One Amino Acid Change of Angiotensin II Diminishes Its Effects on Abdominal Aortic Aneurysm

Angiotensin (Ang) A is formed by the decarboxylation of the N terminal residue of AngII. The present study determined whether this one amino acid change impacted effects of AngII on abdominal aortic aneurysm (AAA) formation in mice. Computational analyses implicated that AngA had comparable binding affinity to both AngII type 1 and 2 receptors as AngII. To compare effects of these two octapeptides in vivo, male low-density lipoprotein receptor (Ldlr) or apolipoprotein E (Apoe) deficient mice were infused with either AngII or AngA (1 μg/kg/min) for 4 weeks. While AngII infusion induced AAA consistently in both mouse strains, the equivalent infusion rate of AngA did not lead to AAA formation. We also determined whether co-infusion of AngA would influence AngII-induced aortic aneurysm formation in male Apoe−/− mice. Co-infusion of the same infusion rate of AngII and AngA did not change AngII-induced AAA formation. Since it was reported that a 10-fold higher concentration of AngA elicited comparable vasoconstrictive responses as AngII, we compared a 10-fold higher rate (10 μg/kg/min) of AngA infusion into male Apoe−/− mice with AngII (1 μg/kg/min). This rate of AngA led to abdominal aortic dilation in three of ten mice, but no aortic rupture, whereas the 10-fold lower rate of AngII infusion led to abdominal aortic dilation or rupture in eight of ten mice. In conclusion, AngA, despite only being one amino acid different from AngII, has diminished effects on aortic aneurysmal formation, implicating that the first amino acid of AngII has important pathophysiological functions

Can China’s Growth be Sustained? A Productivity Perspective

China’s gradual approach to economic transition has resulted in sustained high growth. However, in recent years Chinese economists have increasingly referred to the growth pattern as “extensive,” generated mainly through the expansion of inputs. Our investigation of the Chinese economy during the reform period finds that reform measures often resulted in one-time level effects on total factor productivity (TFP). China now needs to adjust its reform program toward sustained increases in productivity. Market and ownership reforms, and open door policies have improved the conditions under which Chinese firms operate, but further institutional reforms are required to consolidate China’s move to a full-fledged market economy

Synergistic drug-cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicity

Idiosyncratic drug hepatotoxicity represents a major problem in drug development due to inadequacy of current preclinical screening assays, but recently established rodent models utilizing bacterial LPS co-administration to induce an inflammatory background have successfully reproduced idiosyncratic hepatotoxicity signatures for certain drugs. However, the low-throughput nature of these models renders them problematic for employment as preclinical screening assays. Here, we present an analogous, but high-throughput, in vitro approach in which drugs are administered to a variety of cell types (primary human and rat hepatocytes and the human HepG2 cell line) across a landscape of inflammatory contexts containing LPS and cytokines TNF, IFNγ, IL-1α, and IL-6. Using this assay, we observed drug–cytokine hepatotoxicity synergies for multiple idiosyncratic hepatotoxicants (ranitidine, trovafloxacin, nefazodone, nimesulide, clarithromycin, and telithromycin) but not for their corresponding non-toxic control compounds (famotidine, levofloxacin, buspirone, and aspirin). A larger compendium of drug–cytokine mix hepatotoxicity data demonstrated that hepatotoxicity synergies were largely potentiated by TNF, IL-1α, and LPS within the context of multi-cytokine mixes. Then, we screened 90 drugs for cytokine synergy in human hepatocytes and found that a significantly larger fraction of the idiosyncratic hepatotoxicants (19%) synergized with a single cytokine mix than did the non-hepatotoxic drugs (3%). Finally, we used an information theoretic approach to ascertain especially informative subsets of cytokine treatments for most highly effective construction of regression models for drug- and cytokine mix-induced hepatotoxicities across these cell systems. Our results suggest that this drug–cytokine co-treatment approach could provide a useful preclinical tool for investigating inflammation-associated idiosyncratic drug hepatotoxicity.Pfizer Inc.Institute for Collaborative BiotechnologiesMIT Center for Cell Decision ProcessesNational Institute of Mental Health (U.S.) (grant P50-GM68762)National Institute of Mental Health (U.S.) (grant T32-GM008334)Massachusetts Institute of Technology. Biotechnology Process Engineering CenterMassachusetts Institute of Technology. Center for Environmental Health SciencesNational Institute of Mental Health (U.S.) (grant U19ES011399)Whitaker Foundatio

An Urban Neo-Poverty Population-Based Quality of Life and Related Social Characteristics Investigation from Northeast China

OBJECTIVE: To investigate quality of life (QOL) and related characteristics among an urban neo-poverty population in northeast China, and to compare this population with a traditional poverty cohort. DESIGN: The research was a cross-sectional survey executed from June 2005 to October 2007, with a sample of 2940 individuals ages 36 to 55 in three different industrial cities of northeast China. Data were collected on QOL status and sociodemographic characteristics. QOL was assessed using the 36-item Short Form Health Survey (Chinese version). Multiple regression analysis was employed to analyze association between sociodemographic variables and QOL. RESULTS: The scores for QOL in the neo-poverty group were higher than those in the traditional poverty group, but lower than those in the general population. When the neo-poverty population was divided into two subgroups by age, 36-45 years and 46-55 years, the differences in QOL scores were not significant. However, there were significant differences in several dimensions between two subgroups according to unemployment time (<5 years and >5 years). Additionally, stepwise regression analysis indicated that disease burden, including disease and medical expenditures, was a common risk factor for declining QOL in the neo-poverty group. CONCLUSIONS: Despite some limitations, this study provides initial evidence that the QOL of the urban neo-poverty population lies between that of the general population and traditional poverty. QOL of the neo-poverty group approached QOL of the traditional poverty group with increased unemployment years. In addition to decreased income, disease burden is the most important factor influencing QOL status in urban neo-poverty

Portable X-ray Computed Tomography

With the advantages of non-intrusiveness and high spatial resolution, X-ray Computed Tomography (XCT) has been widely used in various fields. But the traditional XCT is notorious for its huge size, long tuning period and potential safety damage to operator. Besides that, heavy high voltage system and numerous control lines for system control and data transfer are must-have for XCT. This makes it almost impossible for outdoor and filed measurement applications. To solve this problem, a portable Computed Tomography (PCT) based on X-ray was designed and the prototype scanner was developed (Fig.1). Powered by lithium polymer battery and controlled via WIFI signal, this scanner can be easily assembled for measurement and disassembled into a roller luggage for transportation. With the patented parameters determination method based on raw projection and improved reconstruction algorithm, the measurement accuracy gets guaranteed. A continuous stirred tank reactor was scanned with the newly developed PCT (Fig.2). The measurement result shows that this PCT scanner is easy to use and has a spatial resolution of 1mm, and has lots of potential applications in multiphase flow study.</p

Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence

Exploring the physical mechanisms of complex systems and making effective use of them are the keys to dealing with the complexity of the world. The emergence of big data and the enhancement of computing power, in conjunction with the improvement of optimization algorithms, are leading to the development of artificial intelligence (AI) driven by deep learning. However, deep learning fails to reveal the underlying logic and physical connotations of the problems being solved. Mesoscience provides a concept to understand the mechanism of the spatiotemporal multiscale structure of complex systems, and its capability for analyzing complex problems has been validated in different fields. This paper proposes a research paradigm for AI, which introduces the analytical principles of mesoscience into the design of deep learning models. This is done to address the fundamental problem of deep learning models detaching the physical prototype from the problem being solved; the purpose is to promote the sustainable development of AI. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company