How do technical change and technological distance influence the size of the Okun’s Law coefficient?

How does technical change influence the size of the Okun’s Law coefficient? Using a nonlinear version of Okun’s Law augmented with technical change and technological distance, we show that the impact of output movements on unemployment variations is influenced by the imitation or innovation origins of technical change

Une IgA à coefficient de sédimentation 11 S dans les sécrétions externes de l'espèce bovine

The sedimentation coefficient of a secretory IgA found in bovine colostrum and saliva is compared with that of IgG and IgM from the same colostrum. The IgA fraction gives a value of 10.8 S, whereas the major part of the IgG has a value of 7.1 S and the IgM 19.2 S. The sedimentation coefficient of the free secretory piece has also been determined: its value is 4.95 S.

Lipid composition of fingermark residue and donor classification using GC/MS

Lipids available in fingermark residue represent important targets for enhancement and dating techniques. While it is well known that lipid composition varies among fingermarks of the same donor (intra-variability) and between fingermarks of different donors (inter-variability), the extent of this variability remains uncharacterised. Thus, this worked aimed at studying qualitatively and quantitatively the initial lipid composition of fingermark residue of 25 different donors. Among the 104 detected lipids, 43 were reported for the first time in the literature. Furthermore, palmitic acid, squalene, cholesterol, myristyl myristate and myristyl myristoleate were quantified and their correlation within fingermark residue was highlighted. Ten compounds were then selected and further studied as potential targets for dating or enhancement techniques. It was shown that their relative standard deviation was significantly lower for the intra-variability than for the inter-variability. Moreover, the use of data pretreatments could significantly reduce this variability. Based on these observations, an objective donor classification model was proposed. Hierarchical cluster analysis was conducted on the pre-treated data and the fingermarks of the 25 donors were classified into two main groups, corresponding to "poor" and "rich" lipid donors. The robustness of this classification was tested using fingermark replicates of selected donors. 86% of these replicates were correctly classified, showing the potential of such a donor classification model for research purposes in order to select representative donors based on compounds of interest.

Composition of fingermark residue: a qualitative and quantitative review

This article describes the composition of fingermark residue as being a complex system with numerous compounds coming from different sources and evolving over time from the initial composition (corresponding to the composition right after deposition) to the aged composition (corresponding to the evolution of the initial composition over time). This complex system will additionally vary due to effects of numerous influence factors grouped in five different classes: the donor characteristics, the deposition conditions, the substrate nature, the environmental conditions and the applied enhancement techniques. The initial and aged compositions as well as the influence factors are thus considered in this article to provide a qualitative and quantitative review of all compounds identified in fingermark residue up to now. The analytical techniques used to obtain these data are also enumerated. This review highlights the fact that despite the numerous analytical processes that have already been proposed and tested to elucidate fingermark composition, advanced knowledge is still missing. Thus, there is a real need to conduct future research on the composition of fingermark residue, focusing particularly on quantitative measurements, aging kinetics and effects of influence factors. The results of future research are particularly important for advances in fingermark enhancement and dating technique developments.

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.

Variabilité intra/interobservateur du coefficient de diffusion apparente dans les lésions hépatiques malignes traitées

Objectifs : Le coefficient de diffusion apparente (ADC) est utilisé pour le suivi des lésions hépatiques malignes traitées. Cependant, l'ADC est généralement mesuré dans la lésion entière, alors que cela devrait être réalisé dans la zone la plus restreinte (ZLPR), cette dernière représentant potentiellement du résidu tumoral. Notre objectif était d'évaluer la variabilité inter/intraobservateur de l'ADC dans la tumeur entière et dans la ZLPR. Matériels et méthodes : Quarante patients traités par chimioembolisation ou radiofréquence ont été évalués. Après consensus, deux lecteurs ont indépendamment mesuré l'ADC de la lésion entière et de la ZLPR. Les mêmes mesures ont été répétées deux semaines plus tard. Le test de Spearman et la méthode de Bland-Altman ont été utilisées. Résultats : La corrélation interobservateur de l'ADC dans la lésion entière et dans la ZLPR était de 0,962 et de 0,884. La corrélation intraobservateur était de 0,992 et de 0,979, respectivement. Les limites de variabilité interobservateur (mm2/sec*10 - 3) étaient entre -0,25/+0,28 dans la lésion entière et entre -0,51/+0,46 dans la ZLPR. Les limites de variabilité intraobservateur étaient respectivement : -0,25/+0,24 et -0,43/+0,47. Conclusion : La corrélation inter/intraobservateur dans les mesures d'ADC est bonne. Toutefois, une variabilité limitée existe et doit être considérée lors de l'interprétation des valeurs d'ADC des tumeurs hépatiques.

Composition of fingermark residue: a qualitative and quantitative review

This article describes the composition of fingermark residue as being a complex system with numerous compounds coming from different sources and evolving over time from the initial composition (corresponding to the composition right after deposition) to the aged composition (corresponding to the evolution of the initial composition over time). This complex system will additionally vary due to effects of numerous influence factors grouped in five different classes: the donor characteristics, the deposition conditions, the substrate nature, the environmental conditions and the applied enhancement techniques. The initial and aged compositions as well as the influence factors are thus considered in this article to provide a qualitative and quantitative review of all compounds identified in fingermark residue up to now. The analytical techniques used to obtain these data are also enumerated. This review highlights the fact that despite the numerous analytical processes that have already been proposed and tested to elucidate fingermark composition, advanced knowledge is still missing. Thus, there is a real need to conduct future research on the composition of fingermark residue, focusing particularly on quantitative measurements, aging kinetics and effects of influence factors. The results of future research are particularly important for advances in fingermark enhancement and dating technique developments.

Probabilistic evidential assessment of gunshot residue particle evidence (Part II) : Bayesian parameter estimation for experimental count data.

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models - in the form of Bayesian networks - address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates useable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR).

Interobserver and intraobserver variability of the apparent diffusion coefficient in treated malignant hepatic lesions on a 3.0T machine: measurements in the whole lesion versus in the area with the most restricted diffusion.

PURPOSE: To assess the inter/intraobserver variability of apparent diffusion coefficient (ADC) measurements in treated hepatic lesions and to compare ADC measurements in the whole lesion and in the area with the most restricted diffusion (MRDA). MATERIALS AND METHODS: Twenty-five patients with treated malignant liver lesions were examined on a 3.0T machine. After agreeing on the best ADC image, two readers independently measured the ADC values in the whole lesion and in the MRDA. These measurements were repeated 1 month later. The Bland-Altman method, Spearman correlation coefficients, and the Wilcoxon signed-rank test were used to evaluate the measurements. RESULTS: Interobserver variability for ADC measurements in the whole lesion and in the MRDA was 0.17 x 10(-3) mm(2)/s [-0.17, +0.17] and 0.43 x 10(-3) mm(2)/s [-0.45, +0.41], respectively. Intraobserver limits of agreement could be as low as [-0.10, +0.12] 10(-3) mm(2)/s and [-0.20, +0.33] 10(-3) mm(2)/s for measurements in the whole lesion and in the MRDA, respectively. CONCLUSION: A limited variability in ADC measurements does exist, and it should be considered when interpreting ADC values of hepatic malignancies. This is especially true for the measurements of the minimal ADC.

Identification of a key lysine residue in heat shock protein 90 required for azole and echinocandin resistance in Aspergillus fumigatus.

Heat shock protein 90 (Hsp90) is an essential chaperone involved in the fungal stress response that can be harnessed as a novel antifungal target for the treatment of invasive aspergillosis. We previously showed that genetic repression of Hsp90 reduced Aspergillus fumigatus virulence and potentiated the effect of the echinocandin caspofungin. In this study, we sought to identify sites of posttranslational modifications (phosphorylation or acetylation) that are important for Hsp90 function in A. fumigatus. Phosphopeptide enrichment and tandem mass spectrometry revealed phosphorylation of three residues in Hsp90 (S49, S288, and T681), but their mutation did not compromise Hsp90 function. Acetylation of lysine residues of Hsp90 was recovered after treatment with deacetylase inhibitors, and acetylation-mimetic mutations (K27A and K271A) resulted in reduced virulence in a murine model of invasive aspergillosis, supporting their role in Hsp90 function. A single deletion of lysine K27 or an acetylation-mimetic mutation (K27A) resulted in increased susceptibility to voriconazole and caspofungin. This effect was attenuated following a deacetylation-mimetic mutation (K27R), suggesting that this site is crucial and should be deacetylated for proper Hsp90 function in antifungal resistance pathways. In contrast to previous reports in Candida albicans, the lysine deacetylase inhibitor trichostatin A (TSA) was active alone against A. fumigatus and potentiated the effect of caspofungin against both the wild type and an echinocandin-resistant strain. Our results indicate that the Hsp90 K27 residue is required for azole and echinocandin resistance in A. fumigatus and that deacetylase inhibition may represent an adjunctive anti-Aspergillus strategy.

Constant coefficient tests for random coefficient regression

Random coefficient regression models have been applied in differentfields and they constitute a unifying setup for many statisticalproblems. The nonparametric study of this model started with Beranand Hall (1992) and it has become a fruitful framework. In thispaper we propose and study statistics for testing a basic hypothesisconcerning this model: the constancy of coefficients. The asymptoticbehavior of the statistics is investigated and bootstrapapproximations are used in order to determine the critical values ofthe test statistics. A simulation study illustrates the performanceof the proposals.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.