Protective Effect of Hesperidin against Cyclophosphamide Hepatotoxicity in Rats

The protective effect of hesperidin was investigated in rats exposed to liver injury induced by a single intraperitoneal injection of cyclophosphamide (CYP) at a dose of 150 mg kg-1. Hesperidin treatment (100 mg kg-1/day, orally) was applied for seven days, starting five days before CYP administration. Hesperidin significantly decreased the CYP-induced elevations of serum alanine aminotransferase, and hepatic malondialdehyde and myeloperoxidase activity, significantly prevented the depletion of hepatic glutathione peroxidase activity resulted from CYP administration. Also, hesperidin ameliorated the CYP-induced liver tissue injury observed by histopathological examination. In addition, hesperidin decreased the CYP-induced expression of inducible nitric oxide synthase, tumor necrosis factor-α, cyclooxygenase-2, Fas ligand, and caspase-9 in liver tissue. It was concluded that hesperidin may represent a potential candidate to protect against CYP-induced hepatotoxicity

Protective Effect of Hesperidin against Cyclophosphamide Hepatotoxicity in Rats

The protective effect of hesperidin was investigated in rats exposed to liver injury induced by a single intraperitoneal injection of cyclophosphamide (CYP) at a dose of 150 mg kg-1. Hesperidin treatment (100 mg kg-1/day, orally) was applied for seven days, starting five days before CYP administration. Hesperidin significantly decreased the CYP-induced elevations of serum alanine aminotransferase, and hepatic malondialdehyde and myeloperoxidase activity, significantly prevented the depletion of hepatic glutathione peroxidase activity resulted from CYP administration. Also, hesperidin ameliorated the CYP-induced liver tissue injury observed by histopathological examination. In addition, hesperidin decreased the CYP-induced expression of inducible nitric oxide synthase, tumor necrosis factor-α, cyclooxygenase-2, Fas ligand, and caspase-9 in liver tissue. It was concluded that hesperidin may represent a potential candidate to protect against CYP-induced hepatotoxicity

Protective Effect of Hesperidin against Cyclophosphamide Hepatotoxicity in Rats

The protective effect of hesperidin was investigated in rats exposed to liver injury induced by a single intraperitoneal injection of cyclophosphamide (CYP) at a dose of 150 mg kg-1. Hesperidin treatment (100 mg kg-1/day, orally) was applied for seven days, starting five days before CYP administration. Hesperidin significantly decreased the CYP-induced elevations of serum alanine aminotransferase, and hepatic malondialdehyde and myeloperoxidase activity, significantly prevented the depletion of hepatic glutathione peroxidase activity resulted from CYP administration. Also, hesperidin ameliorated the CYP-induced liver tissue injury observed by histopathological examination. In addition, hesperidin decreased the CYP-induced expression of inducible nitric oxide synthase, tumor necrosis factor-α, cyclooxygenase-2, Fas ligand, and caspase-9 in liver tissue. It was concluded that hesperidin may represent a potential candidate to protect against CYP-induced hepatotoxicity

Effect of Blast Loading on Seismically Detailed RC Columns and Buildings

Explosions caused by standoff charges near buildings have drastic effects on the internal and external structural elements which can cause loss of life and fatal injuries in case of failure or collapse of the structural element. Providing structural elements with blast resistance is therefore gaining increasing importance. This paper presents numerical investigation of RC columns with different reinforcement detailing subjected to near-field explosions. Detailed finite element models are made using LS-DYNA software package for several columns having seismic and conventional reinforcement detailing which were previously tested under blast loads. The numerical results show agreement with the published experimental results regarding displacements and damage pattern. Seismic detailing of columns enhances the failure shape of the column and decrease the displacement values compared to columns with conventional reinforcement detailing. Further, the effect of several modeling parameters are studied such as mesh sensitivity analysis, inclusion of air medium and erosion values on the displacements and damage pattern. The results show that decreasing the mesh size, increasing erosion value and inclusion of air region provide results that are very close to experimental results. Additionally, application is made on a slab-column multistory building provided with protective walls having different connection details subjected to blast loads. The results of this study are presented and discussed. Use of a top and bottom floor slab connection of protective RC walls are better than using the full connection at the four sides to the adjacent columns and slabs. This leads to minimizing the distortion and failure of column, and therefore it increases the chance of saving the building from collapse and saving human lives. Doi: 10.28991/cej-2021-03091733 Full Text: PD

A robust CNN Model for Diagnosis of COVID-19 based on CT scan images and DL techniques

The 2019 Coronavirus (COVID-19) virus has caused damage on people\u27s respiratory systems over the world.  Computed Tomography (CT) is a faster complement for RT-PCR during peak virus spread times. Nowadays, Deep Learning (DL) with CT provides more robust and reliable methods for classifying patterns in medical pictures. In this paper, we proposed a simple low training proposed customized Convolutional Neural Networks (CNN) customized model based on CNN architecture that layers which are optionals may be included such as the layer of batch normalization to reduce time taken for training and a layer with a dropout to deal with overfitting. We employed a huge dataset of chest CT slices images from diverse sources COVIDx-CT, which consists of a 16,146-image dataset with 810 patients of various nationalities. The proposed customized model\u27s classification results compared to the VGG-16, Alex Net, and ResNet50 Deep Learning models. The proposed CNN model shows robustness by achieving an overall accuracy of 93% compared to 88%, 89%, and 95% for the VGG-16, Alex Net, and ResNet50 DL models for the classification of 3 classes. When this relates to binary classification, the classification accuracy of the proposed model and the VGG-16 models were identical (almost 100% accurate), with 0.17% of misclassification in the class of Non-Covid-19, the Alex Net model achieved almost 100% classification accuracy with 0.33% misclassification in the class of Non-Covid-19. Finally, ResNet50 achieved 95% classification accuracy with 5% misclassification in the Non-Covid-19 class.

A robust CNN Model for Diagnosis of COVID-19 based on CT scan images and DL techniques

The 2019 Coronavirus (COVID-19) virus has caused damage on people's respiratory systems over the world.  Computed Tomography (CT) is a faster complement for RT-PCR during peak virus spread times. Nowadays, Deep Learning (DL) with CT provides more robust and reliable methods for classifying patterns in medical pictures. In this paper, we proposed a simple low training proposed customized Convolutional Neural Networks (CNN) customized model based on CNN architecture that layers which are optionals may be included such as the layer of batch normalization to reduce time taken for training and a layer with a dropout to deal with overfitting. We employed a huge dataset of chest CT slices images from diverse sources COVIDx-CT, which consists of a 16,146-image dataset with 810 patients of various nationalities. The proposed customized model's classification results compared to the VGG-16, Alex Net, and ResNet50 Deep Learning models. The proposed CNN model shows robustness by achieving an overall accuracy of 93% compared to 88%, 89%, and 95% for the VGG-16, Alex Net, and ResNet50 DL models for the classification of 3 classes. When this relates to binary classification, the classification accuracy of the proposed model and the VGG-16 models were identical (almost 100% accurate), with 0.17% of misclassification in the class of Non-Covid-19, the Alex Net model achieved almost 100% classification accuracy with 0.33% misclassification in the class of Non-Covid-19. Finally, ResNet50 achieved 95% classification accuracy with 5% misclassification in the Non-Covid-19 class.

An Efficient Fully Automated Method for Gridding Microarray Images

Abstract DNA microarray is a powerful tool and is widely used in genetics to monitor expression levels of thousands of genes in parallel. The gene expression process consists of three stages: gridding, segmentation and quantification. Gridding deals with finding areas in the microarray image which contain one spot using grid lines. This step can be done manually or automatically. In this paper, we propose an efficient and simple automatic gridding method for microarray image analysis. This method was implemented using MATLAB software and found very effective for gridding arrays with low intensity, poor quality spotsand tested by a number of microarray images. Results show that this method gives high accuracy of 76.9% improved to 98.6% when a preprocessing step is considered, rendering the method a promising technique for an efficient and automatic gridding the noisy microarray images

Ultrasound-Guided Erector Spinae Plane Block: A Comparative Study to Assess its Analgesic Efficacy in Pediatric Patients Undergoing Aortic Coarctation Repair

Background: Effective postoperative analgesia is an important aspect of both anesthetic practice and postoperative outcomes. Thoracotomy for the repair of coarctation of the aorta is a painful surgical procedure; inadequate postoperative analgesia may result in postoperative respiratory complications with the possible prolonged need for oxygen therapy. In addition, paradoxical hypertension is a well-recognized complication of repair. We hypothesize that erector spinae plane block (ESPB) by providing adequate analgesia and blocking sympathetic stimulation may reduce opioid consumption, accelerate weaning of oxygen therapy, and reduce the incidence of early postoperative paradoxical hypertension. Material and methods: Open-labeled randomized controlled trial carried out on 40 patients divided into two groups. Group (B) received ESPB before the skin incision and group (C), the control group received no block. Results: Patients who received ESPB had significantly less intraoperative fentanyl consumption than the control group (P-value<0.001), and significantly less postoperative fentanyl consumption by 50% than the control group in the first 12 hours 2.025 ±0.273 μg/kg and 4.05 ±0.527 μg/kg respectively (P-value<0.001). while there was no statistically significant difference between both groups regarding the incidence of postoperative vasodilator infusion for paradoxical hypertension (P-value=0.054), the pediatric anesthesia emergence delirium (PAED) (P-value=0.06) nor the time to wean oxygen supply (P-value=0.49).  Conclusion: Erector spinae plane block effectively reduces postoperative pain in pediatric patients undergoing repair of coarctation of the aorta. However, it did not significantly accelerate weaning from oxygen therapy nor reduce the incidence of vasodilator use for postprocedural hypertension