Improved blood glucose disposal and altered insulin secretion patterns in adenosine A<sub>1</sub>receptor knockout mice
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is characterized by the inability of the pancreatic β-cells to secrete enough insulin to meet the demands of the body. Therefore, research of potential therapeutic approaches to treat T2DM has focused on increasing insulin output from β-cells or improving systemic sensitivity to circulating insulin. In this study, we examined the role of the A(1) receptor in glucose homeostasis with the use of A(1) receptor knockout mice (A(1)R(-/-)). A(1)R(-/-) mice exhibited superior glucose tolerance compared with wild-type controls. However, glucose-stimulated insulin release, insulin sensitivity, weight gain, and food intake were comparable between the two genotypes. Following a glucose challenge, plasma glucagon levels in wild-type controls decreased, but this was not observed in A(1)R(-/-) mice. In addition, pancreas perfusion with oscillatory glucose levels of 10-min intervals produced a regular pattern of pulsatile insulin release with a 10-min cycling period in wild-type controls and 5 min in A(1)R(-/-) mice. When the mice were fed a high-fat diet (HFD), both genotypes exhibited impaired glucose tolerance and insulin resistance. Increased insulin release was observed in HFD-fed mice in both genotypes, but increased glucagon release was observed only in HFD-fed A(1)R(-/-) mice. In addition, the regular patterns of insulin release following oscillatory glucose perfusion were abolished in HFD-fed mice in both genotypes. In conclusion, A(1) receptors in the pancreas are involved in regulating the temporal patterns of insulin release, which could have implications in the development of glucose intolerance seen in T2DM.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".