229 research outputs found
2003 Manifesto on the California Electricity Crisis
The authors, an ad-hocgroup of professionals with experience in regulatory and energy economics, share a common concern with the continuing turmoil facing the electricity industry ("the industry") in California. Most ofthe authorsendorsed the first California Electricity Manifesto issued on January 25, 2001. Almost two years have passed since that first Manifesto. While wholesale electric prices have moderated and California no longer faces the risk of blackouts, in many ways the industry is in worse shape now than it was at the start of 2001. As a result, the group of signatories continues to have a deep concern with the conflicting policy directions being pursued for the industry at both the State and Federal levels of government and the impact the uncertainties associated with these conflicting policies will have, long term, on the economy of California. Theauthorshave once again convened under the auspices of the Institute of Management, Innovation and Organization at the University of California, Berkeley, to put forward ourtheir ideas on a basic set of necessary policies to move the industry forward for the benefit of all Californians and the nation. The authors point out that theydo not pretend to be "representative." They do bring, however, a very diverse range of backgrounds and expertise.Technology and Industry, Regulatory Reform
The USNO-B Catalog
USNO-B is an all-sky catalog that presents positions, proper motions,
magnitudes in various optical passbands, and star/galaxy estimators for
1,042,618,261 objects derived from 3,643,201,733 separate observations. The
data were obtained from scans of 7,435 Schmidt plates taken for the various sky
surveys during the last 50 years. USNO-B1.0 is believed to provide all-sky
coverage, completeness down to V = 21, 0.2 arcsecond astrometric accuracy at
J2000, 0.3 magnitude photometric accuracy in up to five colors, and 85%
accuracy for distinguishing stars from non-stellar objects. A brief discussion
of various issues is given here, but the actual data are available from
http://www.nofs.navy.mil and other sites.Comment: Accepted by Astronomical Journa
Reversing age: Dual species measurement of epigenetic age with a single clock
Young blood plasma is known to confer beneficial effects on various organs in mice. However, it was not known whether young plasma rejuvenates cells and tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly-accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n=593 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain-, liver-, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n=850 human tissue samples to the training data. We employed these six clocks to investigate the rejuvenation effects of a plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers and behavioral responses to assess cognitive functions. Cellular senescence, which is not associated with epigenetic aging, was also considerably reduced in vital organs. Overall, this study demonstrates that a plasma-derived treatment markedly reverses aging according to epigenetic clocks and benchmark biomarkers of aging.Fil: Horvath, Steve. University of California at Los Angeles; Estados UnidosFil: Singh, Kavita. NMIMS University; IndiaFil: Raj, Ken. Public Health England; Reino UnidoFil: Khairnar, Shraddha. NMIMS University; IndiaFil: Sanghav, Akshay. Nugenics Research Pvt Ltd; IndiaFil: Shrivastava, Agnivesh. Nugenics Research Pvt Ltd; IndiaFil: Zoller, Joseph A.. University of California at Los Angeles; Estados UnidosFil: Li, Caesar Z.. University of California at Los Angeles; Estados UnidosFil: Hereñú, Claudia Beatriz. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - Córdoba. Instituto de FarmacologÃa Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias QuÃmicas. Instituto de FarmacologÃa Experimental de Córdoba; ArgentinaFil: Canatelli Mallat, Martina. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - La Plata. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; ArgentinaFil: Lehmann, Marianne. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - La Plata. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; ArgentinaFil: Solberg Woods, Leah C.. Wake Forest University School of Medicine; Estados UnidosFil: Garcia Martinez, Angel. University of Tennessee; Estados UnidosFil: Wang, Tengfei. University of Tennessee; Estados UnidosFil: Chiavellini, Priscila. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - La Plata. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; ArgentinaFil: Levine, Andrew J.. University of California at Los Angeles; Estados UnidosFil: Chen, Hao. University of Tennessee; Estados UnidosFil: Goya, Rodolfo Gustavo. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - La Plata. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner". Universidad Nacional de la Plata. Facultad de Ciencias Médicas. Instituto de Investigaciones BioquÃmicas de La Plata "Prof. Dr. Rodolfo R. Brenner"; ArgentinaFil: Katcher, Harold L.. Nugenics Research Pvt Ltd; Indi
Data mining of high density genomic variant data for prediction of Alzheimer's disease risk
<p>Abstract</p> <p>Background</p> <p>The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.</p> <p>Methods</p> <p>Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.</p> <p>Results</p> <p>The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with <it>APOE and GAB2 </it>SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with <it>ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH </it>respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included <it>APOE </it>and <it>GAB2 </it>SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.</p> <p>Conclusions</p> <p>With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.</p
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Study of the impact of ice formation in leads upon the sea ice pack mass balance using a new frazil and grease ice parameterization
Leads are cracks in sea ice that often form because of deformation. During winter months, leads expose the ocean to the cold atmosphere, resulting in supercooling and the formation of frazil ice crystals within the mixed layer. Here the authors investigate the role of frazil ice formation in leads on the mass balance of the sea ice pack through the incorporation of a new module into the Los Alamos sea ice model (CICE). The frazil ice module considers an initial cooling of leads followed by a steady-state formation of uniformly distributed single size frazil ice crystals that precipitate to the ocean surface as grease ice. The grease ice is pushed against one of the lead edges by wind and water drag that the authors represent through a variable collection thickness for new sea ice. Simulations of the sea ice cover in the Arctic and Antarctic are performed and compared to a model that treats leads the same as the open ocean. The processes of ice formation in the new module slow down the refreezing of leads, resulting in a longer period of frazil ice production. The fraction of frazil-derived sea ice increases from 10% to 50%, corresponding better to observations. The new module has higher ice formation rates in areas of high ice concentration and thus has a greater impact within multiyear ice than it does in the marginal seas. The thickness of sea ice in the central Arctic increases by over 0.5 m, whereas within the Antarctic it remains unchanged
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