Aberrant Regulation of Human Intestinal Proglucagon Gene Expression in the NCI-H716 Cell Line
Bibliographic record
Abstract
Despite interest in understanding glucagon-like peptide-1 (GLP-1) production, the factors important for GLP-1 biosynthesis remain poorly understood. We examined control of human proglucagon gene expression in NCI-H716 cells, a cell line that secretes GLP-1 in a regulated manner. Insulin, phorbol myristate acetate, or forskolin, known regulators of rodent proglucagon gene expression, had no effect, whereas sodium butyrate decreased levels of NCI-H716 proglucagon mRNA transcripts. The inhibitory effect of sodium butyrate was mimicked by trichostatin A but was not detected with sodium acetate or isobutyrate. The actions of butyrate were not diminished by the ERK1/2 inhibitor PD98059, p38 inhibitor SB203580, or soluble guanylate cyclase inhibitor LY83583 or following treatment of cells with KT5823, a selective inhibitor of cGMP-dependent protein kinase. NCI-H716 cells expressed multiple proglucagon gene transcription factors including isl-1, pax-6, pax-2, cdx-2/3, pax-4, hepatocyte nuclear factor (HNF)-3 alpha, HNF-3beta, HNF-3 gamma, and Nkx2.2. Nevertheless, the butyrate-dependent inhibition of proglucagon gene expression was not associated with coordinate changes in transcription factor expression and both the human and rat transfected proglucagon promoters were transcriptionally inactive in NCI-H716 cells. Hence, NCI-H716 cells may not be a physiologically optimal model for studies of human enteroendocrine proglucagon gene transcription.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".