Enteric glia mediate neuronal outgrowth through release of neurotrophic factors.
Bibliographic record
Abstract
Previous studies have shown that transplanted enteric glia enhance axonal regeneration, reduce tissue damage, and promote functional recovery following spinal cord injury. However, the mechanisms by which enteric glia mediate these beneficial effects are unknown. Neurotrophic factors can promote neuronal differentiation, survival and neurite extension. We hypothesized that enteric glia may exert their protective effects against spinal cord injury partially through the secretion of neurotrophic factors. In the present study, we demonstrated that primary enteric glia cells release nerve growth factor, brain-derived neurotrophic factor and glial cell line-derived neurotrophic factor over time with their concentrations reaching approximately 250, 100 and 50 pg/mL of culture medium respectively after 48 hours. The biological relevance of this secretion was assessed by incubating dissociated dorsal root ganglion neuronal cultures in enteric glia-conditioned medium with and/or without neutralizing antibodies to each of these proteins and evaluating the differences in neurite growth. We discovered that conditioned medium enhances neurite outgrowth in dorsal root ganglion neurons. Even though there was no detectable amount of neurotrophin-3 secretion using ELISA analysis, the neurite outgrowth effect can be attenuated by the antibody-mediated neutralization of each of the aforementioned neurotrophic factors. Therefore, enteric glia secrete nerve growth factor, brain-derived neurotrophic factor, glial cell line-derived neurotrophic factor and neurotrophin-3 into their surrounding environment in concentrations that can cause a biological effect.
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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) | 0.001 | 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".