The Cytoskeletal Transport Protein, Secretagogin, Is Essential for Diurnal Glucagon-like Peptide-1 Secretion in Mice
Bibliographic record
Abstract
The intestinal L-cell incretin, glucagon-like peptide-1 (GLP-1), exhibits a circadian pattern of secretion, thereby entraining diurnal insulin release. Secretagogin (Scgn), an actin-binding regulatory protein, is essential for the temporal peak of GLP-1 secretion in vitro. To interrogate the role of Scgn in diurnal GLP-1 secretion in vivo, peak and trough GLP-1 release were evaluated in knockout mice (Scgn-/-, Gcg-CreERT2/+; Scgnfl/fl and Vil-CreERT2/+; Scgnfl/fl), and RNA sequencing (RNA-Seq) was conducted in Scgn knockdown L-cells. All 3 knockout models demonstrated loss of the diurnal rhythm of GLP-1 secretion in response to oral glucose. Gcg-CreERT2/+; Scgnfl/fl mice also lost the normal pattern in glucagon secretion, while Scgn-/- and Vil-CreERT2/+; Scgnfl/fl animals demonstrated impaired diurnal secretion of the related incretin, glucose-dependent insulinotrophic polypeptide. RNA-Seq of mGLUTag L-cells showed decreased pathways regulating vesicle transport, transport and binding, and protein-protein interaction at synapse, as well as pathways related to proteasome-mediated degradation including chaperone-mediated protein complex assembly following Scgn knockdown. Scgn is therefore essential for diurnal L-cell GLP-1 secretion in vivo, likely mediated through effects on secretory granule dynamics.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".