Clustering is the partitioning of a set of objects into groups (clusters) so that objects within a group are more similar to each others than objects in different groups. Most of the clustering algorithms depend on some assumptions in order to define the subgroups present in a data set. As a consequence, the resulting clustering scheme requires some sort of evaluation as regards its validity.The evaluation procedure has to tackle difficult problems such as the quality of clusters, the degree with which a clustering scheme fits a specific data set and the optimal number of clusters in a partitioning. In the literature, a wide variety of indices have been proposed to find the optimal number of clusters in a partitioning of a data set during the clustering process. However, for most of indices proposed in the literature, programs are unavailable to test these indices and compare them.The R package NbClust has been developed for that purpose. It provides 30 indices which determine the number of clusters in a data set and it offers also the best clustering scheme from different results to the user. In addition, it provides a function to perform k-means and hierarchical clustering with different distance measures and aggregation methods. Any combination of validation indices and clustering methods can be requested in a single function call. This enables the user to simultaneously evaluate several clustering schemes while varying the number of clusters, to help determining the most appropriate number of clusters for the data set of interest.

Owing to variable clinical symptoms of phaeochromocytoma in these 100 cases of MEN 2 A, systemic biological adrenal assay is required. The search for phaeochromocytoma in medullary thyroid carcinoma (and vice versa) has to be systematically performed, even in apparently sporadic cases. Screening for phaeochromocytoma must be repeated for years, owing to the frequency of bilateral adrenal disease.

The Inuit population is often described as being protected against CVD due to their traditional dietary patterns and their unique genetic background. The objective of the present study was to examine gene -diet interaction effects on plasma lipid levels in the Inuit population. Data from the Qanuippitaa Nunavik Health Survey (n 553) were analysed via regression models which included the following: genotypes for thirty-five known polymorphisms (SNP) from twenty genes related to lipid metabolism; dietary fat intake including total fat (TotFat) and saturated fat (SatFat) estimated from a FFQ; plasma lipid levels, namely total cholesterol (TC), LDL-cholesterol (LDL-C), HDL-cholesterol (HDL-C) and TAG. The results demonstrate that allele frequencies were different in the Inuit population compared with the Caucasian population. Further, seven SNP (APOA1 2 75G/A (rs670), APOB XbAI (rs693), AGT M235T (rs699), LIPC 480C/T (rs1800588), APOA1 84T/C (rs5070), PPARG2 2618C/G (rs10865710) and APOE 219G/T (rs405509)) in interaction with TotFat and SatFat were significantly associated with one or two plasma lipid parameters. Another four SNP (APOC3 3238C . G (rs5128), CETP I405V (rs5882), CYP1A1 A4889G (rs1048943) and ABCA1 Arg219Lys (rs2230806)) in interaction with either TotFat or SatFat intake were significantly associated with one plasma lipid variable. Further, an additive effect of these SNP in interaction with TotFat or SatFat intake was significantly associated with higher TC, LDL-C or TAG levels, as well as with lower HDL-C levels. In conclusion, the present study supports the notion that gene -diet interactions play an important role in modifying plasma lipid levels in the Inuit population.

Background: Methylmercury (MeHg) exposure has been linked to an increased risk of coronary heart disease (CHD). Paraoxonase 1 (PON1), an enzyme located in the high-density–lipoprotein (HDL) fraction of blood lipids, may protect against CHD by metabolizing toxic oxidized lipids associated with low-density liproprotein and HDL. MeHg has been shown to inhibit PON1 activity in vitro, but this effect has not been studied in human populations.Objectives: This study was conducted to determine whether blood mercury levels are linked to decreased plasma PON1 activities in Inuit people who are highly exposed to MeHg through their seafood-based diet.Methods: We measured plasma PON1 activity using a fluorogenic substrate and blood concentrations of mercury and selenium by inductively coupled plasma mass spectrometry in 896 Inuit adults. Sociodemographic, anthropometric, clinical, dietary, and lifestyle variables as well as PON1 gene variants (rs705379, rs662, rs854560) were considered as possible confounders or modifiers of the mercury–PON1 relation in multivariate analyses.Results: In a multiple regression model adjusted for age, HDL cholesterol levels, omega-3 fatty acid content of erythrocyte membranes, and PON1 variants, blood mercury concentrations were inversely associated with PON1 activities [β-coefficient = –0.063; 95% confidence interval (CI), –0.091 to –0.035; p < 0.001], whereas blood selenium concentrations were positively associated with PON1 activities (β-coefficient = 0.067; 95% CI, 0.045–0.088; p < 0.001). We found no interaction between blood mercury levels and PON1 genotypes.Conclusions: Our results suggest that MeHg exposure exerts an inhibitory effect on PON1 activity, which seems to be offset by selenium intake.

BackgroundTissue concentrations of fatty acids (FAs) and genetic variations are well-known factors which affect the cardiovascular disease (CVD) risk. The objective was to examine whether the genetic variability of 20 candidate genes and red blood cells (RBCs) percentage of total n-3 polyunsaturated fatty acids (PUFA), a biomarker of dietary n-3 PUFA intake, modulate lipid related CVD risk factors in the Inuit population.MethodsData from the Qanuippitaa Nunavik Health Survey (n = 553) were analysed via multivariate regression models with 40 known polymorphisms, RBCs percentage of n-3 PUFA, and the interaction term to take into account the effect on plasma lipid and apolipoporotein levels.ResultsIndividuals being heterozygotes for CETP C-4502T (rs183130) or G-971A (rs4783961) together with higher n-3 PUFA had lower triacylglycerol (TG) concentrations compared to homozygotes for the minor allele. Further, effects of a stronger beneficial association between n-3 PUFA in RBCs and plasma lipid parameters- including lower total cholesterol (TC), lower low-density lipoprotein cholesterol (LDL-C) or higher high-density lipoprotein cholesterol (HDL-C) concentrations- were associated with AGT M235T (rs699) TT genotype, CETP G-971A (rs4783961) AG genotype, T allele carriers of CETP C-4502T (rs183130), and T allele carriers of CETP Ile405Val (rs5882). In contrast, higher n-3 PUFA in RBCs were associated with adverse lipid profiles- including increased LDL-C, increased apolipoprotein B100 or decreased HDL-C concentrations- in G allele carriers of the APOA5 -3 A/G (rs651821), C allele carriers of APOA5 T-1131C (rs662799), G carriers of APOC3 SstI (rs5128) and G carriers of APOA4 Asn147Ser (rs5104).ConclusionOverall, these results suggest that percentage of total n-3 PUFA of RBCs are associated with lipids related CVD risk factors conferred by genetic variations in the Inuit population.