Cooperative Effects of Electron Donors and Acceptors for the Stabilization of Elusive Metal Cluster Frameworks: Synthesis and Solid-State Structures of Pt-19(CO)(24)(mu(4)-AuPPh3)(3)](-) and Pt-19(CO)(24){mu(4)-Au-2(PPh3)(2)}(2)]

The anionic cluster Pt-19(CO)(22)](4-) (1), of pentagonal symmetry, reacts with CO and AuPPh3+ fragments. Upon increasing the Au:Pt-19, molar ratio, different species are sequentially formed, but only the last two members of the series could be characterized by X-ray diffraction, namely, Pt-19(CO)(24)(mu(4)-AuPPh3)(3)](-) (2) and Pt-19(CO)(24){mu(4)-Au-2(PPh3)(2)}(2)] (3).The metallic framework of the starting cluster is completely modified after the addition of CO and AuL+, and both products display the same platinum core of trigonal symmetry, with closely packed metal atoms. The three AuL+ units cap three different square faces in 2, whereas four AuL+ fragments are grouped in two independent bimetallic units in the neutral cluster 3. Electrochemical and spectroelectrochemical studies on 2 showed that its redox ability is comparable with that of the homometallic 1.

A Near-Real-Time Automatic Orbit Determination System for COSMIC and Its Follow-On Satellite Mission: Analysis of Orbit and Clock Errors on Radio Occultation

The COSMIC-2 mission is a follow-on mission of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) with an upgraded payload for improved radio occultation (RO) applications. The objective of this paper is to develop a near-real-time (NRT) orbit determination system, called NRT National Chiao Tung University (NCTU) system, to support COSMIC-2 in atmospheric applications and verify the orbit product of COSMIC. The system is capable of automatic determinations of the NRT GPS clocks and LEO orbit and clock. To assess the NRT (NCTU) system, we use eight days of COSMIC data (March 24-31, 2011), which contain a total of 331 GPS observation sessions and 12 393 RO observable files. The parallel scheduling for independent GPS and LEO estimations and automatic time matching improves the computational efficiency by 64% compared to the sequential scheduling. Orbit difference analyses suggest a 10-cm accuracy for the COSMIC orbits from the NRT (NCTU) system, and it is consistent as the NRT University Corporation for Atmospheric Research (URCA) system. The mean velocity accuracy from the NRT orbits of COSMIC is 0.168 mm/s, corresponding to an error of about 0.051 μrad in the bending angle. The rms differences in the NRT COSMIC clock and in GPS clocks between the NRT (NCTU) and the postprocessing products are 3.742 and 1.427 ns. The GPS clocks determined from a partial ground GPS network [from NRT (NCTU)] and a full one [from NRT (UCAR)] result in mean rms frequency stabilities of 6.1E-12 and 2.7E-12, respectively, corresponding to range fluctuations of 5.5 and 2.4 cm and bending angle errors of 3.75 and 1.66 μrad .

Observation errors in early historical upper-air observations

Upper-air observations are a fundamental data source for global atmospheric data products, but uncertainties, particularly in the early years, are not well known. Most of the early observations, which have now been digitized, are prone to a large variety of undocumented uncertainties (errors) that need to be quantified, e.g., for their assimilation in reanalysis projects. We apply a novel approach to estimate errors in upper-air temperature, geopotential height, and wind observations from the Comprehensive Historical Upper-Air Network for the time period from 1923 to 1966. We distinguish between random errors, biases, and a term that quantifies the representativity of the observations. The method is based on a comparison of neighboring observations and is hence independent of metadata, making it applicable to a wide scope of observational data sets. The estimated mean random errors for all observations within the study period are 1.5 K for air temperature, 1.3 hPa for pressure, 3.0 ms−1for wind speed, and 21.4° for wind direction. The estimates are compared to results of previous studies and analyzed with respect to their spatial and temporal variability.

Toward a cognitive taxonomy of medical errors.

One critical step in addressing and resolving the problems associated with human errors is the development of a cognitive taxonomy of such errors. In the case of errors, such a taxonomy may be developed (1) to categorize all types of errors along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to explain why, and even predict when and where, a specific error will occur, and (4) to generate intervention strategies for each type of error. Based on Reason's (1992) definition of human errors and Norman's (1986) cognitive theory of human action, we have developed a preliminary action-based cognitive taxonomy of errors that largely satisfies these four criteria in the domain of medicine. We discuss initial steps for applying this taxonomy to develop an online medical error reporting system that not only categorizes errors but also identifies problems and generates solutions.

Mixing-cell boundary conditions and apparent mass balance errors for advective-dispersive solute transport

In many field or laboratory situations, well-mixed reservoirs like, for instance, injection or detection wells and gas distribution or sampling chambers define boundaries of transport domains. Exchange of solutes or gases across such boundaries can occur through advective or diffusive processes. First we analyzed situations, where the inlet region consists of a well-mixed reservoir, in a systematic way by interpreting them in terms of injection type. Second, we discussed the mass balance errors that seem to appear in case of resident injections. Mixing cells (MC) can be coupled mathematically in different ways to a domain where advective-dispersive transport occurs: by assuming a continuous solute flux at the interface (flux injection, MC-FI), or by assuming a continuous resident concentration (resident injection). In the latter case, the flux leaving the mixing cell can be defined in two ways: either as the value when the interface is approached from the mixing-cell side (MC-RT -), or as the value when it is approached from the column side (MC-RT +). Solutions of these injection types with constant or-in one case-distance-dependent transport parameters were compared to each other as well as to a solution of a two-layer system, where the first layer was characterized by a large dispersion coefficient. These solutions differ mainly at small Peclet numbers. For most real situations, the model for resident injection MC-RI + is considered to be relevant. This type of injection was modeled with a constant or with an exponentially varying dispersion coefficient within the porous medium. A constant dispersion coefficient will be appropriate for gases because of the Eulerian nature of the usually dominating gaseous diffusion coefficient, whereas the asymptotically growing dispersion coefficient will be more appropriate for solutes due to the Lagrangian nature of mechanical dispersion, which evolves only with the fluid flow. Assuming a continuous resident concentration at the interface between a mixing cell and a column, as in case of the MC-RI + model, entails a flux discontinuity. This flux discontinuity arises inherently from the definition of a mixing cell: the mixing process is included in the balance equation, but does not appear in the description of the flux through the mixing cell. There, only convection appears because of the homogeneous concentration within the mixing cell. Thus, the solute flux through a mixing cell in close contact with a transport domain is generally underestimated. This leads to (apparent) mass balance errors, which are often reported for similar situations and erroneously used to judge the validity of such models. Finally, the mixing cell model MC-RI + defines a universal basis regarding the type of solute injection at a boundary. Depending on the mixing cell parameters, it represents, in its limits, flux as well as resident injections. (C) 1998 Elsevier Science B.V. All rights reserved.

Can prospective usability evaluation predict data errors?

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance.

Further characterization of the epa gene cluster and Epa polysaccharides of Enterococcus faecalis.

We previously identified a gene cluster, epa (for enterocococcal polysaccharide antigen), involved in polysaccharide biosynthesis of Enterococcus faecalis and showed that disruption of epaB and epaE resulted in attenuation in translocation, biofilm formation, resistance to polymorphonuclear leukocyte (PMN) killing, and virulence in a mouse peritonitis model. Using five additional mutant disruptions in the 26-kb region between orfde2 and OG1RF_0163, we defined the epa locus as the area from epaA to epaR. Disruption of epaA, epaM, and epaN, like prior disruption of epaB and epaE, resulted in alteration in Epa polysaccharide content, more round cells versus oval cells with OG1RF, decreased biofilm formation, attenuation in a mouse peritonitis model, and resistance to lysis by the phage NPV-1 (known to lyse OG1RF), while mutants disrupted in orfde2 and OG1RF_163 (the epa locus flanking genes) behaved like OG1RF in those assays. Analysis of the purified Epa polysaccharide from OG1RF revealed the presence of rhamnose, glucose, galactose, GalNAc, and GlcNAc in this polysaccharide, while carbohydrate preparation from the epaB mutant did not contain rhamnose, suggesting that one or more of the glycosyl transferases encoded by the epaBCD operon are necessary to transfer rhamnose to the polysaccharide. In conclusion, the epa genes, uniformly present in E. faecalis strains and involved in biosynthesis of polysaccharide in OG1RF, are also important for OG1RF shape determination, biofilm formation, and NPV-1 replication/lysis, as well as for E. faecalis virulence in a mouse peritonitis model.

The origin of the 'Mycoplasma mycoides cluster' coincides with domestication of ruminants.

The 'Mycoplasma mycoides cluster' comprises the ruminant pathogens Mycoplasma mycoides subsp. mycoides the causative agent of contagious bovine pleuropneumonia (CBPP), Mycoplasma capricolum subsp. capripneumoniae the agent of contagious caprine pleuropneumonia (CCPP), Mycoplasma capricolum subsp. capricolum, Mycoplasma leachii and Mycoplasma mycoides subsp. capri. CBPP and CCPP are major livestock diseases and impact the agricultural sector especially in developing countries through reduced food-supply and international trade restrictions. In addition, these diseases are a threat to disease-free countries. We used a multilocus sequence typing (MLST) approach to gain insights into the demographic history of and phylogenetic relationships among the members of the 'M. mycoides cluster'. We collected partial sequences from seven housekeeping genes representing a total of 3,816 base pairs from 118 strains within this cluster, and five strains isolated from wild Caprinae. Strikingly, the origin of the 'M. mycoides cluster' dates to about 10,000 years ago, suggesting that the establishment and spread of the cluster coincided with livestock domestication. In addition, we show that hybridization and recombination may be important factors in the evolutionary history of the cluster.

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Identification of antigen-encoding genes of Enterococcus faecalis during human infections and characterization of a gene cluster for the biosynthesis of an antigenic polysaccharide

Genomic libraries of two Enterococcus faecalis strains, OG1RF and TX52 (an isolate from an endocarditis patient), were constructed in Escherichia coli and were screened with serum from a rabbit immunized with surface proteins of an E. faecalis endocarditis isolate and sera from four patients with enterococcal endocarditis. Thirty-eight immunopositive cosmid clones reacted with at least two of the patient sera and contained distinct inserts based on their DNA restriction patterns. These were chosen for further subcloning in a pBluescript SK ($-$) vector. Each sublibrary was screened with one of the five sera. Analysis of sequences from the immunopositive subclones revealed similarities to a range of proteins, including bacterial virulence factors, transporters, two-component regulators, metabolic enzymes, and membrane or cell surface proteins. Fourteen subclones did not show significant similarity to any sequence in the databases and may contain novel genes. Thirteen of the immunopositive cosmid clones did not yield immunopositive subclones and one such cosmid clone, TX5159, produced an antigenic polysaccharide in Escherichia coli. The insert of TX5159 was found to contain a multicistronic gene cluster containing genes similar to those involved in the biosynthesis and export of polysaccharides from both Gram-positive and Gram-negative organisms. Insertions in several genes within the cluster abolished the immunoreactivity of TX5159. RT-PCR of genes within the cluster with total RNA from OG1RF showed that these genes are transcribed. The polysaccharide was detected in two recently reported E. faecalis mucoid strains using specific antibody, but not in the other strains tested. This is the first report on a gene cluster of E. faecalis involved in the biosynthesis of an antigenic polysaccharide. ^

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

Improvement of antibiotic prescription in outpatient care: a cluster-randomized intervention study using a sentinel surveillance network of physicians.

OBJECTIVES To assess the effectiveness of implementing guidelines, coupled with individual feedback, on antibiotic prescribing behaviour of primary care physicians in Switzerland. METHODS One hundred and forty general practices from a representative Swiss sentinel network of primary care physicians participated in this cluster-randomized prospective intervention study. The intervention consisted of providing guidelines on treatment of respiratory tract infections (RTIs) and uncomplicated lower urinary tract infections (UTIs), coupled with sustained, regular feedback on individual antibiotic prescription behaviour during 2 years. The main aims were: (i) to increase the percentage of prescriptions of penicillins for all RTIs treated with antibiotics; (ii) to increase the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics; (iii) to decrease the percentage of quinolone prescriptions for all cases of exacerbated COPD (eCOPD) treated with antibiotics; and (iv) to decrease the proportion of sinusitis and other upper RTIs treated with antibiotics. The study was registered at ClinicalTrials.gov (NCT01358916). RESULTS While the percentage of antibiotics prescribed for sinusitis or other upper RTIs and the percentage of quinolones prescribed for eCOPD did not differ between the intervention group and the control group, there was a significant increase in the percentage of prescriptions of penicillins for all RTIs treated with antibiotics [57% versus 49%, OR = 1.42 (95% CI 1.08-1.89), P = 0.01] and in the percentage of trimethoprim/sulfamethoxazole prescriptions for all uncomplicated lower UTIs treated with antibiotics [35% versus 19%, OR = 2.16 (95% CI 1.19-3.91), P = 0.01] in the intervention group. CONCLUSIONS In our setting, implementing guidelines, coupled with sustained individual feedback, was not able to reduce the proportion of sinusitis and other upper RTIs treated with antibiotics, but increased the use of recommended antibiotics for RTIs and UTIs, as defined by the guidelines.

Assessment of patient setup errors in IGRT in combination with a six degrees of freedom couch

PURPOSE The range of patient setup errors in six dimensions detected in clinical routine for cranial as well as for extracranial treatments, were analyzed while performing linear accelerator based stereotactic treatments with frameless patient setup systems. Additionally, the need for re-verification of the patient setup for situations where couch rotations are involved was analyzed for patients treated in the cranial region. METHODS AND MATERIALS A total of 2185 initial (i.e. after pre-positioning the patient with the infrared system but before image guidance) patient setup errors (1705 in the cranial and 480 in the extracranial region) obtained by using ExacTrac (BrainLAB AG, Feldkirchen, Germany) were analyzed. Additionally, the patient setup errors as a function of the couch rotation angle were obtained by analyzing 242 setup errors in the cranial region. Before the couch was rotated, the patient setup error was corrected at couch rotation angle 0° with the aid of image guidance and the six degrees of freedom (6DoF) couch. For both situations attainment rates for two different tolerances (tolerance A: ± 0.5mm, ± 0.5°; tolerance B: ± 1.0 mm, ± 1.0°) were calculated. RESULTS The mean (± one standard deviation) initial patient setup errors for the cranial cases were -0.24 ± 1.21°, -0.23 ± 0.91° and -0.03 ± 1.07° for the pitch, roll and couch rotation axes and 0.10 ± 1.17 mm, 0.10 ± 1.62 mm and 0.11 ± 1.29 mm for the lateral, longitudinal and vertical axes, respectively. Attainment rate (all six axes simultaneously) for tolerance A was 0.6% and 13.1% for tolerance B, respectively. For the extracranial cases the corresponding values were -0.21 ± 0.95°, -0.05 ± 1.08° and -0.14 ± 1.02° for the pitch, roll and couch rotation axes and 0.15 ± 1.77 mm, 0.62 ± 1.94 mm and -0.40 ± 2.15 mm for the lateral, longitudinal and vertical axes. Attainment rate (all six axes simultaneously) for tolerance A was 0.0% and 3.1% for tolerance B, respectively. After initial setup correction and rotation of the couch to treatment position a re-correction has to be performed in 77.4% of all cases to fulfill tolerance A and in 15.6% of all cases to fulfill tolerance B. CONCLUSION The analysis of the data shows that all six axes of a 6DoF couch are used extensively for patient setup in clinical routine. In order to fulfill high patient setup accuracies (e.g. for stereotactic treatments), a 6DoF couch is recommended. Moreover, re-verification of the patient setup after rotating the couch is required in clinical routine.