Model representation of secondary organic aerosol in CMAQv4.7

Numerous scientific upgrades to the representation of secondary organic aerosol (SOA) are incorporated into the Community Multiscale Air Quality (CMAQ) modeling system. Additions include several recently identified SOA precursors: benzene, isoprene, and sesquiterpenes; and pathways: in-cloud oxidation of glyoxal and methylglyoxal, particle-phase oligomerization, and acid enhancement of isoprene SOA. NO(x)-dependent aromatic SOA yields are also added along with new empirical measurements of the enthalpies of vaporization and organic mass-to-carbon ratios. For the first time, these SOA precursors, pathways and empirical parameters are included simultaneously in an air quality model for an annual simulation spanning the continental U.S. Comparisons of CMAQ-modeled secondary organic carbon (OC(sec)) with semiempirical estimates screened from 165 routine monitoring sites across the U.S. indicate the new SOA module substantially improves model performance. The most notable improvement occurs in the central and southeastern U.S. where the regionally averaged temporal correlations (r) between modeled and semiempirical OC(sec) increase from 0.5 to 0.8 and 0.3 to 0.8, respectively, when the new SOA module is employed. Wintertime OC(sec) results improve in all regions of the continental U.S. and the seasonal and regional patterns of biogenic SOA are better represented.     

Top-down proteomics on a chromatographic time scale using linear ion trap fourier transform hybrid mass spectrometers

Proteomics has grown significantly with the aid of new technologies that consistently are becoming more streamlined. While processing of proteins from a whole cell lysate is typically done in a bottom-up fashion utilizing MS/MS of peptides from enzymatically digested proteins, top-down proteomics is becoming a viable alternative that until recently has been limited largely to offline analysis by tandem mass spectrometry. Here we describe a method for high-resolution tandem mass spectrometery of intact proteins on a chromatographic time scale. In a single liquid chromatography-tandem mass spectrometry (LC-MS/MS) run, we have identified 22 yeast proteins with molecular weights from 14 to 35 kDa. Using anion exchange chromatography to fractionate a whole cell lysate before online LC-MS/MS, we have detected 231 metabolically labeled (14N/15N) protein pairs from Saccharomyces cerevisiae. Thirty-nine additional proteins were identified and characterized from LC-MS/MS of selected anion exchange fractions. Automated localization of multiple acetylations on Histone H4 was also accomplished on an LC time scale from a complex protein mixture. To our knowledge, this is the first demonstration of top-down proteomics (i.e., many identifications) on linear ion trap Fourier transform (LTQ FT) systems using high-resolution MS/MS data obtained on a chromatographic time scale.     

Nonfunctionalized nanocrystals can exploit a cell's active transport machinery delivering them to specific nuclear and cytoplasmic compartments

We use high content cell analysis, live cell fluorescent imaging, and transmission electron microscopy approaches combined with inhibitors of cellular transport and nuclear import to conduct a systematic study of the mechanism of interaction of nonfunctionalized quantum dots (QDs) with live human blood monocyte-derived primary macrophages and cell lines of phagocytic, epithelial, and endothelial nature. Live human macrophages are shown to be able to rapidly uptake and accumulate QDs in distinct cellular compartment specifically to QDs size and charge. We show that the smallest QDs specifically target histones in cell nuclei and nucleoli by a multistep process involving endocytosis, active cytoplasmic transport, and entering the nucleus via nuclear pore complexes. Treatment of the cells with an anti-microtubule agent nocodazole precludes QDs cytoplasmic transport whereas a nuclear import inhibitor thapsigargin blocks QD import into the nucleus. These results demonstrate that the nonfunctionalized QDs exploit the cell's active transport machineries for delivery to specific intranuclear destinations.     

Psychometric properties and U.S. National norms of the Evidence-Based Practice Attitude Scale (EBPAS).

[Correction Notice: An erratum for this article was reported in Vol 22(3) of Psychological Assessment (see record 2010-18043-022). There were three errors in Table 1 on p. 360. In the last row, the row label should be “Overall EBPAS mean,” M = 2.73, and SD = 0.49. The revised Table 1 appears in the erratum.] The Evidence-Based Practice Attitude Scale (EBPAS) assesses mental health and social service provider attitudes toward adopting evidence-based practices. Scores on the EBPAS derive from 4 subscales (i.e., Appeal, Requirements, Openness, and Divergence) as well as the total scale, and preliminary studies have linked EBPAS scores to clinic structure and policies, organizational culture and climate, and first-level leadership. EBPAS scores are also related to service provider characteristics, including age, education level, and level of professional development. The present study examined the factor structure, reliability, and norms of EBPAS scores in a sample of 1,089 mental health service providers from a nationwide sample drawn from 100 service institutions in 26 states in the United States. The study also examined associations of provider demographic characteristics with EBPAS subscale and total scores. Confirmatory factor analysis supported a second-order factor model, and reliability coefficients for the subscales ranged from .91 to .67 (total scale = .74). The study establishes national norms for the EBPAS so that comparisons can be drawn for U.S. local as well as international studies of attitudes toward evidence-based practices. The results suggest that the factor structure and reliability are likely generalizable to a variety of service provider contexts and different service settings and that the EBPAS subscales are associated with provider characteristics. Directions for future research are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Genetic selection for hoof health traits and cow mobility scores can accelerate the rate of genetic gain in producer-scored lameness in dairy cows

Cattle breeding programs that strive to reduce the animal-level incidence of lameness are often hindered by the availability of informative phenotypes. As a result, indicator traits of lameness (i.e., hoof health and morphological conformation scores) can be used to improve the accuracy of selection and subsequent genetic gain. Therefore, the objectives of the present study were to estimate the variance components for hoof health traits using various phenotypes collected from a representative sample of Irish dairy cows. Also of interest to the present study was the genetic relationship between both hoof health traits and conformation traits with producer-scored lameness. Producer-recorded lameness events and linear conformation scores from 307,657 and 117,859 Irish dairy cows, respectively, were used. Data on hoof health (i.e., overgrown sole, white line disease, and sole hemorrhage), mobility scores, and body condition scores were also available from a research study on up to 11,282 Irish commercial dairy cows. Linear mixed models were used to quantify variance components for each trait and to estimate genetic correlations among traits. The estimated genetic parameters for hoof health traits in the present study were greater (i.e., heritability range: 0.005 to 0.27) than previously reported in dairy cows. With the exception of analyses that considered hoof health traits in repeatability models, little difference in estimated variance components existed among the various hoof-health phenotypes. Results also suggest that producer-recorded lameness is correlated with both hoof health (i.e., genetic correlation up to 0.48) and cow mobility (i.e., genetic correlation = 0.64). Moreover, cows that genetically tend to have rear feet that appear more parallel when viewed from the rear are also genetically more predisposed to lameness (genetic correlation = 0.39); genetic correlations between lameness and other feet and leg type traits, as well as between lameness and frame type traits, were not different from zero. Results suggest that if the population breeding goal was to reduce lameness incidence, improve hoof health, or improve cow mobility, genetic selection for either of these traits should indirectly benefit the other traits. Results were used to quantify the genetic gains achievable for lameness when alternative phenotypes are available.     

Prediction of genetic merit for live weight and body condition score in dairy cows using routinely available linear type and carcass data

Accurate estimates of genetic merit for both live weight and body condition score (BCS) could be useful additions to both national- and herd-breeding programs. Although recording live weight and BCS is not technologically arduous, data available for use in routine genetic evaluations are generally lacking. The objective of the present study was to explore the usefulness of routinely recorded data, namely linear type traits (which also included BCS but only assessed visually) and carcass traits in the pursuit of genetic evaluations for both live weight and BCS in dairy cows. The data consisted of on-farm records of live weight and BCS (assessed using both visual and tactile cues) from 33,242 dairy cows in 201 commercial Irish herds. These data were complemented with information on 6 body-related linear type traits (i.e., stature, angularity, chest width, body depth, BCS, and rump width) and 3 cull cow carcass measures (i.e., carcass weight, conformation, and fat cover) on a selection of these animals plus close relatives. (Co)variance components were estimated using animal linear mixed models. The genetic correlation between the type traits stature, angularity, body depth, chest width, rump width, and visually-assessed BCS with live weight was 0.68, ?0.28, 0.43, 0.64, 0.61, and 0.44, respectively. The genetic correlation between angularity and BCS measured on farm (based on both visual and tactile appraisal) was ?0.79; the genetic and phenotypic correlation between BCS assessed visually as part of the linear assessment with BCS assessed by producers using both tactile and visual cues was 0.90 and 0.27, respectively. The genetic (phenotypic) correlation between cull cow carcass weight and live weight was 0.81 (0.21), and the genetic (phenotypic) correlation between cull cow carcass fat cover and BCS assessed on live cows was 0.44 (0.12). Estimated breeding values (EBV) for live weight and BCS in a validation population of cows were generated using a multitrait evaluation with observations for just the type traits, just the carcass traits, and both the type traits and carcass traits; the EBV were compared with the respective live weight and BCS phenotypic observations. The regression of phenotypic live weight on its EBV from the multitrait evaluations was 1.00 (i.e., the expectation) when the EBV was generated using just linear type trait data, but less than 1 (0.83) when using just carcass data. However, the regression changed across parities and stages of lactation. The partial correlation (after adjusting for contemporary group, parity by stage of lactation, heterosis, and recombination loss) between phenotypic live weight and EBV for live weight estimated using the 3 different scenarios (i.e., type only, carcass only, type plus carcass) ranged from 0.38 to 0.43. Although the prediction of phenotypic BCS from its respective EBV was relatively good when using just the linear type trait data (regression coefficient of 0.83 with a partial correlation of 0.22), the predictive ability of BCS EBV based on just carcass data was poor and should not be used. Overall, linear type trait data are a useful source of information to predict live weight and BCS with minimal additional predictive value from also including carcass data. Nonetheless, in the absence of linear type trait data, information on carcass traits can be useful in predicting genetic merit for mature cow live weight. Prediction of cow BCS from cow carcass data is not recommended.     

Probing Cell‐Type‐Specific Intracellular Nanoscale Barriers Using Size‐Tuned Quantum Dots

The compartmentalization of size‐tuned luminescent semiconductor nanocrystal quantum dots (QDs) in four distinctive cell lines, which would be representative of the most likely environmental exposure routes to nanoparticles in humans, is studied. The cells are fixed and permeabilized prior to the addition of the QDs, thus eliminating any cell‐membrane‐associated effects due to active QD uptake mechanisms or to specificity of signaling routes in different cell types, but leaving intact the putative physical subcellular barriers. All quantitative assays are performed using a high content analysis (HCA) platform, thereby obtaining robust data on large cell populations. While smaller QDs 2.1 nm in diameter enter the nuclei and localize to the nucleoli in all cell types, the rate and dynamics of their passage vary depending on the cell origin. As the QD size is increased to 4.4 nm, penetration into the cell is reduced but each cell line displays its own cutoff size thresholds reflecting cell‐type‐determined cytoplasmic and nuclear pore penetration specificity. These results give rise to important considerations regarding the differential compartmentalization and susceptibility of organs, tissues, and cells to nanoparticles, and may be of prime importance for biomedical imaging and drug‐delivery research employing nanoparticle‐based probes and systems.