Identification of the downstream target of misshapen in regulating photoreceptor growth-cone targeting in Drosophila
Bibliographic record
Abstract
Neuronal growth cones guide the growing axons toward their target to establish precise neuronal connections during embryogenesis. The growth cone expresses cell surface receptors for recognizing guidance and targeting signals. It also possesses the intracellular signal transduction machinery to convert the extracellular signals into the reorganization of cytoskeletal structures in controlling growth-cone movement. Previous studies identified the SH2/SH3 adapter protein Dock as a key component of an evolutionarily conserved signaling pathway that transduces signals from cell-surface receptors to the growth-cone cytoskeleton to regulate growth cone motility. My M.Sc. studies (Ruan et al., 1999) demonstrated that the Ste20-like Serine/Threonine kinase Misshapen (Msn) functions downstream of Dock to regulate the proper targeting of a subset of R cell (R1-6) growth cones in the developing Drosophila visual system. To identify downstream targets of Msn, I have undertaken a genetic approach to search for second-site mutations that suppress a growth cone premature termination phenotype induced by Msn overexpression. We found that reducing the dosage of bifocal (bif), a gene encoding a putative cytoskeletal regulator, substantially suppressed the msn overexpression phenotype. Phenotypic analysis of bif mutants demonstrates that like loss of msn, loss of bif also specifically caused a failure of R1-6 growth cones to stop at lamina. Eye-specific expression of bif in bif mutants substantially rescued R1-6 targeting defect, indicating that bif is required in R1-6 growth cones for targeting decisions. Like overexpression of Msn, overexpression of Bif also caused pre-target growth cone termination. Biochemical studies show that Msn associated directly with Bif and phosphorylated Bif in vitro. Expression of Bif in cultured cells dramatically increased F-actin level and induced filopodium formation. Bif-induced cytoskeletal changes could be modulated subst
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".