Regulation of chemotropic guidance of nerve growth cones by microRNA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it