Effect of Energy Substrates on Protein Degradation in Isolated Small Intestinal Enterocytes From Rats
Bibliographic record
Abstract
BACKGROUND: Nutrients affect small intestinal protein mass and metabolism, but studies on the effect of nutrients on small intestinal protein degradation are very limited due to a lack of a proper method. The objectives of this study were to establish a method to directly estimate protein degradation in isolated enterocytes from rats and to test the effect of energy substrates on protein degradation. METHODS: Male Sprague-Dawley rats (150-200 g, n>or=8 per treatment) were used. Cell viability, tyrosine release as an indicator of protein degradation, and the effect of osmolarity, 50 mmol/L glucose, 20 mmol/L beta-hydroxybutyrate, 4.7 mmol/L butyrate, and 30 mmol/L glutamine on protein degradation were measured. RESULTS: The average viability of enterocytes at time 30 minutes was 85.8% (range, 81%-94%). Tyrosine release was linear over the course of experiments, indicating constant protein degradation (R2=0.9943; p<.05). Osmolarity, glucose, and glutamine had no effect on protein degradation in isolated enterocytes. Beta-hydroxybutyrate significantly decreased it (-16%; p<.05), whereas butyrate slightly increased it (+5%; p<.05). CONCLUSIONS: A high viability and constant protein degradation indicate a successful establishment of a method to estimate protein degradation in isolated small intestinal enterocytes from rats. The large effect of beta-hydroxybutyrate suggests a potential positive role for ketone bodies to limit the loss of small intestinal protein mass by decreasing protein degradation.
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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) | 0.001 | 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 | 0.001 |
| 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".