Insulin detemir enhances proglucagon gene expression in the intestinal L cells via stimulating β-catenin and CREB activities
Bibliographic record
Abstract
Insulin therapy using insulin detemir (d-INS) has demonstrated weight-sparing effects compared with other insulin formulations. Mechanisms underlying these effects, however, remain largely unknown. Here we postulate that the intestinal tissues' selective preference allows d-INS to exert enhanced action on proglucagon (Gcg) expression and the production of glucagon-like peptide (GLP)-1, an incretin hormone possessing both glycemia-lowering and weight loss effects. To test this hypothesis, we used obese type 2 diabetic db/db mice and conducted a 14-day intervention with daily injection of a therapeutic dose of d-INS or human insulin (h-INS) in these mice. The body weight of the mice after 14-day daily injection of d-INS (5 IU/kg) was decreased significantly compared with those injected with the same dose of h-INS or saline. The weight-sparing effect of d-INS was associated with significantly elevated circulating levels of total GLP-1 and reduced food intake. Histochemistry analysis demonstrated that d-INS induced rapid phosphorylation of protein kinase B (Akt) in the gut L cells of normal mice. Western blotting showed that d-INS stimulated Akt activation in a more rapid and enhanced fashion in the mouse distal ileum compared with those by h-INS. In vitro investigation in primary fetal rat intestinal cell (FRIC) cultures showed that d-INS increased Gcg mRNA expression as determined by Northern blotting and real-time RT-PCR. Consistent with these in vivo investigations, d-INS significantly increased GLP-1 secretion in FRIC cultures. Consistently, d-INS was also shown to induce rapid phosphorylation of Akt in the clonal gut cell line GLUTag. Furthermore, d-INS increased β-catenin phosphorylation, its nuclear translocation, and enhanced cAMP response element-binding protein (CREB) phosphorylation in a phosphatidylinositol 3-kinase and/or mitogen-activated protein kinase kinase/extracellular signal-regulated kinase-sensitive manner. We suggest that the weight-sparing benefit of d-INS in mice is related to its intestinal tissues preference that leads to profound stimulation of Gcg expression and enhanced GLP-1 secretion in intestinal L cells, potentially involving the activation of insulin/β-catenin/CREB signaling pathways.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".