Adrenergic Control Of Renal Hemodynamics In Different Pathophysiological States With Renal Impairment : The Role Of 1-Adrenoceptor Subtypes [RC904. H995 2007 f rb].

Kajian ini menyelidik samada berlaku sebarang perubahan dalam populasi α1- adrenoseptor berfungsi dalam mengawalatur vasokonstriksi ginjal diaruh secara adrenergik di dalam model-model haiwan berpenyakit dengan kecacatan ginjal. This study investigated whether there is any alteration in the functional population of α1-adrenoceptors in mediating adrenergically induced renal vasoconstrictions in animal models of some pathological states characterized with renal impairment

Simulation of transient blood flow in models of arterial stenosis and aneurysm

The Large Eddy Simulation (LES) technique with the Smagorinsky-Lilly dynamic subgrid model and two-equation Standard k-ω Transitional turbulence model are applied to investigate non-spiral and spiral blood flow through three dimensional models of arterial stenosis and aneurysm. A spiral pattern of blood flow is thought to have many beneficial effects on hemodynamics. Previous computational studies on spiral blood flow involve only steady spiral flow in a straight stenosed pipe without considering an upstream curved section of the artery. But a spiral pattern in the blood flow may exist due to the presence of an upstream curved section in the artery. On the other hand, pressure is generally considered a constant quantity in studies on pulsatile flow through either arterial stenosis or aneurysm; however, blood pressure is a waveform in a physiological flow. Although cosine-type or smooth regular stenoses are generally taken in investigations of blood flow in a three-dimensional model of arterial stenosis, in reality, stenoses are of irregular shape. Besides stenosis and aneurysm, another abnormal condition of the artery is the presence of stenosis with an adjacent aneurysm in the same arterial segment, especially in the posterior circulation. A study on (steady or pulsatile) flow through such arterial stenosis with an adjacent aneurysm in the same arterial segment is not available so far. Therefore, taking above things into consideration, thorough investigations of steady and unsteady pulsatile non-spiral and spiral blood flow in three-dimensional models of stenosis and aneurysm are needed to give a sound understanding of the transition-to-turbulence of blood flow due to stenosis and aneurysm and to study the the effects of spiral velocity on the transition-to-turbulence. The LES technique has mostly been used to investigate turbulent flow in engineering fields other than bio-fluid mechanics. In the last decade, LES has seen its excellent potential for studying the transition-to-turbulence of physiological flow in bio-fluid mechanics. Though the k-ω Transitional model is used in few instances, mainly LES is applied in this study. Firstly, investigations of steady non-spiral and spiral blood flow through threedimensionalmodels of cosine-type regular stenosed tube without and with upstream curved segment of varying angles of curvature are performed by using the k-ω Transitional model and LES. A fully developed Poiseuille velocity profile for blood is introduced at the inlets of the models. To introduce a spiral effect at the inlet, onesixth of the bulk velocity is taken as the tangential velocity at the inlet along with the axial velocity profile there. Secondly, physiological pulsatile non-spiral and spiral blood flow through a three-dimensional model of a straight tube having cosine-type regular stenosis are investigated by using mainly LES. A two-equation k-ω Transitional model is also used in one non-spiral flow case. The first four harmonics of the Fourier series of pressure pulse are used to generate physiological velocity profiles at the inlet. At the outlet, a pressure waveform is introduced. The effects of percentage of area reduction in the stenosis, length of the stenosis, amplitude of pulsation and Womersley number are also examined. Thirdly, transient pulsatile non-spiral and spiral blood flow through a threedimensional model of irregular stenosis are investigated by applying LES and comparison is drawn between non-spiral flow through a regular stenosis and that through an irregular stenosis. Lastly, pulsatile non-spiral and spiral blood flow through a three-dimensional model of irregular stenosis with an adjacent post-stenotic irregular aneurysm in the same arterial segment are studied by applying LES and the k-ω Transitional model. The effects of variation in spiral velocity are also examined. The results presented in this thesis are analysed with relevant pathophysioloical consequences. In steady flow through the straight stenosed tube, excellent agreement between LES results for Re = 1000 and 2000 and the corresponding experimental results are found when the appropriate inlet perturbations are introduced. In the models with an upstream curved segment, no significant effect of spiral flow on any flow property is found for the investigated Reynolds numbers; spiral pattern disappears before the stenosis – which may be due the rigid wall used in the models and/or a steady flow at the inlet. The effects of the curved upstream model can be seen mainly in the maximum turbulent kinetic energy (TKE), the maximum pressure drop and the maximum wall shear stress (WSS), which in the curved upstream models generally increase significantly compared with the corresponding results in the straight stenosed tube. The maximumcontributions of the SGS motion to the large-scale motion in both non-spiral and spiral flow through a regular stenosis, an irregular stenosis and an irregular stenosis with an adjacent post-stenotic irregular aneurysm are 50%, 55%and 25%, respectively, for the highest Reynolds number investigated in each model. Although the wall pressure and shear stress obtained from the k-ω Transitional model agree quite well with the corresponding LES results, the turbulent results obtained from the k-ω Transitional model differ significantly from the corresponding LES results – this shows unsuitability of the k-ω model for pulsatile flow simulation. Large permanent recirculation regions are observed right after the stenosis throat in both non-spiral and spiral flow, which in the model of a stenosis with an adjacent post-stenotic aneurysm are stretched beyond the aneurysm and the length of the recirculation regions increases with spiral velocity. This study shows that, in both steady and unsteady pulsatile flow through the straight tube model having either a stenosis (regular or irregular) or an irregular stenosis with an adjacent post-stenotic irregular aneurysm, the TKE rises significantly at some locations and phases if a spiral effect is introduced at the inlet of the model. However, the maximum value of the TKE in a high spiral flow drops considerably compared with that in a low spiral flow. The maximum wall pressure drop and shear stress occur around the stenosis throat during all the phases of the pulsatile cycle. In the model of a stenosis only, the wall pressure rises in the immediate post-stenotic region after its drop at the stenosis throat. However, in the model of a stenosis with an adjacent aneurysm, the wall pressure does not rise to regain its undisturbed value before the start of the last quarter of the aneurysm. The effects of the spiral flow on the wall pressure and WSS are visible only in the downstream region where they take oscillatory pattern. The break frequencies of energy spectra for velocity and pressure fluctuations from −5/3 power slope to −10/3 power slope and −7/3 power slope, respectively, are observed in the downstream transition-to-turbulence region in both the non-spiral and spiral flow. At some locations in the transition region, the velocity spectra in the spiral flow has larger inertial subrange region than that in non-spiral flow. The effects of the spiral flow on the pressure spectra is insignificant. Also, the maximum wall pressure drop, the maximum WSS and the maximum TKE in the non-spiral flow through the irregular stenosis rise significantly compared with the corresponding results in the non-spiral flow through the regular stenosis. When the area reduction in the stenosis is increased, the maximum pressure drop, the maximumWSS and the TKE rise sharply. As for the effects of the length of the stenosis, the maximum WSS falls significantly and the maximum TKE rises sharply due to the increase in the length of the stenosis; but the maximum pressure drop is almost unaffected by the increase in the stenosis length. The increase in the amplitude of pulsation causes both the maximum pressure drop and the maximum WSS to increase significantly under the inlet peak flow condition. While the increased amplitude of pulsation decrease the maximum TKE, it is nonetheless responsible for the sharp rise in the TKE found at some places in the transition-toturbulence region. The decrease in the Womersley number causes the maximum TKE to increase dramatically; however, the maximum pressure drop and the maximum WSS decrease slightly under the inlet peak flow condition as a result of the decrease in the Womersley number. The author does believe that the present study makes a breakthrough in understanding the non-spiral and spiral transient blood flows through arteries having a stenosis and a stenosis with an adjacent post-stenotic aneurysm. The findings of the thesis would, therefore, help the interested groups such as pathologists,medical surgeons and researchers greatly in gaining better insight into the transient non-spiral and spiral blood flow through models of arterial stenosis and aneurysm

Novel Omega-3 Fatty Acid Epoxygenase Metabolite Reduces Kidney Fibrosis.

Cytochrome P450 (CYP) monooxygenases epoxidize the omega-3 polyunsaturated fatty acid (PUFA) docosahexaenoic acid into novel epoxydocosapentaenoic acids (EDPs) that have multiple biological actions. The present study determined the ability of the most abundant EDP regioisomer, 19,20-EDP to reduce kidney injury in an experimental unilateral ureteral obstruction (UUO) renal fibrosis mouse model. Mice with UUO developed kidney tubular injury and interstitial fibrosis. UUO mice had elevated kidney hydroxyproline content and five-times greater collagen positive fibrotic area than sham control mice. 19,20-EDP treatment to UUO mice for 10 days reduced renal fibrosis with a 40%-50% reduction in collagen positive area and hydroxyproline content. There was a six-fold increase in kidney α-smooth muscle actin (α-SMA) positive area in UUO mice compared to sham control mice, and 19,20-EDP treatment to UUO mice decreased α-SMA immunopositive area by 60%. UUO mice demonstrated renal epithelial-to-mesenchymal transition (EMT) with reduced expression of the epithelial marker E-cadherin and elevated expression of multiple mesenchymal markers (FSP-1, α-SMA, and desmin). Interestingly, 19,20-EDP treatment reduced renal EMT in UUO by decreasing mesenchymal and increasing epithelial marker expression. Overall, we demonstrate that a novel omega-3 fatty acid metabolite 19,20-EDP, prevents UUO-induced renal fibrosis in mice by reducing renal EMT

Dementia with Lewy bodies – a clinicopathological update

Dementia is one of the major burdens of our aging society. According to certain predictions, the number of patients will double every 20 years. Although Alzheimer’s disease (AD), as the most frequent neurodegenerative dementia, has been extensively analysed, less is known about dementia with Lewy bodies (DLB). Neuropathological hallmarks of DLB are the deposition of intracellular Lewy bodies (LB) and Lewy neurites (LN). DLB belongs to the α-synucleinopathies, as the major component of these inclusions is pathologically aggregated α-synuclein. Depending on the localization of LBs and LNs in the central nervous system cognitive and motor symptoms can occur. In our work, we will systematically review the possible etiology and epidemiology, pathological (both macroscopic and microscopic) features, structural and functional imaging findings, with a special emphasis on the clinico-pathological correlations. Finally, we summarize the latest clinical symptoms-based diagnostic criteria and the novel therapeutic approaches. Since DLB is frequently accompanied with AD pathology, highlighting possible differential diagnostic approaches is an integral part of our paper. Although our present knowledge is insufficient, the rapid development of diagnostic and research methods provide hope for better diagnosis and more efficient treatment, contributing to a better quality of life

Power distance among leaders in tourism

The purpose of this study is to explore the influence of power distance on leadership in tourism industry. This paper aimed to understand behaviours in leadership conducts and the aspects of power distance affecting these behaviours. The findings of the paper depict that where power distance is concerned, a leader in the tourism industry needs to be someone who is evasive and a win/win problem solver

Effect of traffic dataset on various machine-learning algorithms when forecasting air quality

© Emerald Publishing Limited. This is the accepted manuscript version of an article which has been published in final form at https://10.1108/JEDT-10-2021-0554Purpose (limit 100 words) Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic datasets on air quality predictions has not been clearly investigated. This research investigates the effects traffic dataset have on the performance of Machine Learning (ML) predictive models in air quality prediction. Design/methodology/approach (limit 100 words) To achieve this, we have set up an experiment with the control dataset having only the Air Quality (AQ) dataset and Meteorological (Met) dataset. While the experimental dataset is made up of the AQ dataset, Met dataset and Traffic dataset. Several ML models (such as Extra Trees Regressor, eXtreme Gradient Boosting Regressor, Random Forest Regressor, K-Neighbors Regressor, and five others) were trained, tested, and compared on these individual combinations of datasets to predict the volume of PM2.5, PM10, NO2, and O3 in the atmosphere at various time of the day. Findings (limit 100 words) The result obtained showed that various ML algorithms react differently to the traffic dataset despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%. Research limitations/implications (limit 100 words) This research is limited in terms of the study area and the result cannot be generalized outside of the UK as many conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research. Therefore, leaving out a few other ML algorithms. Practical implications (limit 100 words) This study reinforces the belief that the traffic dataset has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form traffic dataset in the development of an air quality prediction model. This implies that developers and researchers in air quality prediction need to identify the ML algorithms that behave in their best interest before implementation. Originality/value (limit 100 words) This will enable researchers to focus more on algorithms of benefit when using traffic datasets in air quality prediction.Peer reviewe

Air Pollution Prediction using Machine Learning: A Review

In the effort to achieve accurate air pollution predictions, researchers have contributedvarious methodologies with varying data and different approaches that can be judgedaccurate in their respective contexts. Diverse approaches have been used so far in theliterature to achieve optimal accuracy in the prediction of air pollution. Researchers havealso used different combinations of data such as Meteorological, Traffic and Air Qualitydata. Hence, creating a situation where there are open questions on which of the machinelearning (ML) algorithms or ensemble of algorithms is best suited for various combinationsof data and varying dependent and independent variables. While it is obvious that there isa need for a more optimally performing predictive model for air pollution prediction, it isdifficult to know what combination of algorithms and data is best suited for variousdependent variables. In this study, we reviewed 26 research articles reported recently in theliterature and the methods applied to different data to identify what combination of MLalgorithms and data works best for the prediction of various air pollutants. The studyrevealed that despite the availability of many datasets, researchers in this domain cannotavoid the use of Air Quality and Meteorological datasets. However, Random Forest appearsto perform well for various combinations of datasets

Epoxyeicosatrienoic Acid Analog EET-A Blunts Development of Lupus Nephritis in Mice

Systemic lupus erythematosus (SLE) is a chronic autoimmune inflammatory disorder that causes life threatening renal disease and current therapies are limited with serious side-effects. CYP epoxygenase metabolites of arachidonic acid epoxyeicosatrienoic acids (EETs) demonstrate strong anti-inflammatory and kidney protective actions. We investigated the ability of an orally active EET analog, EET-A to prevent kidney injury in a mouse SLE model. Twenty-weeks old female NZBWF1 (SLE) and age-matched NZW/LacJ (Non SLE) were treated with vehicle or EET-A (10 mg/kg/d, p.o.) for 14 weeks and urine and kidney tissues were collected at the end of the protocol. SLE mice demonstrated marked renal chemotaxis with 30–60% higher renal mRNA expression of CXC chemokine receptors (CXCR) and CXC chemokines (CXCL) compared to Non SLE mice. In SLE mice, the elevated chemotaxis is associated with 5-15-fold increase in cytokine mRNA expression and elevated inflammatory cell infiltration in the kidney. SLE mice also had elevated BUN, serum creatinine, proteinuria, and renal fibrosis. Interestingly, EET-A treatment markedly diminished renal CXCR and CXCL renal mRNA expression in SLE mice. EET-A treatment also reduced renal TNF-α, IL-6, IL-1β, and IFN-γ mRNA expression by 70–80% in SLE mice. Along with reductions in renal chemokine and cytokine mRNA expression, EET-A reduced renal immune cell infiltration, BUN, serum creatinine, proteinuria and renal fibrosis in SLE mice. Overall, we demonstrate that an orally active EET analog, EET-A prevents renal injury in a mouse model of SLE by reducing inflammation

Complement biomarkers as predictors of disease progression in Alzheimer's disease

There is a critical unmet need for reliable markers of disease and disease course in mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). The growing appreciation of the importance of inflammation in early AD has focused attention on inflammatory biomarkers in cerebrospinal fluid or plasma; however, non-specific inflammation markers have disappointed to date. We have adopted a targeted approach, centered on an inflammatory pathway already implicated in the disease. Complement, a core system in innate immune defense and potent driver of inflammation, has been implicated in pathogenesis of AD based on a confluence of genetic, histochemical, and model data. Numerous studies have suggested that measurement of individual complement proteins or activation products in cerebrospinal fluid or plasma is useful in diagnosis, prediction, or stratification, but few have been replicated. Here we apply a novel multiplex assay to measure five complement proteins and four activation products in plasma from donors with MCI, AD, and controls. Only one complement analyte, clusterin, differed significantly between control and AD plasma (controls, 295 mg/l; AD, 388 mg/l: p < 10- 5). A model combining clusterin with relevant co-variables was highly predictive of disease. Three analytes (clusterin, factor I, terminal complement complex) were significantly different between MCI individuals who had converted to dementia one year later compared to non-converters; a model combining these three analytes with informative co-variables was highly predictive of conversion. The data confirm the relevance of complement biomarkers in MCI and AD and build the case for using multi-parameter models for disease prediction and stratification