Mechanisms of High Glucose-induced Decrease in β-cell Function
Bibliographic record
Abstract
Chronic hyperglycemia, a hallmark of type 2 diabetes, can decrease β-cell function and mass (β-cell glucotoxicity); however, the mechanisms are incompletely understood. The objective was to examine the mechanisms of β-cell glucotoxicity using in vivo and ex vivo models. The hypothesis is that oxidative stress plays a causal role in high glucose-induced β-cell dysfunction in vivo via pathways that involve endoplasmic reticulum (ER) stress and JNK. The model of β-cell glucotoxicity was achieved by prolonged i.v. glucose infusion (to achieve hyperglycemia). \nIn Study 1, 48h glucose infusion increased total and mitochondrial superoxide levels in islets, and impaired β-cell function in vivo and ex vivo. Co-infusion of the superoxide dismutase mimetic Tempol decreased total and mitochondrial superoxide, and prevented high glucose-induced β-cell dysfunction in vivo and ex vivo. These results suggest that increased superoxide generation plays a role in β-cell glucotoxicity.\nIn Study 2, 48h glucose infusion increased activation of the unfolded protein response (XBP-1 mRNA splicing and phospho-eIF2α levels). This was partially prevented by Tempol. Co-infusion of the chemical chaperone 4-phenylbutyrate with glucose decreased spliced XBP-1 levels, and prevented high glucose-induced β-cell dysfunction in vivo and ex vivo. Co-infusion of 4-phenylbutyrate also decreased total and mitochondrial superoxide induced by high glucose. These results suggest that 1) ER stress plays a causal role in high glucose-induced β-cell dysfunction, and 2) there is a link between oxidative stress and ER stress in high glucose-induced β-cell dysfunction in vivo.\nIn Study 3, JNK inhibition using the inhibitor SP600125 in rats or JNK-1 null mice prevented high glucose-induced β-cell dysfunction ex vivo and in vivo. SP600125 prevented high-glucose-induced β-cell dysfunction without decreasing total and mitochondrial superoxide levels. Both Tempol and 4-phenylbutyrate prevented JNK activation induced by high glucose. These results suggest a role of JNK activation in high glucose-induced β-cell dysfunction downstream of increased superoxide generation and ER stress in vivo. \nTogether, the results suggest that 1) oxidative stress, ER stress and JNK activation are causally involved in β-cell glucotoxicity, and 2) High glucose-induced oxidative stress and ER stress are linked, and both impair β-cell dysfunction via JNK activation in vivo.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".