173 Characterization of urea transport mechanisms in the intestinal tract of growing pigs
Bibliographic record
Abstract
Abstract Previous studies have indicated that pigs are capable of nitrogen salvage via urea recycling, which involves the movement of urea into the gastrointestinal tract and incorporation of nitrogen into endogenous or microbially produced amino acids. Aquaporins (AQP) and urea transporter B (UT-B) have been shown to contribute to urea transport in ruminants; however, it is unclear whether the same processes contribute to urea movement in the intestinal tract of the pig. The objective of this study was to characterize the presence and relative contribution of known urea transporters to urea flux in the growing pig. A total of 9 barrows of 50.8±0.9 kg BW were euthanized and samples of intestinal tissue were obtained from the duodenum, jejunum, ileum, cecum, and colon. All tissue samples were analyzed for mRNA abundance of UT-B and AQP-3, 7, and 10 via qPCR. Immediately after tissue collection, samples from jejunum and cecum were placed in Ussing chambers for analysis of serosal-to-mucosal urea flux using 14C-urea (49.95 kBq). Serosal-to-mucosal urea flux was measured across intestinal tissue samples with no inhibition or with addition of phloretin (1 mM) to inhibit UT-B-mediated transport, NiCl2 (1 mM) to inhibit AQP-mediated transport, or both inhibitors. UT-B was most highly expressed in the cecum (P < 0.05), while AQP-3, 7, and 10 were most highly expressed in the jejunum (P < 0.05). Serosal-to-mucosal urea flux occurred in both the jejunum and the cecum and was higher in the cecum (42.7 vs. 67.8±5.01 µmol/cm2/h; P < 0.05), confirming the capacity for urea recycling into the gut in pigs; however, neither flux rate was influenced by urea transporter inhibitors (P > 0.05). The results of this study indicate that while known urea transporters are present in the gastrointestinal tract of pigs, they do not play a significant role in urea transport.
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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) | 0.001 | 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".