A Quantitative Cell Migration Assay for Murine Enteric Neural Progenitors
Bibliographic record
Abstract
Neural crest cells (NCC) are a transient and multipotent cell population that originates from the dorsal neural tube and migrates extensively throughout the developing vertebrate embryo. In addition to providing peripheral glia and neurons, NCC generate melanocytes as well as most of the cranio-facial skeleton. NCC migration and differentiation is controlled by a combination of their axial origin along the neural tube and their exposure to regionally distinct extracellular cues. Such contribution of extracellular ligands is especially evident during the formation of the enteric nervous system (ENS), a complex interconnected network of neural ganglia that locally controls (among other things) gut muscle movement and intestinal motility. Most of the ENS is derived from a small initial pool of NCC that undertake a long journey in order to colonize - in a rostral to caudal fashion - the entire length of the prospective gut. Among several signaling pathways known to influence enteric NCC colonization, GDNF/RET signaling is recognized as the most important. Indeed, spatiotemporally controlled secretion of the RET ligand GDNF by the gut mesenchyme is chiefly responsible for the attraction and guidance of RET-expressing enteric NCC to and within the embryonic gut. Here, we describe an ex vivo cell migration assay, making use of a transgenic mouse line possessing fluorescently labeled NCC, which allows precise quantification of enteric NCC migration potential in the presence of various growth factors, including GDNF.
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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 | 0.000 | 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".