Gemeenschappelijke regeling. De voorwaarden voor uittreding.

Afdeling bestuursrechtspraak van de Raad van State420The Legitimacy and Effectiveness of Law & Governance in a World of Multilevel Jurisdiction

Prejudiciële vragen, gezag van gewijsde, effectieve handhaving van het (Europese) staatssteunrecht.

Hof van Justitie van de Europese UnieGst. 2016/34The Legitimacy and Effectiveness of Law & Governance in a World of Multilevel Jurisdiction

Evaluation of the α-glucosidase inhibitory and free radical scavenging activities of selected traditional medicine plant species used in treating diabetes

Plants constitute a major ingredient in traditional or folk medicine. The therapeutic claims made on the use of these traditional medicinal plants range from simple conditions such as fevers and migraines, to more complex diseases such as cancer, metabolic syndrome and diabetes mellitus. The aqueous ethanolic extracts of five medicinal plant species; Cosmos caudatus, Leucaena leucocephala, Momordica charantia, Pereskia bleo and Averrhoa bilimbi were assessed for glucose lowering effect via the in vitro α-glucosidase inhibition assay. Their antioxidant potential, represented by their DPPH radical scavenging activity and total phenolic contents were also measured. The most potent α-glucosidase inhibitory activity was recorded for the leaf extract of C. caudatus with IC50 of 21.90 ± 3.60 µg/mL, followed by L. leucocephala with IC50 value of 30.80 ± 2.50 µg/mL. Momordica charantia, P. bleo and A. bilimbi did not show any significant inhibition of α-glucosidase. Meanwhile C. caudatus also gave the highest DPPH radical scavenging activity with IC50 value of 272.46 ± 8.98 µg/mL, and the highest total phenolic content with a value of 0.263 ± 0.02 g GAE/g DW. The present work provides a priority list of interesting plants for further study with respect to the treatment of diabetes

Do changes in ace-2 expression affect sars-cov-2 virulence and related complications: A closer look into membrane-bound and soluble forms

The SARS-CoV-2 virus utilizes angiotensin converting enzyme (ACE-2) for cell entry and infection. This enzyme has important functions in the renin-angiotensin aldosterone system to preserve cardiovascular function. In addition to the heart, it is expressed in many tissues including the lung, intestines, brain, and kidney, however, its functions in these organs are mostly unknown. ACE-2 has membrane-bound and soluble forms. Its expression levels are altered in disease states and by a variety of medications. Currently, it is not clear how altered ACE-2 levels influence ACE-2 virulence and relevant complications. In addition, membrane-bound and soluble forms are thought to have different effects. Most work on this topic in the literature is on the SARS-CoV virus that has a high genetic resemblance to SARS-Co-V-2 and also uses ACE-2 enzyme to enter the cell, but with much lower affinity. More recent studies on SARS-CoV-2 are mainly clinical studies aiming at relating the effect of medications that are thought to influence ACE-2 levels, with COVID-19 outcomes for patients under these medications. This review paper aims to summarize what is known about the relationship between ACE-2 levels and SARS-CoV/SARS-CoV-2 virulence under altered ACE-2 expression states.The publication of this article was covered with a generous support from BARZAN HOLDING

Application of a flow-induced stress wave and investigation of associated injuries on cell monolayers using a parallel plate flow chamber

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Parallel plate flow chambers are widely used to expose cultured cells to physiological flows for the investigation of a variety of diseases. These applications usually involve the generation of continuous and steady fluid flow over cell monolayers for extended durations, usually a few days. Another technique is to generate a fast high-stress wave over the cells to see the immediate effect of flow-induced stresses. This can be achieved by propagating an air/liquid interface, in other words, a bubble, over cell monolayers. The approach is relevant to the reopening event of fluid-filled lung bronchioles and alveoli during mechanical ventilation therapy of Acute Respiratory Distress Syndrome. This article explains how we generate a stress wave using a parallel plate flow chamber and presents representative results of this wave on cultured lung epithelial cells

Antimicrobial modification of PLA scaffolds with ascorbic and fumaric acids via plasma treatment

An optimal medical scaffold should be biocompatible and biodegradable and should have adequate mechanical properties and scaffold architecture porosity, a precise three-dimensional shape, and a reasonable manufacturing method. Polylactic acid (PLA) is a natural biodegradable thermoplastic aliphatic polyester that can be fabricated into nanofiber structures through many techniques, and electrospinning is one of the most widely used methods. Medical fiber mat scaffolds have been associated with inflammation and infection and, in some cases, have resulted in tissue degradation. Therefore, surface modification with antimicrobial agents represents a suitable solution if the mechanical properties of the fiber mats are not affected. In this study, the surfaces of electrospun PLA fiber mats were modified with naturally occurring L-ascorbic acid (ASA) or fumaric acid (FA) via a plasma treatment method. It was found that 30 s of radio-frequency (RF) plasma treatment was effective enough for the wettability enhancement and hydroperoxide formation needed for subsequent grafting reactions with antimicrobial agents upon their decomposition. This modification led to changes in the surface properties of the PLA fiber mats, which were analyzed by various spectroscopic and microscopic techniques. FTIR-ATR confirmed the chemical composition changes after the modification process and the surface morphology/topography changes were proven by SEM and AFM. Moreover, nanomechanical changes of prepared PLA fiber mats were investigated by AFM using amplitude modulation-frequency modulation (AM-FM) technique. A significant enhancement in antimicrobial activity of such modified PLA fiber mats against gram-positive Staphylococcus aureus and gram-negative Escherichia coli are demonstrated herein. © 2020 The AuthorsQatar National Research Fund (a member of The Qatar Foundation) [22-076-1-011]; Qatar University Collaborative Grant [QUCG-CAM-20/21-3]; Czech Science FoundationGrant Agency of the Czech Republic [19-16861S

Autoimmune Diseases of the GI Tract Part II: Emergence of Diagnostic Tools and Treatments

Autoimmune diseases (AD) have emerged as a pandemic in our modern societies, especially after the World War II. In part I, we have reviewed five main diseases and shed light on different aspects from introducing the concept of autoimmunity, the description of the disease’s pathogenesis and the diagnosis, the role of antibodies as markers for the prediction of the disease, the link between the gut and brain through what is known as the gut–brain axis, and the relationship of this axis in GI autoimmune diseases. In this chapter, we review the role of antibodies as markers for the prediction of the disease, artificial intelligence in GI autoimmune diseases, the nutritional role and implications in the five GI autoimmune diseases, and finally the treatment of those diseases

Deep Learning Technique for Congenital Heart Disease Detection Using Stacking-Based CNN-LSTM Models from Fetal Echocardiogram: A Pilot Study

Congenital heart defects (CHDs) are a leading cause of death in infants under 1 year of age. Prenatal intervention can reduce the risk of postnatal serious CHD patients, but current diagnosis is based on qualitative criteria, which can lead to variability in diagnosis between clinicians. Objectives: To detect morphological and temporal changes in cardiac ultrasound (US) videos of fetuses with hypoplastic left heart syndrome (HLHS) using deep learning models. A small cohort of 9 healthy and 13 HLHS patients were enrolled, and ultrasound videos at three gestational time points were collected. The videos were preprocessed and segmented to cardiac cycle videos, and five different deep learning CNN-LSTM models were trained (MobileNetv2, ResNet18, ResNet50, DenseNet121, and GoogleNet). The top-performing three models were used to develop a novel stacking CNN-LSTM model, which was trained using five-fold cross-validation to classify HLHS and healthy patients. The stacking CNN-LSTM model outperformed other pre-trained CNN-LSTM models with the accuracy, precision, sensitivity, F1 score, and specificity of 90.5%, 92.5%, 92.5%, 92.5%, and 85%, respectively for video-wise classification, and with the accuracy, precision, sensitivity, F1 score, and specificity of 90.5%, 92.5%, 92.5%, 92.5%, and 85%, respectively for subject-wise classification using ultrasound videos. This study demonstrates the potential of using deep learning models to classify CHD prenatal patients using ultrasound videos, which can aid in the objective assessment of the disease in a clinical setting.This study was funded by Qatar National Research Fund (QNRF), National Priorities Research Program (NPRP 10-0123-170222). The open access publication of this article was funded by the Qatar National Library

Population structure study of Anzali wetland zooplankton

Anzali wetland is one of the most important places for spawning fishes and zooplankton groups are the first consumer in this ecosystem. They are the perfect food for the larvae of fishes. Zooplankton status was evaluated in 6 stations of different areas of the Anzali wetland during March 2011 to February 2012. Sampling was done by tube (PVC) and passing through of 30 micron planktonic net. The samples were identified and counted by invert microscope. According to the results were identified 60 Genus and 6 phylum (11, 31, 10, 2, 1, 1, 1, 2 genus of phylum Protozoa, Rotatoria, Arthropoda, Gastrotricha, Mollusca, Tardigrada, Nematoda, Porifera, Annelida) respectively. The results showed that the maximum annual average density of zooplankton was observed with 2497 number per liter in Karkan station and the population was more in the summer than in other seasons. Phylum of Rotatoria,, protozoa and superclass Copepoda formed 48, 45 and 6percent of the density respectively. According to the results the population of zooplankton did not change much compared to past studies, excluding Protozoa but the diversity of all zooplankton group are declined very much. According to the statistical analysis Kruskal Wallis are not significant differences between density of zooplankton in different stations, months and seasons (p > 0.05), but significant differences were found in different phylum together (p<0.05)

Microfluidic-based virus detection methods for respiratory diseases

With the recent SARS-CoV-2 outbreak, the importance of rapid and direct detection of respiratory disease viruses has been well recognized. The detection of these viruses with novel technologies is vital in timely prevention and treatment strategies for epidemics and pandemics. Respiratory viruses can be detected from saliva, swab samples, nasal fluid, and blood, and collected samples can be analyzed by various techniques. Conventional methods for virus detection are based on techniques relying on cell culture, antigen-antibody interactions, and nucleic acids. However, these methods require trained personnel as well as expensive equipment. Microfluidic technologies, on the other hand, are one of the most accurate and specific methods to directly detect respiratory tract viruses. During viral infections, the production of detectable amounts of relevant antibodies takes a few days to weeks, hampering the aim of prevention. Alternatively, nucleic acid–based methods can directly detect the virus-specific RNA or DNA region, even before the immune response. There are numerous methods to detect respiratory viruses, but direct detection techniques have higher specificity and sensitivity than other techniques. This review aims to summarize the methods and technologies developed for microfluidic-based direct detection of viruses that cause respiratory infection using different detection techniques. Microfluidics enables the use of minimal sample volumes and thereby leading to a time, cost, and labor effective operation. Microfluidic-based detection technologies provide affordable, portable, rapid, and sensitive analysis of intact virus or virus genetic material, which is very important in pandemic and epidemic events to control outbreaks with an effective diagnosis.Qatar National Research Fun