Input data quality control for NDNQI national comparative statistics and quarterly reports: A contrast of three robust scale estimators for multiple outlier detection

ABSTRACT: BACKGROUND: To evaluate institutional nursing care performance in the context of national comparative statistics (benchmarks), approximately one in every three major healthcare institutions (over 1,800 hospitals) across the United States, have joined the National Database for Nursing Quality Indicators[REGISTERED SIGN] (NDNQI[REGISTERED SIGN]). With over 18,000 hospital units contributing data for nearly 200 quantitative measures at present, a reliable and efficient input data screening for all quantitative measures for data quality control is critical to the integrity, validity, and on-time delivery of NDNQI reports. METHODS: With Monte Carlo simulation and quantitative NDNQI indicator examples, we compared two ad-hoc methods using robust scale estimators, Inter Quartile Range (IQR) and Median Absolute Deviation from the Median (MAD), to the classic, theoretically-based Minimum Covariance Determinant (FAST-MCD) approach, for initial univariate outlier detection. RESULTS: While the theoretically based FAST-MCD used in one dimension can be sensitive and is better suited for identifying groups of outliers because of its high breakdown point, the ad-hoc IQR and MAD approaches are fast, easy to implement, and could be more robust and efficient, depending on the distributional property of the underlying measure of interest. CONCLUSION: With highly skewed distributions for most NDNQI indicators within a short data screen window, the FAST-MCD approach, when used in one dimensional raw data setting, could overestimate the false alarm rates for potential outliers than the IQR and MAD with the same pre-set of critical value, thus, overburden data quality control at both the data entry and administrative ends in our setting.     

Enhanced dark field microscopy for rapid artifact-free detection of nanoparticle binding to Candida albicans cells and hyphae

We surveyed a panel of 13 metal nanoparticle (NP) catalysts for their antifungal activities against Candida albicans ATCC 90028. Initial characterization using scanning electron microscopy (SEM) suggested that our ability to detect NP binding to Candida surfaces with this method was impeded by preparation artifacts. As an alternative method for visualizing NP binding, we used an enhanced dark field illumination system (CytoViva®) attached to a standard light microscope. When viewed using this system, all NP produced intense optical signals due to resonant light scattering. To assay binding, NP were allowed to interact with C. albicans hyphae and cells in spent RPMI broth for 15 min with gentle inversion, followed by viewing with the CytoViva® system. The antifungal efficacy of NP preparations was determined separately using a 24-h broth microdilution test. For single-metal NP, observations of binding at 15 min made via CytoViva® corresponded to antifungal efficacy at 24 h, with the most antifungal NP yielding complete coverage of hyphal surfaces. Our work suggests the utility of visual screening using the CytoViva® system for rapid, simple and artifact-free viewing of NP-cell interactions in support of antimicrobial screening efforts. This approach provides a quick and accessible alternative to SEM for imaging of NP-cell interactions.     

A network model of early events in epidermal growth factor receptor signaling that accounts for combinatorial complexity

We consider a model of early events in signaling by the epidermal growth factor (EGF) receptor (EGFR). The model includes EGF, EGFR, the adapter proteins Grb2 and Shc, and the guanine nucleotide exchange factor Sos, which is activated through EGF-induced formation of EGFR-Grb2-Sos and EGFR-Shc-Grb2-Sos assemblies at the plasma membrane. The protein interactions involved in signaling can potentially generate a diversity of protein complexes and phosphoforms; however, this diversity has been largely ignored in models of EGFR signaling. Here, we develop a model that accounts more fully for potential molecular diversity by specifying rules for protein interactions and then using these rules to generate a reaction network that includes all chemical species and reactions implied by the protein interactions. We obtain a model that predicts the dynamics of 356 molecular species, which are connected through 3749 unidirectional reactions. This network model is compared with a previously developed model that includes only 18 chemical species but incorporates the same scope of protein interactions. The predictions of this model are reproduced by the network model, which also yields new predictions. For example, the network model predicts distinct temporal patterns of autophosphorylation for different tyrosine residues of EGFR. A comparison of the two models suggests experiments that could lead to mechanistic insights about competition among adapter proteins for EGFR binding sites and the role of EGFR monomers in signal transduction.     

Isolation and identification of eight microsatellite loci in the Cherokee darter (Etheostoma scotti) and their variability in other members of the genera Etheostoma, Ammocrypta, and Percina

The Cherokee darter Etheostoma scotti is a federally threatened fish endemic to the Etowah River system of northwest Georgia. In order to analyse the population structure and genetic diversity of this fish, eight tetranucleotide microsatellite genetic markers were developed. The marker set was applied to 13 additional darter species to test cross-species amplification and polymorphism. Successful amplification was obtained for all eight loci in each of the 13 other species of darters, with between seven and eight polymorphic loci per species.     

Assessing the generality of global leaf trait relationships

Global-scale quantification of relationships between plant traits gives insight into the evolution of the world's vegetation, and is crucial for parameterizing vegetation-climate models. A database was compiled, comprising data for hundreds to thousands of species for the core 'leaf economics' traits leaf lifespan, leaf mass per area, photosynthetic capacity, dark respiration, and leaf nitrogen and phosphorus concentrations, as well as leaf potassium, photosynthetic N-use efficiency (PNUE), and leaf N : P ratio. While mean trait values differed between plant functional types, the range found within groups was often larger than differences among them. Future vegetation-climate models could incorporate this knowledge. The core leaf traits were intercorrelated, both globally and within plant functional types, forming a 'leaf economics spectrum'. While these relationships are very general, they are not universal, as significant heterogeneity exists between relationships fitted to individual sites. Much, but not all, heterogeneity can be explained by variation in sample size alone. PNUE can also be considered as part of this trait spectrum, whereas leaf K and N : P ratios are only loosely related.     

Systems genetic analysis of multivariate response to iron deficiency in mice

The aim of this study was to identify genes that influence iron regulation under varying dietary iron availability. Male and female mice from 20+ BXD recombinant inbred strains were fed iron-poor or iron-adequate diets from weaning until 4 mo of age. At death, the spleen, liver, and blood were harvested for the measurement of hemoglobin, hematocrit, total iron binding capacity, transferrin saturation, and liver, spleen and plasma iron concentration. For each measure and diet, we found large, strain-related variability. A principal-components analysis (PCA) was performed on the strain means for the seven parameters under each dietary condition for each sex, followed by quantitative trait loci (QTL) analysis on the factors. Compared with the iron-adequate diet, iron deficiency altered the factor structure of the principal components. QTL analysis, combined with PosMed (a candidate gene searching system) published gene expression data and literature citations, identified seven candidate genes, Ptprd, Mdm1, Picalm, lip1, Tcerg1, Skp2, and Frzb based on PCA factor, diet, and sex. Expression of each of these is cis-regulated, significantly correlated with the corresponding PCA factor, and previously reported to regulate iron, directly or indirectly. We propose that polymorphisms in multiple genes underlie individual differences in iron regulation, especially in response to dietary iron challenge. This research shows that iron management is a highly complex trait, influenced by multiple genes. Systems genetics analysis of iron homeostasis holds promise for developing new methods for prevention and treatment of iron deficiency anemia and related diseases.     

Gene Order of Encephalomyocarditis Virus as Determined by Studies with Pactamycin

Previous work has shown that translation of the encephalomyocarditis (EMC) viral ribonucleic acid (RNA) generates at least three primary products, polypeptides A, F, and C. The A and C polypeptides then undergo post-translational cleavages to complete the production of the stable viral polypeptides (delta, beta, gamma, alpha, G, I, F, H, and E). In this communication we show that A, F, and C are produced in equimolar amounts giving further support to the theory that the RNA of picornaviruses has only a single site for the initiation of protein synthesis. The biosynthesis of viral proteins in EMC virus-infected HeLa cells was studied in the presence of pactamycin at concentrations which preferentially inhibit the initiation of protein synthesis. The amount of each polypeptide formed during the residual period of protein synthesis observed after the addition of pactamycin was used as a criterion for ordering the genes on the viral RNA. The results obtained indicate that the primary gene products are ordered on the EMC viral RNA 5' --> 3' A-F-C and that the stable products are ordered delta-beta-gamma-alpha-G-I-F-H-E. Moreover, the intermediate chains B and epsilon map in the capsid region, whereas the intermediate chain D maps in the E region. This order is largely consistent with previously established relationships of the viral polypeptides and thus indicates that pactamycin is a valid tool for "genetic" mapping of polycistronic RNA molecules with single initiation sites.