Gene Expression Profiling and Its Relevance to the Blood-Epididymal Barrier in the Human Epididymis1
Bibliographic record
Abstract
The luminal environment along the epididymal duct is important for spermatozoal maturation. This environment is unique and created by the blood-epididymal barrier, which is formed by tight and adhering junctions. For the human epididymis, little information exists on the proteins that comprise these junctions. Our objectives were to assess the gene expression profiles in the different segments of the human epididymis and to identify the proteins that make up the blood-epididymal barrier. Using microarrays, we identified 2980 genes that were differentially expressed by at least 2-fold between the various segments. Of the many genes involved in diverse functions, were those that encoded adhesion proteins (cadherins and catenins) and tight junctional proteins (claudins [CLDN] and others). PCR analyses confirmed the microarray data. Immunolocalization of CLDNs 1, 3, 4, 8, and 10 revealed that the localization of CLDNs differed along the epididymis. In all three segments, CLDNs 1, 3, and 4 were localized to tight junctions, along the lateral margins of adjacent principal cells, and at the interface between basal and principal cells. CLDN8 was localized to tight junctions in all three segments, in addition to being localized in the caput along the lateral margins of principal cells, and in the corpus, at the interface between principal and basal cells. CLDN10, tight junction protein 1, and occludin were localized exclusively to tight junctions in all three epididymal segments. These data indicate that the epididymis displays a complex pattern of gene expression, which includes genes that are implicated in the formation of the blood-epididymal barrier, which suggests complex regulation of this barrier.
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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 | 0.001 | 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".