Regulation of chemotropic guidance of nerve growth cones by microRNA
Bibliographic record
Abstract
BACKGROUND: The small non-coding microRNAs play an important role in development by regulating protein translation, but their involvement in axon guidance is unknown. Here, we investigated the role of microRNA-134 (miR-134) in chemotropic guidance of nerve growth cones. RESULTS: We found that miR-134 is highly expressed in the neural tube of Xenopus embryos. Fluorescent in situ hybridization also showed that miR-134 is enriched in the growth cones of Xenopus spinal neurons in culture. Importantly, overexpression of miR-134 mimics or antisense inhibitors blocked protein synthesis (PS)-dependent attractive responses of Xenopus growth cones to a gradient of brain-derived neurotrophic factor (BDNF). However, miR-134 mimics or inhibitors had no effect on PS-independent bidirectional responses of Xenopus growth cones to bone morphogenic protein 7 (BMP7). Our data further showed that Xenopus LIM kinase 1 (Xlimk1) mRNA is a potential target of miR-134 regulation. CONCLUSIONS: These findings demonstrate a role for miR-134 in translation-dependent guidance of nerve growth cones. Different guidance cues may act through distinct signaling pathways to elicit PS-dependent and -independent mechanisms to steer growth cones in response to a wide array of spatiotemporal cues during development.
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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 | 0.000 |
| 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".