CLOVE OR GREEN TEA ADMINISTRATION ANTAGONIZES KHAT HEPATOTOXICITY IN RATS

Objective: Khat consumption has become a common problem that affects the health aspects of life in Yemen and other parts in the world. The liver has been suspected to be particularly vulnerable to the harmful effects of khat use and until now khat hepatotoxicity effects are still controversial. This study was conducted to investigate the hepatoprotective effects of aqueous extracts of clove and green tea, as medicinal herbs with established antioxidant properties, against controversial hepatotoxicity effects of khat in rats. Methods: Rats received a daily oral dose of khat extract alone or in combination with green tea or clove extract for six weeks. To study the effects on liver cells, histopathology, routine liver function tests, malondialdehyde (MDA), total antioxidant capacity (TAC) and the activities of superoxide dismutase (SOD) and catalase (CAT) enzymes were investigated. Results: Khat administration showed marked liver injury; congestion in the portal vein with fibrous tissue proliferation, extended from the portal area and forming intralobular Porto-portal bridging fibrous septae. Besides significant routine liver function tests alterations, lipid peroxides elevation, and TAC reduction with significant inhibition of SOD and CAT activities. Conclusion: Combined administration of khat with clove or green tea protected hepatocytes via oxidative stress inhibition. They significantly counteracted the alterations in liver function tests, decreased lipid peroxidation and restored the antioxidant status to near normal levels. These results confirm khat hepatotoxicity and suggest that clove or green tea administration has strong hepatoprotective effects against khat induced hepatotoxicity in rats via antioxidant mediated mechanism.Â

Endovenous Laser Ablation, Radiofrequency Ablation and Flebogrif versus Conventional Surgery in Treatment of Primary Varicose Vein of the Lower Limb: Prospective Randomized Controlled Study

Background: Endovenous laser ablation (EVLA), radiofrequency ablation (RFA) and mechanochemical ablation (MOCA) of primary varicose vein are thought to minimise postoperative morbidity and reduce work loss compared with the conventional surgical procedure. Objective: To determine, whether endovenous ablation methods (radiofrequency, laser and mechanochemical) have any advantages or disadvantages in comparison with conventional surgery, in the treatment of primary varicose vein. Patients and Methods: This was a prospective randomized study, conducted on forty patients presented at Vascular Outpatient Clinic for management of chronic venous insufficiency. All patients underwent clinical examination and duplex ultrasonography. Ten (10) patients were treated with ligation and stripping of the great saphenous vein (GSV). Ten (10) patients were treated with radiofrequency ablation. Ten (10) patients were treated with endovenous laser ablation. Ten (10) patients were treated with Flebogrif. Results: Compared with conventional surgery, endovenous ablation methods reduced postoperative discomfort and pain, with a lower complication rate after treatment for avoidance of a groin incision and dissection at the saphenofemoral confluence. Cosmetic demands were also better satisfied. Non-controlled clinical trials have shown that the ablation rate of GSV after EVLA is over 90%. However, risks of EVLA, RFA and Flebogrif remain in terms of recanalization and neoreflux via junctional tributaries. Conclusion: RFA, EVLA, and Flebogrif are minimally invasive procedures. Their potential early benefits, by avoiding groin dissection and GSV stripping, have been confirmed by the findings from this trial. Current evidence based on randomized trials consistently demonstrates significant early benefits after RFA, EVLA and Flebogrif in suitable patients with varicose veins

Synthesis and studying the antitumor activity of novel 5-(2-methylbenzimidazol-5-yl)-1,3,4-oxadiazole-2(3H)-thiones

The influence of the incorporation of 1,3,4-oxadiazole ring into 2-methyl-1H-benzimidazole derivatives producing a series of substituted 5(6)-(2-methylbenzimidazol-5-yl)-1,3,4-oxadiazoles on the antitumor activity was studied in this study. The antitumor activity of the new compounds was tested against breast cancer cell line MCF-7 and lung cancer cell line A549. S-5-(2-methyl-1H-benzo[d]imidazol-5-yl)-1,3,4-oxadiazol-2-yl 2-nitrobenzenesulfonothioate (9) showed potent activity against both MCF-7 and A549 cell lines. Whereas, compounds 7, 11-13 and 15-17 have moderate growth inhibitory activity on the two cell lines

Jensen, Ostrowski and Hermite-Hadamard type inequalities for h-convex stochastic processes by means of center-radius order relation

Please read abstract in the article.Prince Sattam bin Abdulaziz University.http://www.aimspress.com/journal/MathMathematics and Applied Mathematic

Steady three-dimensional MHD mixed convection couple stress flow of hybrid nanofluid with hall and ion slip effect

The heat transfer ratio has some important applications in industries and the engineering sector. In this model, the authors used the hybrid nanofluid because the heat transfer ratio of hybrid nanofluid is more as compared to the base fluid; the key objective of this research work is to boost up the heat transfer ratio, for example, to regulate the energy is possible only by adding the heat transmission mechanism in the flow model. The current research paper investigates the steady 3D MHD mixed convection couple stress flow of hybrid nanofluid with hall and ion slip effect. The objective of the current research work is to increase the heat consignment ratio, which is the demand of the manufacturing and engineering sector, this type of flow has some important applications in the industries sector and engineering sector for the purpose of cooling and hotness effect, also hotness and cooling play some important role in daily life. To transform the nonlinear partial differential equation to a nonlinear ordinary differential equation we used the defined similarity transformation. The transform nonlinear ordinary differential equations are solved by an approximate analytical method. The important obtained results are presented in the graphs. The influence of different parameters such as couple stress parameter, mixed convection parameter, nanoparticle volume friction, Hall parameter, magnetic field parameter, thermophores parameter, Eckert number, and prandtl number are taken over graphs. The Сƒ(skin friction coefficient), N u (nusselt number), convergence control parameter, and comparison of the present work with the published work are described in the form of tables

Brain tumor MRI medical images classification model based on CNN (BTMIC-CNN)

This research discusses a fully automatic brain tumour MRI medical images classification model that use Convolutional Neural Network (BTMIC-CNN). The proposed neural model adopted Design Science Research Methodology (DSRM) to classify MRI medical images from two datasets. One for binary classification task (contains tumorous and non-tumorous images). And the second for multiclass classification task (contains three types of brain tumor MRI medical images namely: Glioma, meningioma, and pituitary). The model's excellent performance was confirmed using the evaluation metrics and reported an overall accuracy of 99%. It outperforms existing methods in terms of classification accuracy and is expected to help radiologists and doctors accurately classify brain tumours’ images. This study contributes to goal three of the Sustainable Development Goals (SDGs), which involves excellent health and well-being

A Combined Use of Rhizobacteria and Moringa Leaf Extract Mitigates the Adverse Effects of Drought Stress in Wheat (Triticum aestivum L.)

Less nutrient availability and drought stress are some serious concerns of agriculture. Both biotic and abiotic stress factors have the potential to limit crop productivity. However, several organic extracts obtained from moringa leaves may induce immunity in plants under nutritional and drought stress for increasing their survival. Additionally, some rhizobacterial strains have the ability to enhance root growth for better nutrient and water uptake in stress conditions. To cover the knowledge gap on the interactive effects of beneficial rhizobacteria and moringa leaf extracts (MLEs), this study was conducted. The aim of this experimental study was to investigate the effectiveness of sole and combined use of rhizobacteria and MLEs against nutritional and drought stress in wheat. Nitrogen-fixing bacteria Pseudomonas aeruginosa (Pa) (10(8) CFU ml(-1)) was inoculated to wheat plants with and without foliar-applied MLEs at two different concentrations (MLE 1 = 1:15 v/v and MLE 2 = 1:30 v/v) twice at 25 and 35 days after seed sowing (50 ml per plant) after the establishment of drought stress. Results revealed that Pa + MLE 2 significantly increased fresh weight (FW), dry weight (DW), lengths of roots and shoot and photosynthetic contents of wheat. A significant enhancement in total soluble sugars, total soluble proteins, calcium, potassium, phosphate, and nitrate contents validated the efficacious effect of Pa + MLE 2 over control-treated plants. Significant decrease in sodium, proline, glycine betaine, electrolyte leakage, malondialdehyde, hydrogen peroxide, superoxide dismutase (SOD), and peroxide (POD) concentrations in wheat cultivated under drought stress conditions also represents the imperative role of Pa + MLE 2 over control. In conclusion, Pa + MLE 2 can alleviate nutritional stress and drought effects in wheat. More research in this field is required to proclaim Pa + MLE 2 as the most effective amendment against drought stress in distinct agroecological zones, different soil types, and contrasting wheat cultivars worldwide.Peer reviewe

Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16

The ability to estimate conclusions without direct human input in healthcare systems via computer algorithms is known as Artificial intelligence (AI) in healthcare. Deep learning (DL) approaches are already being employed or exploited for healthcare purposes, and in the case of medical images analysis, DL paradigms opened a world of opportunities. This paper describes creating a DL model based on transfer learning of VGG16 that can correctly classify MRI images as either (tumorous) or (non-tumorous). In addition, the model employed data augmentation in order to balance the dataset and increase the number of images. The dataset comes from the brain tumour classification project, which contains publicly available tumorous and non-tumorous images. The result showed that the model performed better with the augmented dataset, with its validation accuracy reaching ~100 %