Integrins are necessary for the development and maintenance of the glial layers in the<i>Drosophila</i>peripheral nerve
Bibliographic record
Abstract
Peripheral nerve development involves multiple classes of glia that cooperate to form overlapping glial layers paired with the deposition of a surrounding extracellular matrix (ECM). The formation of this tubular structure protects the ensheathed axons from physical and pathogenic damage and from changes in the ionic environment. Integrins, a major family of ECM receptors, play a number of roles in the development of myelinating Schwann cells, one class of glia ensheathing the peripheral nerves of vertebrates. However, the identity and the role of the integrin complexes utilized by the other classes of peripheral nerve glia have not been determined in any animal. Here, we show that, in the peripheral nerves of Drosophila melanogaster, two integrin complexes (αPS2βPS and αPS3βPS) are expressed in the different glial layers and form adhesion complexes with integrin-linked kinase and Talin. Knockdown of the common beta subunit (βPS) using inducible RNAi in all glial cells results in lethality and glial defects. Analysis of integrin complex function in specific glial layers showed that loss of βPS in the outermost layer (the perineurial glia) results in a failure to wrap the nerve, a phenotype similar to that of Matrix metalloproteinase 2-mediated degradation of the ECM. Knockdown of βPS integrin in the innermost wrapping glia causes a loss of glial processes around axons. Together, our data suggest that integrins are employed in different glial layers to mediate the development and maintenance of the protective glial sheath in Drosophila peripheral nerves.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".