Roundabout 1 exists predominantly as a basal dimeric complex and this is unaffected by binding of the ligand Slit2
Bibliographic record
Abstract
Robo (Roundabout) receptors and their Slit polypeptide ligands are known to play key roles in neuronal development and have been implicated in both angiogenesis and cancer. Like the other family members, Robo1 is a large single transmembrane domain polypeptide containing a series of well-defined extracellular elements. However, the intracellular domain lacks structural definition and little is known about the quaternary structure of Robo receptors or how binding of a Slit might affect this. To address these questions combinations of both autofluorescent protein-based FRET imaging and time-resolved FRET were employed. Both approaches identified oligomeric organization of Robo1 that did not require the presence of the intracellular domain. SpIDA (spatial intensity distribution analysis) of eGFP-tagged forms of Robo1 indicated that for a C-terminally deleted version approximately two-thirds of the receptor was present as a dimer and one-third as a monomer. By contrast, full-length Robo1 was present almost exclusively as a dimer. In each case this was unaffected by the addition of Slit2, although parallel studies demonstrated the biological activity of Slit2 and its interaction with Robo1. Deletion of both the immunoglobulin and fibronectin type III extracellular repeats prevented dimer formation, with the immunoglobulin repeats providing the bulk of the protein-protein interaction affinity.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".