Gliotactin, a novel marker of tricellular junctions, is necessary for septate junction development in <i>Drosophila </i>
Bibliographic record
Abstract
Septate junctions (SJs), similar to tight junctions, function as transepithelial permeability barriers. Gliotactin (Gli) is a cholinesterase-like molecule that is necessary for blood-nerve barrier integrity, and may, therefore, contribute to SJ development or function. To address this hypothesis, we analyzed Gli expression and the Gli mutant phenotype in Drosophila epithelia. In Gli mutants, localization of SJ markers neurexin-IV, discs large, and coracle are disrupted. Furthermore, SJ barrier function is lost as determined by dye permeability assays. These data suggest that Gli is necessary for SJ formation. Surprisingly, Gli distribution only colocalizes with other SJ markers at tricellular junctions, suggesting that Gli has a unique function in SJ development. Ultrastructural analysis of Gli mutants supports this notion. In contrast to other SJ mutants in which septa are missing, septa are present in Gli mutants, but the junction has an immature morphology. We propose a model, whereby Gli acts at tricellular junctions to bind, anchor, or compact SJ strands apically during SJ development.
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 | 0.000 | 0.000 |
| 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".