Impaired Ca2+ Signaling in β-Cells Lacking Leptin Receptors by Cre-loxP Recombination
Bibliographic record
Abstract
Obesity is a major risk factor for diabetes and is typically associated with hyperleptinemia and a state of leptin resistance. The impact of chronically elevated leptin levels on the function of insulin-secreting β-cells has not been elucidated. We previously generated mice lacking leptin signaling in β-cells by using the Cre-loxP strategy and showed that these animals develop increased body weight and adiposity, hyperinsulinemia, impaired glucose-stimulated insulin secretion and insulin resistance. Here, we performed several in vitro studies and observed that β-cells lacking leptin signaling in this model are capable of properly metabolizing glucose, but show impaired intracellular Ca(2+) oscillations and lack of synchrony within the islets in response to glucose, display reduced response to tolbutamide and exhibit morphological abnormalities including increased autophagy. Defects in intracellular Ca(2+) signaling were observed even in neonatal islets, ruling out the possible contribution of obesity to the β-cell irregularities observed in adults. In parallel, we also detected a disrupted intracellular Ca(2+) pattern in response to glucose and tolbutamide in control islets from adult transgenic mice expressing Cre recombinase under the rat insulin promoter, despite these animals being glucose tolerant and secreting normal levels of insulin in response to glucose. This unexpected observation impeded us from discerning the consequences of impaired leptin signaling as opposed to long-term Cre expression in the function of insulin-secreting cells. These findings highlight the need to generate improved Cre-driver mouse models or new tools to induce Cre recombination in β-cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".