Electrophysiological and morphological properties of submucosal neurons in the mouse distal colon
Bibliographic record
Abstract
The pathophysiology of intestinal secretion is increasingly studied using transgenic mouse models of colonic inflammation, but little is known about the properties of single submucosal neurons regulating epithelial secretion in the mouse. Therefore, these neurons were characterized in the mouse distal colon submucosal plexus using electrophysiological and morphological techniques. Action potentials and synaptic responses in single neurons were recorded in submucosal preparations in vitro using intracellular electrodes filled with neurobiotin, enabling subsequent morphological examination. Most neurons (approximately 90%) were classified as S-type neurons based on the presence of fast excitatory postsynaptic potentials (EPSPs), absence of prolonged after-hyperpolarizations, and uni-axonal morphology. These neurons rarely fired more than one action potential in response to intracellular depolarization but spontaneous fast EPSPs were observed. Fibre tract stimulation (20 Hz) elicited slow EPSPs in many neurons (37%) and slow inhibitory potentials were also observed in a subset of neurons (18%). None of these cells exhibited electrophysiological features suggestive of AH neurons. However, morphological studies demonstrated that 12% of neurons had two axons, and an immunohistochemical marker of mouse AH neurons, calcitonin gene-related peptide, was co-localized with the pan-neuronal marker HuD in 9% of neurons. Cell counts indicated that mouse distal colon ganglia were much smaller (> 80% contain one to five neurons) compared to guinea-pig distal colon ganglia (approximately 30% contain >10 neurons). This study has shown that mouse distal colon submucosal ganglia are relatively small and, based on combined morphological and electrophysiological features, most neurons exhibit S-type characteristics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".