Intragastric infusion of arginine stimulated greater liver protein synthesis compared to IV infusion in TPN‐fed Yucatan miniature piglets
Bibliographic record
Abstract
Total parenteral nutrition (TPN) induced gut atrophy reduces de novo synthesis of intestinal arginine (Arg) in neonates which may limit Arg availability. Our objective was to assess the effect of route of Arg intake on tissue protein synthesis in TPN‐fed piglets with gut atrophy. Piglets (14‐17 d) were fed TPN (1.0 g Arg/kg/d) until study d 4, then switched to Arg‐free TPN and randomized to receive a continuous intragastric infusion (2 mL/kg/hr) of either IG Low Arg (0.6 g/kg/d) or IG High Arg (1.6 g/kg/d). A 3 rd group was switched to high Arg TPN (1.6 g/kg/d) (IV High Arg). A group of sow‐fed (SF) littermates was also included. On d 7, piglets received an IV flooding dose of 3 H‐phenylalanine to measure protein synthesis (Ks, %/d). Liver Ks was greater in IG High Arg compared to IV High Arg. Mucosal Ks was highest in SF animals, with no differences in the TPN‐fed groups. Table values are mean (SD), N=3‐6 per tissue and group. Different superscripts by row, p<0.05 (ANOVA) Provision of high dietary Arg alone into the gut did not appear to enhance mucosal protein synthesis. Muscle protein synthesis was also not different, but was highly variable. IG delivery of Arg promoted liver protein synthesis compared to IV feeding; the mechanism is likely not related to Arg availability as there was no difference in liver free Arg. (CIHR)
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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) | 0.001 | 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) | 0.001 | 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".