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Analisi storiografica dei rapporti fra diritto (romano) ed economia fra il XIX e il XXI secolo, affrontata seguendo l’accidentato percorso di quei pochi studiosi – giuristi o economisti di formazione – che, nello stesso torno di tempo, hanno tentato in vario modo di usare gli strumenti concettuali della scienza economica per l’analisi delle fonti giuridiche

Aggregated tau protein is associated with over 20 neurological disorders, which include Alzheimer's disease. Previous work has shown that tau's sequence segments VQIINK and VQIVYK drive its aggregation, but inhibitors based on the structure of the VQIVYK segment only partially inhibit full-length tau aggregation and are ineffective at inhibiting seeding by full-length fibrils. Here we show that the VQIINK segment is the more powerful driver of tau aggregation. Two structures of this segment determined by the cryo-electron microscopy method micro-electron diffraction explain its dominant influence on tau aggregation. Of practical significance, the structures lead to the design of inhibitors that not only inhibit tau aggregation but also inhibit the ability of exogenous full-length tau fibrils to seed intracellular tau in HEK293 biosensor cells into amyloid. We also raise the possibility that the two VQIINK structures represent amyloid polymorphs of tau that may account for a subset of prion-like strains of tau.

Aggregated tau protein is associated with over 20 neurological disorders, which include Alzheimer's disease. Previous work has shown that tau's sequence segments VQIINK and VQIVYK drive its aggregation, but inhibitors based on the structure of the VQIVYK segment only partially inhibit full-length tau aggregation and are ineffective at inhibiting seeding by full-length fibrils. Here we show that the VQIINK segment is the more powerful driver of tau aggregation. Two structures of this segment determined by the cryo-electron microscopy method micro-electron diffraction explain its dominant influence on tau aggregation. Of practical significance, the structures lead to the design of inhibitors that not only inhibit tau aggregation but also inhibit the ability of exogenous full-length tau fibrils to seed intracellular tau in HEK293 biosensor cells into amyloid. We also raise the possibility that the two VQIINK structures represent amyloid polymorphs of tau that may account for a subset of prion-like strains of tau.

Analisi storiografica dei rapporti fra diritto (romano) ed economia fra il XIX e il XXI secolo, affrontata seguendo l’accidentato percorso di quei pochi studiosi – giuristi o economisti di formazione – che, nello stesso torno di tempo, hanno tentato in vario modo di usare gli strumenti concettuali della scienza economica per l’analisi delle fonti giuridiche

The implementation of a database of digitised mammograms is discussed. The digitised images were collected beginning in 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals as a first step in developing and implementing a computer-aided detection (CAD) system. All 3,369 mammograms were collected from 967 patients and classified according to lesion type and morphology, breast tissue and pathology type. A dedicated graphical user interface was developed to visualise and process mammograms to support the medical diagnosis directly on a high-resolution screen. The database has been the starting point for developing other medical imaging applications, such as a breast CAD, currently being upgraded and optimised for use in a distributed environment with grid services, in the framework of the Instituto Nazionale di Fisicia Nucleare (INFN)-funded Medical Applications on a Grid Infrastructure Connection (MAGIC)-5 project.

In this work a comparison of different classification methods for the identification of mass lesions in digitized mammograms is performed. These methods, used in order to develop Computer Aided Detection (CAD) systems, have been implemented in the framework of the MAGIC-5 Collaboration. The system for identification of mass lesions is based on a three-step procedure: a) preprocessing and segmentation, b) region of interest (ROI) searching, c) feature extraction and classification. It was tested on a very large mammographic database (3369 mammographic images from 967 patients). Each ROI is characterized by eight features extracted from a co-occurrence matrix containing spatial statistics information on the ROI pixel grey tones.

Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic)curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting masses in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration (Medical Applications on a Grid Infrastructure Connection). A reduction of the whole image's area under investigation is achieved through a segmentation process, by means of a ROI Hunter algorithm, without loss of meaningful information. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters. Once the features are computed for each ROI, they are used as inputs to a supervised neural network with momentum. The output neuron provides the probability that the ROI is pathological or not. Results are provided in terms of ROC and FROC curves: the area under the ROC curve was found to be A Z =0.862plusmn0.007, and we get a 2.8 FP/Image at a sensitivity of 82%. This software is included in the CAD station actually working in the hospitals belonging to the MAGIC-5 Collaboration

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, an alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) the training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features extracted from co-occurrence matrix containing spatial statistics information on ROI pixel grey tones. A dissimilarity representation of these features is made before the classification. A feed-forward neural network is employed to distinguish pathological records, from nonpathological ones by the new features. The results obtained in terms of sensitivity and specificity will be presented.

In this paper we investigate the feasibility of some typical techniques of pattern recognition for the classification of medical examples. The learning of the classifiers is not made in the traditional features space but it can be made by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) the training samples. Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features extracted from co-occurrence matrix containing spatial statistics information on ROI pixel gray tones. A dissimilarity representation of these features is made before the classification. A Feed-Forward Neural Network (FF-NN), a K-Nearest Neighbour (K-NN) and a Linear Discriminant Analysis (LDA) are employed to distinguish pathological records from not-pathological ones by the new features. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of healthy ROIs correctly classified) will be comparatively presented. The K-NN classifier gives slightly better results than FF-NN and LDA accuracy (percentage of cases correctly classified) on two-classes problem (pathologic or healthy patients).

The structure of pig pancreatic alpha-amylase has been determined by X-ray diffraction analysis using multiple isomorphous replacement in a crystal of space group P2(1)2(1)2(1) (a = 70.6 A, b = 114.8 A, c = 118.8 A) containing nearly 75% solvent. The structure was refined by simulated annealing and Powell minimization, as monitored by 2Fo-Fc difference Fourier syntheses, to a conventional R of 0.168 at 2.1 A resolution. The final model consists of all 496 amino acid residues, a chloride and a calcium ion, 145 water molecules and an endogenous disaccharide molecule that contiguously links protein molecules related by the 2(1) crystallographic operator along x. The protein is composed of a large domain (amino acid residues 1 to 403) featuring a central alpha ta-barrel of eight parallel strands and connecting helices with a prominent excursion between strand beta 3 and helix alpha 3 (amino acid residues 100 to 168). The final 93 amino acid residues at the carboxyl terminus form a second small domain consisting of a compact Greek key beta-barrel. The domains are tightly associated through hydrophobic interfaces. The beta 3/alpha 3 excursion and portions of the central alpha/beta-barrel provide four protein ligands to the tightly bound Ca ion; three water molecules complete the coordination. The Cl- ion is bound within one end of the alpha/beta-barrel by two arginine residues in a manner suggesting a plausible mechanism for its allosteric activation of the enzyme. A crystalline complex of the pancreatic alpha-amylase with alpha-cyclodextrin, a cyclic substrate analog of six glucose residues, reveals, in difference Fourier maps, three unique binding sites. One of the alpha-cyclodextrin sites is near the center of the long polysaccharide binding cleft that traverses one end of the alpha/beta-barrel, another is at the extreme of this cleft. By symmetry this can also be considered as two half sites located at the extremes of the active site cleft. This latter alpha-cyclodext

The structure of pig pancreatic alpha-amylase has been determined by X-ray diffraction analysis using multiple isomorphous replacement in a crystal of space group P2(1)2(1)2(1) (a = 70.6 A, b = 114.8 A, c = 118.8 A) containing nearly 75% solvent. The structure was refined by simulated annealing and Powell minimization, as monitored by 2Fo-Fc difference Fourier syntheses, to a conventional R of 0.168 at 2.1 A resolution. The final model consists of all 496 amino acid residues, a chloride and a calcium ion, 145 water molecules and an endogenous disaccharide molecule that contiguously links protein molecules related by the 2(1) crystallographic operator along x. The protein is composed of a large domain (amino acid residues 1 to 403) featuring a central alpha ta-barrel of eight parallel strands and connecting helices with a prominent excursion between strand beta 3 and helix alpha 3 (amino acid residues 100 to 168). The final 93 amino acid residues at the carboxyl terminus form a second small domain consisting of a compact Greek key beta-barrel. The domains are tightly associated through hydrophobic interfaces. The beta 3/alpha 3 excursion and portions of the central alpha/beta-barrel provide four protein ligands to the tightly bound Ca ion; three water molecules complete the coordination. The Cl- ion is bound within one end of the alpha/beta-barrel by two arginine residues in a manner suggesting a plausible mechanism for its allosteric activation of the enzyme. A crystalline complex of the pancreatic alpha-amylase with alpha-cyclodextrin, a cyclic substrate analog of six glucose residues, reveals, in difference Fourier maps, three unique binding sites. One of the alpha-cyclodextrin sites is near the center of the long polysaccharide binding cleft that traverses one end of the alpha/beta-barrel, another is at the extreme of this cleft. By symmetry this can also be considered as two half sites located at the extremes of the active site cleft. This latter alpha-cyclodext

The crystalline complex of pancreatic ribonuclease (RNase) with oligomers of d(pA)4 has been solved by x-ray diffraction methods and refined by standard procedures to a conventional crystallographic R factor of 0.22 at 2.5 angstrom resolution. The asymmetric unit is a complex of one RNase molecule associated with four d(pA)4 oligomers. Although the DNA in this complex is segmented, and therefore shows some discontinuities, it nevertheless traces a continuous path 12 nucleotides in length that passes through the active site cleft of the enzyme and over the surface of the protein. The DNA makes a series of eight to nine electrostatic bonds between its phosphate groups and lysine and arginine residues on the protein, as well as specific chemical interactions at the active site. The path described by the sequence of nucleotides is likely to be that taken by an extended polynucleotide chain when it is bound by the enzyme.

Twenty-one soluble proteins, five tRNAs, and three protein-nucleic acid complexes were studied in a systematic manner with regard to their crystallization behavior from polyethylene glycol and ammonium sulfate solutions in the presence of 0 to 1.5% beta-octyl glucoside. Our observations suggest that this neutral detergent does influence in a very positive way the growth characteristics of the macromolecules included in this experiment. In general, more reproducible and rapid growth was noted with an increased number of large individual crystals at the expense of microcrystals. In several cases, new crystal forms were discovered. Selected x-ray diffraction analyses imply that crystals grown in the presence of beta-octyl glucoside diffract as well or better than those grown in its absence. In addition, a screen of two proteins grown in the presence of 14 different common detergents suggested that a general detergent effect may be beneficial for the growth of crystals of biological macromolecules.

The major extracellular protein of Penicillium cyclopium has been isolated from its culture media and purified by ammonium sulfate fractionation, gel, and ion-exchange chromatography. We show this secreted protein to be endopeptidase. The molecular weight is approximately 32,000, the pI is 5.0, and the pH optimum using a variety of protein and synthetic substrates is around 7.0. Inhibition studies show that the protease is not inhibited by pepstatin nor by p-chloromercuribenzoic acid, indicating, respectively, that it is not an aspartyl protease nor a thiol protease. Complete inhibition is observed, however, with phenylmethanesulfonyl fluoride. Three crystal forms suitable for high resolution x-ray diffraction studies have been obtained from this purified protease with reflections being observed to well beyond 3.0 A resolution. One form having a needle morphology is of the orthorhombic crystal class and has space group P2(1)2(1)2(1). The unit cell dimensions are a = 41.9 A, b = 43.2 A, and c = 111.5 A with 1 molecule of the protease occurring in the asymmetric unit. The second form grown at pH values less than 6.0 has a plate morphology, is of orthorhombic space group P2(1)2(1)2(1), and has unit cell dimensions a = 59.12 A, b = 62.33 A, and c = 70.62 A. The third form is polyhedral in habit, is also of space group P2(1)2(1)2(1), and appears when the pH of the mother liquor is greater than 7.0. The cell dimensions of this crystal form are a = 57.07 A, b = 58.82 A, c = 70.79 A, and again there is 1 molecule/asymmetric unit. Three-dimensional structural analysis by x-ray diffraction is now underway. All crystal forms are somewhat denser than the norm having mass to volume ratios of 1.58, 2.00, and 1.85 A3/dalton, respectively.

The major extracellular protein of Penicillium cyclopium has been isolated from its culture media and purified by ammonium sulfate fractionation, gel, and ion-exchange chromatography. We show this secreted protein to be endopeptidase. The molecular weight is approximately 32,000, the pI is 5.0, and the pH optimum using a variety of protein and synthetic substrates is around 7.0. Inhibition studies show that the protease is not inhibited by pepstatin nor by p-chloromercuribenzoic acid, indicating, respectively, that it is not an aspartyl protease nor a thiol protease. Complete inhibition is observed, however, with phenylmethanesulfonyl fluoride. Three crystal forms suitable for high resolution x-ray diffraction studies have been obtained from this purified protease with reflections being observed to well beyond 3.0 A resolution. One form having a needle morphology is of the orthorhombic crystal class and has space group P2(1)2(1)2(1). The unit cell dimensions are a = 41.9 A, b = 43.2 A, and c = 111.5 A with 1 molecule of the protease occurring in the asymmetric unit. The second form grown at pH values less than 6.0 has a plate morphology, is of orthorhombic space group P2(1)2(1)2(1), and has unit cell dimensions a = 59.12 A, b = 62.33 A, and c = 70.62 A. The third form is polyhedral in habit, is also of space group P2(1)2(1)2(1), and appears when the pH of the mother liquor is greater than 7.0. The cell dimensions of this crystal form are a = 57.07 A, b = 58.82 A, c = 70.79 A, and again there is 1 molecule/asymmetric unit. Three-dimensional structural analysis by x-ray diffraction is now underway. All crystal forms are somewhat denser than the norm having mass to volume ratios of 1.58, 2.00, and 1.85 A3/dalton, respectively.

Twenty-one soluble proteins, five tRNAs, and three protein-nucleic acid complexes were studied in a systematic manner with regard to their crystallization behavior from polyethylene glycol and ammonium sulfate solutions in the presence of 0 to 1.5% beta-octyl glucoside. Our observations suggest that this neutral detergent does influence in a very positive way the growth characteristics of the macromolecules included in this experiment. In general, more reproducible and rapid growth was noted with an increased number of large individual crystals at the expense of microcrystals. In several cases, new crystal forms were discovered. Selected x-ray diffraction analyses imply that crystals grown in the presence of beta-octyl glucoside diffract as well or better than those grown in its absence. In addition, a screen of two proteins grown in the presence of 14 different common detergents suggested that a general detergent effect may be beneficial for the growth of crystals of biological macromolecules.

The crystalline complex of pancreatic ribonuclease (RNase) with oligomers of d(pA)4 has been solved by x-ray diffraction methods and refined by standard procedures to a conventional crystallographic R factor of 0.22 at 2.5 angstrom resolution. The asymmetric unit is a complex of one RNase molecule associated with four d(pA)4 oligomers. Although the DNA in this complex is segmented, and therefore shows some discontinuities, it nevertheless traces a continuous path 12 nucleotides in length that passes through the active site cleft of the enzyme and over the surface of the protein. The DNA makes a series of eight to nine electrostatic bonds between its phosphate groups and lysine and arginine residues on the protein, as well as specific chemical interactions at the active site. The path described by the sequence of nucleotides is likely to be that taken by an extended polynucleotide chain when it is bound by the enzyme.