Geometrical Description of Quantum Mechanics - Transformations and Dynamics

In this paper we review a proposed geometrical formulation of quantum mechanics. We argue that this geometrization makes available mathematical methods from classical mechanics to the quantum frame work. We apply this formulation to the study of separability and entanglement for states of composite quantum systems.Comment: 22 pages, to be published in Physica Script

Protein structure analysis through Hough Transform and Range Tree

The Generalized Hough Transform (GHT) allows to recognize general patterns once defined a model to be recognized, a reference point (RP) rigid with the model, and a mapping rule. This rule establishes the contributions in the parameters space; this space, generally speaking, is given by the parameters of a rigid motion leading to overlap a model item with an equal item detected on the unknown pattern. In this paper we introduce the GHT applied to motifs, domains and entire proteins retrieval into a protein data base. The spatial attitude of a single protein secondary structure (SS) constitutes the item supporting the contributions. If the unknown pattern contains a block of N SS of the model to be recognized, the N corresponding votes will have a common point, so accumulating N contributions. An analysis of the neighborhoods around the areas with high contributions density is necessary. It is not sufficient and often inaccurate to limit the analysis to the peaks even if the number of contribution is closed to the expected one. Both convenient data structures for effectively operating in the neighborhoods (a range tree data structure) and suitable decision criteria have been introduced. Preliminary results of comparative analysis are given

Physical properties of Ce3-xTe4 below room temperature

The physical properties of polycrystalline Ce3-xTe4 were investigated by measurements of the thermoelectric properties, Hall coefficient, heat capacity, and magnetization. The fully-filled, metallic x=0 compound displays a soft ferromagnetic transition near 4K, and analysis of the corresponding heat capacity anomaly suggests a doublet ground state for Ce^{3+}. The transition is suppressed to below 2K in the insulating x=0.33 composition, revealing that magnetic order in Ce3-xTe4 is driven by an RKKY-type interaction. The thermoelectric properties trend with composition as expected from simple electron counting, and the transport properties in Ce3Te4 are observed to be similar to those in La3Te4. Trends in the low temperature thermal conductivity data reveal that the phonons are efficiently scattered by electrons, while all compositions examined have a lattice thermal conductivity near 1.2W/m/K at 200K.Comment: Submitted to Phys. Rev.

A data structure for protein-ligand morphological matching

Pattern recognition techniques can be applied very profitably to proteomics because of the strong linkage of the protein’s molecule morphology and proteins functionalities. In fact, geometric and topological congruence (concavity and convexity correspondences) can be often considered certainly not sufficient but in many cases necessary conditions. In this connection, considering that the “active sites” are always located in one of the biggest concavities (in one of the largest “pockets”) and that the ligand must match this concavity, its effective part must be mainly convex. For this reason, the matching potential can be evaluated through an Extended Gaussian Image (EGI) shape representation. The original EGI, and a few extensions (namely Complex EGI and Enriched Complex EGI) representations and their correspondent concrete data-structures are here discussed. This data structure is then exploited for the implementation and evaluation of the matching stance between the small ligand molecule and a pocket of a protein macromolecule

Domain wall displacement in Py square ring for single nanometric magnetic bead detection

A new approach based on the domain wall displacement in confined ferromagnetic nanostructures for attracting and sensing a single nanometric magnetic particles is presented. We modeled and experimentally demonstrated the viability of the approach using an anisotropic magnetoresistance device made by a micron-size square ring of Permalloy designed for application in magnetic storage. This detection concept can be suitable to biomolecular recognition, and in particular to single molecule detection.Comment: 8pages, 3figure

Protein Gaussian Image (PGI): A protein structural representation based on the spatial attitude of secondary structure

A well-known shape representation usually applied for 3D object recognition is the Extended Gaussian Image (EGI) which maps the histogram of the orientations of the object surface on the unitary sphere. We propose to adopt an analogous “abstract” data-structure named Protein Gaussian Image (PNM) for representing the orientation of the protein secondary structures (e.g. helices or strands) which combines the characteristics of the EGI and the ones of needle maps. The “concrete” data structures is the same as for the EGI, with a hierarchy that starting with a discretization corresponding to the 20 orientations of the icosahedron facets, it is iteratively refined with a factor 4 at each new level (80, 320, 1280, . . . ) up to the maximum precision required. However, in this case to each orientation does not correspond the area of the patches having that orientation but the features of the protein secondary structures having that direction. Among the features we may include the versus (origin versus surface or vice versa), the length of the structure (e.g. the number of amino acids), biochemical properties, and even the sequence of the amino acids (stored as a list). We consider this representation very effective for a preliminary screening when looking in a protein data base for retrieval of a given structural block, or a domain, or even an entire protein. In fact, on this structure it is possible to identify the presence of a given motif, or also sheets (note that parallel or anti-parallel β-sheets are characterized by common or opposite directions of ladders). Herewith some known proteins are described with common typical motifs easily marked in the PGI

The Geometric Phase and Ray Space Isometries

We study the behaviour of the geometric phase under isometries of the ray space. This leads to a better understanding of a theorem first proved by Wigner: isometries of the ray space can always be realised as projections of unitary or anti-unitary transformations on the Hilbert space. We suggest that the construction involved in Wigner's proof is best viewed as an use of the Pancharatnam connection to ``lift'' a ray space isometry to the Hilbert space.Comment: 17 pages, Latex file, no figures, To appear in Pramana J. Phy

Targeting the gut to treat multiple sclerosis

The gut-brain axis (GBA) refers to the complex interactions between the gut microbiota and the nervous, immune, and endocrine systems, together linking brain and gut functions. Perturbations of the GBA have been reported in people with multiple sclerosis (pwMS), suggesting a possible role in disease pathogenesis and making it a potential therapeutic target. While research in the area is still in its infancy, a number of studies revealed that pwMS are more likely to exhibit altered microbiota, altered levels of short chain fatty acids and secondary bile products, and increased intestinal permeability. However, specific microbes and metabolites identified across studies and cohorts vary greatly. Small clinical and preclinical trials in pwMS and mouse models, in which microbial composition was manipulated through the use of antibiotics, fecal microbiota transplantation, and probiotic supplements, have provided promising outcomes in preventing CNS inflammation. However, results are not always consistent, and large-scale randomized controlled trials are lacking. Herein, we give an overview of how the GBA could contribute to MS pathogenesis, examine the different approaches tested to modulate the GBA, and discuss how they may impact neuroinflammation and demyelination in the CNS