Extracellular microRNAs from the epididymis as potential mediators of cell-to-cell communication
Bibliographic record
Abstract
Ribonucleic acid (RNA) was previously thought to remain inside cells as an intermediate between genes and proteins during translation. However, it is now estimated that 98% of the mammalian genomic output is transcribed as noncoding RNAs, which are involved in diverse gene expression regulatory mechanisms and can be transferred from one cell to another through extracellular communication. For instance, microRNAs are 22-nucleotide-long noncoding RNAs that are generated by endonuclease cleavage of precursors inside the cells and are secreted as extracellular microRNAs to regulate target cell posttranscriptional gene expression via RNA interference. We and others have shown that different populations of microRNAs are expressed in distinct regions of the human epididymis and regulate the expression of target genes that are involved in the control of male fertility as indicated by knock-out mouse models. Importantly, some microRNAs, including the microRNA-888 (miR-888) cluster that is exclusively expressed in the reproductive system of human and nonhuman primates, are released in the sperm-surrounding fluid in the epididymis via extracellular vesicles, the so-called epididymosomes. In addition to interacting with the membrane of maturing spermatozoa, these extracellular vesicles containing microRNAs communicate with epithelial cells located downstream from their release site, suggesting a role in the luminal exocrine control of epididymal functions. Apart from their potential roles as mediators of intercellular communication within the epididymis, these extracellular microRNAs are potent molecular targets for the noninvasive diagnosis of male infertility.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".