Exploring monocarboxylate transporter inhibition for cancer treatment
Bibliographic record
Abstract
Cells are separated from the environment by a lipid bilayer membrane that is relatively impermeable to solutes. The transport of ions and small molecules across this membrane is an essential process in cell biology and metabolism. Monocarboxylate transporters (MCTs) belong to a vast family of solute carriers (SLCs) that facilitate the transport of certain hydrophylic small compounds through the bilipid cell membrane. The existence of 446 genes that code for SLCs is the best evidence of their importance. In-depth research on MCTs is quite recent and probably promoted by their role in cancer development and progression. Importantly, it has recently been realized that these transporters represent an interesting target for cancer treatment. The search for clinically useful monocarboxylate inhibitors is an even more recent field. There is limited pre-clinical and clinical experience with new inhibitors and their precise mechanism of action is still under investigation. What is common to all of them is the inhibition of lactate transport. This review discusses the structure and function of MCTs, their participation in cancer, and old and newly developed inhibitors. Some suggestions on how to improve their anticancer effects are also discussed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".