Effect of Massive Small Bowel Resection on Components of the Peptidergic Innervation of the Rat Small Intestine
Bibliographic record
Abstract
The effect of massive small bowel resection on the immunostaining of neuropeptides in the submucous plexus of the retained small intestine was examined. The neuropeptides chosen were somatostatin and vasoactive intestinal polypeptide because these are markers for two of the major populations of neurons in the plexus. Three different methods were used to assess the effect of resection on the enteric nervous system. Firstly immunocytochemical staining of neuropeptide containing neurons and nerve fibers was compared between test and control animals. The results demonstrated a significant increase in the number and size of the vasoactive intestinal polypeptide containing neurons with no change in the number of somatostatin neurons although these were also increased in size. Secondly the possibility that the increase in neuron number might be the result of neuronal division was examined by 3H-thymidine incorporation experiments. The results demonstrated that no neuronal elements were labelled. Finally the possibility that the increase in vasoactive intestinal peptide was the result of an increase in transcription was assessed by Northern blot analysis. The results demonstrated a small but significant increase in mRNA levels. It was concluded that massive small bowel resection directly affects neuropeptide levels in the submucous plexus, resulting in an increase in vasoactive intestinal polypeptide-immunoreactive neurons.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".