BackgroundLifestyle-related diseases represented by metabolic syndrome develop as results of complex interaction. By using health check-up data from two large studies collected during a long-term follow-up, we searched for risk factors associated with the development of metabolic syndrome.MethodsIn our original study, we selected 77 case subjects who developed metabolic syndrome during the follow-up and 152 healthy control subjects who were free of lifestyle-related risk components from among 1803 Japanese male employees. In a replication study, we selected 2196 case subjects and 2196 healthy control subjects from among 31343 other Japanese male employees. By means of a bioinformatics approach using a fuzzy neural network (FNN), we searched any significant combinations that are associated with MetS. To ensure that the risk combination selected by FNN analysis was statistically reliable, we performed logistic regression analysis including adjustment.ResultsWe selected a combination of an elevated level of γ-glutamyltranspeptidase (γ-GTP) and an elevated white blood cell (WBC) count as the most significant combination of risk factors for the development of metabolic syndrome. The FNN also identified the same tendency in a replication study. The clinical characteristics of γ-GTP level and WBC count were statistically significant even after adjustment, confirming that the results obtained from the fuzzy neural network are reasonable. Correlation ratio showed that an elevated level of γ-GTP is associated with habitual drinking of alcohol and a high WBC count is associated with habitual smoking.ConclusionsThis result obtained by fuzzy neural network analysis of health check-up data from large long-term studies can be useful in providing a personalized novel diagnostic and therapeutic method involving the γ-GTP level and the WBC count.

Aim: Two peptide cocktail vaccines using glypican-3, WD-repeat-containing protein up-regulated in hepatocellular carcinoma (HCC) and nei endonuclease VIII-like three epitopes were evaluated in advanced HCC in two Phase I studies. Patients & methods: Study 1 evaluated dose-limiting toxicities (DLTs) of peptides 1–3 (HLA-A24-restricted) and study 2 evaluated DLTs of peptides 1–6 (HLA-A24 or A02-restricted). Results: Overall, 18 and 14 patients were enrolled in studies 1 and 2, respectively. No DLTs were observed up to 7.1 mg of the vaccine cocktail. No complete response/partial response was observed. Stable disease was reported in nine and five patients with a disease control rate of 52.9% and 35.7% in studies 1 and 2, respectively. Conclusion: Both vaccines showed good tolerability and potential usefulness against HCC. Clinical trial registration: JapicCTI-121933 ; JapicCTI-142477

Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP—SNP interaction, SNP—environment interaction, and SNP—clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS.

Physical environmental factors of housing are affected to emotional feeling of human being who is living in the housing. The effect of some physical environmental factors of the housing on comfortableness (emotion) against the housing itself should be precisely investigated because physical factors such as sunshine, colour of interior, temperature, sound and so on would be set in comfortable degree. In the present study, physical and sensory environmental factors against the actual housing and comfortableness factors of the housing were collected by questionnaire sheet with Visual Analog Scale method and the correlation between those factors was analyzed. Three comfortableness factors such as "Kaitekisei", "Okiniiri" and "Kenkoteki" was divided into three groups such as Comfortable("Manzoku"), Unconfortable("Fumanzoku") and Medium. When the combination analysis of physical and sensory environmental factors affecting to these three factors was performed by means of Fuzzy Neural Network, more than 90% of accuracy was obtained. The values were fairly high compared with conventional statistical analysis, such as CART and LDA. From the acquired rule, it was found that intimate feeling "Kutsurogu" as emotional environment and lighting or color of housing as housing physical environment were affected to "Kaitekisei" and "Okiniiri" and those comfortableness factors could be elucidated by the housing environment.