Circadian Regulation of the Pancreatic Beta Cell
Bibliographic record
Abstract
Beta cell dysfunction is central to the development of type 2 diabetes (T2D). In T2D, environmental and genetic influences can manifest beta cell dysfunction in many ways, including impaired glucose-sensing and secretion coupling mechanisms, insufficient adaptative responses to stress, and aberrant beta cell loss through increased cell death and/or beta cell de-differentiation. In recent years, circadian disruption has emerged as an important environmental risk factor for T2D. In support of this, genetic disruption of the circadian timing system in rodents impairs insulin secretion and triggers diabetes development, lending important evidence that the circadian timing system is intimately connected to, and essential for the regulation of pancreatic beta cell function; however, the role of the circadian timing system in the regulation of beta cell biology is only beginning to be unraveled. Here, we review the recent literature that explores the importance of the pancreatic islet/beta cell circadian clock in the regulation of various aspects of beta cell biology, including transcriptional and functional control of daily cycles of insulin secretion capacity, regulation of postnatal beta cell maturation, and control of the adaptive responses of the beta cell to metabolic stress and acute injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".