Zinc oxide nanoparticles augment CD4, CD8, and GLUT‐4 expression and restrict inflammation response in streptozotocin‐induced diabetic rats

This study evaluated the biochemical, molecular, and histopathological mechanisms involved in the hypoglycaemic effect of zinc oxide nanoparticles (ZnONPs) in experimental diabetic rats. ZnONPs were prepared by the sol–gel method and characterised by scanning and transmission electron microscopy (SEM and TEM). To explore the possible hypoglycaemic and antioxidant effect of ZnONPs, rats were grouped as follows: control group, ZnONPs treated group, diabetic group, and diabetic + ZnONPs group. Upon treatment with ZnONPs, a significant alteration in the activities of superoxide dismutase, glutathione peroxidase, and the levels of insulin, haemoglobin A1c, and the expression of cluster of differentiation 4+ (CD4+), CD8+ T cells, glucose transporter type‐4 (GLUT‐4), tumour necrosis factor, and interleukin‐6 when compared to diabetic and their control rats. ZnONPs administration to the diabetic group showed eminent blood glucose control and restoration of the biochemical profile. This raises their active role in controlling pancreas functions to improve glycaemic status as well as the inflammatory responses. Histopathological investigations showed the non‐toxic and therapeutic effect of ZnONPs on the pancreas. TEM of pancreatic tissues displayed restoration of islets of Langerhans and increased insulin‐secreting granules. This shows the therapeutic application of ZnONPs as a safe anti‐diabetic agent and to have a potential for the control of diabetes.Inspec keywords: nanoparticles, transmission electron microscopy, cellular biophysics, sugar, nanomedicine, nanofabrication, zinc compounds, molecular biophysics, biochemistry, tumours, enzymes, biomedical materials, biological organs, blood, diseases, patient treatment, II‐VI semiconductors, wide band gap semiconductors, scanning electron microscopy, sol‐gel processing, semiconductor growthOther keywords: molecular mechanisms, histopathological mechanisms, zinc oxide nanoparticles, experimental diabetic rats, hypoglycaemic effect, antioxidant effect, control group, diabetic group, CD4+, CD8+ T cells, glucose transporter type‐4, control rats, GLUT‐4 expression, streptozotocin‐induced diabetic rats, biochemical mechanisms, safe antidiabetic agent, inflammation response, sol‐gel method, transmission electron microscopy, scanning electron microscopy, SEM, TEM, superoxide dismutase, glutathione peroxidase, insulin levels, haemoglobin A1c, differentiation 4+ T cells, tumour necrosis factor, interleukin‐6, blood glucose control, pancreas functions, glycaemic status, therapeutic effect, pancreatic tissues, Langerhans islets, insulin‐secreting granules, ZnO     

Design of a compact size tag antenna based on split ring resonator for UHF RFID application

In this article, a new design of miniaturized split‐ring resonator antenna using a meander line technique with a simple impedance matching method applicable to UHF‐RFID tags is presented. The new approach is based on the integration of a meander line into the radiating element of SRR to reduce the electrical tag size and a theoretical demonstration to calculate the conjugate impedance matching and directly attach the antenna with the chip. The new SRR antenna, which is printed on the flexible substrate Arlon CuClad 250LX, is designed using Alien Higgs 3 RFID ASIC whose input impedance is 25‐j190. The prototype antenna has a low‐cost compact size (18.28 mm × 18.28 mm) with a read range higher than 4 m within the RFID UHF band and with a roughly 4.2‐m peak range at 915 MHz. As a proof of behavior, a tag prototype is fabricated and measured to operate at a UHF RFID band. Based on some works' results, an optimized design is obtained with a 48% size reduction compared with the classic split ring resonator antenna and with a good impedance matching the antenna with RFID ASIC without the need for any external matching network.     

The effects of discontinuity surface roughness on the shear strength of weathered granite joints

Surface roughness is one of the most important parameters governing the shear strength of rock discontinuities. Roughness types may vary based on genesis, physico-mechanical, and mineralogical properties of rocks. In this study, granite samples representing three different weathering degrees were selected to evaluate the effects of surface roughness and weathering degree on shear strength. To this aim, we determined the profile roughness coefficient (PRC), profile roughness angle (PRA), and joint roughness coefficient (JRC) for the selected fresh and weathered granite joint samples. Values of PRC were in the range of about 1.043–1.073, and PRA and JRC varied in the ranges of 16.67–21.45 and 12–18, respectively. Weathering led to the increment of joint surface roughness of the selected granitic joints due to the higher resistance of quartz crystals in the weathered matrix. However, the increment in surface roughness did not result in an increase in the shear strength. On the contrary, the shear strength of discontinuities dramatically decreased.     

Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks

The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries and is approaching approximately 101,917,147 cases worldwide according to the statistics of World Health Organization. There are a limited number of COVID-19 test kits available in hospitals due to the increasing cases daily. Therefore, it is necessary to implement an automatic detection system as a quick alternative diagnosis option to prevent COVID-19 spreading among people. In this study, five pre-trained convolutional neural network-based models (ResNet50, ResNet101, ResNet152, InceptionV3 and Inception-ResNetV2) have been proposed for the detection of coronavirus pneumonia-infected patient using chest X-ray radiographs. We have implemented three different binary classifications with four classes (COVID-19, normal (healthy), viral pneumonia and bacterial pneumonia) by using five-fold cross-validation. Considering the performance results obtained, it has been seen that the pre-trained ResNet50 model provides the highest classification performance (96.1% accuracy for Dataset-1, 99.5% accuracy for Dataset-2 and 99.7% accuracy for Dataset-3) among other four used models.

     

Restoration of heavily polluted branches of the Shatt Al-Arab river, Iraq

In view of the desire to improve the water quality of the heavily polluted branches of the Shatt al-Arab River at the City of Basrah, it was proposed to maintain effective flushing as well as contracting sewerage system. The present study was conducted in order to examine the water quality of these branches in an attempt to evaluate the effectiveness of the proposed flushing system. It has been found that their waters contained very low levels of dissolved oxygen and relatively high amounts of both COD and BOD₅. The annual average water quality parameters for Basrah Branches were: dissolved oxygen 3.4 ppm; pH 7.67; hydrogen sulphide 1.4 ppm; ammonia 97 μg-at. N l⁻¹; COD 15.9 mg l⁻¹; BOD₅ 12.7 mg l⁻¹; dissolved silicates 202 μg-at. Si l⁻¹; dissolved reactive phosphate 13.4 μg-at. P-PO₄³⁻ l⁻¹; nitrate 10.4 μg-at. N-NO₃⁻ l⁻¹; nitrite 2.1 μg-at. N-NO₂⁻ l⁻¹ and chlorophyll-α 14.3 mg m⁻³. Based on our calculations, it has been concluded that the proposed system is effective, thus within a flushing cycle all of the above mentioned parameters will become within the acceptable values of the Shatt al-Arab water quality. Moreover, this system has no appreciable effect upon the water quality characteristics of the Shatt al-Arab River due to the fact that it discharges a high volume of water annually. However, It has been recommended to dredge the deposited sludge to a minimum depth of 50 cm.     

Race Classification Using Deep Learning

Race classification is a long-standing challenge in the field of face image analysis. The investigation of salient facial features is an important task to avoid processing all face parts. Face segmentation strongly benefits several face analysis tasks, including ethnicity and race classification. We propose a race-classification algorithm using a prior face segmentation framework. A deep convolutional neural network (DCNN) was used to construct a face segmentation model. For training the DCNN, we label face images according to seven different classes, that is, nose, skin, hair, eyes, brows, back, and mouth. The DCNN model developed in the first phase was used to create segmentation results. The probabilistic classification method is used, and probability maps (PMs) are created for each semantic class. We investigated five salient facial features from among seven that help in race classification. Features are extracted from the PMs of five classes, and a new model is trained based on the DCNN. We assessed the performance of the proposed race classification method on four standard face datasets, reporting superior results compared with previous studies.     

Impact of ultrafiltration/diafiltration sequence on the production of soy protein isolate by membrane technologies

In previous studies, the advantages of combining electrodialysis using a bipolar-cationic membranes configuration to acidify a soy protein extract to pH 6 with ultrafiltration/diafiltration (UF/DF) using a 100 kDa membrane to produce a soy protein isolate with low phytic acid content and improved solubility between pH 2 and 4 was demonstrated, when compared to the production of soy protein isolates by isoelectric precipitation and by UF/DF of a soy protein extract at pH 9. However, limited work was done to establish the impact of the UF/DF sequence for the purification of the pH 6 extract. Therefore, the purpose of this work was to study the impact of four different UF/DF sequences with a total permeate volume of 1.5–1.6 times the initial volume, on membrane fouling and permeate flux, as well as on the isolate protein, ash and phytic acid contents and solubility profile. Of the investigated UF/DF sequences, the VCR 5, VD 4 sequence was shown to be the one with the most severe fouling and consequently the most severe permeate flux decline. At the same time, it was also the VCR 5, VD 4 sequence which was the most efficient in terms of ash and phytic acid removal, followed by the VCR 5, re-VCR5 sequence, the VCR 2, VD 2 sequence and the VCR 2, (re-VCR 2)X 2 sequence, respectively. It was also observed that isolate with low phytic acid content resulted in narrower protein solubility profiles around the isoelectric point and higher protein solubility for the pH range of 2 to 4.Industrial relevancePlant proteins have made up a higher proportion of the human diet in recent years. Soybeans are the most important source of plant protein ingredients accounting for some 68% of global plant protein consumption in the world. Soy protein isolate is traditionally prepared by isoelectric precipitation process. This process has high productivity, however, it results in products with poor functional properties due to protein denaturation and to the presence of phytic acid (1–3% w/w) which alters the solubility of the isolates especially for the pH below the proteins' isoelectric point. In this work, we combined electrodialysis using a bipolar-cationic membranes configuration to acidify a soy protein extract to pH 6 with ultrafiltration/diafiltration (UF/DF) using a 100 kDa membrane to produce soy protein isolates with low phytic acid content. The impact of four different UF/DF sequences on membrane fouling, permeate flux, isolate composition and solubility profile was studied. Of the investigated UF/DF sequences, the VCR 5, VD 4 sequence was shown to be the one with the most severe fouling but at the same time the most efficient in terms of ash and phytic acid removal. It was also observed that the isolate produced by the VCR 5, VD 4 sequence shows narrower protein solubility profiles around the isoelectric point and higher protein solubility for the pH range of 2 to 4 than isolates produced by alternative UF/DF sequences. This isolate could be considered as a valuable ingredient for the formulation of fruit juice beverages or power juices, considering that the pH of these liquid food products is around 3.5.     

Cu2+ Selective Chromogenic Behavior of Calix[4]arene Derivative

This study involves the copper selective chromogenic response of 5, 11, 17, 23-Tetrakis (N-pyrrolidinomethyl)-25, 26, 27, 28-tetrahydroxycalix[4]arene based mannich base (3). Complexation ability of (3) was explored by examining the effect of a series of various metal ions, such as Li⁺, Na⁺, K⁺, Ag⁺, Ba²⁺, Ca²⁺, Mn²⁺, Mg²⁺, Sr²⁺, Ni²⁺, Cd²⁺, Co²⁺, Cu²⁺, Hg²⁺, Pb²⁺, Zn²⁺, Fe²⁺, Fe³⁺, and Al³⁺, by using UV-visible spectroscopy. Ligand (3) exhibited pronounced selectivity toward Cu²⁺ even in the presence of various co-existing ions. The stoichiometric analysis, i.e., Job's plot revealed that (3) form 1:1 complex with Cu²⁺ ion in DMF-H₂O system. The complexation phenomenon was confirmed by FT-IR spectroscopy that favors the selective nature of (3) with Cu²⁺.     

Lignan contents in sesame seeds and products

Sesame seed (Sesamum indicum L.) is a rich source of furofuran lignans with a wide range of potential biological activities. The major lignans in sesame seeds are the oil‐soluble sesamin and sesamolin, as well as glucosides of sesaminol and sesamolinol that reside in the defatted sesame flour. Upon refining of sesame oil, acid‐catalyzed transformation of sesamin to episesamin and of sesamolin to epimeric sesaminols takes place, making the profile of refined sesame oils different from that of virgin oils. In this study, the total lignan content of 14 sesame seeds ranged between 405 and 1178 mg/100 g and the total lignan content in 14 different products, including tahini, ranged between 11 and 763 mg/100 g. The content of sesamin and sesamolin in ten commercial virgin and roasted sesame oils was in the range of 444–1601 mg/100 g oil. In five refined sesame oils, sesamin ranged between 118 and 401 mg/100 g seed, episesamin between 12 and 206 mg/100 g seed, and the total contents of sesaminol epimers between 5 and 35 mg/100 g seed, and no sesamolin was found. Thus, there is a great variation in the types and amounts of lignans in sesame seeds, seed products and oils. This knowledge is important for nutritionists working on resolving the connection between diet and health. Since the consumption of sesame seed products is increasing steadily in Europe and USA, it is important to include sesame seed lignans in databases and studies pertinent to the nutritional significance of antioxidants and phytoestrogens. It is also important to differentiate between virgin, roasted and refined sesame oils.     

Highly selective determination of perchlorate by a novel potentiometric sensor based on a synthesized complex of copper

In this paper, a highly selective poly (vinyl chloride) (PVC) membrane electrode based on (1, 9-dibenzyl-1, 3, 7, 9, 11, 15-hexaaza cyclohexa decane) copper(II) perchlorate; [Cu((benzyl)₂[16]aneN₆)](ClO₄)₂; as a synthesized ionophore, for perchlorate-selective electrode is reported. The influence of membrane composition, pH and possible interfering anions were investigated on the response properties of the electrode. The sensor responds to perchlorate ion in linear range from 1.0 × 10^? 6 to 1.0 × 10^? 1 M with a slope ? 59.4 ± 0.3 mV per decade. The limit of detection of the electrode was 4.0 × 10^? 7 M ClO₄^–. Selectivity coefficients indicate a good discriminating ability towards ClO₄^– ion in comparison to other anions. The proposed sensor has a fast response time of about 7 s and can be used for at least 2 months without any considerable divergence in potential. Due to importance of analysis of perchlorate in water samples, this selective electrode was applied as potentiometric sensor in determination of perchlorate ion in real samples.