Localizing synaptic mRNAs at the neuromuscular junction: It takes more than transcription
Bibliographic record
Abstract
The neuromuscular junction has been used for several decades as an excellent model system to examine the cellular and molecular events involved in the formation and maintenance of a differentiated chemical synapse. In this context, several laboratories have focused their efforts over the last 15 years on the important contribution of transcriptional mechanisms to the regulation of the development and plasticity of the postsynaptic apparatus in muscle fibers. Converging lines of evidence now indicate that post-transcriptional events, operating at the level of mRNA stability and targeting, are likely to also play key roles at the neuromuscular junction. Here, we present the recent findings highlighting the role of these additional molecular events and extend our review to include data showing that post-transcriptional events are also important in the control of the expression of genes encoding synaptic proteins in muscle cells placed under different conditions. Finally, we discuss the possibility that mis-regulation of post-transcriptional events can occur in certain neuromuscular diseases and cause abnormalities of the neuromuscular junction.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".