The Maasai are a pastoral people in Kenya and Tanzania, whose traditional diet of milk, blood and meat is rich in lactose, fat and cholesterol. In spite of this, they have low levels of blood cholesterol, and seldom suffer from gallstones or cardiac diseases. Field studies in the 1970s suggested that the Maasai have a genetic adaptation for cholesterol homeostasis. Analysis of HapMap 3 data using Fixation Index (Fst) and two metrics of haplotype diversity: the integrated Haplotype Score (iHS) and the Cross Population Extended Haplotype Homozygosity (XP-EHH), identified genomic regions and single nucleotide polymorphisms (SNPs) as strong candidates for recent selection for lactase persistence and cholesterol regulation in 143–156 founder individuals from the Maasai population in Kinyawa, Kenya (MKK). The non-synonmous SNP with the highest genome-wide Fst was the TC polymorphism at rs2241883 in Fatty Acid Binding Protein 1(FABP1), known to reduce low density lipoprotein and tri-glyceride levels in Europeans. The strongest signal identified by all three metrics was a 1.7 Mb region on Chr2q21. This region contains the genes LCT (Lactase) and MCM6 (Minichromosome Maintenance Complex Component) involved in lactase persistence, and the gene Rab3GAP1 (Rab3 GTPase-activating Protein Catalytic Subunit), which contains polymorphisms associated with total cholesterol levels in a genome-wide association study of >100,000 individuals of European ancestry. Sanger sequencing of DNA from six MKK samples showed that the GC-14010 polymorphism in the MCM6 gene, known to be associated with lactase persistence in Africans, is segregating in MKK at high frequency (∼58%). The Cytochrome P450 Family 3 Subfamily A (CYP3A) cluster of genes, involved in cholesterol metabolism, was identified by Fst and iHS as candidate loci under selection. Overall, our study identified several specific genomic regions under selection in the Maasai which contain polymorphisms in genes associated with lactase persistence and cholesterol regulation.

Reactive oxygen species (ROS) elicited by oxidative stress are widely recognized as a major initiator in the dege-neration of dopaminergic neurons distinctive of Parkinson's disease (PD). The interaction of ROS with mitochondria triggers sequential events in the mitochondrial cell death pathway, which is thought to be responsible for ROS-mediated neurodegeneration in PD. α-lipoic acid (LA) is a pleiotropic compound with potential pharmacotherapeutic value against a range of pathophysiological insults. Its protective actions against oxidative damage by scavenging ROS and reducing production of free radicals have been reported in various in vitro and in vivo systems. This study analyzed the ability of LA to protect PC12 neuronal cells from toxicity of 1-methyl-4-phenylpyridinium (MPP+), the neurotoxic metabolite of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) which is known to kill dopaminergic neurons selectively and to cause severe parkinsonism-like symptoms in humans and primate animals. Our results demonstrate that the apoptosis of PC12 cells elicited by MPP+ could be significantly prevented by pretreatment with LA for 1 h. In addition, LA inhibits intercellular ROS levels and the mitochondrial transmembrane permeability, the key players in the pathogenesis of PD, thereby protecting dopaminergic neuronal cells against oxidative damage.

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To obtain the genuine load spectra of the components of engineering vehicles, the influencing factors in the extrapolation of load spectra should be considered because these are of paramount importance. In the present paper, a multi-criteria decision-making method (MCDM) is proposed to determine the proper upcrossing of the high and low levels (UHLL) for extrapolation of the Rainflow matrix (RFM). First, the distribution characteristics of load amplitude extracted from observed RFMs are obtained. Subsequently, five criteria, namely, the statistic of mean, statistic of variance, coefficient of skewness, coefficient of kurtosis, and the experts’ preference, are selected to describe the fitting accuracy of the Weibull probability density function. Finally, the relationship between the load threshold and the level crossing function is determined after calculating their relative importance, and consequently, the proper UHLL is obtained. The usefulness and validity of the proposed method is illustrated by two typical load-time histories. Results show that the MCDM-based method can combine the subjective and objective factors and obtain an optimal load level.

ATP-binding cassette sub-family G member 5 (ABCG5) and ABCG8 are members of an ATP-binding cassette transporter superfamily. ABCG5 and ABCG8 variants affected serum levels of cholesterol and were considered as risk factors for coronary heart disease (CHD). The present control study analyzed ABCG5 and ABCG8 variants in a population for association with the risk of CHD. A total of 417 CHD patients and 267 controls were recruited for genotyping of four single nucleotide polymorphisms (SNPs; i.e. i7892T>C in ABCG5 and Tyr54CysA>G, Thr400LysC>A and 5U145A>C in ABCG8) using quantitative PCR high-resolution melting (qPCR-HRM). Serum lipid levels were measured using an automatic biochemical analyzer. The association of ABCG5/8 variants with lipid levels was analyzed using a Chi-square test. The impact of candidate ABCG5/8 SNPs on CHD was evaluated in a dominant genetic model with stepwise multiple regression analysis. Subgroup analyses were performed with regard to these SNPs, tobacco smoking status, alcohol consumption and gender. Genotypic and allelic frequencies of ABCG8 Thr400LysC>A were significantly different (P<0.05) between CHD patients and controls. CC homozygotes of the ABCG8 Thr400LysC>A SNP had greater triglyceride levels than CA/AA carriers with CHD. Logistic analysis revealed CHD risk was significantly higher in CC homozygotes of ABCG8 Thr400LysC>A than in carriers of the A allele (adjusted P=0.048; OR=2.034; 95% CI=0.983-4.207). Furthermore, there was a significant gene-tobacco smoking interaction. CC homozygotes of ABCG8 Thr400LysC>A SNP had significantly higher triglyceride concentrations (P=0.012) and an increased risk of CHD than tobacco smoking carriers of the A allele. The data from the current study suggested that ABCG8 Thr400LysC>A SNP genetic variants modulated plasma triglyceride levels and thereby affected CHD risk in the population studied. The genetic variant of ABCG8 also contributed to CHD risk through interaction with tobacco smoking.