Loci affecting gamma-glutamyl transferase in adults and adolescents show age x SNP interaction and cardiometabolic disease associations

Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 x 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 x 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 x 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 x 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

Changes in markers of muscle damage, inflammation and HSP70 after an Ironman triathlon race

We investigated the effects of an Ironman triathlon race on markers of muscle damage, inflammation and heat shock protein 70 (HSP70). Nine well-trained male triathletes (mean +/- SD age 34 +/- 5 years; VO(2peak) 66.4 ml kg(-1) min(-1)) participated in the 2004 Western Australia Ironman triathlon race (3.8 km swim, 180 km cycle, 42.2 km run). We assessed jump height, muscle strength and soreness, and collected venous blood samples 2 days before the race, within 30 min and 14-20 h after the race. Plasma samples were analysed for muscle proteins, acute phase proteins, cytokines, heat shock protein 70 (HSP70), and clinical biochemical variables related to dehydration, haemolysis, liver and renal functions. Muscular strength and jump height decreased significantly (P < 0.05) after the race, whereas muscle soreness and the plasma concentrations of muscle proteins increased. The cytokines interleukin (IL)-1 receptor antagonist, IL-6 and IL-10, and HSP70 increased markedly after the race, while IL-12p40 and granulocyte colony-stimulating factor (G-CSF) were also elevated. IL-4, IL-1beta and tumour necrosis factor-alpha did not change significantly, despite elevated C-reactive protein and serum amyloid protein A on the day after the race. Plasma creatinine, uric acid and total bilirubin concentrations and gamma-glutamyl transferase activity also changed after the race. In conclusion, despite evidence of muscle damage and an acute phase response after the race, the pro-inflammatory cytokine response was minimal and anti-inflammatory cytokines were induced. HSP70 is released into the circulation as a function of exercise duration.

Evaluation of piezoelectric PVDF polymers for use in space environments. III. Comparison of the effects of vacuum UV and gamma radiation

Films of piezoelectric PVDF and P(VDF-TrFE) were exposed to vacuum UV (115-300 nm VUV) and -radiation to investigate how these two forms of radiation affect the chemical, morphological, and piezoelectric properties of the polymers. The extent of crosslinking was almost identical in both polymers after -irradiation, but surprisingly, was significantly higher for the TrFE copolymer after VUV-irradiation. Changes in the melting behavior were also more significant in the TrFE copolymer after VUV-irradiation due to both surface and bulk crosslinking, compared with only surface crosslinking for the PVDF films. The piezoelectric properties (measured using d33 piezoelectric coefficients and D-E hysteresis loops) were unchanged in the PVDF homopolymer, while the TrFE copolymer exhibited more narrow D-E loops after exposure to either - or VUV-radiation. The more severe damage to the TrFE copolymer in comparison with the PVDF homopolymer after VUV-irradiation is explained by different energy deposition characteristics. The short wavelength, highly energetic photons are undoubtedly absorbed in the surface layers of both polymers, and we propose that while the longer wavelength components of the VUV-radiation are absorbed by the bulk of the TrFE copolymer causing crosslinking, they are transmitted harmlessly in the PVDF homopolymer.

Gamma-tocotrienol as an effective agent in targeting prostate cancer stem cell-like population

Emerging evidence supports that prostate cancer originates from a rare sub-population of cells, namely prostate cancer stem cells (CSCs). Conventional therapies for prostate cancer are believed to mainly target the majority of differentiated tumor cells but spare CSCs, which may account for the subsequent disease relapse after treatment. Therefore, successful elimination of CSCs may be an effective strategy to achieve complete remission from this disease. Gamma-tocotrienols (-T3) is one of the vitamin-E constituents which have been shown to have anticancer effects against a wide-range of human cancers. Recently, we have reported that -T3 treatment not only inhibits prostate cancer cell invasion but also sensitizes the cells to docetaxel-induced apoptosis, suggesting that -T3 may be an effective therapeutic agent against advanced stage prostate cancer. Here, we demonstrate for the first time that -T3 can down-regulate the expression of prostate CSC markers (CD133/CD44) in androgen independent (AI) prostate cancer cell lines (PC-3 & DU145), as evident from western blotting analysis. Meanwhile, the spheroid formation ability of the prostate cancer cells was significantly hampered by -T3 treatment. In addition, pre-treatment of PC-3 cells with -T3 was found to suppress tumor initiation ability of the cells. More importantly, while CD133-enriched PC-3 cells were highly resistant to docetaxel treatment, these cells were as sensitive to -T3 treatment as the CD133-depleted population. Our data suggest that -T3 may be an effective agent in targeting prostate CSCs, which may account for its anticancer and chemosensitizing effects reported in previous studies.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros