Tissue-specific and isoform-specific changes in MCT1 and MCT4 in heart and soleus muscle during a 1-yr period
Bibliographic record
Abstract
We examined the postnatal changes (days 10, 36, 84, 160, 365) of monocarboxylate transporters (MCT)1 and MCT4 in rat heart and soleus muscle. In the heart, MCT1 protein and mRNA remained unaltered from day 10 until 1 yr of age. Both MCT4 protein and mRNA in the heart were detected at 10 days of age, but the MCT4 protein and transcript were not detected thereafter. In the soleus muscle, MCT1 protein (+38%) and mRNA (+136%) increased during the first 84 days and remained stable until 1 yr of age. In contrast, soleus MCT4 protein decreased by 90% over the course of 1 yr, with the most rapid decrease (-60%) occurring by day 84 (P < 0.05). At the same time, MCT4 mRNA was increased by 74% from days 10 to 84 (P < 0.05), remaining stable thereafter. In conclusion, developmental changes in MCT transport proteins are tissue specific and isoform specific. Furthermore, it appears that MCT1 expression in the heart and MCT1 and MCT4 expression in the soleus are regulated by pretranslational processes, whereas posttranscriptional processes regulate MCT4 expression in the soleus muscle.
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) | 0.001 | 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".