Determination of transport stoichiometry for two cation‐coupled <i>myo</i>‐inositol cotransporters: SMIT2 and HMIT
Bibliographic record
Abstract
Three different mammalian myo-inositol cotransporters are currently known; two are Na+-coupled (SMIT1 and SMIT2) and one is proton-coupled (HMIT). Although their transport stoichiometries have not been directly determined, significant cooperativities in the Na+ activation of SMIT1 and SMIT2 suggest that more than one Na+ ion drives the transport of each myo-inositol. The two techniques used here to determine transport stoichiometry take advantage of the electrogenicity of both SMIT2 and HMIT expressed in Xenopus oocytes. The first method compares the measurement of charge transferred into voltage-clamped oocytes with the simultaneous uptake of radiolabelled substrate. The second approach uses high accuracy volume measurements to determine the transport-dependent osmolyte uptake and compares it to the amount of charge transported. This method was calibrated using a potassium channel (ROMK2) and was validated with the Na+/glucose cotransporter SGLT1, which has a known stoichiometry of 2 : 1. Volume measurements indicated a stoichiometric ratio of 1.78 +/- 0.27 ion per alpha-methyl-glucose (alphaMG) for SGLT1 whereas the radiotracer uptake method indicated 2.14 +/- 0.05. The two methods yielded a SMIT2 stoichiometry measurement of 1.75 +/- 0.30 and 1.82 +/- 0.10, both in agreement with a 2 Na+:1 myo-inositol stoichiometry. For HMIT, the flux ratio was 1.02 +/- 0.04 charge per myo-inositol, but the volumetric method suggested 0.67 +/- 0.05 charge per myo-inositol molecule. This last value is presumed to be an underestimate of the true stoichiometry of one proton for one myo-inositol molecule due to some proton exchange for osmotically active species. This hypothesis was confirmed by using SGLT1 as a proton-driven glucose cotransporter. In conclusion, despite the inherent difficulty in estimating the osmotic effect of a proton influx, the volumetric method was found valuable as it has the unique capacity of detecting unidentified transported substrates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".