Hydrophobic residues as a key determinant in hexoses exchange urate mechanism mediated by human glucose transporter 9, hSLC2A9
Bibliographic record
Abstract
Human GLUT9 (hSLC2A9) is a urate/hexose transporter expressed predominantly in the liver and kidney where human urate homeostasis is achieved. hSLC2A9 has two splice variants: 9a and 9b differing in their N‐termini and targeted differentially within polarized epithelia. The transporter shows trans‐acceleration between urate and hexoses, however, the mechanism is unknown. Hydrophobic residues in TM7 of GLUTs have been shown to play a role in hexose selectivity. Objective To investigate urate/hexose exchange mediated by SLC2A9 isoforms and their mutants. Methods hSLC2A9 isoforms and I335V mutants were overexpressed in X. laevis oocytes. Urate induced currents and I‐V curves were obtained using Two Micro‐Electrode Voltage Clamp (TEVC) recordings. Urate transport and hexose trans‐stimulation activities were determined by radiolabelled urate uptake and efflux measurements. Results TEVC studies demonstrated that the membrane potential plays a major role in urate transport mediated by hSLC2A9. Fructose was found to trans‐stimulate urate uptake and efflux in wild type hSLC2A9a; whereas it stimulates only urate efflux in the I335V mutant. These finding advance our understanding of how fructose intake is linked with serum urate levels and implicates hSLC2A9 as an important transporter that may contribute to pathophysiological conditions involving urate or fructose. Supported by 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) | 0.000 | 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".