Pancreatic islet cell autophagy during aging in rats
Bibliographic record
Abstract
PURPOSE: Autophagy induces pancreatic β cell death. The purpose of the present study was to examine the hypothesis that the extent of pancreatic autophagy is associated with aging and age-related diabetes. METHODS: Pancreatic tissue and blood samples were collected from Sprague Dawley rats receiving a normal diet at 2 (the young group), 6 (the adult group), 12 (the middle-age group) and 20-24 (the aged group) months of age. Body weight and fasting blood glucose, serum lipid levels and serum insulin levels were determined. Pancreatic cell structure and autophagy were determined using transmission electron microscopy of rats at 6, 12 and 24 months of age. Lamp2 and LC3b protein expression levels were determined by both immunohistochemistry and Western blot analyses, and islet cell apoptosis was assessed using the TUNEL assay. RESULTS: Fasting blood glucose, triglyceride and FFA levels increased significantly with age (p < 0.05). Compared with levels seen in two-month-old rats, insulin secretion of islet cells in vitro was significantly reduced at 6, 12, and 20 months of age (p < 0.05). Autophagosomes were only observed in islet cells of 24 month-old rats. Increased expression of the autophagic markers, Lamp2 and LC3b, was observed with age. A significant increase in apoptotic index was observed between young rats (two-months-old) and older rats (six-, 12- and 24-months-old), but no differences were observed between rats six, 12 and 24 months of age. CONCLUSION: Appearance of autophagosomes and increased Lamp2 and LC3b expression in pancreatic islet cells coincided with a significant decrease in insulin secretion and elevation of fasting blood glucose in aged rats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".