ϒ-secretase and LARG mediate distinct RGMa activities to control appropriate layer targeting within the optic tectum
Bibliographic record
Abstract
While a great deal of progress has been made in understanding the molecular mechanisms that regulate retino-tectal mapping, the determinants that target retinal projections to specific layers of the optic tectum remain elusive. Here we show that two independent RGMa-peptides, C- and N-RGMa, activate two distinct intracellular pathways to regulate axonal growth. C-RGMa utilizes a Leukemia-associated RhoGEF (LARG)/Rho/Rock pathway to inhibit axonal growth. N-RGMa on the other hand relies on ϒ-secretase cleavage of the intracellular portion of Neogenin to generate an intracellular domain (NeICD) that uses LIM-only protein 4 (LMO4) to block growth. In the developing tectum (E18), overexpression of C-RGMa and dominant-negative LARG (LARG-PDZ) induced overshoots in the superficial tectal layer but not in deeper tectal layers. In younger embryos (E12), C-RGMa and LARG-PDZ prevented ectopic projections toward deeper tectal layers, indicating that C-RGMa may act as a barrier to descending axons. In contrast both N-RGMa and NeICD overexpression resulted in aberrant axonal-paths, all of which suggests that it is a repulsive guidance molecule. Thus, two RGMa fragments activate distinct pathways resulting in different axonal responses. These data reveal how retinal projections are targeted to the appropriate layer in their target tissue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".