Effects of Vasectomy on Gene Expression Profiling along the Human Epididymis1
Bibliographic record
Abstract
Worldwide, almost 100 million men rely on vasectomy for male contraceptive purposes. Due to changes in their personal lives, an increasing number of these men request surgical vasectomy reversal. Unfortunately, a significant proportion of these men remain infertile, despite the reestablishment of patent ducts, possibly due to epididymal damage caused by vasectomy. In animal models, vasectomy affects different epididymal physiological and biochemical parameters. However, the consequences of vasectomy on epididymal function are poorly understood. Furthermore, results obtained with animal models cannot be extrapolated to humans to understand the consequences of vasectomy on epididymal function. Gene expression along the epididymis is highly regulated. We previously showed that the human epididymal expression pattern of two genes is altered after vasectomy. To complete the list of epididymal genes affected by vasectomy, we analyzed the epididymal gene expression pattern of three vasectomized donors using the Affymetrix human GeneChip U133 Plus 2. These results were compared with the gene expression pattern of three "normal" donors. The data generated allowed the identification of many human epididymal genes for which expression is modified after vasectomy. Quantitative (Qt)-PCR and Western blot analysis of six selected genes known to be expressed in specific epididymal segments were performed. The Qt-PCR results confirmed the selected transcripts expression pattern deduced from microarray data. However, Western blot analysis revealed some differences in protein distribution along the epididymis when compared with the encoding transcripts expression pattern. These results contribute to an understanding of the reasons why fertility is not recovered in vasovasostomized men, even though spermogram values suggest surgical success of vasectomy reversal.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".