Motoneurons Derived from Embryonic Stem Cells Express Transcription Factors and Develop Phenotypes Characteristic of Medial Motor Column Neurons
Bibliographic record
Abstract
Embryonic stem (ES) cells differentiate into functional motoneurons when treated with a sonic hedgehog (Shh) agonist and retinoic acid (RA). Whether ES cells can be directed to differentiate into specific subtypes of motoneurons is unknown. We treated embryoid bodies generated from HBG3 ES cells with a Shh agonist and RA for 5 d in culture to induce motoneuron differentiation. Enhanced green fluorescent protein (eGFP) expression was used to identify putative motoneurons, because eGFP is expressed under the control of the Hb9 promoter in HBG3 cells. We found that 96 +/- 0.7% of the differentiated eGFP+ motoneurons expressed Lhx3, a homeobox gene expressed by postmitotic motoneurons in the medial motor column (MMCm), when the treated cells were plated on a neurite-promoting substrate for 5 d. When the treated embryoid bodies were transplanted into stage 17 chick neural tubes, the eGFP+ motoneurons migrated to the MMCm, expressed Lhx3, projected axons to the appropriate target for MMCm motoneurons (i.e., epaxial muscles), and contained synaptic vesicles within intramuscular axonal branches. In ovo and in vitro studies indicated that chemotropic factors emanating from the epaxial muscle and/or surrounding mesenchyme likely guide Lhx3+ motoneurons to their correct target. Finally, whole-cell patch-clamp recordings of transplanted ES cell-derived motoneurons demonstrated that they received synaptic input, elicited repetitive trains of action potentials, and developed passive membrane properties that were similar to host MMCm motoneurons. These results indicate that ES cells can be directed to form subtypes of neurons with specific phenotypic properties.
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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 | 0.001 |
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".