Quantification of the relationship between glycemia and β-cell mass adaptation in vivo
Bibliographic record
Abstract
Beta-cell mass dynamics play an important role in the adaptation to obesity, as well as in the pathogenesis of type 2 diabetes. Here we used a 24-hour modified hyperglycemic clamp protocol to investigate the effect of increasing glucose concentrations (15, 20, 25, or 35 mmol/L) on beta-cell mass and rates of beta-cell replication, death, and neogenesis in 6-week-old Sprague Dawley rats (n = 40). During the first 4 h of glucose infusion, plasma insulin levels rose to an approximate steady state in each group, but by the end of 24 h, there was no difference in insulin levels between any of the groups. There was also no difference in beta-cell mass between groups. Mean beta-cell replication rates displayed a linear relationship to mean plasma glucose levels in all hyperglycemic animals (r(2) = 0.98, p < 0.05). Relative to the uninfused basal control animals, replication rates were significantly reduced in the 15 mmol/L glucose group. The percentage of TUNEL-positive beta-cells was not different between groups. There was also no significant difference in markers of neogenesis. Thus, these data demonstrate that hyperglycemia for 24 h had no effect on beta-cell mass, death, or neogenesis in 6-week-old Sprague Dawley rats. We demonstrate a linear relationship, however, between hyperglycemia and beta-cell replication rates 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".