Short‐chain fatty acids and total parenteral nutrition affect intestinal gene expression
Bibliographic record
Abstract
BACKGROUND: The supplementation of total parenteral nutrition (TPN) formulas with short-chain fatty acids (SCFAs) increases glucose uptake and the expression of glucose transporters in parenterally fed animals. Several signals may be involved in intestinal adaptation; however, increased messenger RNA (mRNA) levels for proglucagon and several early-response genes, including c-myc and c-fos, are seen in animals receiving SCFA-supplemented TPN. Although the effects of a mixture of SCFAs are well documented, the relative contribution of individual SCFAs is unknown. Butyrate is a preferred fuel of colonocytes, with documented effects on cellular proliferation and gene expression. Accordingly, this study was undertaken to determine the relative role of butyrate in initiating an adaptive response in nonresected rats receiving TPN. METHODS: Animals received standard TPN for 66 hours, followed by 6 hours of either standard TPN, TPN supplemented with a mixture of SCFAs (acetate, propionate, and butyrate, 60 mmol/L total), or TPN supplemented with butyrate alone (9 mmol/L). An oral control group was fed an elemental diet, similar in macronutrient content to the TPN, so that all animals received the same amount of energy daily. RESULTS: SCFAs increased ileal glucose transporter 2 (GLUT2) mRNA expression compared with the orally fed group. SCFAs also increased proglucagon mRNA expression compared with the TPN group. No changes in Na+K(+)-adenosine triphosphatase or early-response gene expression were found in this study. CONCLUSIONS: In a rat model of TPN, the use of 9 mmol/L butyrate did not have the same effect on GLUT2 and proglucagon expression as a 60-mmol/L mixture of SCFAs. This suggests that the effect of a mixture of SCFAs on intestinal gene expression is not butyrate specific.
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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 | 0.000 |
| 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".