Electron microscopic analysis of the influence of iPSC-derived motor neurons on bioengineered human skeletal muscle tissues
Bibliographic record
Abstract
Abstract 3D bioengineered skeletal muscle macrotissues are increasingly important for studies of cell biology and development of therapeutics. Tissues derived from immortalized cells obtained from patient samples or from stem cells can be co-cultured with motor-neurons to create models of human neuromuscular junctions in culture. In this study, we present foundational work on 3D cultured muscle ultrastructure, with and without motor neurons, which is enabled by the development of a new co-culture platform. Our results show that tissues from Duchenne muscular dystrophy patients are poorly organized compared to tissues grown from healthy donor and that the presence of motor neurons invariably improves sarcomere organization. Electron micrographs show that in the presence of motor neurons, filament directionality, banding patterns, z-disc continuity and appearance of presumptive SSR and T-tubule profiles all improve in healthy, DMD and iPSC derived muscle tissue. Further work to identify the underlying defects of DMD tissue disorganization and the trophic mechanisms by which motor neurons support muscle are likely to yield potential new therapeutic approaches for treating patients suffering from Duchenne muscular dystrophy.
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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".