Kazan Federal University

About: Kazan Federal University is a education organization based out in Kazan’, Russia. It is known for research contribution in the topics: Population & Chemistry. The organization has 9868 authors who have published 14390 publications receiving 135726 citations. The organization is also known as: Kazan (Volga region) Federal University & Kazan State University.

Planck 2013 results. IV. Low Frequency Instrument beams and window functions

Abstract: This paper presents the characterization of the in-flight beams, the beam window functions, and the associated uncertainties for the Planck Low Frequency Instrument (LFI). The structure of the paper is similar to that presented in the 2013 Planck release; the main differences concern the beam normalization and the delivery of the window functions to be used for polarization analysis. The in-flight assessment of the LFI main beams relies on measurements performed during observations of Jupiter. By stacking data from seven Jupiter transits, the main beam profiles are measured down to –25 dB at 30 and 44 GHz, and down to –30 dB at 70 GHz. It has been confirmed that the agreement between the simulated beams and the measured beams is better than 1% at each LFI frequency band (within the 20 dB contour from the peak, the rms values are 0.1% at 30 and 70 GHz; 0.2% at 44 GHz). Simulated polarized beams are used for the computation of the effective beam window functions. The error budget for the window functions is estimated from both main beam and sidelobe contributions, and accounts for the radiometer band shapes. The total uncertainties in the effective beam window functions are 0.7% and 1% at 30 and 44 GHz, respectively (at l ≈ 600); and 0.5% at 70 GHz (at l ≈ 1000).

Screening of Conditionally Reprogrammed Patient-Derived Carcinoma Cells Identifies ERCC3–MYC Interactions as a Target in Pancreatic Cancer

Abstract: Purpose: Even when diagnosed prior to metastasis, pancreatic ductal adenocarcinoma (PDAC) is a devastating malignancy with almost 90% lethality, emphasizing the need for new therapies optimally targeting the tumors of individual patients. Experimental Design: We first developed a panel of new physiologic models for study of PDAC, expanding surgical PDAC tumor samples in culture using short-term culture and conditional reprogramming with the Rho kinase inhibitor Y-27632, and creating matched patient-derived xenografts (PDX). These were evaluated for sensitivity to a large panel of clinical agents, and promising leads further evaluated mechanistically. Results: Only a small minority of tested agents was cytotoxic in minimally passaged PDAC cultures in vitro. Drugs interfering with protein turnover and transcription were among most cytotoxic. Among transcriptional repressors, triptolide, a covalent inhibitor of ERCC3, was most consistently effective in vitro and in vivo causing prolonged complete regression in multiple PDX models resistant to standard PDAC therapies. Importantly, triptolide showed superior activity in MYC-amplified PDX models and elicited rapid and profound depletion of the oncoprotein MYC, a transcriptional regulator. Expression of ERCC3 and MYC was interdependent in PDACs, and acquired resistance to triptolide depended on elevated ERCC3 and MYC expression. The Cancer Genome Atlas analysis indicates ERCC3 expression predicts poor prognosis, particularly in CDKN2A-null, highly proliferative tumors. Conclusions: This provides initial preclinical evidence for an essential role of MYC–ERCC3 interactions in PDAC, and suggests a new mechanistic approach for disruption of critical survival signaling in MYC-dependent cancers. Clin Cancer Res; 22(24); 6153–63. ©2016 AACR.

Carbon and nitrogen losses from soil depend on degradation of Tibetan Kobresia pastures

Abstract: Degradation of Kobresia pygmaea pastures has strongly increased on the Tibetan Plateau over the last few decades and contributed to a high loss of soil organic carbon and nutrients. The pathways of carbon (C) and nitrogen (N) losses from degraded K. pygmaea pastures are still unclear, but this is a prerequisite to assess the recovery of Tibetan grasslands. We investigated the response of dayand nighttime CO2 efflux and leaching of dissolved organic C and N, NH4 + and NO3 from K. pygmaea root mats in three degradation stages: living root mat, dying root mat and dead root mat. Dying root mat had the highest C loss as CO2 and as leached dissolved organic carbon. This indicates K. pygmaea pastures shift from a C sink to a C source following plant death. In contrast, living root mat had the lowest daytime CO2 efflux (0·38 ± 0·1μgC g 1 h ) because CO2 was assimilated via photosynthesis. Nighttime CO2 efflux positively correlated with soil moisture for living and dead root mats. It indicates that increasing precipitation might accelerate C losses due to enhanced soil organic carbon decomposition. Furthermore, dead root mat had the highest average NO3 loss (23 ± 2·6mgNL ) from leaching compared with other root mats. Consequently, leaching increases the negative impacts of pasture degradation on N availability in these often N limited ecosystems and thus impedes the recovery of K. pastures following degradation. Copyright © 2016 John Wiley & Sons, Ltd. key words: Kobresia pygmaea pasture; CO2 efflux; NO3 leaching; grassland degradation; dissolved organic carbon

How Rheumatoid Arthritis Can Result from Provocation of the Immune System by Microorganisms and Viruses

Abstract: The pathogenesis of rheumatoid arthritis (RA), similar to development of a majority of inflammatory and autoimmune disorders, is largely due to an inappropriate or inadequate immune response to environmental challenges. Among these challenges, infectious agents are the undisputed leaders. Since the 1870s, an impressive list of microorganisms suspected of provoking RA has formed, and the list is still growing. Although a definite causative link between a specific infectious agent and the disease has not been established, several arguments support such a possibility. First, in the absence of a defined pathogen, the spectrum of triggering agents may include polymicrobial communities or the cumulative effect of several bacterial/viral factors. Second, the range of infectious episodes (i.e. clinical manifestations caused by pathogens) may vary in the process of RA development from preclinical to late-stage disease. Third, infectious agents might not trigger RA in all cases, but trigger it in a certain subset of the cases, or the disease onset may arise from an unfortunate combination of infections along with, for example, psychological stress and/or chronic joint tissue microtrauma. Fourth, genetic differences may have a role in the disease onset. In this review, two aspects of the problem of “microorganisms and RA” are debated. First, is there an acquired immune deficiency and, in turn, susceptibility to infections in RA patients due to the too frequent and too lengthy infections, which at last break the tolerance of self antigens? Or, second, is there a congenital deficiency in tolerance and inflammation control, which may occur even with ordinary infection frequency and duration?

Healthcare Services Innovations Based on the State of the Art Technology Trend Industry 4.0

Abstract: The contextual compendium analysis presented in this paper focuses on the Industry 4.0 and healthcare services innovation that relate to it. The appraisal discerns the specific components of Industry 4.0 and their related innovations or contribution in the healthcare industry. The first component, Cyber-physical systems, has led to Medical Cyber-physical systems applied in different circumstance to improve the efficiency of service provision. The second component, Internet of Things, has brought with it expanded networks, biosensors, smart pharmaceuticals, and other artificial organs. The final component has inspired the integrated of Natural Language Processing model as a calm-system operating in the background to complete a host of the process that improves diagnoses among other service provision and assistance functions. Additionally, the paper discusses Cognitive Computing, mHealth, and eHealth as emerging medical fields that can benefit from Industry 4.0.