Identification of an accessory protein necessary for the activation of the Na <sup>+</sup> /glucose cotransporter 2 (892.37)
Bibliographic record
Abstract
The Na+/glucose cotransporter SGLT2, which accounts for over 90% of renal glucose reabsorption, has become a major pharmaceutical target for type 2 diabetes treatment. Unfortunately, functional studies on SGLT2 have been hindered due to its lack of activity when expressed heterologously. Using an expression cloning strategy to identify a required accessory protein for SGLT2 function, we have identified MAP17 (membrane associated protein of 17 kDa) which is specifically expressed in the kidney proximal tubule, along with SGLT2. Using electrophysiology (oocytes) and radioactive uptakes (oocytes/OK cells), we demonstrate that MAP17 increases the activity of SGLT2 in both oocytes (150 fold) and OK cells (15 fold). Furthermore, Western blot and immunofluorescence studies using FLAG‐SGLT2 show that the cell surface density for SGLT2 is independent of MAP17 expression, which suggests that MAP17 stimulates the activity of SGLT2, but not its targeting. Finally, functional assays of disease‐causing mutations to SGLT2 (familial renal glucosuria) expressed in OK cells confirm these mutations to be non‐functional, even in the presence of MAP17. In conclusion, we have identified a cofactor responsible for the activation of SGLT2 which enables its characterization in heterologous systems.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".