The calcium‐activated protease calpain regulates netrin‐1 receptor deleted in colorectal cancer‐induced axon outgrowth in cortical neurons
Bibliographic record
Abstract
During development, neurons extend axons toward their appropriate synaptic targets to establish functional neuronal connections. The growth cone, a highly motile structure at the tip of the axon, is capable of recognizing extracellular guidance cues and translating them into directed axon outgrowth through modulation of the actin cytoskeleton. Netrin-1 mediates its attractive function through the receptor deleted in colorectal cancer (DCC) to promote axon outgrowth and guidance. The calcium-activated protease calpain is involved in the cleavage of cytoskeletal proteins, which plays an important role during adhesion turnover and cell migration. However, its function during neuronal development is less understood. Here we demonstrate that netrin-1 activated calpain in embryonic rat cortical neurons in an extracellular-regulated kinase 1/2-dependent manner. In addition, we found that netrin-1 stimulation led to an increase in calpain-1 localization in the axon, whereas its endogenous inhibitor calpastatin was decreased in the growth cones of cortical neurons by indirect immunofluorescence. Interestingly, calpain-1 was able to cleave DCC in vitro. Furthermore, netrin-1 induced the cleavage of the cytoskeletal proteins spectrin and focal adhesion kinase concomitantly with the intracellular domain of DCC in a calpain-dependent manner in embryonic rat cortical neurons. Cortical neurons over-expressing calpastatin or calpain-depleted neurons displayed increased basal axon length and were unresponsive to netrin-1 stimulation. Altogether, we propose a novel model whereby netrin-1/DCC-mediated axon outgrowth is modulated by calpain-mediated proteolysis of DCC and cytoskeletal targets in embryonic cortical neurons. Open Science: This manuscript was awarded with the Open Materials Badge For more information see: https://cos.io/our-services/open-science-badges/.
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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 | 0.000 |
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".