2,664 research outputs found

    Ten Years» Experience of Aortic Aneurysm Associated with Systemic Lupus Erythematosus

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    AbstractBackground: aortic aneurysm is a rare but life-threatening cardiovascular complication in patients with systemic lupus erythematosus (SLE). The purpose of this study was to clarify the characteristic clinical features and the pathological mechanism of aneurysmal formation in these patients. Methods: among 429 patients operated on for abdominal aortic aneurysm (AAA) during the past 10 years, five cases with SLE were treated surgically. Their clinical data were reviewed, and the resected aneurysmal wall of the five patients was also examined histologically. Results: the mean age of the patients with SLE was 55 years, which was statistically younger than that of the other patients (mean 77 years, s.d. 7.9, p <0.05). They had received long-term corticosteroid therapy for the treatment of SLE for a mean of 23 years. Histologically, destruction of the medial elastic lamina was characteristic. Four patients had no complications in the postoperative follow-up period (mean 4 years), while the remaining patient died of rupture of a dissecting aneurysm two years after operation.Conclusion : prolonged steroid therapy may play a major role in accelerating atherosclerosis, which can result in aortic aneurysmal enlargement, possibly together with primary aortic wall involvement and/or vasculitic damage in patients with SLE

    Mathematical Identification of Critical Reactions in the Interlocked Feedback Model

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    Dynamic simulations are necessary for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. Sensitivity analysis allows the linking of robustness to network structure. However, it yields only local properties regarding a particular choice of plausible parameter values, because it is hard to know the exact parameter values in vivo. Global and firm results are needed that do not depend on particular parameter values. We propose mathematical analysis for robustness (MAR) that consists of the novel evolutionary search that explores all possible solution vectors of kinetic parameters satisfying the target dynamics and robustness analysis. New criteria, parameter spectrum width and the variability of solution vectors for parameters, are introduced to determine whether the search is exhaustive. In robustness analysis, in addition to single parameter sensitivity analysis, robustness to multiple parameter perturbation is defined. Combining the sensitivity analysis and the robustness analysis to multiple parameter perturbation enables identifying critical reactions. Use of MAR clearly identified the critical reactions responsible for determining the circadian cycle in the Drosophila interlocked circadian clock model. In highly robust models, while the parameter vectors are greatly varied, the critical reactions with a high sensitivity are uniquely determined. Interestingly, not only the per-tim loop but also the dclk-cyc loop strongly affect the period of PER, although the dclk-cyc loop hardly changes its amplitude and it is not potentially influential. In conclusion, MAR is a powerful method to explore wide parameter space without human-biases and to link a robust property to network architectures without knowing the exact parameter values. MAR identifies the reactions critically responsible for determining the period and amplitude in the interlocked feedback model and suggests that the circadian clock intensively evolves or designs the kinetic parameters so that it creates a highly robust cycle

    Trends in antimicrobial-drug resistance in Japan.

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    Multidrug resistance in gram-positive bacteria has become common worldwide. In Japan until recently, gram-negative bacteria such as Pseudomonas aeruginosa, Klebsiella pneumoniae, and Serratia marcescens were controlled by carbapenems, fluoroquinolones, and aminoglycosides. However, several of these microorganisms have recently developed resistance against many antimicrobial drugs

    Evaluating regional emission estimates using the TRACE-P observations

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    Measurements obtained during the NASA Transport and Chemical Evolution over the Pacific (TRACE-P) experiment are used in conjunction with regional modeling analysis to evaluate emission estimates for Asia. A comparison between the modeled values and the observations is one method to evaluate emissions. Based on such analysis it is concluded that the inventory performs well for the light alkanes, CO, ethyne, SO2, and NOₓ. Furthermore, based on model skill in predicting important photochemical species such as O₃, HCHO, OH, HO₂, and HNO₃, it is found that the emissions inventories are of sufficient quality to support preliminary studies of ozone production. These are important finding in light of the fact that emission estimates for many species (such as speciated NMHCs and BC) for this region have only recently been estimated and are highly uncertain. Using a classification of the measurements built upon trajectory analysis, we compare observed species distributions and ratios of species to those modeled and to ratios estimated from the emissions inventory. It is shown that this technique can reconstruct a spatial distribution of propane/benzene that looks remarkably similar to that calculated from the emissions inventory. A major discrepancy between modeled and observed behavior is found in the Yellow Sea, where modeled values are systematically underpredicted. The integrated analysis suggests that this may be related to an underestimation of emissions from the domestic sector. The emission is further tested by comparing observed and measured species ratios in identified megacity plumes. Many of the model derived ratios (e.g., BC/CO, SOₓ/C₂H₂) fall within ∼25% of those observed and all fall outside of a factor of 2.5. (See Article file for details of the abstract.)Department of Civil and Environmental EngineeringAuthor name used in this publication: Wang, T
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