Comparison of intestinal glucose flux and electrogenic current demonstrates two absorptive pathways in pig and one in Nile tilapia and rainbow trout
Bibliographic record
Abstract
The mucosal-to-serosal flux of14C 3- O-methyl-d-glucose was compared against the electrogenic transport of d-glucose across ex vivo intestinal segments of Nile tilapia, rainbow trout, and pig in Ussing chambers. The difference in affinities ( Km“fingerprints”) between pig flux and electrogenic transport of glucose, and the absence of this difference in tilapia and trout, suggest two absorptive pathways in the pig and one in the fish species examined. More specifically, the total mucosal-to-serosal flux revealed a super high-affinity, high-capacity (sHa/Hc) total glucose transport system in tilapia; a super high-affinity, low-capacity (sHa/Lc) total glucose transport system in trout and a low-affinity, low-capacity (La/Lc) total glucose transport system in pig. Comparatively, electrogenic glucose absorption revealed similar Kmin both fish species, with a super high-affinity, high capacity (sHa/Hc) system in tilapia; a super high-affinity/super low-capacity (sHa/sLc) system in trout; but a different Kmfingerprint in the pig, with a high-affinity, low-capacity (Ha/Lc) system. This was supported by different responses to inhibitors of sodium-dependent glucose transporters (SGLTs) and glucose transporter type 2 (GLUT2) administered on the apical side between species. More specifically, tilapia flux was inhibited by SGLT inhibitors, but not the GLUT2 inhibitor, whereas trout lacked response to inhibitors. In contrast, the pig responded to inhibition by both SGLT and GLUT2 inhibitors with a higher expression of GLUT2. Altogether, it would appear that two pathways are working together in the pig, allowing it to have continued absorption at high glucose concentrations, whereas this is not present in both tilapia and trout.
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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 | 0.001 |
| 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".