Mind the (sr)GAP – roles of Slit–Robo GAPs in neurons, brains and beyond
Bibliographic record
Abstract
The Slit-Robo GTPase-activating proteins (srGAPs) were first identified as potential Slit-Robo effectors that influence growth cone guidance. Given their N-terminal F-BAR, central GAP and C-terminal SH3 domains, srGAPs have the potential to affect membrane dynamics, Rho family GTPase activity and other binding partners. Recent research has clarified how srGAP family members act in distinct ways at the cell membrane, and has expanded our understanding of the roles of srGAPs in neuronal and non-neuronal cells. Gene duplication of the human-specific paralog of srGAP2 has resulted in srGAP2 family proteins that may have increased the density of dendritic spines and promoted neoteny of the human brain during crucial periods of human evolution, underscoring the importance of srGAPs in the unique sculpting of the human brain. Importantly, srGAPs also play roles outside of the nervous system, including during contact inhibition of cell movement and in establishing and maintaining cell adhesions in epithelia. Changes in srGAP expression may contribute to neurodevelopmental disorders, cancer metastasis and inflammation. As discussed in this Review, much remains to be discovered about how this interesting family of proteins functions in a diverse set of processes in metazoans and the functional roles srGAPs play in human disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".