Recent Insights Into Mechanisms of β-Cell Lipo- and Glucolipotoxicity in Type 2 Diabetes
Bibliographic record
Abstract
The deleterious effects of chronically elevated free fatty acid (FFA) levels on glucose homeostasis are referred to as lipotoxicity, and the concurrent exposure to high glucose may cause synergistic glucolipotoxicity. Lipo- and glucolipotoxicity have been studied for over 25 years. Here, we review the current evidence supporting the role of pancreatic β-cell lipo- and glucolipotoxicity in type 2 diabetes (T2D), including lipid-based interventions in humans, prospective epidemiological studies, and human genetic findings. In addition to total FFA quantity, the quality of FFAs (saturation and chain length) is a key determinant of lipotoxicity. We discuss in vitro and in vivo experimental models to investigate lipo- and glucolipotoxicity in β-cells and describe experimental pitfalls. Lipo- and glucolipotoxicity adversely affect many steps of the insulin production and secretion process. The molecular mechanisms underpinning lipo- and glucolipotoxic β-cell dysfunction and death comprise endoplasmic reticulum stress, oxidative stress and mitochondrial dysfunction, impaired autophagy, and inflammation. Crosstalk between these stress pathways exists at multiple levels and may aggravate β-cell lipo- and glucolipotoxicity. Lipo- and glucolipotoxicity are therapeutic targets as several drugs impact the underlying stress responses in β-cells, potentially contributing to their glucose-lowering effects in T2D.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".