Calcium signaling recruits substrate transporters GLUT4 and CD36 to the sarcolemma without increasing cardiac substrate uptake
Bibliographic record
Abstract
Activation of AMP-activated protein kinase (AMPK) in cardiomyocytes induces translocation of glucose transporter GLUT4 and long-chain fatty acid (LCFA) transporter CD36 from endosomal stores to the sarcolemma to enhance glucose and LCFA uptake, respectively. Ca(2+)/calmodulin-activated kinase kinase-β (CaMKKβ) has been positioned directly upstream of AMPK. However, it is unknown whether acute increases in [Ca(2+)]i stimulate translocation of GLUT4 and CD36 and uptake of glucose and LCFA or whether Ca(2+) signaling converges with AMPK signaling to exert these actions. Therefore, we studied the interplay between Ca(2+) and AMPK signaling in regulation of cardiomyocyte substrate uptake. Exposure of primary cardiomyocytes to inhibitors or activators of Ca(2+) signaling affected neither AMPK-Thr(172) phosphorylation nor basal and AMPK-mediated glucose and LCFA uptake. Despite their lack of an effect on substrate uptake, Ca(2+) signaling activators induced GLUT4 and CD36 translocation. In contrast, AMPK activators stimulated GLUT4/CD36 translocation as well as glucose/LCFA uptake. When cardiomyocytes were cotreated with Ca(2+) signaling and AMPK activators, Ca(2+) signaling activators further enhanced AMPK-induced glucose/LCFA uptake. In conclusion, Ca(2+) signaling shows no involvement in AMPK-induced GLUT4/CD36 translocation and substrate uptake but elicits transporter translocation via a separate pathway requiring CaMKKβ/CaMKs. Ca(2+)-induced transporter translocation by itself appears to be ineffective to increase substrate uptake but requires additional AMPK activation to effectuate transporter translocation into increased substrate uptake. Ca(2+)-induced transporter translocation might be crucial under excessive cardiac stress conditions that require supraphysiological energy demands. Alternatively, Ca(2+) signaling might prepare the heart for substrate uptake during physiological contraction by inducing transporter translocation.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".