Relationship between adult height and body weight and risk of carotid atherosclerosis assessed in terms of carotid intima-media thickness: The Nagasaki Islands study

Background

Previous studies have reported an inverse association between height and risk of cardiovascular disease. However, evidence is limited for the association between risk of atherosclerosis and height. Further, although the association between atherosclerosis and body mass index (BMI) is reportedly positive, there have been no reports of studies on associations between height and atherosclerosis in relation to BMI.

Methods

We conducted a cross-sectional study of Japanese men aged 30 to 89 years undergoing general health check-ups.

Results

Of the 1,337 men, 312 were diagnosed with carotid atherosclerosis (carotid intima-media thickness (CIMT) ≥ 1.1 mm), but no significant association was found between height and carotid atherosclerosis for the entire study group. Stratification by BMI status of those analytical findings disclosed a significant inverse association between height and carotid atherosclerosis among overweight (BMI ≥ 25 kg/m²) but not among non-overweight (BMI < 25 kg/m²) men. The classical cardiovascular risk factors-adjusted odds ratio (OR) and 95% confidence interval (CI) of carotid atherosclerosis for an increment of one SD (standard deviation) in height (6.70 cm) were 0.71 (0.54 to 0.94) for overweight (BMI ≥ 25 kg/m²) and 1.05 (0.87 to 1.27) for non-overweight (BMI < 25 kg/m²) men.

Conclusion

Independent from classical cardiovascular risk factors, height was found to be inversely associated with carotid atherosclerosis for overweight but not for non-overweight men.     

Chemical modifications of imidazole-containing alkoxyamines increase C–ON bond homolysis rate: Effects on their cytotoxic properties in glioblastoma cells

Previously, we described alkoxyamines bearing a pyridine ring as new pro-drugs with low molecular weights and theranostic activity. Upon chemical stimulus, alkoxyamines undergo homolysis and release free radicals, which can, reportedly, enhance magnetic resonance imaging and trigger cancer cell death. In the present study, we describe the synthesis and the anti-cancer activity of sixteen novel alkoxyamines that contain an imidazole ring. Activation of the homolysis was conducted by protonation and/or methylation. These new molecules displayed cytotoxic activities towards human glioblastoma cell lines, including the U251-MG cells that are highly resistant to the conventional chemotherapeutic agent Temozolomide. We further showed that the biological activities of the alkoxyamines were not only related to their half-life times of homolysis. We lastly identified the alkoxyamine (RS/SR)-4a, with both a high antitumour activity and favourable logD_7.4 and pK_a values, which make it a robust candidate for blood-brain barrier penetrating therapeutics against brain neoplasia.     

Empirical Bayes inference of pairwise F(ST) and its distribution in the genome

Populations often have very complex hierarchical structure. Therefore, it is crucial in genetic monitoring and conservation biology to have a reliable estimate of the pattern of population subdivision. F(ST)'s for pairs of sampled localities or subpopulations are crucial statistics for the exploratory analysis of population structures, such as cluster analysis and multidimensional scaling. However, the estimation of F(ST) is not precise enough to reliably estimate the population structure and the extent of heterogeneity. This article proposes an empirical Bayes procedure to estimate locus-specific pairwise F(ST)'s. The posterior mean of the pairwise F(ST) can be interpreted as a shrinkage estimator, which reduces the variance of conventional estimators largely at the expense of a small bias. The global F(ST) of a population generally varies among loci in the genome. Our maximum-likelihood estimates of global F(ST)'s can be used as sufficient statistics to estimate the distribution of F(ST) in the genome. We demonstrate the efficacy and robustness of our model by simulation and by an analysis of the microsatellite allele frequencies of the Pacific herring. The heterogeneity of the global F(ST) in the genome is discussed on the basis of the estimated distribution of the global F(ST) for the herring and examples of human single nucleotide polymorphisms (SNPs).     

Personalized medicine and proteomics: lessons from non-small cell lung cancer

Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.     

Prediction of GPCR-G protein coupling specificity using features of sequences and biological functions

Understanding the coupling specificity between G protein-coupled receptors （GPCRs） and specific classes of G proteins is important for further elucidation of receptor functions within a cell. Increasing information on GPCR sequences and the G protein family would facilitate prediction of the coupling properties of GPCRs. In this study, we describe a novel approach for predicting the coupling specificity between GPCRs and G proteins. This method uses not only GPCR sequences but also the functional knowledge generated by natural language processing, and can achieve 92.2% prediction accuracy by using the C4.5 algorithm. Furthermore, rules related to GPCR-G protein coupling are generated. The combination of sequence analysis and text mining improves the prediction accuracy for GPCR-G protein coupling specificity, and also provides clues for understanding GPCR signaling.     

Hypoxia-inducible factor 1 mediates upregulation of telomerase (hTERT)

Hypoxia occurs during the development of the placenta in the first trimester and correlates with both trophoblast differentiation and the induction of telomerase activity through hTERT expression. We sought to determine the mechanism of regulation of hTERT expression during hypoxia. We show that hypoxia-inducible factor 1alpha (HIF-1alpha) and hTERT expression in the human placenta decrease with gestational age and that these are overexpressed in preeclamptic placenta, a major complication of pregnancy. Hypoxia not only transactivates the hTERT promoter activity but also enhances endogenous hTERT expression. The hTERT promoter region between -165 and +51 contains two HIF-1 consensus motifs, and in vitro reporter assays show that these are essential for hTERT transactivation by HIF-1. Introduction of an antisense oligonucleotide for HIF-1 diminishes hTERT expression during hypoxia, indicating that upregulation of hTERT by hypoxia is directly mediated through HIF-1. Our results provide persuasive evidence that the regulation of hTERT promoter activity by HIF-1 represents a mechanism for trophoblast growth during hypoxia and suggests that this may be a generalized response to hypoxia in various human disorders including resistance to cancer therapeutics by upregulating telomerase.