Partial ablation of leptin signaling in mouse pancreatic α-cells does not alter either glucose or lipid homeostasis
Bibliographic record
Abstract
The role of glucagon in the pathological condition of diabetes is gaining interest, and it has been recently reported that its action is essential for hyperglycemia to occur. Glucagon levels, which are elevated in some diabetic models, are reduced following leptin therapy. Likewise, hyperglycemia is corrected in type 1 diabetic mice treated with leptin, although the mechanisms have not been fully determined. A direct inhibitory effect of leptin on mouse and human α-cells has been demonstrated at the levels of electrical activity, calcium signaling, and glucagon secretion. In the present study we employed the Cre-loxP strategy to generate Lepr(flox/flox) Gcg-cre mice, which specifically lack leptin receptors in glucagon-secreting α-cells, to determine whether leptin resistance in α-cells contributes to hyperglucagonemia, and also whether leptin action in α-cells is required to improve glycemia in type 1 diabetes with leptin therapy. Immunohistochemical analysis of pancreas sections revealed Cre-mediated recombination in ∼ 43% of the α-cells. We observed that in vivo Lepr(flox/flox) Gcg-cre mice display normal glucose and lipid homeostasis. In addition, leptin administration in streptozotocin-induced diabetic Lepr(flox/flox) Gcg-cre mice restored euglycemia similarly to control mice. These findings suggest that loss of leptin receptor signaling in close to one-half of α-cells does not alter glucose metabolism in vivo, nor is it sufficient to prevent the therapeutic action of leptin in type 1 diabetes.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".