Neurturin is a PGC-1α1-controlled myokine that promotes motor neuron recruitment and neuromuscular junction formation
Bibliographic record
Abstract
OBJECTIVE: We examined whether skeletal muscle overexpression of PGC-1α1 or PGC-1α4 affected myokine secretion and neuromuscular junction (NMJ) formation. METHODS: A microfluidic device was used to model endocrine signaling and NMJ formation between primary mouse myoblast-derived myotubes and embryonic stem cell-derived motor neurons. Differences in hydrostatic pressure allowed for fluidic isolation of either cell type or unidirectional signaling in the fluid phase. Myotubes were transduced to overexpress PGC-1α1 or PGC-1α4, and myokine secretion was quantified using a proximity extension assay. Morphological and functional changes in NMJs were measured by fluorescent microscopy and by monitoring muscle contraction upon motor neuron stimulation. RESULTS: Skeletal muscle transduction with PGC-1α1, but not PGC-1α4, increased NMJ formation and size. PGC-1α1 increased muscle secretion of neurturin, which was sufficient and necessary for the effects of muscle PGC-1α1 on NMJ formation. CONCLUSIONS: Our findings indicate that neurturin is a mediator of PGC-1α1-dependent retrograde signaling from muscle to motor neurons.
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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".