[P57]: A simple method for directing the differentiation of embryonic stem (ES) cells into functional motoneurones
Bibliographic record
Abstract
Directing embryonic stem (ES) cells to differentiate into functional motoneurones has proven to be a strong technique for studying neuronal development as well as being a potential source of cells for cell replacement therapies involving spinal cord disorders. Unfortunately, the mitogenic reagents currently used for directed differentiation are not commercially available and thus this technique has not been widely accessible to the scientific community. Here, we present a novel and simple method to derive motoneurones from ES cells using readily attainable reagents. ES cells were derived from a transgenic mouse in which enhanced green fluorescent protein (eGFP) was linked to the Hb9 promoter. Because Hb9 is expressed by motoneurones, eGFP expression was used to screen directed differentiation. ES cells were plated onto a monolayer of HK 293 cells that carry a stably integrated construct for the expression of murine sonic hedgehog (Shh) under ecdysone-inducible control (293 EcR Shh cells; ATCC). To initiate motoneurone differentiation, ES cell/HK 293 cell co-cultures were treated with Ponesterone A (PA) and retinoic acid (RA) for 5 days. PA induces ecdysone and thus drives Shh expression. To assess motoneurone differentiation the treated ES cells were either plated on Matrigel for standard immunocytochemical analysis or myotubes for electrophysiology recordings. A comparative study was also performed using ES cells treated with RA and recombinant human Shh (R&D Systems). ES cells differentiated into eGFP+ motoneurones that express Lhx3 and Isl1/2 in the co-cultures treated with PA and RA. Very poor motoneurone differentiation was achieved using RA and recombinant human Shh. ES cell derived motoneurones from the ES cell/HK 293 cell co-cultures also formed functional synaptic connections when plated on myotubes. This simple treatment paradigm produces functional motoneurones that can be used for developmental and pre-clinical studies. Support contributed by NSERC, CIHR and NSHRF.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".