Crystallization and preliminary X-ray analysis of monalysin, a novel β-pore-forming toxin from the entomopathogen Pseudomonas entomophila.

Monalysin was recently described as a novel pore-forming toxin (PFT) secreted by the Drosophila pathogen Pseudomonas entomophila. Recombinant monalysin is multimeric in solution, whereas PFTs are supposed to be monomeric until target membrane association. Monalysin crystals were obtained by the hanging-drop vapour-diffusion method using PEG 8000 as precipitant. Preliminary X-ray diffraction analysis revealed that monalysin crystals belonged to the monoclinic space group C2, with unit-cell parameters a = 162.4, b = 146.2, c = 144.4 Å, β = 122.8°, and diffracted to 2.85 Å resolution using synchrotron radiation. Patterson self-rotation analysis and Matthews coefficient calculation indicate that the asymmetric unit contains nine copies of monalysin. Heavy-atom derivative data were collected and a Ta6Br14 cluster derivative data set confirmed the presence of ninefold noncrystallographic symmetry.

Good genes and good luck: Ammonoid diversity and the end-Permian mass extinction

The end-Permian mass extinction removed more than 80% of marine genera. Ammonoid cephalopods were among the organisms most affected by this crisis. The analysis of a global diversity data set of ammonoid genera covering about 106 million years centered on the Permian-Triassic boundary (PTB) shows that Triassic ammonoids actually reached levels of diversity higher than in the Permian less than 2 million years after the PTB. The data favor a hierarchical rather than logistic model of diversification coupled with a niche incumbency hypothesis. This explosive and nondelayed diversification contrasts with the slow and delayed character of the Triassic biotic recovery as currently illustrated for other, mainly benthic groups such as bivalves and gastropods.

Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects

Self-potential (SP) data are of interest to vadose zone hydrology because of their direct sensitivity to water flow and ionic transport. There is unfortunately little consensus in the literature about how to best model SP data under partially saturated conditions, and different approaches (often supported by one laboratory data set alone) have been proposed. We argue that this lack of agreement can largely be traced to electrode effects that have not been properly taken into account. A series of drainage and imbibition experiments were considered in which we found that previously proposed approaches to remove electrode effects were unlikely to provide adequate corrections. Instead, we explicitly modeled the electrode effects together with classical SP contributions using a flow and transport model. The simulated data agreed overall with the observed SP signals and allowed decomposing the different signal contributions to analyze them separately. After reviewing other published experimental data, we suggest that most of them include electrode effects that have not been properly taken into account. Our results suggest that previously presented SP theory works well when considering the modeling uncertainties presently associated with electrode effects. Additional work is warranted to not only develop suitable electrodes for laboratory experiments but also to assure that associated electrode effects that appear inevitable in longer term experiments are predictable, so that they can be incorporated into the modeling framework.

Comparative analysis of amino acid repeats in rodents and humans

Amino acid tandem repeats, also called homopolymeric tracts, are extremely abundant in eukaryotic proteins. To gain insight into the genome-wide evolution of these regions in mammals, we analyzed the repeat content in a large data set of rat-mouse-human orthologs. Our results show that human proteins contain more amino acid repeats than rodent proteins and that trinucleotide repeats are also more abundant in human coding sequences. Using the human species as an outgroup, we were able to address differences in repeat loss and repeat gain in the rat and mouse lineages. In this data set, mouse proteins contain substantially more repeats than rat proteins, which can be at least partly attributed to a higher repeat loss in the rat lineage. The data are consistent with a role for trinucleotide slippage in the generation of novel amino acid repeats. We confirm the previously observed functional bias of proteins with repeats, with overrepresentation of transcription factors and DNA-binding proteins. We show that genes encoding amino acid repeats tend to have an unusually high GC content, and that differences in coding GC content among orthologs are directly related to the presence/absence of repeats. We propose that the different GC content isochore structure in rodents and humans may result in an increased amino acid repeat prevalence in the human lineage.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Sensitivity to Change of the Ultrasound synovitis SONAR Score in RA Patients: Results of the Scqm Cohort

Background/Purpose: Since the end of 2009, an ultrasound scoring call SONAR has been implemented for RA patients as a routine tool in the SCQM registry (Swiss Clinical Quality Management registry for rheumatic diseases). A cross-sectional evaluation of patients with active disease and clinical remission according to the DAS28ESR and the novel ACR/EULAR remission criteria from 2010 clearly indicated a good correlational external validity of synovial pathologies with clinical disease activity in RA (2012 EULAR meeting. Objective: of this study was to evaluate the sensitivity to change of B-mode and Power-Doppler scores in a longitudinal perspective along with the changes in DAS28ESR in two consecutive visits among the patients included in the SCQM registry Methods: All patients who had at least two SONAR scores and simultaneous DAS28ESR evaluations between December 2009 and June 2012 were included in this study. The data came from 20 different operators working mostly in hospitals but also in private practices, who had received a previous teaching over 3 days in a reference center. The SONAR score includes a semi-quantitative B mode and Power-Doppler evaluation of 22 joints from 0 to 3, maximum 66 points for each score. The selection of these 22 joints was done in analogy to a 28 joint count and further restricted to joint regions with published standard ultrasound images. Both elbows and wrist joints were dynamically scanned from the dorsal and the knee joints from a longitudinal suprapatellar view in flexion and in joint extension. The bilateral evaluation of the second to fifth metacarpophalangeal and proximal interphalangeal joints was done from a palmar view in full extension, and the Power-Doppler scoring from a dorsal view with hand and finger position in best relaxation. Results: From the 657 RA patients with at least one score performed, 128 RA patients with 2 or more consultations of DAS28ESR, and a complete SONAR data set could be included. The mean (SD) time between the two evaluations was 9.6 months (54). The mean (SD) DAS28ESR was: 3.5 (1.3) at the first visit and was significantly lower (mean 3.0, SD.2.0, p:_0.0001) at the second visit. The mean (SD) of the total B mode was 12 (9.5) at baseline and 9.6 (7.6) at follow-up (p_0.0004). The Power-Doppler score at entry was 2.9 (5.7) and 1.9 (3.6), at the second visit, p _0.0001. The Pearson r correlation between change in DAS28ESR and the B mode was 0.44 (95% CI: 0.29, 0.57, p_ 0.0001),and 0.35 (95% CI: 0.16, 0.50, p _ 0.0002) for the Power-Doppler score,. Clinical relevant change in DAS (_1.1) was associated with a change of total B mode score _3 in 23/32 patients and a change a Doppler score _0.5 in 19/26. Conclusion: This study confirms that the SONAR score is sensitive to change and provides a complementary method of assessing RA disease activity to the DAS that could be very useful in daily practice.

Use of the Cognitive Performance Scale (CPS) to detect cognitive impairment in the acute care setting: concurrent and predictive validity.

The Cognitive Performance Scale (CPS) was initially designed to assess cognition in long term care residents. Subsequently, the CPS has also been used among in-home, post-acute, and acute care populations even though CPS' clinimetric performance has not been studied in these settings. This study aimed to determine CPS agreement with the Mini Mental Status Exam (MMSE) and its predictive validity for institutionalization and death in a cohort (N=401) of elderly medical inpatients aged 75 years and over. Medical, physical and mental status were assessed upon admission. The same day, the patient's nurse completed the CPS by interview. Follow-up data were gathered from the central billing system (nursing home stay) and proxies (death). Cognitive impairment was present in 92 (23%) patients according to CPS (score >or= 2). Agreement with MMSE was moderate (kappa 0.52, P<.001). Analysis of discordant results suggested that cognitive impairment was overestimated by the CPS in dependent patients with comorbidities and depressive symptoms, and underestimated in older ones. During follow-up, subjects with abnormal CPS had increased risks of death (adjusted hazard ratio (adjHR) 1.7, 95% CI 1.0-2.8, P=.035) and institutionalization (adjHR 2.7, 95% CI 1.3-5.3, P=.006), independent of demographic, health and functional status. Interestingly, subjects with abnormal CPS were at increased risk of death only if they also had abnormal MMSE. The CPS predicted death and institutionalization during follow-up, but correlated moderately well with the MMSE. Combining CPS and MMSE provided additional predictive information, suggesting that domains other than cognition are assessed by professionals when using the CPS in elderly medical inpatients.

La renda salarial a Osona. Estimació, distribució espacial i mesures de desigualtat

Aquest estudi analitza la distribució de la renda salarial a la comarca d’Osona, en comparació amb la resta de comarques de Catalunya i la seva distribució entre els municipis, utilitzant una base de dades original creada a partir de la informació sobre salaris de l’Enquesta d’Estructura Salarial i sobre la població dels censos de 1996 i 2001. La unitat espacial utilitzada, la secció censal, permet obtenir estimacions per als diferents àmbits geogràfics i calcular i descompondre índexs de desigualtat que mostren les característiques de les distribucions.

Investigation of Rapid Thermal Analysis Procedures for Prediction of the Service Life of PCCP Carbonate Coarse Aggregate, HR-337, 1993

The major objective of this research project was to use thermal analysis techniques in conjunction with x-ray analysis methods to identify and explain chemical reactions that promote aggregate related deterioration in portland cement concrete. Twenty-two different carbonate aggregate samples were subjected to a chemical testing scheme that included: • bulk chemistry (major, minor and selected trace elements) • bulk mineralogy (minor phases concentrated by acid extraction) • solid-solution in the major carbonate phases • crystallite size determinations for the major carbonate phases • a salt treatment study to evaluate the impact of deicer salts Test results from these different studies were then compared to information that had been obtained using thermogravimetric analysis techniques. Since many of the limestones and dolomites that were used in the study had extensive field service records it was possible to correlate many of the variables with service life. The results of this study have indicated that thermogravimetric analysis can play an important role in categorizing carbonate aggregates. In fact, with modern automated thermal analysis systems it should be possible to utilize such methods on a quality control basis. Strong correlations were found between several of the variables that were monitored in this study. In fact, several of the variables exhibited significant correlations to concrete service life. When the full data set was utilized (n = 18), the significant correlations to service life can be summarized as follows ( a = 5% level): • Correlation coefficient, r, = -0.73 for premature TG loss versus service life. • Correlation coefficient, r, = 0.74 for relative crystallite size versus service life. • Correlation coefficient, r, = 0.53 for ASTM C666 durability factor versus service life. • Correlation coefficient, r, = -0.52 for acid-insoluble residue versus service life. Separation of the carbonate aggregates into their mineralogical categories (i.e., calcites and dolomites) tended to increase the correlation coefficients for some specific variables (r sometimes approached 0.90); however, the reliability of such correlations was questionable because of the small number of samples that were present in this study.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa, Volume I: An Electronic Database for PIle LOad Tests (PILOT), TR-573, 2011

For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.

Simulated-annealing-based conditional simulation for the local-scale characterization of heterogeneous aquifers

Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

The 2010 May Flaring Episode of Cygnus X-3 in Radio, X-rays, and γ-rays

In 2009, Cygnus X-3 (Cyg X-3) became the first microquasar to be detected in the GeV γ-ray regime, via the satellites Fermi and AGILE. The addition of this new band to the observational toolbox holds promise for building a more detailed understanding of the relativistic jets of this and other systems. We present a rich data set of radio, hard and soft X-ray, and γ-ray observations of Cyg X-3 made during a flaring episode in 2010 May. We detect a ~3 day softening and recovery of the X-ray emission, followed almost immediately by a ~1 Jy radio flare at 15 GHz, followed by a 4.3σ γ-ray flare (E > 100 MeV) ~1.5 days later. The radio sampling is sparse, but we use archival data to argue that it is unlikely the γ-ray flare was followed by any significant unobserved radio flares. In this case, the sequencing of the observed events is difficult to explain in a model in which the γ-ray emission is due to inverse Compton scattering of the companion star's radiation field. Our observations suggest that other mechanisms may also be responsible for γ-ray emission from Cyg X-3.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.