Type 2 diabetes is associated with suppression of autophagy and lipid accumulation in β‐cells
Bibliographic record
Abstract
Both type 2 diabetes (T2D) and obesity are characterized by excessive hyperlipidaemia and subsequent lipid droplet (LD) accumulation in adipose tissue. To investigate whether LDs also accumulate in β-cells of T2D patients, we assessed the expression of PLIN2, a LD-associated protein, in non-diabetic (ND) and T2D pancreata. We observed an up-regulation of PLIN2 mRNA and protein in β-cells of T2D patients, along with significant changes in the expression of lipid metabolism, apoptosis and oxidative stress genes. The increased LD buildup in T2D β-cells was accompanied by inhibition of nuclear translocation of TFEB, a master regulator of autophagy and by down-regulation of lysosomal biomarker LAMP2. To investigate whether LD accumulation and autophagy were influenced by diabetic conditions, we used rat INS-1 cells to model the effects of hyperglycaemia and hyperlipidaemia on autophagy and metabolic gene expression. Consistent with human tissue, both LD formation and PLIN2 expression were enhanced in INS-1 cells under hyperglycaemia, whereas TFEB activation and autophagy gene expression were significantly reduced. Collectively, these results suggest that lipid clearance and overall homeostasis is markedly disrupted in β-cells under hyperglycaemic conditions and interventions ameliorating lipid clearance could be beneficial in reducing functional impairments in islets caused by glucolipotoxicity.
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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".