Genetic Variants Associated with Lipid Profiles in Chinese Patients with Type 2 Diabetes

Dyslipidemia is a strong risk factor for cardiovascular disease among patients with type 2 diabetes (T2D). The aim of this study was to identify lipid-related genetic variants in T2D patients of Han Chinese ancestry. Among 4,908 Chinese T2D patients who were not taking lipid-lowering medications, single nucleotide polymorphisms (SNPs) in seven genes previously found to be associated with lipid traits in genome-wide association studies conducted in populations of European ancestry (ABCA1, GCKR, BAZ1B, TOMM40, DOCK7, HNF1A, and HNF4A) were genotyped. After adjusting for multiple covariates, SNPs in ABCA1, GCKR, BAZ1B, TOMM40, and HNF1A were identified as significantly associated with triglyceride levels in T2D patients (P < 0.05). The associations between the SNPs in ABCA1 (rs3890182), GCKR (rs780094), and BAZ1B (rs2240466) remained significant even after correction for multiple testing (P = 8.85×10⁻³, 7.88×10⁻⁷, and 2.03×10⁻⁶, respectively). BAZ1B (rs2240466) also was associated with the total cholesterol level (P = 4.75×10⁻²). In addition, SNP rs157580 in TOMM40 was associated with the low-density lipoprotein cholesterol level (P = 6.94×10⁻³). Our findings confirm that lipid-related genetic loci are associated with lipid profiles in Chinese patients with type 2 diabetes.     

Tongxinluo Protects against Hypertensive Kidney Injury in Spontaneously-Hypertensive Rats by Inhibiting Oxidative Stress and Activating Forkhead Box O1 Signaling

Hypertension is an independent risk factor for the progression of chronic renal failure, and oxidative stress plays a critical role in hypertensive renal damage. Forkbox O1(FoxO1) signaling protects cells against oxidative stress and may be a useful target for treating oxidative stress-induced hypertension. Tongxinluo is a traditional Chinese medicine with cardioprotective and renoprotective functions. Therefore, this study aimed to determine the effects of Tongxinluo in hypertensive renal damage in spontaneously hypertensive rats(SHRs)and elucidate the possible involvement of oxidative stress and FoxO1 signaling in its molecular mechanisms. SHRs treated with Tongxinluo for 12 weeks showed a reduction in systolic blood pressure. In addition to increasing creatinine clearance, Tongxinluo decreased urinary albumin excretion, oxidative stress injury markers including malondialdehyde and protein carbonyls, and expression of nicotinamide adenine dinucleotide phosphate oxidase subunits and its activity in SHR kidneys. While decreasing phosphorylation of FoxO1, Tongxinluo also inhibited the phosphorylation of extracellular signal-regulated kinase1/2 and p38 and enhanced manganese superoxide dismutase and catalase activities in SHR kidneys. Furthermore, histology revealed attenuation of glomerulosclerosis and renal podocyte injury, while Tongxinluo decreased the expression of α-smooth muscle actin, extracellular matrixprotein, transforming growth factor β1 and small mothers against decapentaplegic homolog 3,and improved tubulointerstitial fibrosis in SHR kidneys. Finally, Tongxinluo inhibited inflammatory cell infiltration as well as expression of tumor necrosis factor-α and interleukin-6. In conclusion, Tongxinluo protected SHRs against hypertension-induced renal injury by exerting antioxidant, antifibrotic, and anti-inflammatory activities. Moreover, the underlying mechanisms of these effects may involve inhibition of oxidative stress and functional activation of FoxO1 signaling.     

Accelerating Neuroimage Registration through Parallel Computation of Similarity Metric

Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT with the correlation ratio (CR) as the similarity metric and a GPU accelerated correlation coefficient (CC) calculation for the symmetric diffeomorphic registration of ANTs have been developed. The comparison with their corresponding original tools shows that our accelerated algorithms can greatly outperform the original algorithm in terms of computational efficiency. This paper demonstrates the great potential of applying these registration tools in clinical applications.