male factor infertility. The emerging use of proteomic technologies has played an instrumental role in our understanding of spermatogenesis by providing information regarding the genes involved. This article reviews existing proteomic literature regarding spermatogenesis and sperm function, including the proteomic characterization of spermatogenic cell types, subcellular proteomics, post-translational modifications, interactomes, and clinical studies. Future directions in the application of proteomics to the study of spermatogenesis and sperm function are also discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".