Five stages of progressive β-cell dysfunction in the laboratory Nile rat model of type 2 diabetes
Bibliographic record
Abstract
We compared the evolution of insulin resistance, hyperglycemia, and pancreatic β-cell dysfunction in the Nile rat (Arvicanthis niloticus), a diurnal rodent model of spontaneous type 2 diabetes (T2D), when maintained on regular laboratory chow versus a high-fiber diet. Chow-fed Nile rats already displayed symptoms characteristic of insulin resistance at 2 months (increased fat/lean mass ratio and hyperinsulinemia). Hyperglycemia was first detected at 6 months, with increased incidence at 12 months. By this age, pancreatic islet structure was disrupted (increased α-cell area), insulin secretion was impaired (reduced insulin secretion and content) in isolated islets, insulin processing was compromised (accumulation of proinsulin and C-peptide inside islets), and endoplasmic reticulum (ER) chaperone protein ERp44 was upregulated in insulin-producing β-cells. By contrast, high-fiber-fed Nile rats had normoglycemia with compensatory increase in β-cell mass resulting in maintained pancreatic function. Fasting glucose levels were predicted by the α/β-cell ratios. Our results show that Nile rats fed chow recapitulate the five stages of progression of T2D as occurs in human disease, including insulin-resistant hyperglycemia and pancreatic islet β-cell dysfunction associated with ER stress. Modification of diet alone permits long-term β-cell compensation and prevents 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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".