Asymmetric Subcellular Distribution of Glucose Transporters in the Endothelium of Small Contractile Arteries
Bibliographic record
Abstract
The authors have recently reported the presence and asymmetric distribution of the glucose transporters GLUT-1 to -5 and SGLT-1 in the endothelium of rat coronary artery (Gaudreault et al. 2004, Diabetologica, 47, 2081-2092). In the present study the authors investigate and compare the presence and subcellular distribution of the classic glucose transporter isoforms in endothelial cells of cerebral, renal, and mesenteric arteries. The GLUTs and SGLT-1 were examined with immunohistochemistry and wide-field fluorescence microscopy coupled to deconvolution in en face preparation of intact artery. We identified GLUT-1 to -5 and SGLT-1 in the endothelial cells of all three vascular beds. The relative level of expression for each isoform was found comparable amongst arteries. Clusters of the glucose transporter isoforms were found at a high density in proximity to the cell-to-cell junctions. In addition, a consistent asymmetric distribution of GLUT-1 to -5 was found, predominantly located on the abluminal side of the endothelium in all three vascular beds examined (ranging from 68% to 91%, p<.05). The authors conclude that the expression and subcellular distribution of glucose transporters are similar in endothelial cells from vascular beds of comparable diameter and suggest that their subcellular organization may facilitate transendothelial transport of glucose in small contractile arteries.
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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 | 0.000 | 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".