Transcriptional Activation of the Proglucagon Gene by Lithium and β-Catenin in Intestinal Endocrine L Cells
Bibliographic record
Abstract
The proglucagon gene encodes several peptide hormones that regulate blood glucose homeostasis, growth of the small intestine, and satiety. Among them, glucagon-like peptide 1 (GLP-1) lowers blood glucose levels in patients with diabetes and inhibits eating and drinking in fasted rats. Although proglucagon transcription and GLP-1 synthesis were shown to be activated by forskolin and other protein kinase A (PKA) activators, deleting or mutating the cAMP-response element (CRE) only moderately attenuates the proglucagon gene promoter in response to PKA activation. Therefore, PKA may activate proglucagon transcription via a mechanism independent of the CRE motif. Recently, PKA was shown to phosphorylate and inactivate GSK-3beta, a key mediator in the Wnt signaling pathway. We show here that lithium, an inhibitor of GSK-3beta, activates proglucagon gene transcription and stimulates GLP-1 synthesis in an intestinal endocrine L cell line, GLUTag. The activation was also observed in primary fetal rat intestinal cell (FRIC) cultures, but not in a pancreatic A cell line. Co-transfection of beta-catenin, a downstream effector of GSK-3beta activities, activated the proglucagon gene promoter without a CRE. Furthermore, forskolin and 8-Br-cAMP phosphorylated GSK-3beta at serine 9 in intestinal proglucagon-producing cells, and both lithium and forskolin induced the accumulation of free beta-catenin in these cell lines. These observations indicate that the proglucagon gene is among the targets of the Wnt signaling pathway.
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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".