Tsg101 Is Involved in the Sorting and Re-Distribution of Glucose Transporter-4 to the Sarcolemma Membrane of Cardiac Myocytes
Bibliographic record
Abstract
Cardiac cells can adapt to pathological stress-induced energy crisis by shifting from fatty acid oxidation to glycolysis. However, the use of glucose-insulin-potassium (GIK) solution in patients undergoing cardiac surgery does not alleviate ischemia/reperfusion (I/R)-induced energy shortage. This indicates that insulin-mediated translocation of glucose transporter-4 (Glut-4) is impaired in ischemic hearts. Indeed, cardiac myocytes contain two intracellular populations of Glut-4: an insulin-dependent non-endosomal pool (also referred to as Glut-4 storage vesicles, GSVs) and an insulin-independent endosomal pool. Tumor susceptibility gene 101 (Tsg101) has been implicated in the endosomal recycling of membrane proteins. In this study, we aimed to examine whether Tsg101 regulated the sorting and re-distribution of Glut-4 to the sarcolemma membrane of cardiomyocytes under basal and ischemic conditions, using gain- and loss-of-function approaches. Forced overexpression of Tsg101 in mouse hearts and isolated cardiomyocytes could promote Glut-4 re-distribution to the sarcolemma, leading to enhanced glucose entry and adenosine triphosphate (ATP) generation in I/R hearts which in turn, attenuation of I/R-induced cardiac dysfunction. Conversely, knockdown of Tsg101 in cardiac myocytes exhibited opposite effects. Mechanistically, we identified that Tsg101 could interact and co-localize with Glut-4 in the sarcolemma membrane of cardiomyocytes. Our findings define Tsg101 as a novel regulator of cardiac Glut-4 trafficking, which may provide a new therapeutic strategy for the treatment of ischemic heart disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".