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The main lesion of cisplatin nephrotoxicity is damage to proximal tubular cells due to increased apoptosis via the mitochondrial and death receptor pathways, which may be alleviated by appropriate promotion of autophagy. Fenofibrate, a peroxisome proliferator-activated receptor-alpha (PPAR-α) activator, is recently reported to promote autophagy as well as protect against cisplatin nephrotoxicity, although the mechanisms were only partially analyzed. Here, the detailed mechanisms of these putative protective effects were investigated in a murine renal proximal tubular (mProx) cell line. Fenofibrate attenuated cisplatin-induced apoptosis of mProx cells based on flow cytometry. As for the mitochondrial apoptotic pathway, the reagent reduced cisplatin-stimulated caspase-3 activation by decreasing the phosphorylation of p53, JNK, and 14-3-3, cytosolic and mitochondrial Puma accumulation, cytochrome C release to the cytosol, and resulting cytosolic caspase-9 activation. Fenofibrate also decreased cisplatin-stimulated activation of caspases-8 by suppressing MAPK and NFkB pathways and reducing the gene expression of TNF-α, TL1A, and Fas, main mediators of the death receptor apoptotic pathway. Autophagy defined by p62 reduction and an increase in LC3 II/I was promoted by fenofibrate in mProx cells under starvation. Autophagy inhibition using 3-MA further increased basal and cisplatin-induced caspase-3 and -8 activation, but had no influence on the inhibitory effects of fenofibrate on caspase activation. In conclusion, our study suggests fenofibrate to be a candidate agent to mitigate cisplatin nephrotoxicity by inhibiting the mitochondrial and death apoptotic pathways rather than by promoting autophagy.

Aim: Smaller low-density lipoprotein (LDL) size has recently been reported as a non-traditional lipid risk factor for coronary artery disease (CAD). Cholesteryl ester transfer protein (CETP) and the C/T hepatic lipase (HL) gene polymorphism may promote LDL size reduction via the CETP-mediated exchange of CE for triglyceride (TG) and subsequent HL-mediated TG hydrolysis in LDL. However, little is known about LDL size status and its relationship with CAD prevalence in haemodialysis (HD) patients who are at high risk for atherosclerosis. Methods: CETP levels, HL genotypes and LDL size were determined, and the determinants of LDL size and its association with CAD prevalence in HD patients (n = 236) aged over 30 years were investigated. Results: The HD patients had a similar LDL size to the healthy subjects. In the HD group, high-density lipoprotein cholesterol was an independent positive determinant of LDL size, while log10 (TG) was an independent negative determinant in the high (≥2.1 µg/mL) but not low (

Hepatic lipase mutation may reduce vascular disease prevalence in hemodialysis patients with high CETP levels.BackgroundUremic dyslipidemia characterized by reduced high-density lipoprotein (HDL) cholesterol levels is one of the major contributors to the high incidence of cardiovascular disease in hemodialysis patients. Hepatic lipase (HL), together with cholesteryl ester transfer protein (CETP), may not only promote reverse cholesterol transport but also enhance production of small, dense, more atherogenic low-density lipoprotein (LDL). A common C-514T mutation of the promoter region of the HL gene reportedly increases HDL cholesterol levels. However, whether the HL mutation is antiatherogenic or proatherogenic has remained unknown in uremic patients and the general population.MethodsWe investigated the influence of the mutation and its interaction with CETP on HDL cholesterol levels and the apparent atherosclerotic complications in 183 hemodialysis patients aged over 30years who had received no antilipemic drugs.ResultsIn patients with CETP levels ≥2.2 μg/mL [high CETP (HCT) group, N = 97], subjects with the TT genotype had a significantly higher level of HDL cholesterol than those without TT genotype (56.8 ± 15.9mg/dL vs. 45.7 ± 13.4mg/dL, P < 0.001), but not in patients with CETP levels

This paper describes a method for automatically approximating an unknown image transformation from an original image to its target image by the use of a sequence of several known image filters, where the target image is an ideally processed image made manually. This automatic construction problem is regarded as a combinatorial optimization problem for the ordering of image filters and a genetic algorithm is employed to solve it. A population of individuals whose chromosomes represent sequences of image filters is evolved. In generation iterations, each individual is evaluated based on the difference between the target image and the image processed according to the filter sequence defined by its chromosome. This method can deal with arbitrary image transformations, and it can be applied to expert systems for image processing.