Characterization of Neuromuscular Junctions in Mice by Combined Confocal and Super-Resolution Microscopy
Bibliographic record
Abstract
Neuromuscular junctions (NMJs) are highly specialized synapses between lower motor neurons and skeletal muscle fibers that play an essential role in the transmission of molecules from the nervous system to voluntary muscles, leading to contraction. They are affected in many human diseases, including inherited neuromuscular disorders such as Duchenne muscular dystrophy (DMD), congenital myasthenic syndromes (CMS), spinal muscular atrophy (SMA), and amyotrophic lateral sclerosis (ALS). Therefore, monitoring the morphology of neuromuscular junctions and their alterations in disease mouse models represents a valuable tool for pathological studies and preclinical assessment of therapeutic approaches. Here, methods for labeling and analyzing the three-dimensional (3D) morphology of the pre- and postsynaptic parts of motor endplates from murine teased muscle fibers are described. The procedures to prepare samples and measure NMJ volume, area, tortuosity and axon terminal morphology/occupancy by confocal imaging, and the distance between postsynaptic junctional folds and acetylcholine receptor (AChR) stripe width by super-resolution stimulated emission depletion (STED) microscopy are detailed. Alterations in these NMJ parameters are illustrated in mutant mice affected by SMA and CMS.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".