Fermi surface renormalization in Hubbard ladders

We derive the one-loop renormalization equations for the shift in the Fermi-wavevectors for one-dimensional interacting models with four Fermi-points (two left and two right movers) and two Fermi velocities v_1 and v_2. We find the shift to be proportional to (v_1-v_2)U^2, where U is the Hubbard-U. Our results apply to the Hubbard ladder and to the t_1-t_2 Hubbard model. The Fermi-sea with fewer particles tends to empty. The stability of a saddle point due to shifts of the Fermi-energy and the shift of the Fermi-wavevector at the Mott-Hubbard transition are discussed.Comment: 5 pages, 4 Postscript figure

A Simulation Method for the Computation of the E

We propose a set of numerical methods for the computation of the frequency-dependent eff ective primary wave velocity of heterogeneous rocks. We assume the rocks' internal microstructure is given by micro-computed tomography images. In the low/medium frequency regime, we propose to solve the acoustic equation in the frequency domain by a Finite Element Method (FEM). We employ a Perfectly Matched Layer to truncate the computational domain and we show the need to repeat the domain a su cient number of times to obtain accurate results. To make this problem computationally tractable, we equip the FEM with non-fitting meshes and we precompute multiple blocks of the sti ffness matrix. In the high-frequency range, we solve the eikonal equation with a Fast Marching Method. Numerical results con rm the validity of the proposed methods and illustrate the e ffect of density, porosity, and the size and distribution of the pores on the e ective compressional wave velocity

Early Science with the Large Millimeter Telescope: an energy-driven wind revealed by massive molecular and fast X-ray outflows in the Seyfert Galaxy IRAS 17020+4544

We report on the coexistence of powerful gas outflows observed in millimeter and X-ray data of the Radio-Loud Narrow Line Seyfert 1 Galaxy IRAS 17020+4544. Thanks to the large collecting power of the Large Millimeter Telescope, a prominent line arising from the 12CO(1-0) transition was revealed in recent observations of this source. The complex profile is composed by a narrow double-peak line and a broad wing. While the double-peak structure may be arising in a disk of molecular material, the broad wing is interpreted as the signature of a massive outflow of molecular gas with an approximate bulk velocity of -660 km/s. This molecular wind is likely associated to a multi-component X-ray Ultra-Fast Outflow with velocities reaching up to ~0.1c and column densities in the range 10^{21-23.9} cm^-2 that was reported in the source prior to the LMT observations. The momentum load estimated in the two gas phases indicates that within the observational uncertainties the outflow is consistent with being propagating through the galaxy and sweeping up the gas while conserving its energy. This scenario, which has been often postulated as a viable mechanism of how AGN feedback takes place, has so far been observed only in ULIRGs sources. IRAS 17020+4544 with bolometric and infrared luminosity respectively of 5X10^{44} erg/s and 1.05X10^{11} L_sun appears to be an example of AGN feedback in a NLSy1 Galaxy (a low power AGN). New proprietary multi-wavelength data recently obtained on this source will allow us to corroborate the proposed hypothesis.Comment: Accepted for publication on ApJ Letters, 9 pages, 4 figure

Bayesian analysis of the association between casein complex haplotype variants and milk yield, composition, and curve shape parameters in murciano-granadina goats

Considering casein haplotype variants rather than SNPs may maximize the understanding of heritable mechanisms and their implication on the expression of functional traits related to milk production. Effects of casein complex haplotypes on milk yield, milk composition, and curve shape parameters were used using a Bayesian inference for ANOVA. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized into 86 haplotypes. The Ali and Schaeffer model was chosen as the best fitting model for milk yield (Kg), protein, fat, dry matter, and lactose (%), while parabolic yield-density was chosen as the best fitting model for somatic cells count (SCC × 103 sc/mL). Peak and persistence for all traits were computed respectively. Statistically significant differences (p < 0.05) were found for milk yield and components. However, no significant difference was found for any curve shape parameter except for protein percentage peak. Those haplotypes for which higher milk yields were reported were the ones that had higher percentages for protein, fat, dry matter, and lactose, while the opposite trend was described by somatic cells counts. Conclusively, casein complex haplotypes can be considered in selection strategies for economically important traits in dairy goats

Software-automatized individual lactation model fitting, peak and persistence and Bayesian criteria comparison for milk yield genetic studies in Murciano-Granadina goats

SPSS model syntax was defined and used to evaluate the individual performance of 49 linear and non-linear models to fit the lactation curve of 159 Murciano-Granadina goats selected for genotyping analyses. Lactation curve shape, peak and persistence were evaluated for each model using 3107 milk yield controls with an average of 3.78 ± 2.05 lactations per goat. Best fit (Adjusted R2) values (0.47) were reached by the five-parameter logarithmic model of Ali and Schaeffer. Three main possibilities were detected: non-fitting (did not converge), standard (Adjusted R2 over 75%) and atypical curves (Adjusted R2 below 75%). All the goats fitted for 38 models. The ability to fit different possible functional forms for each goat, which progressively increased with the number of parameters comprised in each model, translated into a higher sensitivity to explaining curve shape individual variability. However, for models for which all goats fitted, only moderate increases in explanatory and predictive potential (AIC, AICc or BIC) were found. The Ali and Schaeffer model reported the best fitting results to study the genetic variability behind goat milk yield and perhaps enhance the evaluation of curve parameters as trustable future selection criteria to face the future challenges offered by the goat dairy industry

Progress in the development of early diagnosis and a drug with unique pharmacology to improve cancer therapy

Cancer continues to be one of the major health and socio-economic problems worldwide, despite considerable efforts to improve its early diagnosis and treatment. The identification of new constituents as biomarkers for early diagnosis of neoplastic cells and the discovery of new type of drugs with their mechanistic actions are crucial to improve cancer therapy. New drugs have entered the market, thanks to industrial and legislative efforts ensuring continuity of pharmaceutical development. New targets have been identified, but cancer therapy and the anti-cancer drug market still partly depend on anti-mitotic agents. The objective of this paper is to show the effects of KAR-2, a potent anti-mitotic compound, and TPPP/p25, a new unstructured protein, on the structural and functional characteristics of the microtubule system. Understanding the actions of these two potential effectors on the microtubule system could be the clue for early diagnosis and improvement of cancer therapy

Cathepsin B-associated Activation of Amyloidogenic Pathway in Murine Mucopolysaccharidosis Type I Brain Cortex

Mucopolysaccharidosis type I (MPS I) is caused by genetic deficiency of alpha-l-iduronidase and impairment of lysosomal catabolism of heparan sulfate and dermatan sulfate. In the brain, these substrates accumulate in the lysosomes of neurons and glial cells, leading to neuroinflammation and neurodegeneration. Their storage also affects lysosomal homeostasis-inducing activity of several lysosomal proteases including cathepsin B (CATB). In the central nervous system, increased CATB activity has been associated with the deposition of amyloid plaques due to an alternative pro-amyloidogenic processing of the amyloid precursor protein (APP), suggesting a potential role of this enzyme in the neuropathology of MPS I. In this study, we report elevated levels of protein expression and activity of CATB in cortex tissues of 6-month-old MPS I (Idua -/- mice. Besides, increased CATB leakage from lysosomes to the cytoplasm of Idua -/- cortical pyramidal neurons was indicative of damaged lysosomal membranes. The increased CATB activity coincided with an elevated level of the 16-kDa C-terminal APP fragment, which together with unchanged levels of beta-secretase 1 was suggestive for the role of this enzyme in the amyloidogenic APP processing. Neuronal accumulation of Thioflavin-S-positive misfolded protein aggregates and drastically increased levels of neuroinflammatory glial fibrillary acidic protein (GFAP)-positive astrocytes and CD11b-positive activated microglia were observed in Idua -/- cortex by confocal fluorescent microscopy. Together, our results point to the existence of a novel CATB-associated alternative amyloidogenic pathway in MPS I brain induced by lysosomal storage and potentially leading to neurodegeneration

Virtual karyotyping with SNP microarrays reduces uncertainty in the diagnosis of renal epithelial tumors

<p>Abstract</p> <p>Background</p> <p>Renal epithelial tumors are morphologically, biologically, and clinically heterogeneous. Different morphologic subtypes require specific management due to markedly different prognosis and response to therapy. Each common subtype has characteristic chromosomal gains and losses, including some with prognostic value. However, copy number information has not been readily accessible for clinical purposes and thus has not been routinely used in the diagnostic evaluation of these tumors. This information can be useful for classification of tumors with complex or challenging morphology. 'Virtual karyotypes' generated using SNP arrays can readily detect characteristic chromosomal lesions in paraffin embedded renal tumors and can be used to correctly categorize the common subtypes with performance characteristics that are amenable for routine clinical use.</p> <p>Methods</p> <p>To investigate the use of virtual karyotypes for diagnostically challenging renal epithelial tumors, we evaluated 25 archived renal neoplasms where sub-classification could not be definitively rendered based on morphology and other ancillary studies. We generated virtual karyotypes with the Affymetrix 10 K 2.0 mapping array platform and identified the presence of genomic lesions across all 22 autosomes.</p> <p>Results</p> <p>In 91% of challenging cases the virtual karyotype unambiguously detected the presence or absence of chromosomal aberrations characteristic of one of the common subtypes of renal epithelial tumors, while immunohistochemistry and fluorescent in situ hybridization had no or limited utility in the diagnosis of these tumors.</p> <p>Conclusion</p> <p>These results show that virtual karyotypes generated by SNP arrays can be used as a practical ancillary study for the classification of renal epithelial tumors with complex or ambiguous morphology.</p