Abundance and condition indices of coyotes on Hart Mountain National Antelope Refuge, Oregon

U.S. Fish and Wildlife Service staff at Hart Mountain National Antelope Refuge (HMNAR), southeastern Oregon, documented high pronghorn ( Antilocapra americana ) fawn mortality, subsequent low fawn recruitment, and declining pronghorn numbers from 1996 to 1999. Coyote ( Canis latrans ) predation was the primary cause, accounting for 60-85% of fawn mortalities each year, and fawns were not physiologically predisposed to predation. Therefore, we investigated certain coyote population parameters (age structure, survival, density, physiology) to evaluate how or if these factors influence coyote predation rates on pronghorn fawns. We captured 11 coyotes (5 male and 6 female) in December 1998. Age of captured animals ranged from 1.7 to 10.7 yrs (￣x = 5.0 years), and all coyotes appeared healthy upon capture. There were no known mortalities through December 1999. We estimated pre-whelping (December through February 1997-1999) density from howling surveys conducted within HMNAR to be 0.40-0.53 km -2 . Compared to other published studies, we found significant ( P ≤ 0.05) differences in selected blood parameters (e.g., blood urea nitrogen, total protein, white blood cell counts), indicating coyote nutrition may be marginal to deficient during winter at HMNAR. A high percentage of coyotes (91%) tested positive for serum-neutralizing antibodies to canine parvovirus. We judged that parasite ( Toxascaris spp., Alaria spp., Sarcocystis spp., and Isospora spp.) prevalence and intensity were not high enough to influence coyote condition. Based on our data, the coyote population at HMNAR is old aged, at a relatively high density, and stable, but their nutrition may be marginal to deficient during winter. Presently, we are unable to draw direct conclusions relating the parameters we sampled with predation rates by this unexploited coyote population.     

Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells

Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ～100?picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10?megabases. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.     

Novel role of PKR in inflammasome activation and HMGB1 release

The inflammasome regulates the release of caspase activation-dependent cytokines, including interleukin (IL)-1β, IL-18 and high-mobility group box 1 (HMGB1). By studying HMGB1 release mechanisms, here we identify a role for double-stranded RNA-dependent protein kinase (PKR, also known as EIF2AK2) in inflammasome activation. Exposure of macrophages to inflammasome agonists induced PKR autophosphorylation. PKR inactivation by genetic deletion or pharmacological inhibition severely impaired inflammasome activation in response to double-stranded RNA, ATP, monosodium urate, adjuvant aluminium, rotenone, live Escherichia coli, anthrax lethal toxin, DNA transfection and Salmonella typhimurium infection. PKR deficiency significantly inhibited the secretion of IL-1β, IL-18 and HMGB1 in E. coli-induced peritonitis. PKR physically interacts with several inflammasome components, including NOD-like receptor (NLR) family pyrin domain-containing 3 (NLRP3), NLRP1, NLR family CARD domain-containing protein 4 (NLRC4), absent in melanoma 2 (AIM2), and broadly regulates inflammasome activation. PKR autophosphorylation in a cell-free system with recombinant NLRP3, apoptosis-associated speck-like protein containing a CARD (ASC, also known as PYCARD) and pro-caspase-1 reconstitutes inflammasome activity. These results show a crucial role for PKR in inflammasome activation, and indicate that it should be possible to pharmacologically target this molecule to treat inflammation.     

Deep Geothermal:The‘Moon Landing’ Mission in the Unconventional Energy and Minerals Space

Deep geothermal from the hot crystalline basement has remained an unsolved frontier for the geothermal industry for the past 30 years. This poses the challenge for developing a new un-conventional geom...     

C-terminal truncations in human 3'-5' DNA exonuclease TREX1 cause autosomal dominant retinal vasculopathy with cerebral leukodystrophy

Autosomal dominant retinal vasculopathy with cerebral leukodystrophy is a microvascular endotheliopathy with middle-age onset. In nine families, we identified heterozygous C-terminal frameshift mutations in TREX1, which encodes a 3'-5' exonuclease. These truncated proteins retain exonuclease activity but lose normal perinuclear localization. These data have implications for the maintenance of vascular integrity in the degenerative cerebral microangiopathies leading to stroke and dementias.     

Multivariate GARCH Models with Correlation Clustering

A new clustered correlation multivariate generalized autoregressive conditional heteroskedasticity (CC‐MGARCH) model that allows conditional correlations to form clusters is proposed. This model generalizes the time‐varying correlation structure of Tse and Tsui (2002, Journal of Business and Economic Statistics 20 : 351–361) by classifying the correlations among the series into groups. To estimate the proposed model, Markov chain Monte Carlo methods are adopted. Two efficient sampling schemes for drawing discrete indicators are also developed. Simulations show that these efficient sampling schemes can lead to substantial savings in computation time in Monte Carlo procedures involving discrete indicators. Empirical examples using stock market and exchange rate data are presented in which two‐cluster and three‐cluster models are selected using posterior probabilities. This implies that the conditional correlation equation is likely to be governed by more than one set of decaying parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Forecasting and trading strategies based on a price trend model

In this paper, we consider the price trend model in which it is assumed that the time series of a security's prices contain a stochastic trend component which remains constant on each of a sequence of time intervals, with each interval having random duration. A quasi‐maximum likelihood method is used to estimate the model parameters. Optimal one‐step‐ahead forecasts of returns are derived. The trading rule based on these forecasts is constructed and is found to bear similarity to a popular trading rule based on moving averages. When applying the methods to forecast the returns of the Hang Seng Index Futures in Hong Kong, we find that the performance of the newly developed trading rule is satisfactory. Copyright © 2000 John Wiley & Sons, Ltd.