Functional Properties of Motoneurons Derived from Mouse Embryonic Stem Cells
Bibliographic record
Abstract
The capacity of embryonic stem (ES) cells to form functional motoneurons (MNs) and appropriate connections with muscle was investigated in vitro. ES cells were obtained from a transgenic mouse line in which the gene for enhanced green fluorescent protein (eGFP) is expressed under the control of the promotor of the MN specific homeobox gene Hb9. ES cells were exposed to retinoic acid (RA) and sonic hedgehog agonist (Hh-Ag1.3) to stimulate differentiation into MNs marked by expression of eGFP and the cholinergic transmitter synthetic enzyme choline acetyltransferase. Whole-cell patch-clamp recordings were made from eGFP-labeled cells to investigate the development of functional characteristics of MNs. In voltage-clamp mode, currents, including EPSCs, were recorded in response to exogenous applications of GABA, glycine, and glutamate. EGFP-labeled neurons also express voltage-activated ion channels including fast-inactivating Na(+) channels, delayed rectifier and I(A)-type K(+) channels, and Ca(2+) channels. Current-clamp recordings demonstrated that eGFP-positive neurons generate repetitive trains of action potentials and that l-type Ca(2+) channels mediate sustained depolarizations. When cocultured with a muscle cell line, clustering of acetylcholine receptors on muscle fibers adjacent to developing axons was seen. Intracellular recordings of muscle fibers adjacent to eGFP-positive axons revealed endplate potentials that increased in amplitude and frequency after glutamate application and were sensitive to TTX and curare. In summary, our findings demonstrate that MNs derived from ES cells develop appropriate transmitter receptors, intrinsic properties necessary for appropriate patterns of action potential firing and functional synapses with muscle fibers.
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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".