Characterization of the segmental transport mechanisms of DL-methionine hydroxy analogue along the intestinal tract of rainbow trout with an additional comparison to DL-methionine
Bibliographic record
Abstract
The aim of this study was to identify the unknown transport mechanism of the extensively used monocarboxylate methionine feed supplement DL-methionine hydroxy analogue (DL-MHA) in rainbow trout intestine. Transport across the pyloric caeca (PC), midgut (MG), and hindgut (HG) regions were kinetically studied in Na+- and H+-dependent manners. Gene expression of monocarboxylate (MCTs) and sodium monocarboxylate transporters (SMCTs) were assessed. Results demonstrated that DL-MHA transport from 0.2‐20 mM was Na+-dependent and obeyed Michaelis-Menten kinetics with low affinity in PC & MG in apical/basal pH of 7.7/7.7. Changes in apical/basal pH (6.0/6.0, 6.0/7.7, and 7.7/8.7) had insignificant effects on kinetics. In contrast, HG flux kinetics were only obtained in pH 7.7/8.7 or in the presence of lactate with medium affinity. Additionally, DL-MHA transport from 0‐150 μM demonstrated the presence of a Na+-dependent high-affinity transporter in PC & MG. Conclusively, two distinct carrier-mediated DL-MHA transport mechanisms along the trout gut were found: 1) in PC & MG: apical transport was regulated by Na+-requiring systems that possibly contained low- and high-affinity transporters, and basolateral transport was primarily achieved through a H+-independent transporter; 2) in HG: uptake was apically mediated by a Na+-dependent transporter with medium affinity, and basolateral exit was largely controlled by an H+-dependent transporter. Finally, two major methionine feed supplements, DL-MHA and DL-methionine (DL-Met) were compared to understand the differences in their bioefficacy. Flux rates of DL-MHA were only about 42.2–66.0% in PC and MG compared to DL-Met, suggesting intestinal transport of DL-MHA was lower than DL-Met.
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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".