MAP17 Is a Necessary Activator of Renal Na+/Glucose Cotransporter SGLT2
Bibliographic record
Abstract
The renal proximal tubule reabsorbs 90% of the filtered glucose load through the Na + -coupled glucose transporter SGLT2, and specific inhibitors of SGLT2 are now available to patients with diabetes to increase urinary glucose excretion. Using expression cloning, we identified an accessory protein, 17 kDa membrane-associated protein (MAP17), that increased SGLT2 activity in RNA-injected Xenopus oocytes by two orders of magnitude. Significant stimulation of SGLT2 activity also occurred in opossum kidney cells cotransfected with SGLT2 and MAP17. Notably, transfection with MAP17 did not change the quantity of SGLT2 protein at the cell surface in either cell type. To confirm the physiologic relevance of the MAP17–SGLT2 interaction, we studied a cohort of 60 individuals with familial renal glucosuria. One patient without any identifiable mutation in the SGLT2 coding gene ( SLC5A2 ) displayed homozygosity for a splicing mutation (c.176+1G>A) in the MAP17 coding gene ( PDZK1IP1 ). In the proximal tubule and in other tissues, MAP17 is known to interact with PDZK1, a scaffolding protein linked to other transporters, including Na + /H + exchanger 3, and to signaling pathways, such as the A-kinase anchor protein 2/protein kinase A pathway. Thus, these results provide the basis for a more thorough characterization of SGLT2 which would include the possible effects of its inhibition on colocalized renal transporters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".