Enhanced islet neogenesis and beta‐cell proliferation in pre‐insulitic diabetes‐prone rats fed a hydrolyzed casein diet
Bibliographic record
Abstract
Diabetes incidence is reduced in diabetes‐prone BioBreeding (BBdp) rats fed a hydrolyzed casein (HC) diet compared with a standard cereal‐based rodent diet such as NTP‐2000 (NTP). To further characterize the basis of this protective effect, islet neogenesis, apoptosis and cell proliferation were analyzed using immunohistochemistry, morphometry, Laser Capture Microdissection, and RT‐PCR in BBdp rats weaned onto an NTP or HC diet at 23 d and sacrificed at 25, 30, and 45 d. Islet area fraction was greater in medium and large islets of HC‐fed rats at 30 d and in large islets only at 45 d. There were more small islets in HC‐fed rats both at 30 and 45 d and β‐cell mass was significantly greater at 45 d. Cell cycle analysis revealed an increased ratio of S+G2/G0+G1 in HC‐fed animals between 25 and 45 d. PDX‐1 + clusters (<4 cells) were increased in HC‐fed rats, whereas extra‐islet insulin + clusters (EIC) and insulin + cells in ducts, representative of islet neogenesis, were increased at 45 d. Ngn3 mRNA was higher in EIC of HC‐fed rats at 24 d. Glucagon‐like peptide‐1 receptor protein and mRNA were increased in islets of HC‐fed rats. In summary, the protective HC diet increased β‐cell mass in diabetes‐prone rats through upregulation of islet neogenesis and β‐cell proliferation. (GSW and LMK contributed equally; Supported by Canadian Diabetes Association and Canadian Institutes of Health Research)
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".