Highly bioavailable Berberine formulation improves Glucocorticoid Receptor-mediated Insulin Resistance <i>via</i> reduction in association of the Glucocorticoid Receptor with phosphatidylinositol-3-kinase
Bibliographic record
Abstract
Excess glucocorticoid (GC) production is known to induce obesity and insulin resistance through increased activation of the glucocorticoid receptor (GR). The molecular mechanism for the non-genomic effects of excessive circulating GC on the insulin-signalling pathway in skeletal muscle is unknown. The plant alkaloid berberine has been shown to attenuate insulin resistance and inhibit gluconeogenesis in type 2 diabetic animals. A highly bioavailable berberine formulation termed Huang-Gui solid dispersion (HGSD), is a preparation of berberine coupled to sodium caprate and this markedly improving berberines bioavailability. Here we examined how HGSD treatment attenuated GR-mediated alteration in PI3K signalling and insulin resistance in diabetic rats, dexamethasone-treated mice and in insulin resistant C2C12 skeletal muscle cells. Blood glucose and skeletal muscle GC levels were increased and insulin signalling impaired in skeletal muscle of type 2 diabetic rats compared to controls. Treatment of these animals with HGSD restored blood glucose and skeletal muscle GC levels to that of controls. Insulin resistant C2C12 skeletal muscle cells exhibited impaired insulin signalling compared to controls and treatment of HGSD and RU486, an antagonist of GR, restored insulin signalling to that of control cells. Administration of dexamethasone to mice increased GR/GRα-associated PI3K and reduced IRS1-associated PI3K, phosphorylated-AKT, and membrane GLUT4 translocation resulting in a higher blood glucose concentration compared to controls. HGSD treatment of these mice improved insulin resistance by reducing the association of GR/GRα with PI3K. Excess GC-induced insulin resistance is mediated by increased association of GR with PI3K and treatment with HGSD attenuates these effects. We hypothesize that HGSD may be a promising candidate drug for the treatment of type 2 diabetes by reducing the association of GR with PI3K in skeletal muscle.
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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".