Npas4 Is a Novel Activity–Regulated Cytoprotective Factor in Pancreatic β-Cells
Bibliographic record
Abstract
Cellular homeostasis requires intrinsic sensing mechanisms to temper function in the face of prolonged activity. In the pancreatic β-cell, glucose is likely a physiological trigger that activates an adaptive response to stimulation, thereby maintaining cellular homeostasis. Immediate early genes (IEGs) are activated as a first line of defense in cellular homeostasis and are largely responsible for transmitting an environmental cue to a cellular response. Here we examine the regulation and function of the novel β-cell IEG, neuronal PAS domain protein 4 (Npas4). Using MIN6 cells, mouse and human islets, as well as in vivo infusions, we demonstrate that Npas4 is expressed within pancreatic islets and is upregulated by β-cell depolarizing agents. Npas4 tempers β-cell function through a direct inhibitory interaction with the insulin promoter and by blocking the potentiating effects of GLP-1 without significantly reducing glucose-stimulated secretion. Finally, Npas4 expression is induced by classical endoplasmic reticulum (ER) stressors and can prevent thapsigargin- and palmitate-induced dysfunction and cell death. These results suggest that Npas4 is a key activity-dependent regulator that improves β-cell efficiency in the face of stress. We posit that Npas4 could be a novel therapeutic target in type 2 diabetes that could both reduce ER stress and cell death and maintain basal cell function.
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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) | 0.000 | 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 | 0.000 |
| 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".