Quetiapine is an atypical antipsychotic drug (APD) for the treatment of symptoms in patients with schizophrenia. This drug effectively alleviates positive and negative symptoms as well as cognitive impairment [1][2][3]. In addition, quetiapine is well tolerated and causes the lowest incidence of extra-pyramidal symptoms [1,4] We have shown that quetiapine, a new antipsychotic drug, protects cultured cells against oxidative stress-related cytotoxicities induced by amyloid b (Ab)25-35, and that quetiapine prevents memory impairment and decreases Ab plaques in the brains of amyloid precursor protein (APP) ⁄ presenilin-1 (PS-1) double-mutant mice. The aim of this study was to understand why quetiapine has these protective effects. Because the cytotoxicity of both Ab(25-35) and Ab(1-40) requires fibril formation, our first experiments determined the effect of quetiapine on Ab(25-35) aggregation. Quetiapine inhibited Ab(25-35) aggregation in cell-free aqueous solutions and blocked the fibrillar aggregation of Ab(25-35), as observed under an electron microscope. We then investigated why quetiapine inhibits Ab(25-35) aggregation. During the aggregation of Ab(25-35), a hydroxyl radical (OH • ) was released, which in turn amplified Ab(25-35) aggregation. Quetiapine blocked OH• -induced Ab(25-35) aggregation and scavenged the OH• produced in the Fenton system and in the Ab(25-35) solution, as analyzed using electron paramagnetic resonance spectroscopy. Furthermore, new compounds formed by quetiapine and OH• were observed in MS analysis. Finally, we applied Ab(25-35) to PC12 cells to observe the effect of quetiapine on living cells. Ab(25-35) increased levels of intracellular reactive oxygen species and calcium in PC12 cells and caused cell death, but these toxic effects were prevented by quetiapine. These results demonstrate an anti-oxidative stress mechanism of quetiapine, which contributes to its protective effects observed in our previous studies and explains the effectiveness of this drug for Alzheimer's disease patients with psychiatric and behavioral complications.
Using a low coherence interferometry (LCI) model, a comparison of broadband single-Gaussian and multi-Gaussian light sources has been undertaken. For single-Gaussian sources, the axial resolution improves with the source bandwidth, confirming the coherence length relation that the resolution for single Gaussian sources improves with increasing spectral bandwidth. However, narrow bandwidth light sources result in interferograms with overlapping strata peaks and the loss of individual strata information. For multiple-Gaussian sources with the same bandwidth, spectral side lobes increase, reducing A-scan reliability to show accurate layer information without eliminating the side lobes. The simulations show the conditions needed for the resolution of strata information for broadband light sources using both single and multiple Gaussian models. The potential to use the model to study optical coherence tomography (OCT) light sources including super luminescent diodes (SLDs), as reviewed in this paper, as well as optical delay lines and sample structures could better characterize these LCI and OCT elements. Forecasting misinformation in the interferogram may allow preliminary corrections. With improvement to the LCI-OCT model, more applications are envisaged.
Sustainable water management is an essential aspect of all industries. This is particularly true in regional Australia, which in known for its harsh climate, with arid conditions. In this work we investigate the sustainable water management of major Australian regional airports. A specific case study of Mildura Airport, as the largest regional airport in the State of Victoria, is presented. Potable water is of particular importance, as it has the largest cost associated with its use. Sustainable means of supplying potable water can be significant to the operating costs of a regional airport. In an attempt to determine the potential for water harvesting at regional airports a novel image processing approach was taken to analyse the water capture area. This involved utilising satellite imagery and the image processing functionalities of Matlab, with some simple mathematics to estimate roofed areas. From here meteorological data gives rainfall data, in terms of depth, facilitating volume capture potentials. It was found that the average potable water harvesting potential for Mildura Airport is 3.964 megalitres per year.
This study has proposed and empirically tested for the first time genetic algorithm optimization models for modelling Australia's domestic airline passenger demand, as measured by enplaned passengers (GAPAXDE model) and revenue passenger kilometres performed (GARPKSDE model). Data was divided into training and testing datasets; 74 training datasets were used to estimate the weighting factors of the genetic algorithm models and 13 out-of-sample datasets were used for testing the robustness of the genetic algorithm models. The genetic algorithm parameters used in this study comprised population size (n): 200; the generation number: 1,000; and mutation rate: 0.01. The modelling results have shown that both the quadratic GAPAXDE and GARPKSDE models are more accurate, reliable, and have greater predictive capability as compared to the linear models. The mean absolute percentage error in the out of sample testing dataset for the GAPAXDE and GARPKSDE quadratic models are 2.55 and 2.23%, respectively.
U.S. Geological Survey (USGS) science supports groundwater resource management in the Mississippi Alluvial Plain (MAP) region. The USGS Science and Decisions Center is working with the Water Availability and Use Science Program (WAUSP) to integrate economics into a sophisticated model of groundwater in the region. The model will quantify the status of the groundwater system and help researchers, stakeholders, and decision-makers understand and manage groundwater resources. Including economics in the model will let users consider the influence of groundwater levels on regional economics and the effects of economic factors on the demand for groundwater. Agriculture is a major source of economic activity in the Mississippi Alluvial Plain (MAP) region. The MAP region consists of parts of Arkansas, Mississippi, Louisiana, Tennessee, Kentucky, Illinois, and Missouri (fig. 1). Irrigated acreage in the region accounted for 14 percent of total U.S. agriculture in 2015 (Dieter and others, 2018). Major crops grown in the region include corn, cotton, rice, and soybeans. Catfish is an important aquaculture commodity. Agriculture in the region relies on groundwater for irrigation. Approximately 65 percent of farmland in the region relies on groundwater from the Mississippi River Valley alluvial aquifer (MRVAA) for irrigation and aquaculture (Kebede and others, 2014). 1 Irrigated acreage in the region is on the rise; from 2007 to 2012, irrigated acreage in Arkansas and Mississippi increased by about 7.7 and 20.7 percent, respectively
We present a novel numerical method for the Hamilton-Jacobi-Bellman equation governing a class of optimal feedback control problems. The spatial discretization is based on a least-squares collocation Radial Basis Function method and the time discretization is the backward Euler finite difference. A stability analysis is performed for the discretization method. An adaptive algorithm is proposed so that at each time step, the approximate solution can be constructed recursively and optimally. Numerical results are presented to demonstrate the efficiency and accuracy of the method
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