Enteric neurons synthesize netrins and are essential for the development of the vagal sensory innervation of the fetal gut
Bibliographic record
Abstract
During fetal life, vagal sensory fibers establish a reproducible distribution in the gut that includes an association with myenteric ganglia. Previous work has shown that netrin is expressed in the bowel wall and, by acting on its receptor, deleted in colorectal cancer (DCC), mediates the guidance of vagal sensory axons to the developing gut. Because the highest concentration of netrins in fetal bowel is in the endoderm, we tested the hypothesis that the ingrowth of vagal afferents to the gut would be independent of the presence of enteric neurons, although enteric neurons might influence the internal distribution of these fibers. Surprisingly, experiments indicated that the vagal sensory innervation is intrinsic neuron-dependent. To examine the vagal innervation in the absence of enteric ganglia, fetal Ret -/- mice were labeled by applying DiI bilaterally to nodose ganglia. In Ret -/- mice, DiI-labeled vagal sensory axons descended in paraesophageal trunks as far as the proximal stomach, which contains neurons, but did not enter the aganglionic bowel. To determine whether neurons produce netrins, enteric neural-crest-derived cells (ENCDCs) were immunoselected from E15 rat gut. Transcripts encoding netrin-1 and -3 were not detected in the ENCDCs, but appeared after they had given rise to neurons. When these neurons were cocultured with cells expressing c-Myc-tagged netrin-1, the neurons displayed netrin-1, but not c-Myc, immunoreactivity. Enteric neurons thus synthesize netrins. The extent to which neuronal netrin accounts for the dependence of the vagal sensory innervation on intrinsic neurons, remains to be determined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".