23 research outputs found

    Oregon 2100: projected climatic and ecological changes

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    Greenhouse climatic warming is underway and exacerbated by human activities. Future outcomes of these processes can be projected using computer models checked against climatic changes during comparable past atmospheric compositions. This study gives concise quantitative predictions for future climate, landscapes, soils, vegetation, and marine and terrestrial animals of Oregon. Fossil fuel burning and other human activities by the year 2100 are projected to yield atmospheric CO2 levels of about 600-850 ppm (SRES A1B and B1), well above current levels of 400 ppm and preindustrial levels of 280 ppm. Such a greenhouse climate was last recorded in Oregon during the middle Miocene, some 16 million years ago. Oregon’s future may be guided by fossil records of the middle Miocene, as well as ongoing studies on the environmental tolerances of Oregon plants and animals, and experiments on the biological effects of global warming. As carbon dioxide levels increase, Oregon’s climate will move toward warm temperate, humid in the west and semiarid to subhumid to the east, with increased summer and winter drought in the west. Western Oregon lowlands will become less suitable for temperate fruits and nuts and Pinot Noir grapes, but its hills will remain a productive softwood forest resource. Improved pasture and winter wheat crops will become more widespread in eastern Oregon. Tsunamis and stronger storms will exacerbate marine erosion along the Oregon Coast, with significant damage to coastal properties and cultural resources

    Inhibition of BACH1 (FANCJ) helicase by backbone discontinuity is overcome by increased motor ATPase or length of loading strand

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    The BRCA1 associated C-terminal helicase (BACH1) associated with breast cancer has been implicated in double strand break (DSB) repair. More recently, BACH1 (FANCJ) has been genetically linked to the chromosomal instability disorder Fanconi Anemia (FA). Understanding the roles of BACH1 in cellular DNA metabolism and how BACH1 dysfunction leads to tumorigenesis requires a comprehensive investigation of its catalytic mechanism and molecular functions in DNA repair. In this study, we have determined that BACH1 helicase contacts with both the translocating and the non-translocating strands of the duplex are critical for its ability to track along the sugar phosphate backbone and unwind dsDNA. An increased motor ATPase of a BACH1 helicase domain variant (M299I) enabled the helicase to unwind the backbone-modified DNA substrate in a more proficient manner. Alternatively, increasing the length of the 5′ tail of the DNA substrate allowed BACH1 to overcome the backbone discontinuity, suggesting that BACH1 loading mechanism is critical for its ability to unwind damaged DNA molecules

    Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans

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    INTRODUCTION: African Americans' (AAs) late-onset Alzheimer's disease (LOAD) genetic risk profile is incompletely understood. Including clinical covariates in genetic analyses using informed conditioning might improve study power. METHODS: We conducted a genome-wide association study (GWAS) in AAs employing informed conditioning in 1825 LOAD cases and 3784 cognitively normal controls. We derived a posterior liability conditioned on age, sex, diabetes status, current smoking status, educational attainment, and affection status, with parameters informed by external prevalence information. We assessed association between the posterior liability and a genome-wide set of single-nucleotide polymorphisms (SNPs), controlling for APOE and ABCA7, identified previously in a LOAD GWAS of AAs. RESULTS: Two SNPs at novel loci, rs112404845 (P = 3.8 × 10-8), upstream of COBL, and rs16961023 (P = 4.6 × 10-8), downstream of SLC10A2, obtained genome-wide significant evidence of association with the posterior liability. DISCUSSION: An informed conditioning approach can detect LOAD genetic associations in AAs not identified by traditional GWAS

    Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo

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    Meeting Abstracts: Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo Clearwater Beach, FL, USA. 9-11 June 201

    Effect of a Low-Fat Fish Oil Diet on Proinflammatory Eicosanoids and Cell-Cycle Progression Score in Men Undergoing Radical Prostatectomy

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    We previously reported that a 4-6 week low-fat fish oil (LFFO) diet did not affect serum IGF-1 levels (primary outcome) but resulted in lower omega-6 to omega-3 fatty acid ratios in prostate tissue and lower prostate cancer proliferation (Ki67) as compared to a Western diet (WD). In this post-hoc analysis, the effect of the LFFO intervention on serum pro-inflammatory eicosanoids, LTB4 and 15(S)-HETE, and the cell cycle progression (CCP) score were investigated. Serum fatty acids and eicosanoids were measured by gas chromatography and ELISA. CCP score was determined by RT-PCR. Associations between serum eicosanoids, Ki67, and CCP score were evaluated using partial correlation analyses. BLT1 (LTB4 receptor) expression was determined in prostate cancer cell lines and prostatectomy specimens. Serum omega-6 fatty acids and 15(S)-HETE levels were significantly reduced, and serum omega-3 levels were increased in the LFFO group relative to the WD group, whereas there was no change in LTB4 levels. The CCP score was significantly lower in the LFFO compared to the WD group. The 15(S)-HETE change correlated with tissue Ki67 (R=0.48; p<0.01) but not with CCP score. The LTB4 change correlated with the CCP score (r=0.4; p=0.02) but not with Ki67. The LTB4 receptor BLT1 was detected in prostate cancer cell lines and human prostate cancer specimens. In conclusion, a LFFO diet resulted in decreased 15(S)-HETE levels and lower CCP score relative to a WD. Further studies are warranted to determine whether the LFFO diet anti-proliferative effects are mediated through the LTB4/BLT1 and 15(S)-HETE pathways

    The ROC Toolbox: A toolbox for analyzing receiver-operating characteristics derived from confidence ratings

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    Signal-detection theory, and the analysis of receiver-operating characteristics (ROCs), has played a critical role in the development of theories of episodic memory and perception. The purpose of the current paper is to present the ROC Toolbox. This toolbox is a set of functions written in the Matlab programming language that can be used to fit various common signal detection models to ROC data obtained from confidence rating experiments. The goals for developing the ROC Toolbox were to create a tool (1) that is easy to use and easy for researchers to implement with their own data, (2) that can flexibly define models based on varying study parameters, such as the number of response options (e.g. confidence ratings) and experimental conditions, and (3) that provides optimal routines (e.g., Maximum Likelihood estimation) to obtain parameter estimates and numerous goodness-of-fit measures.The ROC toolbox allows for various different confidence scales and currently includes the models commonly used in recognition memory and perception: (1) the unequal variance signal detection (UVSD) model, (2) the dual process signal detection (DPSD) model, and (3) the mixture signal detection (MSD) model. For each model fit to a given data set the ROC toolbox plots summary information about the best fitting model parameters and various goodness-of-fit measures. Here, we present an overview of the ROC Toolbox, illustrate how it can be used to input and analyse real data, and finish with a brief discussion on features that can be added to the toolbox
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