A126 RETROGRADE LABELLING OF NODOSE GANGLIA IN VIVO BY FLUORESCENT TRACERS
Bibliographic record
Abstract
Abstract Background The gut-brain axis is a bidirectional connection between the gastrointestinal tract (GI)and the central nervous system. The vagus nerve has been recognized as a principal component of this axis. Vagus nerve plays important role in maintaining homeostasis and normal GI functions, its afferent fibers can detect microbiota metabolites also. Many studies have demonstrated that the upper GI tract receives dense vagal innervation, which decreases distally throughout the tract. However, the distal colon sensory innervation of the vagus nerve remains controversial. Aims To illuminate the extent to which the vagus nerve innervates the colon, to determine whether anatomical evidence exists for double-labeled vagal afferents supplying the proximal and distal colon in the nodose ganglia. Methods C57Bl/6 mice (n=8) were injected in the proximal and distal colon with alternating solutions of retrograde tracers 1.7% Fast blue (FB) and 5% of lipophilic tracer DiI. Animals were left to recover for 10–13 days then underwent cardiac perfusion. Nodose ganglia were collected and fixed in 4% paraformaldehyde. 12 um tissue sections were then analyzed under a fluorescent microscope at 350nm and 555nm wavelength. Results In total, 27% of nodose cell bodies were labeled from the entire colon. Following proximal DiI injections, the percentage of labeled cell bodies in the nodose ganglia were 24.3± 3.9%. However, we observed a lower percentage of labeled neurons from the distal colon, with 9.3± 1.4% after DiI injections. FB labelling from the distal colon was three times less than that observed for DiI. Within the nodose ganglia, 40% of all distally labelled neurons were labelled with both tracers. Conclusions These findings indicate that in mice, both distal and proximal colon receives visceral sensory innervation from the vagus nerve. Thus, providing evidence for a sensory anatomical connection of the vagus nerve between these two parts of the colon. Funding Agencies CCC, CIHR
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".