The human tumour suppressor gene <i>SLC5A8</i> expresses a Na<sup>+</sup>–monocarboxylate cotransporter
Bibliographic record
Abstract
The orphan cotransport protein expressed by the SLC5A8 gene has been shown to play a role in controlling the growth of colon cancers, and the silencing of this gene is a common and early event in human colon neoplasia. We expressed this protein in Xenopus laevis oocytes and have found that it transports small monocarboxylic acids. The electrogenic activity of the cotransporter, which we have named SMCT (sodium monocarboxylate transporter), was dependent on external Na(+) and was compatible with a 3 : 1 stoichiometry between Na(+) and monocarboxylates. A portion of the SMCT-mediated current was also Cl(-) dependent, but Cl(-) was not cotransported. SMCT transports a variety of monocarboxylates (similar to unrelated monocarboxylate transport proteins) and most transported monocarboxylates demonstrated K(m) values near 100 microm, apart from acetate and d-lactate, for which the protein showed less affinity. SMCT was strongly inhibited by 1 mm probenecid or ibuprofen. In the absence of external substrate, a Na(+)-independent leak current was also observed to pass through SMCT. SMCT activity was strongly inhibited after prolonged exposure to high external concentrations of monocarboxylates. The transport of monocarboxylates in anionic form was confirmed by the observation of a concomitant alkalinization of the cytosol. SMCT, being expressed in colon and kidney, represents a novel means by which Na(+), short-chain fatty acids and other monocarboxylates are transported in these tissues. The significance of a Na(+)-monocarboxylate transporter to colon cancer presumably stems from the transport of butyrate, which is well known for having anti-proliferative and apoptosis-inducing activity in colon epithelial cells.
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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) | 0.002 | 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".