Retrograde influence of muscle fibers on their innervation revealed by a novel marker for slow motoneurons
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
Mammalian limb and trunk skeletal muscles are composed of muscle fibers that differ in contractile and molecular properties. They are commonly divided into four categories according to the myosin heavy chain that they express: I, IIA, IIX and IIB, ranging from slowest to fastest. Individual motor axons innervate tens of muscle fibers, nearly all of which are of the same type. The mechanisms accounting for this striking specificity, termed motor unit homogeneity, remain incompletely understood, in part because there have been no markers for motoneuron types. Here we show in mice that the synaptic vesicle protein SV2A is selectively localized in motor nerve terminals on slow (type I and small type IIA) muscle fibers; its close relatives, SV2B and SV2C, are present in all motor nerve terminals. SV2A is broadly expressed at birth; fast motoneurons downregulate its expression during the first postnatal week. An inducible transgene incorporating regulatory elements from the Sv2a gene permits selective labeling of slow motor units and reveals their composition. Overexpression of the transcriptional co-regulator PGC1α in muscle fibers, which converts them to a slow phenotype, leads to an increased frequency of SV2A-positive motor nerve terminals, indicating a fiber type-specific retrograde influence of muscle fibers on their innervation. This retrograde influence must be integrated with known anterograde influences in order to understand how motor units become homogeneous.
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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