Developmental Expression of Monocarboxylate Transporter 1 and 4 in Rat Liver
Bibliographic record
Abstract
PURPOSE: Monocarboxylate transporters (MCT) are proton-coupled integral membrane proteins that control the influx and efflux of endogenous monocarboxylates such as lactate, acetate and pyruvate. They also transport and mediate the clearance of drugs such as valproate and gamma-hydroxybutyrate. CD147 functions as ancillary protein that chaperones MCT1 and MCT4 to the cell membrane. There is limited data on the maturation of MCT and CD147 expression in tissues related to drug distribution and clearance. The objective of the present study was to quantify hepatic MCT1, MCT4, and CD147 mRNA, whole cell and membrane protein expression from birth to sexual maturity. METHODS: Liver tissues were collected from male and female Sprague Dawley rats at postnatal days (PND) 1, 3, 5, 7, 10, 14, 18, 21, 28, 35, and 42 (n = 3 - 5). Hepatic mRNA, total and membrane protein expression of MCT1, MCT4, and CD147 was evaluated via qPCR and western blot. RESULTS: MCT1 mRNA and protein demonstrated nonlinear maturation patterns. MCT1 and CD147 membrane protein exhibited low expression at birth, with expression increasing three-fold by PND14, followed by a decline in expression at sexual maturity. MCT4 mRNA had highest expression at PND 1, with decreasing expression towards sexual maturity. In contrast, MCT4 membrane protein exhibited minimal expression from birth through weaning before a 10-fold surge at PND35, whereupon there was a sharp decline in expression at PND42. There was a significant positive correlation between MCT1 and CD147 whole cell and membrane expression, while MCT4 membrane expression demonstrated a weak negative correlation with CD147. CONCLUSION: Our study elucidates the transcriptional and translational maturation patterns of MCT1, MCT4 and CD147 expression, with isoform- dependent differences in the liver. Changes in transporter expression during development may greatly influence drug distribution and clearance in pediatric populations.
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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 | 0.001 | 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) | 0.002 | 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".