Surfing the wave, cycle, life history, and genes/proteins expressed by testicular germ cells. Part 5: Intercellular junctions and contacts between germs cells and Sertoli cells and their regulatory interactions, testicular cholesterol, and genes/proteins associated with more than one germ cell generation
Bibliographic record
Abstract
In the testis, cell adhesion and junctional molecules permit specific interactions and intracellular communication between germ and Sertoli cells and apposed Sertoli cells. Among the many adhesion family of proteins, NCAM, nectin and nectin-like, catenins, and cadherens will be discussed, along with gap junctions between germ and Sertoli cells and the many members of the connexin family. The blood-testis barrier separates the haploid spermatids from blood borne elements. In the barrier, the intercellular junctions consist of many proteins such as occludin, tricellulin, and claudins. Changes in the expression of cell adhesion molecules are also an essential part of the mechanism that allows germ cells to move from the basal compartment of the seminiferous tubule to the adluminal compartment thus crossing the blood-testis barrier and well-defined proteins have been shown to assist in this process. Several structural components show interactions between germ cells to Sertoli cells such as the ectoplasmic specialization which are more closely related to Sertoli cells and tubulobulbar complexes that are processes of elongating spermatids embedded into Sertoli cells. Germ cells also modify several Sertoli functions and this also appears to be the case for residual bodies. Cholesterol plays a significant role during spermatogenesis and is essential for germ cell development. Lastly, we list genes/proteins that are expressed not only in any one specific generation of germ cells but across more than one generation.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".