Influence of anti-fibrillation TNGQ peptide and rutin combination on β-cell cytoprotective effects against IAPP-induced cell death and oxidative stress
Bibliographic record
Abstract
Type 2 diabetes development has been associated with islet amyloid polypeptide (IAPP) fibrillation. IAPP fibrils have various deleterious effects, such as oxidative stress and disruption of cellular membrane integrity, resulting in pancreatic β-cell toxicity. Rutin, a plant polyphenol, possesses promising cytoprotective effects as a fibrillation inhibitor. Similarly, bioactive peptides have been identified as potential inhibitors to IAPP fibrillation. In this study, the effect of peptide/polyphenol mixtures consisting of rutin and each peptide, TNGQ, MANT, and YMSV, on anti-fibrillation activity and cellular response was elucidated. Results indicated a 54.7-75.1 % decrease in thioflavin T fluorescence, confirming anti-fibrillation activity. The combination decreased the average particle diameters of IAPP more than the single inhibitors, suggesting a combined effect of peptide/rutin mixtures in enhancing anti-fibrillation activity. IAPP fibrillation-induced rat insulinoma RIN-m cell death was minimized in the presence of the peptide/rutin mixture, but the activity was lower relative to rutin alone, suggesting a non-additive effect of the mixtures. Transmission electron microscopy showed a near-complete inhibition of IAPP fibrillation by TNGQ/rutin mixtures, which translated to a decreased production of membrane-bound IAPP oligomers in RIN-m cells based on immunofluorescence staining. Additionally, TNGQ/rutin mixtures significantly decreased reactive oxygen species production by 30 %, higher than the effects of single inhibitors, but no effect was observed on glucose-stimulated insulin secretion. The results demonstrate the potential of multifunctional compounds as dual inhibitor systems in controlling IAPP fibrillation and provide insight into the implications of peptide/polyphenol mixtures towards the rational development of novel anti-diabetic nutraceutical combinations.
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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) | 0.001 | 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) | 0.001 | 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".