Are you Stanley M H Chan?

Claim your profile

Publications (2)8.35 Total impact

  • Article: Screening for the efficacy on lipid accumulation in 3T3-L1 cells is an effective tool for the identification of new anti-diabetic compounds.
    [show abstract] [hide abstract]
    ABSTRACT: Reducing lipid accumulation in insulin target tissues is critical for the treatment of type 2 diabetes. This study aimed to develop a biochemical assay in cells for high throughput (HTP) screening of anti-diabetic drugs by reducing lipid accumulation via different mechanisms. We designed a new method to extract triglyceride (TG) with KOH to allow biochemical quantification of TGs for HTP screening in 3T3-L1 cells. This new method was validated for its biochemical properties with identical results of TG obtained with or without KOH (r(2) = 0.9978, p < 0.001) and a fourfold improvement in TG extraction recovery rate (88-95%, p < 0.001) as compared to the conventional chloroform/methanol extraction (12-18%). The ability of this phenotype screening to capture potential anti-diabetic drugs was verified by pharmacological agents well known to alter lipid accumulation by different mechanisms including AMPK activators, fatty acid synthesis inhibitors, PPARγ activator and several lipogenic substrates. To further demonstrate the application of this screening tool for discovery of new anti-diabetic drugs, we screened >200 new candidates selected from Chinese medicine and identified 49 compounds from different classes which reduced TG content by >50% at 1 μM or >75% at 10 μM. Finally, we tested two selected leads (albiflorin and oxymatrine) in vivo and confirmed their efficacy in reducing visceral adiposity, glucose intolerance and hepatic steatosis in high fat-fed or high fructose-fed mice. Our results indicate that screening for the efficacy on lipid accumulation in cells by biochemical quantification of TGs with KOH extraction is an effective tool for the identification of new anti-diabetic compounds.
    Biochemical pharmacology 07/2012; 84(6):830-7. · 4.25 Impact Factor
  • Source
    Article: Differing endoplasmic reticulum stress response to excess lipogenesis versus lipid oversupply in relation to hepatic steatosis and insulin resistance.
    [show abstract] [hide abstract]
    ABSTRACT: Mitochondrial dysfunction and endoplasmic reticulum (ER) stress have been implicated in hepatic steatosis and insulin resistance. The present study investigated their roles in the development of hepatic steatosis and insulin resistance during de novo lipogenesis (DNL) compared to extrahepatic lipid oversupply. Male C57BL/6J mice were fed either a high fructose (HFru) or high fat (HFat) diet to induce DNL or lipid oversupply in/to the liver. Both HFru and HFat feeding increased hepatic triglyceride within 3 days (by 3.5 and 2.4 fold) and the steatosis remained persistent from 1 week onwards (p<0.01 vs Con). Glucose intolerance (iAUC increased by ∼60%) and blunted insulin-stimulated hepatic Akt and GSK3β phosphorylation (∼40-60%) were found in both feeding conditions (p<0.01 vs Con, assessed after 1 week). No impairment of mitochondrial function was found (oxidation capacity, expression of PGC1α, CPT1, respiratory complexes, enzymatic activity of citrate synthase & β-HAD). As expected, DNL was increased (∼60%) in HFru-fed mice and decreased (32%) in HFat-fed mice (all p<0.05). Interestingly, associated with the upregulated lipogenic enzymes (ACC, FAS and SCD1), two (PERK/eIF2α and IRE1/XBP1) of three ER stress pathways were significantly activated in HFru-fed mice. However, no significant ER stress was observed in HFat-fed mice during the development of hepatic steatosis. Our findings indicate that HFru and HFat diets can result in hepatic steatosis and insulin resistance without obvious mitochondrial defects via different lipid metabolic pathways. The fact that ER stress is apparent only with HFru feeding suggests that ER stress is involved in DNL per se rather than resulting from hepatic steatosis or insulin resistance.
    PLoS ONE 01/2012; 7(2):e30816. · 4.09 Impact Factor