Modulation of intestinal protein synthesis and protease mRNA by luminal and systemic nutrients
Bibliographic record
Abstract
Route of nutrient supply is important in regulation of intestinal protein metabolism, because total parenteral nutrition, compared with enteral feeding, leads to profound atrophy. Participation of the fractional rate of protein synthesis (Ks), their degradation in regulation of gut protein balance, and their possible modulation by specific nutrients are the focus of our work. We developed an in situ experimental system that allows controlled exposure of intestinal mucosa to nutrients systemically, luminally, or both. We examined the effects of systemic glucose and amino acid (AA) infusion in overnight-fasted piglets. Jejunal segments within each piglet were simultaneously, luminally perfused with solutions containing various AAs or glucose. Intravenous infusion of glucose increased mucosal Ks by 16% (P < 0.05), whereas intravenous infusion of AA had no effect on Ks. Systemic glucose infusion had no effect on mRNA levels for components of the ubiquitin-proteasome proteolytic pathway. However, levels of these mRNA were reduced by intravenous or luminal AA supply. This effect was greatest (-50%) when highest tissue concentrations of AAs were achieved by the simultaneous infusion of AA by both routes (P < 0.05). Our findings suggest that not only is the modulation of protein balance in the intestine in response to nutrients in part attributable to anabolic stimulation of protein synthesis initiated by the systemic appearance of glucose, but a fall in protein degradation is also a likely contributor. AAs appear to be a key factor required to reduce expression of genes connected with proteolysis.
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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 | 0.000 | 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".