Region-specific gene expression profiling along the human epididymis
Bibliographic record
Abstract
During their transit through the epididymis, spermatozoa undergo many biochemical modifications necessary to acquire flagellar motility and fertilizing ability. These modifications, collectively called sperm maturation, are well orchestrated along the epididymis and depend on highly regionalized gene expression patterns. Based on clinical observations, the role of the epididymis in human sperm maturation has been questioned. To further understand the function of the excurrent duct in humans, we analysed gene expression of three donors on 'Affymetrix human GeneChip U133 plus 2' representing 47,000 transcriptional variants. More than 50% of transcripts were detected in each epididymal region. The analysis of hierarchical clustering performed from 2274 modulated qualifers between the three regions revealed that 1184, 713 and 269 were highly expressed in the caput, corpus and cauda region, respectively, in a very specific manner. The expressed qualifers were grouped according their similarity by Gene Ontology to give an overview of the functional features of the encoded proteins and to elucidate their potential roles in the epididymis. Northern blot analysis of eight gene transcripts predicted by microarray data to be highly expressed in the human epididymis was performed. All the transcript expression patterns confirmed the microarrays results. The data generated in this study demonstrate a region-specific gene expression pattern along the human epididymis that seems to coincide with the morphologically distinctive features of the excurrent duct.
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 | 0.000 |
| 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".