Functional and structural dissection of the tape measure protein of lactococcal phage TP901-1

The tail tape measure protein (TMP) of tailed bacteriophages (also called phages) dictates the tail length and facilitates DNA transit to the cell cytoplasm during infection. Here, a thorough mutational analysis of the TMP from lactococcal phage TP901-1 (TMPTP901-1) was undertaken. We generated 56 mutants aimed at defining TMPTP901-1 domains that are essential for tail assembly and successful infection. Through analysis of the derived mutants, we determined that TP901-1 infectivity requires the N-terminal 154 aa residues, the C-terminal 60 residues and the first predicted hydrophobic region of TMPTP901-1 as a minimum. Furthermore, the role of TMPTP901-1 in tail length determination was visualized by electron microscopic imaging of TMP-deletion mutants. The inverse linear correlation between the extent of TMPTP901-1-encoding gene deletions and tail length of the corresponding virion provides an estimate of TMPTP901-1 regions interacting with the connector or involved in initiator complex formation. This study represents the most thorough characterisation of a TMP from a Gram-positive host-infecting phage and provides essential advances to understanding its role in virion assembly, morphology and infection.

L’analyse biomécanique du sprint sur ergomètre non-motorisé : interaction entre les asymétries cinétiques et cinématiques lors d’un sprint de 40 verges

Au sprint 100 mètres et dans de nombreux sport de puissance, la phase d’accélération est un déterminant majeure de la performance. Toutefois, les asymétries cinétiques et cinématiques peuvent avoir une incidence sur la performance. L’objectif de cette étude était d’identifier la présence d’interaction entre différentes variables cinétiques et cinématiques angulaires aux membres inférieures (MI) d’un sprint de haute intensité sur un ergomètre non-motorisé avec résistance (NMR). Suite à une rencontre de familiarisation, 11 sujets ont exécuté des sprints de 40 verges. Les données cinétiques ont été obtenues par l’entremise de plateformes de force intégrées aux appuis de l’ergomètre NMR à 10 Hz et les données cinématiques ont été amassées à l’aide du système Optitrack et du logiciel Motive Tracker à 120Hz. Nous avons effectué un test de corrélation linéaire (Corrélation linéaire de Pearson) pour déterminer la relation entre les données cinétiques et cinématiques (p < 0,05). L’analyse des données a révélée (1) une corrélation positive entre la moyenne d’amplitude articulaire à la cheville et la moyenne des pics de puissance développés (W/kg) lors de la phase de maintien (r = 0,62), (2) une corrélation négative entre l’extension maximale moyenne (calculé à partir de l’angle de flexion le plus petit) à la hanche et la moyenne de pics de puissance développées en fin de poussée lors de la totalité et de la phase de maintien (r = -0,63 et r = -0,69 respectivement), et finalement (3) une corrélation négative entre la différence de dorsiflexion maximale à la cheville et la différence des pics de puissance développés aux MI lors du contact du pied au sol en phase de maintien ( r = -0,62). Les résultats obtenus dans cette étude permettront d’améliorer l’intervention des préparateurs physiques et la pratique des athlètes de sport de puissance en plus d’aider au développant de nouvelles technologies et outils d’entrainement complémentaire au sprint et particulièrement à la phase d’accélération.

Correlation between metal-ceramic bond strength and coefficient of linear thermal expansion difference

The purpose of this study was to evaluate the metal-ceramic bond strength (MCBS) of 6 metal-ceramic pairs (2 Ni-Cr alloys and 1 Pd-Ag alloy with 2 dental ceramics) and correlate the MCBS values with the differences between the coefficients of linear thermal expansion (CTEs) of the metals and ceramics. Verabond (VB) Ni-Cr-Be alloy, Verabond II (VB2), Ni-Cr alloy, Pors-on 4 (P), Pd-Ag alloy, and IPS (I) and Duceram (D) ceramics were used for the MCBS test and dilatometric test. Forty-eight ceramic rings were built around metallic rods (3.0 mm in diameter and 70.0 mm in length) made from the evaluated alloys. The rods were subsequently embedded in gypsum cast in order to perform a tensile load test, which enabled calculating the CMBS. Five specimens (2.0 mm in diameter and 12.0 mm in length) of each material were made for the dilatometric test. The chromel-alumel thermocouple required for the test was welded into the metal test specimens and inserted into the ceramics. ANOVA and Tukey's test revealed significant differences (p=0.01) for the MCBS test results (MPa), with PI showing higher MCBS (67.72) than the other pairs, which did not present any significant differences. The CTE (10-6 oC-1) differences were: VBI (0.54), VBD (1.33), VB2I (-0.14), VB2D (0.63), PI (1.84) and PD (2.62). Pearson's correlation test (r=0.17) was performed to evaluate of correlation between MCBS and CTE differences. Within the limitations of this study and based on the obtained results, there was no correlation between MCBS and CTE differences for the evaluated metal-ceramic pairs.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Exact tests for correlation and for the slope in simple linear regressions without making assumptions

We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.

Correlation between Accurate Electron Density and Linear Optical Properties in Amino Acid Derivatives: L-Histidinium Hydrogen Oxalate

The accurate electron density and linear optical properties of L-histidinium hydrogen oxalate are discussed. Two high-resolution single crystal X-ray diffraction experiments were performed and compared with density functional calculations in the solid state as well as in the gas phase. The crystal packing and the hydrogen bond network are accurately investigated using topological analysis based on quantum theory of atoms in molecules, Hirshfeld surface analysis, and electrostatic potential mapping. The refractive indices are computed from couple perturbed Kohn-Sham calculations and measured experimentally. Moreover, distributed atomic polarizabilities are used to analyze the origin of the linear susceptibility in the crystal, in order to separate molecular and intermolecular causes. The optical properties are also correlated with the electron density distribution. This compound also offers the possibility to test the electron density building block approach for material science and different refinement schemes for accurate positions and displacement parameters of hydrogen atoms, in the absence of neutron diffraction data.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Correlation between carbon isotope discrimination and transpiration efficiency in lines of the C-4 species Sorghum bicolor in the glasshouse and the field

Transpiration efficiency, W, the ratio of plant carbon produced to water transpired and carbon isotope discrimination of leaf dry matter, Delta(d)' were measured together on 30 lines of the C-4 species, Sorghum bicolor in the glasshouse and on eight lines grown in the field. In the glasshouse, the mean W observed was 4.9 mmol C mol(-1) H2O and the range was 0.8 mmol C mol(-1) H2O The mean Delta(d) was 3.0 parts per thousand and the observed range was 0.4 parts per thousand. In the field, the mean W was lower at 2.8 mmol C mol H2O and the mean Delta(d) was 4.6 parts per thousand. Significant positive correlations between W and Delta(d) were observed for plants grown in the glasshouse and in the field. The observed correlations were consistent with theory, opposite to those for C-4 species, and showed that variation in Delta(d) was an integrated measure of long-term variation in the ratio of intercellular to ambient CO2 partial pressure, p(i)/p(a). Detailed gas exchange measurements of carbon isotope discrimination during CO2 uptake, Delta(A) and p(i)/p(a) were made on leaves of eight S. bicolor lines. The observed relationship between Delta(A) and p(i)/p(a) was linear with a negative slope of 3.7 parts per thousand in Delta(A) for a unit change in p(i)/p(a). The slope of this linear relationship between Delta(A) and p(i)/p(a) in C-4 species is dependent on the leakiness of the CO2 concentrating mechanism of the C pathway, We estimated the leakiness (defined as the fraction of CO2 released in the bundle sheath by C-4 acid decarboxylations, which is lost by leakage) to be 0.2. We conclude that, although variation in Delta(d) observed in the 30 lines of S. bicolor is smaller than that commonly observed in C-4 species, it also reflects variation in transpiration efficiency, W. Among the eight lines examined in detail and in the environments used, there was considerable genotype x environment interaction.

Correlation between macular and retinal nerve fibre layer Fourier-domain OCT measurements and visual field loss in chiasmal compression

Purpose The aim of this study was to test the correlation between Fourier-domain (FD) optical coherence tomography (OCT) macular and retinal nerve fibre layer (RNFL) thickness and visual field (VF) loss on standard automated perimetry (SAP) in chiasmal compression. Methods A total of 35 eyes with permanent temporal VF defects and 35 controls underwent SAP and FD-OCT (3D OCT-1000; Topcon Corp.) examinations. Macular thickness measurements were averaged for the central area and for each quadrant and half of that area, whereas RNFL thickness was determined for six sectors around the optic disc. VF loss was estimated in six sectors of the VF and in the central 16 test points in the VF. The correlation between VF loss and OCT measurements was tested with Spearman`s correlation coefficients and with linear regression analysis. Results Macular and RNFL thickness parameters correlated strongly with SAP VF loss. Correlations were generally stronger between VF loss and quadrantic or hemianopic macular thickness than with sectoral RNFL thickness. For the macular parameters, we observed the strongest correlation between macular thickness in the inferonasal quadrant and VF loss in the superior temporal central quadrant (rho=0.78; P<0.001) whereas for the RNFL parameters the strongest correlation was observed between the superonasal optic disc sector and the central temporal VF defect (rho=0.60; P<0.001).

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Correlation of fungi and endotoxin with PM2.5 and meteorological parameters in atmosphere of Sao Paulo, Brazil

Particulate matter, especially PM2.5, is associated with increased morbidity and mortality from respiratory diseases. Studies that focus on the chemical composition of the material are frequent in the literature, but those that characterize the biological fraction are rare. The objectives of this study were to characterize samples collected in Sao Paulo, Brazil on the quantity of fungi and endotoxins associated with PM2.5, correlating with the mass of particulate matter, chemical composition and meteorological parameters. We did that by Principal Component Analysis (PCA) and multiple linear regressions. The results have shown that fungi and endotoxins represent significant portion of PM2.5, reaching average concentrations of 772.23 spores mu g(-1) of PM2.5 (SD: 400.37) and 5.52 EU mg(-1) of PM2.5 (SD: 4.51 EU mg(-1)), respectively. Hyaline basidiospores, Cladosporium and total spore counts were correlated to factor Ba/Ca/Fe/Zn/K/Si of PM2.5 (p < 0.05). Genera Pen/Asp were correlated to the total mass of PM2.5 (p < 0.05) and colorless ascospores were correlated to humidity (p < 0.05). Endotoxin was positively correlated with the atmospheric temperature (p < 0.05). This study has shown that bioaerosol is present in considerable amounts in PM2.5 in the atmosphere of Sao Paulo, Brazil. Some fungi were correlated with soil particle resuspension and mass of particulate matter. Therefore, the relative contribution of bioaerosol in PM2.5 should be considered in future studies aimed at evaluating the clinical impact of exposure to air pollution. (C) 2010 Elsevier Ltd. All rights reserved.

Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.