Distribution of monocarboxylate transporters MCT1-MCT8 in rat tissues and human skeletal muscle
Bibliographic record
Abstract
In the past decade, a family of monocarboxylate transporters (MCTs) have been identified that can potentially transport lactate, pyruvate, ketone bodies, and branched-chain ketoacids. Currently, 14 such MCTs are known. However, many orphan transporters exist that have transport capacities that remain to be determined. In addition, the tissue distribution of many of these MCTs is not well defined. Such a cataloging can, at times, begin to suggest the metabolic role of a particular MCT. Recently, a number of antibodies against selected MCTs (MCT1, -2, -4, and -5 to -8) have become commercially available. Therefore, we examined the protein expression of these MCTs in a large number of rat tissues (heart, skeletal muscle, skin, brain, testes, vas deferens, adipose tissue, liver, kidney, spleen, and pancreas), as well as in human skeletal muscle. Unexpectedly, many tissues coexpressed 4-5 MCTs. In particular, in rat skeletal muscle MCT1, MCT2, MCT4, MCT5, and MCT6 were observed. In human muscle, these same MCTs were present. We also observed a pronounced MCT7 signal in human muscle, whereas a very faint signal occurred for MCT8. In rat heart, which is an important metabolic sink for lactate, we confirmed that MCT1 and -2 were expressed. In addition, MCT6 and -8 were also prominently expressed in this tissue, although it is known that MCT8 does not transport aromatic amino acids or lactate. This catalog of MCTs in skeletal muscle and other tissues has revealed an unexpected complexity of coexpression, which makes it difficult to associate changes in monocarboxylate transport with the expression of a particular MCT. The differences in transport kinetics for lactate and pyruvate are only known for MCT1, -2 and -4. Transport kinetics remain to be established for many other MCTs. In conclusion, this study suggests that in skeletal muscle, as well as other tissues, lactate and pyruvate transport rates may not only involve MCT1 and -4, as other monocarboxylate transporters are also expressed in rat (MCT2, -5, -6) and human skeletal muscle (MCT2, -5, -6, -7).
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 | 0.001 | 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) | 0.004 | 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".