CEO summit. Building the new health care delivery alliance, Part III. Roundtable discussion

In cooperation with McManis Associates, Hospitals & Health Networks recently convened a CEO summit on physician/hospital integration activities. In the third report of a three-part series on the summit, leading health care executives discuss investor capital needs, strategic information management needs, and the management competencies required for capitated managed care success.     

不同磁场作用对AZ31镁合金的凝固组织的影响

镁合金是具有优越性能的金属材料,镁合金的加工是目前国内外正在深入进行研究的新课题.实验发现在镁合金的凝固过程中施加低频或静态磁场都能细化晶粒,但静磁场得到的细化效果要优于低频交流磁场,同时随磁感应强度的增加,静磁场细化晶粒的效果明显提高;在静磁场条件下晶界共晶体组织的厚度明显减小,同时在晶内出现了大量细小块状化合物,这有利于改善镁合金的综合性能.     

Monoclonal antibody-based competitive ELISA for simultaneous detection of rinderpest virus and peste des petits ruminants virus antibodies

An experimental competitive enzyme-linked immunosorbent assay (morbillivirus cELISA) using a recombinant N antigen (rRPV N) expressed in a baculovirus and a ruminant morbillivirus (RPV and PPRV)-specific monoclonal antibody (P-13A9) was developed for simultaneous detection of rinderpest virus (RPV) and peste des petits ruminants virus (PPRV) antibodies and its diagnostic performance was evaluated. A set of known reference antisera against RPV and PPRV belonging to different lineages, experimental sera from cattle vaccinated for a RPV of Asian lineage, and field sera from cattle and sheep/goat populations known to be positive (West Africa) and negative (Korea) for RPV and PPRV were used for the evaluation. Morbillivirus cELISA results on the panel of experimental RPV and PPRV antisera showed high correlation (r=0.97) between the whole virus and the rRPV N antigens, suggesting that the rRPV N contains a ruminant morbillivirus-specific antigenic determinant recognized by the P-13A9 and it may be suitable as an ELISA antigen in place of the whole virus. Morbillivirus cELISA detected anti-RPV and anti-PPRV antibodies in all reference RPV and PPRV antisera containing VN titers >/=1:8, suggesting that the assay can simultaneously detect antibodies against RPV and PPRV. Anti-RPV antibody was detected by morbillivirus cELISA in vaccinated cattle as early as the VNT and continued to be detectable by both the cELISA and the VNT until termination of the study. When applied to field samples from Africa, morbillivirus cELISA showed good agreement with a RP cELISA kit (kappa value of 0.86) in bovine sera and with a peste des petits ruminant cELISA kit (kappa value of 0.81) in caprine/ovine sera. Usefulness of morbillivirus cELISA using the rRPV N protein was discussed.     

Methods for the determination of cyclopropenoid fatty acids. VII. The dilution-HBr-titration technique as a general method

The stepwise HBr titration method for the cyclopropenoid analysis of cottonseed oils is subject to serious inaccuracies when applied to samples containing higher cyclopropenoid concentrations, particularly if they contain appreciable amounts of alumina-adsorbable materials. A modification of the method is described which eliminates these sources of error. Its validity has been established by the analysis of a wide range of synthetic compositions including compositions containing massive amounts of interfering HBr-reactive substances and other alumina-adsorbable materials. The method with further modification can be used to analyze glycerides with the same high degree of accuracy. Presented at the AOCS Meeting in Houston, April 1965. So. Utiliz. Res. Dev. Div., ARS, USDA.     

Combining MODIS and Landsat imagery to estimate and map boreal forest cover loss

Estimation of forest cover change is important for boreal forests, one of the most extensive forested biomes, due to its unique role in global timber stock, carbon sequestration and deposition, and high vulnerability to the effects of global climate change. We used time-series data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to produce annual forest cover loss hotspot maps. These maps were used to assign all blocks (18.5 by 18.5 km) partitioning the boreal biome into strata of high, medium and low likelihood of forest cover loss. A stratified random sample of 118 blocks was interpreted for forest cover and forest cover loss using high spatial resolution Landsat imagery from 2000 and 2005. Area of forest cover gross loss from 2000 to 2005 within the boreal biome is estimated to be 1.63% (standard error 0.10%) of the total biome area, and represents a 4.02% reduction in year 2000 forest cover. The proportion of identified forest cover loss relative to regional forest area is much higher in North America than in Eurasia (5.63% to 3.00%). Of the total forest cover loss identified, 58.9% is attributable to wildfires. The MODIS pan-boreal change hotspot estimates reveal significant increases in forest cover loss due to wildfires in 2002 and 2003, with 2003 being the peak year of loss within the 5-year study period. Overall, the precision of the aggregate forest cover loss estimates derived from the Landsat data and the value of the MODIS-derived map displaying the spatial and temporal patterns of forest loss demonstrate the efficacy of this protocol for operational, cost-effective, and timely biome-wide monitoring of gross forest cover loss.     

Fitting optimal piecewise linear functions using genetic algorithms

Constructing a model for data in R² is a common problem in many scientific fields, including pattern recognition, computer vision, and applied mathematics. Often little is known about the process which generated the data or its statistical properties. For example, in fitting a piecewise linear model, the number of pieces, as well as the knot locations, may be unknown. Hence, the method used to build the statistical model should have few assumptions, yet, still provide a model that is optimal in some sense. Such methods can be designed through the use of genetic algorithms. We examine the use of genetic algorithms to fit piecewise linear functions to data in R². The number of pieces, the location of the knots, and the underlying distribution of the data are assumed to be unknown. We discuss existing methods which attempt to solve this problem and introduce a new method which employs genetic algorithms to optimize the number and location of the pieces. Experimental results are presented which demonstrate the performance of our method and compare it to the performance of several existing methods, We conclude that our method represents a valuable tool for fitting both robust and nonrobust piecewise linear functions     

Analysis of the human immune response to vaccinia by use of a novel protein microarray suggests that antibodies recognize less than 10% of the total viral proteome

Control of smallpox by mass vaccination was one of the most effective public health measures ever employed for eradicating a devastating infectious disease. However, new methods are needed for monitoring smallpox immunity within current vulnerable populations, and for the development of replacement vaccines for use by immunocompromized or low-responding individuals. As a measure for achieving this goal, we developed a protein microarray of the vaccinia virus proteome by using high-throughput baculovirus expression and purification of individual elements. The array was validated with therapeutic-grade, human hyperimmune sera, and these data were compared to results obtained from individuals vaccinated against smallpox using Dryvax. A high level of reproducibility with a very low background were apparent in repetitive assays that confirmed previously reported antigens and identified new proteins that may be important for neutralizing viral infection. Our results suggest that proteins recognized by antibodies from all vaccinees constituted <10% of the total vaccinia proteome.     

Portable Infrared Spectrometer to Characterize and Differentiate Between Organic and Conventional Bovine Butter

The performance of a portable infrared system combined with pattern recognition to discriminate between organically and conventionally produced bovine butter samples as well as to predict the levels of conjugated linoleic acid (CLA) were evaluated. Sixty butter (27 organic and 33 conventional) samples were used in this study. Bovine butter–fat were applied onto an attenuated total reflectance infrared (ATR‐IR) accessory equipped with a five‐bounce ZnSe crystal set at 65 °C for spectral collection. In addition, ATR‐IR spectra of bovine butter were directly collected at room temperature to avoid phase separation. The fatty acid profile and the levels of CLA were determined using reference FAME‐GC‐FID analysis. SIMCA models showed well separated clusters that discriminated between organic and conventional bovine butters due to C=C trans bending out of the plane vibration modes band at 967 cm^?1. Additionally, strong PLSR models were developed to predict CLA levels using butter–fat and bovine butter spectra with SEP of 0.05 % and RPD of 4.7, indicating that the models are suitable for quality control applications. Portable IR technology offers the ability for “in situ” analysis of butters that is much less time consuming than current analytical practices for authentication and quality control efforts by the industry.