The Hyperglycemia-induced Inflammatory Response in Adipocytes
Bibliographic record
Abstract
Hyperglycemia is a major independent risk factor for diabetic macrovascular disease. The consequences of exposure of endothelial cells to hyperglycemia are well established. However, little is known about how adipocytes respond to both acute as well as chronic exposure to physiological levels of hyperglycemia. Here, we analyze adipocytes exposed to hyperglycemia both in vitro as well as in vivo. Comparing cells differentiated at 4 mm to cells differentiated at 25 mm glucose (the standard differentiation protocol) reveals severe insulin resistance in cells exposed to 25 mm glucose. A global assessment of transcriptional changes shows an up-regulation of a number of mitochondrial proteins. Exposure to hyperglycemia is associated with a significant induction of reactive oxygen species (ROS), both in vitro as well as in vivo in adipocytes isolated from streptozotocin-treated hyperglycemic mice. Furthermore, hyperglycemia for a few hours in a clamped setting will trigger the induction of a pro-inflammatory response in adipose tissue from rats that can effectively be reduced by co-infusion of N-acetylcysteine (NAC). ROS levels in 3T3-L1 adipocytes can be reduced significantly with pharmacological agents that lower the mitochondrial membrane potential, or by overexpression of uncoupling protein 1 or superoxide dismutase. In parallel with ROS, interleukin-6 secretion from adipocytes is significantly reduced. On the other hand, treatments that lead to a hyperpolarization of the mitochondrial membrane, such as overexpression of the mitochondrial dicarboxylate carrier result in increased ROS formation and decreased insulin sensitivity, even under normoglycemic conditions. Combined, these results highlight the importance ROS production in adipocytes and the associated insulin resistance and inflammatory response.
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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 | 0.001 |
| 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".