Lipid-induced pancreatic β-cell dysfunction: focus on in vivo studies
Bibliographic record
Abstract
The phenomenon of lipid-induced pancreatic β-cell dysfunction ("lipotoxicity") has been very well documented in numerous in vitro experimental systems and has become widely accepted. In vivo demonstration of β-cell lipotoxicity, on the other hand, has not been consistently demonstrated, and there remains a lack of consensus regarding the in vivo effects of chronically elevated free fatty acids (FFA) on β-cell function. Much of the disagreement relates to how insulin secretion is quantified in vivo and in particular whether insulin secretion is assessed in relation to whole body insulin sensitivity, which is clearly reduced by elevated FFA. By correcting for changes in in vivo insulin sensitivity, we and others have shown that prolonged elevation of FFA impairs β-cell secretory function. Prediabetic animal models and humans with a positive family history of type 2 diabetes are more susceptible to this impairment, whereas those with severe impairment of β-cell function (such as individuals with type 2 diabetes) demonstrate no additional impairment of β-cell function when FFA are experimentally raised. Glucolipotoxicity (i.e., the combined β-cell toxicity of elevated glucose and FFA) has been amply demonstrated in vitro and in some animal studies but not in humans, perhaps because there are limitations in experimentally raising plasma glucose to sufficiently high levels for prolonged periods of time. We and others have shown that therapies directed toward diminishing oxidative stress and ER stress have the potential to reduce lipid-induced β-cell dysfunction in animals and humans. In conclusion, lipid-induced pancreatic β-cell dysfunction is likely to be one contributor to the complex array of genetic and metabolic insults that result in the relentless decline in pancreatic β-cell function in those destined to develop type 2 diabetes, and mechanisms involved in this lipotoxicity are promising therapeutic targets.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".