Continuum model for chiral induced spin selectivity in helical molecules

A minimal model is exactly solved for electron spin transport on a helix. Electron transport is assumed to be supported by well oriented $p_z$ type orbitals on base molecules forming a staircase of definite chirality. In a tight binding interpretation, the SOC opens up an effective $\pi_z-\pi_z$ coupling via interbase $p_{x,y}-p_z$ hopping, introducing spin coupled transport. The resulting continuum model spectrum shows two Kramers doublet transport channels with a gap proportional to the SOC. Each doubly degenerate channel satisfies time reversal symmetry, nevertheless, a bias chooses a transport direction and thus selects for spin orientation. The model predicts which spin orientation is selected depending on chirality and bias, changes in spin preference as a function of input Fermi level and scattering suppression protected by the SO gap. We compute the spin current with a definite helicity and find it to be proportional to the torsion of the chiral structure and the non-adiabatic Aharonov- Anandan phase. To describe room temperature transport we assume that the total transmission is the result of a product of coherent steps limited by the coherence length

Globalización y competitividad económica en las ciudades de la región Centro Occidente de México en la última década del siglo XX

Peer Reviewe

Morphology evolution of thermally annealed polycrystalline thin films

Investigation of the morphology evolution of annealed polycrystalline Au(111) films by atomic force microscopy and x-ray diffraction leads to a continuous model that correlates such an evolution to local interactions between grains triggering different mechanisms of stress accommodation (grain zipping and shear strain) and relaxation (gap filling and grain rotation). The model takes into consideration findings concerning the in-plane reorientation of the grains during the coalescence to provide a comprehensive picture of the grain-size dependence of the interactions (underlying the origin of the growth stress in polycrystalline systems); and in particular it sheds light on the postcoalescence compressive stress as a consequence of the kinetic limitations for the reorientation of larger surface structuresThis paper was supported by the projects F1-54173 (bilateral program CSIC-Conacyt) 200960I182 (CSIC), and CCG10-UAM/MAT-5537 (DGUI-Comunidad de Madrid and Universidad Aut´onoma deMadrid). A.G.G. acknowledges the financial support of the MICINN Spanish Ministry under the project ESP2006-14282-C02-0

General Non-equilibrium Theory of Colloid Dynamics

A non-equilibrium extension of Onsager's canonical theory of thermal fluctuations is employed to derive a self-consistent theory for the description of the statistical properties of the instantaneous local concentration profile n(r,t) of a colloidal liquid in terms of the coupled time evolution equations of its mean value n(r,t) and of the covariance {\sigma}(r,r';t) \equiv of its fluctuations {\delta}n(r, t) = n(r, t) - n(r, t). These two coarse-grained equations involve a local mobility function b(r, t) which, in its turn, is written in terms of the memory function of the two-time correlation function C(r, r' ; t, t') \equiv <{\delta}n(r, t){\delta}n(r',t')>. For given effective interactions between colloidal particles and applied external fields, the resulting self-consistent theory is aimed at describing the evolution of a strongly correlated colloidal liquid from an initial state with arbitrary mean and covariance n^0(r) and {\sigma}^0(r,r') towards its equilibrium state characterized by the equilibrium local concentration profile n^(eq)(r) and equilibrium covariance {\sigma}^(eq)(r,r'). This theory also provides a general theoretical framework to describe irreversible processes associated with dynamic arrest transitions, such as aging, and the effects of spatial heterogeneities

Mapping networks of anti-HIV drug cocktails vs. AIDS epidemiology in the US counties

[Abstract] The implementation of the highly active antiretroviral therapy (HAART) and the combination of anti-HIV drugs have resulted in longer survival and a better quality of life for the people infected with the virus. In this work, a method is proposed to map complex networks of AIDS prevalence in the US counties, incorporating information about the chemical structure, molecular target, organism, and results in preclinical protocols of assay for all drugs in the cocktail. Different machine learning methods were trained and validated to select the best model. The Shannon information invariants of molecular graphs for drugs, and social networks of income inequality were used as input. The nodes in molecular graphs represent atoms weighed by Pauling electronegativity values, and the links correspond to the chemical bonds. On the other hand, the nodes in the social network represent the US counties and have Gini coefficients as weights. We obtained the data about anti-HIV drugs from the ChEMBL database and the data about AIDS prevalence and Gini coefficient from the AIDSVu database of Emory University. Box–Jenkins operators were used to measure the shift with respect to average behavior of drugs from reference compounds assayed with/in a given protocol, target, or organism. To train/validate the model and predict the complex network, we needed to analyze 152,628 data points including values of AIDS prevalence in 2310 counties in the US vs. ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4856 protocols, and 10 possible experimental measures. The best model found was a linear discriminant analysis (LDA) with accuracy, specificity, and sensitivity above 0.80 in training and external validation series.Ministerio de Educación, Cultura y Deportes; AGL2011-30563-C03-0

Serum proteomics of active tuberculosis patients and contacts reveals unique processes activated during Mycobacterium tuberculosis infection.

Tuberculosis (TB) is the most lethal infection among infectious diseases. The specific aim of this study was to establish panels of serum protein biomarkers representative of active TB patients and their household contacts who were either infected (LTBI) or uninfected (EMI-TB Discovery Cohort, Pontevedra Region, Spain). A TMT (Tamdem mass tags) 10plex-based quantitative proteomics study was performed in quintuplicate containing a total of 15 individual serum samples per group. Peptides were analyzed in an LC-Orbitrap Elite platform, and raw data were processed using Proteome Discoverer 2.1. A total of 418 proteins were quantified. The specific protein signature of active TB patients was characterized by an accumulation of proteins related to complement activation, inflammation and modulation of immune response and also by a decrease of a small subset of proteins, including apolipoprotein A and serotransferrin, indicating the importance of lipid transport and iron assimilation in the progression of the disease. This signature was verified by the targeted measurement of selected candidates in a second cohort (EMI-TB Verification Cohort, Maputo Region, Mozambique) by ELISA and nephelometry techniques. These findings will aid our understanding of the complex metabolic processes associated with TB progression from LTBI to active disease