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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with 213 eyes examined in Iraq and obtained AUCs of 0.91–0.92 and an accuracy range of 88–92%. The proposed model is a step toward improving the detection of clinical and subclinical forms of KCN.

Osteoarthritis is the most common form of arthritis, involving inflammation and major structural changes of the joint, causing pain and functional disability. Pain and stiffness, particularly after exercise, are the major symptoms, resulting in considerable impact on ability to perform activities of daily living. There is discordance between symptoms and radiographic changes, with some sufferers not experiencing symptoms, but showing osteoarthritic changes on X-ray. The present study was performed to examine the effect of ginger and turmeric consumption on liver function (ALT, AST), phosphorus, total calcium , ionized calcium, x-ray and histopathologyon osteoporosis rats induced by prednisone acetate at a dose of 4 mg / kg bw three time a week for three weeks. On the other hand, the chemical constituent’s moisture, protein, fat, crude fibre, total digestible nutrients, ash, carbohydrate, phosphorous, calcium was determined for the tested ginger and turmeric. In addition to, volatile compounds and analysis of phytochemicals was determined for the tested ginger and turmeric. This work was carried out on 48 non-pregnant female albino rats (age 6 to 8 weeks and about 160 to 210g body weight) classified into two main groups. The first main group (6) fed on basal diet and the second main group (42 rats)injected with prednisone acetate at a dose of 4 mg / kg bw three time a week for three weeks to cause osteoporosis and divided into seven subgroups such as each group consists of (6rats). Then fed on basal diet containing 10% -15% ginger, 10% -15% turmericand10% -15% ginger and turmeric. Results revealed that all osteoporosis groups administrated with different levels of ginger and turmeric (10-15%) had significant decrease liver function (ALT, AST), phosphorus, total calcium, ionized calcium comparing with the positive control group. On the other hand, x-ray and histopathologyof the positive control group after two months revealed bone loss of different part such as fibula, tibia and femur in addition to bone demineralization and femoral fracture and fibula bone trabexculae showed dystrophy and resorption and osteoporosis. These findings revealed that ginger andturmeric treatment attenuated and treated degrees to osteoporosis in compare to positive control group.

Background Kawasaki disease (kDa) is a self-limiting acute vasculitis that affects small and medium-sized vessels, and is the most common cause of acquired heart disease in children. It is also an important reason for long-term cardiac disease into adulthood. Rapid diagnosis and management of kDa is challenging due to the heterogeneity of the disease, yet is vital for improving outcome. To date, there are no Egyptian nationally agreed, evidence-based guidelines concerning the diagnosis and management of kDa in children. Consequently, treatment regimens vary broadly. Objectives To develop a consensus, evidence-based recommendations for the diagnosis, evaluation and management of children living with kDa. Methods This study was carried out to achieve an Egyptian expert consensus on a management strategy for kDa using Delphi technique. A multistep process strategy was adopted, which started by developing 16 key clinical questions by scientific committee according to the Patient/Population, Intervention, Comparison, Outcomes and Time (PICOT) approach. The core leadership team identified clinicians and researchers with expertise in pediatric rheumatology all over Egypt. An evidence-based, systematic, literature review was conducted to compile evidence for the kDa management. Delphi process was implemented (3-rounds) to reach a consensus. Results Twenty-five expert panel participated in the 3 rounds with response rate 100%. A total of 21 recommendations, categorized into 9 domains (Definition, disease activity, predicting the development of coronary disease, assessment and monitoring (lab, imaging), treatment (acute and after acute attack), management of resistant cases, management of complications (cardiac complications, MAS and arthritis), vaccination and long term follow up. The Agreement with the recommendations (rank 7–9) ranged from 83.6–95.7%. The Consensus was reached (i.e. ≥75% of respondents strongly agreed or agreed) on all the clinical standards. Algorithm for management has also been developed. Conclusion This was an expert, consensus recommendations for the diagnosis and treatment of kDa, based on best available evidence and expert opinion. The recommendations provided a management approach based on easy-to-use algorithm and with the support of complementary tests. The implication to policy, practice, research and advocacy to provide updated recommendations for better management of kDa.

This paper illustrates the design of a system to identify objects on a conveyor belt using machine vision. In the present study, a machine vision based on one line scan sorting was developed, the purpose being to sort objects based on various stages of maturity. Many different methods are available for object identification. But we made design a system that separates and counting them. Different objects placed on the conveyor belt moves along, a camera placed above the belt takes real-time video and feeds it to the MATLAB software for processing the object to compare with the basic template object. The vision camera understands an object based on its physical attributes, such as shape and size for effectively controlling the hardware, which will use in this work. Besides, the number of objects of a particular section that cross the conveyor to demonstrate the identification of moving objects is counted and displayed. A low-speed conveyor belt is manufactured with various test objects that pass through it. For identifying a good object, the wavelength data is used, determining the way to match the geometric patterns and to identify the dimensions, and edge detection is applied. The ability to count specific attributes objects is testing different test paths. The sorting of objects using machine vision was performed using an algorithm of pattern matching of machine vision. A pattern image template was built and stored in a computer's memory. When the object is sorting the application run, the camera receives the image of the object into MATLAB. The vision application investigates the image and transfers it to the classifier if the received image matches the model image or not matches.

Background We aimed to provide a consensus, evidence-based recommendations for the diagnosis, evaluation, and treat-to-target management of children living with FMF. This study was carried out to achieve an expert consensus on a treat-to-target management strategy for FMF using the Delphi technique. The preliminary scientific committee identified a total of 17 key clinical questions according to the Patient/Population, Intervention, Comparison, and Outcomes (PICO) approach. An evidence-based, systematic, literature review was conducted to compile evidence for the benefits and harms associated with JIA treatments. The core leadership team identified researchers and clinicians with expertise in FMF management. Delphi process was implemented (2 rounds) to reach a consensus on the management recommendations of FMF patients. Results Twenty-one expert panel participated in the 2 rounds with a response rate of 100%. A total of 12 recommendations, categorized into 2 sections (4 in the diagnosis section and 8 in management), were obtained. The agreement with the recommendations (rank 7–9) ranged from 85.7 to 100%. The consensus was reached (i.e., ≥75% of respondents strongly agreed or agreed) on all the clinical standards. Algorithms for management have been also developed. Conclusion A wide and representative panel of experts established a consensus regarding the management of FMF. The developed guidelines provide a comprehensive treat-to-target approach to the management of FMF for all healthcare professionals who are involved in its management.

Background Macrophage activation syndrome (MAS) is a severe life-threatening hyperinflammatory state with uncontrolled activation and proliferation of macrophages and T-lymphocytes. MAS has variable causes and risk factors. Early diagnosis and optimum management could be lifesaving. Our aim was to develop a consensus, evidence-based recommendations for the diagnosis, evaluation, and treat-to-target management of pediatric MAS. This study was carried out to achieve an Egyptian expert consensus on a treat-to-target management strategy for MAS using the Delphi technique. The multistep process strategy was used in developing a consensus, evidence-based treatment guidelines for MAS, started by developing 7 key clinical questions by a scientific committee according to the Patient/Population, Intervention, Comparison, and Outcomes (PICO) approach. The core leadership team identified pediatric rheumatology clinicians and researchers throughout Egypt. To generate evidence for MAS management, an evidence-based, systematic literature review was done. To obtain a consensus, the Delphi procedure (3 rounds) was used. Results Twenty-three expert panel participated in the 3 rounds with a response rate of 100%. A total of 19 recommendations, categorized into 2 sections (11 in the diagnosis section and 8 in management), were obtained. The agreement with the recommendations (ranks 7–9) ranged from 86.9 to 95.7%. The consensus was reached (i.e., ≥75% of respondents strongly agreed or agreed) on all the clinical standards. Algorithms for management have been also developed. Conclusion This was an expert, consensus recommendation for the diagnosis and treat to target of MAS, based on the best available evidence and expert opinion. The guidelines fill a gap in the literature as it presents a T2T approach for MAS.

Background These updated guidelines aimed to provide appropriate and convenient guidelines for the treatment of various types of juvenile idiopathic arthritis (JIA). Using the Delphi technique, this study was conducted to reach expert consensus on a treat-to-target management strategy for JIA. According to the PICO (patient/population, intervention, comparison, and outcomes) approach, the preliminary scientific committee identified a total of 17 key clinical questions. To assemble evidence on the advantages and dangers associated with JIA treatments, an evidence-based, systematic literature review was conducted. Researchers and clinicians with experience in JIA management were identified by the core leadership team. To establish a consensus on the management suggestions for JIA patients, a Delphi approach (2 rounds) was used. Results An online survey was applied to the expert panel (n = 27), and 26 of them completed both rounds. At the conclusion of round 2, a total of eighteen (18) recommendation items were gathered, which were divided into four sections to address the four key JIA categories. The percentage of those who agreed with the recommendations (ranks 7–9) ranged from 83.2 to 100% (average 86.8%). The phrasing of all 18 clinical standards identified by the scientific committee was agreed upon (i.e. 75% of respondents strongly agreed or agreed). Algorithms have been proposed for the management of JIA polyarthritis, oligoarthritis, and systemic JIA. Conclusion A wide and representative panel of experts initiated a consensus about the management of JIA. The created guidelines give a complete approach to the management of JIA for all healthcare professionals involved in its management, as well as a means of monitoring and evaluating these guidelines on a regular basis.

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Purpose To develop and assess the accuracy of a hybrid deep learning construct for detecting keratoconus (KCN) based on corneal topographic maps. Methods We collected 3794 corneal images from 542 eyes of 280 subjects and developed seven deep learning models based on anterior and posterior eccentricity, anterior and posterior elevation, anterior and posterior sagittal curvature, and corneal thickness maps to extract deep corneal features. An independent subset with 1050 images collected from 150 eyes of 85 subjects from a separate center was used to validate models. We developed a hybrid deep learning model to detect KCN. We visualized deep features of corneal parameters to assess the quality of learning subjectively and computed area under the receiver operating characteristic curve (AUC), confusion matrices, accuracy, and F1 score to evaluate models objectively. Results In the development dataset, 204 eyes were normal, 123 eyes were suspected KCN, and 215 eyes had KCN. In the independent validation dataset, 50 eyes were normal, 50 eyes were suspected KCN, and 50 eyes were KCN. Images were annotated by three corneal specialists. The AUC of the models for the two-class and three-class problems based on the development set were 0.99 and 0.93, respectively. Conclusions The hybrid deep learning model achieved high accuracy in identifying KCN based on corneal maps and provided a time-efficient framework with low computational complexity. Translational Relevance Deep learning can detect KCN from non-invasive corneal images with high accuracy, suggesting potential application in research and clinical practice to identify KCN.

Background There is an unmet need from paediatric rheumatologists and rheumatologists, managing children with JIA, for a well formulated guidelines aiming at achieving better outcomes of their patients. To establish adequate and easily adopted guidelines in management of different variants of JIA in a relatively low resources country. Method This study was carried out to achieve an Egyptian expert consensus on a treat-to-target management strategy for Juvenile Idiopathic Arthritis using Delphi technique. The preliminary scientific committee identified a total of 17 key clinical questions according to the Patient/Population, Intervention, Comparison, and Outcomes (PICO) approach. An evidence-based, systematic, literature review was conducted to compile evidence for the benefits and harms associated with JIA treatments. The core leadership team identified researchers and clinicians with expertise in JIA management in Egypt upon which Experts were gathered from different governorates and health centres across Egypt. Delphi process was implemented (2-rounds) to reacha consensus on the management recommendations of Egyptian JIA patients. Results: An online questionnaire were sent to expert panel (n = 27), of whom 26 participated in the two rounds. At the end of round 2, a total of eighteen (18) recommendation items, categorized into 4 sections to address the main 4 JIA categories, were obtained. Agreement with the recommendations (rank 7–9) ranged from 83.2–100% (average 86.8%). Consensus was reached (i.e. ≥75% of respondents strongly agreed or agreed) on the wording of all the 18 clinical standards identified by the scientific committee. Algorithms for the management of JIA polyarthritis, oligoarthritis and systemic JIA have been suggested. Conclusion A wide and representative panel of experts established a consensus regarding the management of JIA in Egypt. The developed guidelines provide a comprehensive approach to the management of JIA for ll Egyptian healthcare professionals who are involved in its management for follow up and frequent evaluation of these guidelines.

Background IgAvasculitis (IgAV) is the commonest cause of vasculitis in childhood. It is characterized by small vessel vasculitis of the skin, gastrointestinal tract, kidneys, joints, and, rarely, the lungs and the central nervous system. There is paucity of international guidelines for management of IgA V. the Objective is to develop guidelines specific for Egyptian children with IgA vasculitis. Method This study was carried out to achieve an Egyptian expert consensus on a treat-to-target management strategy for IgA vasculitis using Delphi technique. The preliminary scientific committee identified a total of 16 key clinical questions according to the Patient/Population, Intervention, Comparison, and Outcomes (PICO) approach. Delphi process was implemented (2-rounds) to reach a consensus. Results An online questionnaire were sent to expert panel (n = 26) who participated in the two rounds. At the end of round 2, a total of 20 recommendation items, categorized into 2 sections were obtained. Agreement with the recommendations (rank 7–9) ranged from 91.7–100%. Consensus was reached (i.e. ≥75% of respondents strongly agreed or agreed) on the wording of all the 20 clinical standards identified by the scientific committee. Algorithms for the management have been suggested. Conclusion This was an expert, consensus recommendations for the diagnosis and treatment of IgA V and IgA V nephritis, based on best available evidence and expert opinion.

Background Familial Mediterranean fever (FMF) is the most common monogenic auto-inflammatory disease, with the highest prevalence amongst Mediterranean countries including Egypt (where there is high carrier rate of MEFV gene), characterized by recurrent attacks of fever and polyserositis. Mutations in the MEFV gene encoding pyrin has been associated with the disease, which causes exaggeration of the inflammatory response through uncontrolled interleukin production. Issuing updated treatment recommendations are vital for the treating healthcare professionals to get well acquainted with its diagnosis & treatment. To produce consensus-based recommendations to guide the early diagnosis, management and follow-up of patients with FMF. Methods The Patient/Population, Intervention, Comparison, and Outcomes (PICO) questions were developed and refined by the core team. A qualitative synthesis of scientific evidence based on systematic review and clinical experience was conducted to compile evidence for the diagnosis and management of FMF. A consensus process was conducted among the expert panel to generate the final recommendations and grade their strength. 3 rounds of Delphi process were carried out. Results Following 3 Delphi rounds, recommendations were developed for: early diagnosis, who to treat, treatment targets, genetic testing and its interpretation in association with clinical presentation, treatment of FMF and dealing with acute attacks, monitoring of management, identify treatment response, systemic affection, persistent attacks or inflammation, resistant cases, protracted symptoms, as well as remission status. Algorithm for patients’ diagnosis and management is provided. The final document comprises 12 recommendations, each presented with its degree of agreement (0–10), Level of agreement, grade of recommendation and rationale. The degree of agreement was >7/10 in all instances. Conclusion This guideline provides comprehensive approach to the accurate diagnosis and effective management/monitoring of FMF. It also represents a model for the incorporation of medical genetics practice into the more traditional domains of general medicine.

The present study was performed to examine the effect of an artichoke and milk thistle consumption on liver function, kidney function, and lipid profiles. The chemical constituents were determined for the tested dried artichoke and milk thistle. This search was carried out using 72 adult male white albino rats randomly classified into two main groups. The first main group (36 rats) fed on a basal diet containing 20% - 40% artichoke and 20% - 40% milk thistle (acute liver failure groups). The second main group (36 rats) fed on a basal diet containing 20% - 40% artichoke and 20% - 40% milk thistle (acute renal failure groups).Then, the main groups were divided into six subgroups for each (n = 6). Results revealed that all groups treated with CCl4 or glycerol/ saline solution and administrated with different levels of dried artichoke and milk thistle (20% -40%) had a significant decrease in their liver function, kidney function, total cholesterol, triglycerides, LDL-c and VLDL-c cholesterol compared with the positive control group. On the other hand, a significant increase in HDL-c was recorded in all groups administrated with dried artichoke and milk thistle (20% -40%) compared with the control positive group. The results indicated that the consumption of artichokes and milk thistle could help in reducing the symptoms of acute liver and renal failure.

The Kaup-Boussinesq system has been solved numerically by using two methods, Successive approximation method (SAM) and Adomian decomposition method (ADM). Comparison between the two methods has been made and both can solve this kind of problems, also both methods are accurate and has faster convergence. The comparison showed that the Adomian decomposition method much more accurate than Successive approximation method.

The development of power generators that can function in harsh snowy environments and in contact with snow can be beneficial but challenging to accomplish. Herein, we introduce the first snow-based triboelectric nanogenerator (snow-TENG) that can be used as an energy harvester and a multifunctional sensor based on the principle of snow-triboelectrification. In this work, we used a 3D printing technique for the precise design and deposition of the electrode and triboelectric layer, leading to flexible, stretchable and metal-free triboelectric generators. Based on the single electrode mode, the device can generate an instantaneous output power density as high as 0.2 mW/m(2), an open circuit voltage up to 8 V, and a current density of 40 μA/m(2). In addition, the snow-TENG can function as a miniaturized weather station to monitor the weather in real time to provide accurate information about the snowfall rate, snow accumulation depth, wind direction, and speed in snowy and/or icy environments. In addition, the snow-TENG can be used as a wearable power source and biomechanical sensor to detect human body motions, which may prove useful for snow-related sports. Unlike conventional sensor platforms, our design works without the need for batteries or image processing systems. We envision these devices could potentially be integrated into solar panels to ensure continuous power supply during snowy weather conditions.

Thermal insulation of solid rocket motor casing is necessary to overcome the catastrophic breakdown during the rocket propellant combustion. In our study, a comprehensive review on different types elastomeric heat shielding materials (EHSMs) such as polyurethane, silicon rubber, ethylene propylene diene monomer (EPDM) and nitrile rubber was conducted. Various types of fillers are added to the EHSMs to enhance their thermal, mechanical and ablative performances. The charring phenomenon, which offers a means of protection to the virgin polymer layer from direct flame, as well as the synergetic effect, that may occur between fillers and polymer matrices, were studied. All different methods and machines used for manufacturing EHSMs are described in detail. Moreover, the different techniques used to characterize the EHSMs are discussed. Last but not least, the empirical models that relate the thermal insulation performance to the filler concentration are presented.

Background/Introduction: Clinical Keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologist must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps and Pentacam indices (PI).Methods: We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN) and MobileNet-v2 (MN), and fine-tuned them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision based on the fusion of probabilities.Results: Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features.Conclusions: This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computerassisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and toperform fast and accurate KCN treatment.

Introduction: Peripheral Artery Disease (PAD) affects 12 million people in the US. 11.7% in Pakistan. Diabetes (DM) has a significant correlation with PAD. Patients with PAD and DM have a greater risk of amputation than just PAD. Aim: Our study aimed to measure the prevalence of PAD among diabetics, and to explore quality of management by determining the frequency of ankle-brachial index (ABI) measurement among them. Moreover, it aimed to educate people about PAD and its risk factors. Place and Duration: In the Medicine Unit II of Services Hospital, Lahore for one-year duration from March 2018 to March 2019. Methods and materials: A cross-sectional study involving 161 diabetic patients. They were interviewed using a questionnaire about demographics, past medical history and ordinary history. The second part concerned the physical examination of the lower limbs and ABI measurements; values below 0.9 or higher than 1.3 were considered incorrect. Results: Of the 161 diabetic patients included in the study, 104 (64.6%) were middle-aged 55.3 ± 11.472 and 59.39 ± 12.974 male. 55.9% were hypertensive and 75.8% hypercholesterolemic. 18 (11.2%) smokers were 14 (77.8%) men. 64 (39.8%) cases performed regular exercises, 38 (59.4%) were women. ITB Conclusion: In Pakistan, one fifth of DM patients had PAD; the majority is asymptomatic and was females. Large percent of the subjects were not checked by ABI, or the patient was not well informed about PAD, which urge all physicians to consider a periodic check-up for PAD using ABI. Majority of subjects had multiple co morbidities. Keywords: peripheral artery disease; Diabetes; atherosclerosis; Ankle arm indicator; superiority

Clinicians in the frontline need to assess quickly whether a patient with symptoms indeed has COVID-19 or not. The difficulty of this task is exacerbated in low resource settings that may not have access to biotechnology tests. Furthermore, Tuberculosis (TB) remains a major health problem in several low- and middle-income countries and its common symptoms include fever, cough and tiredness, similarly to COVID-19. In order to help in the detection of COVID-19, we propose the extraction of deep features (DF) from chest X-ray images, a technology available in most hospitals, and their subsequent classification using machine learning that do not require large computational resources. We compiled a five-class dataset of X-ray chest images including a balanced number of COVID-19, viral pneumonia, bacterial pneumonia, TB, and healthy cases. We compared the performance of proposed pipelines combining 14 individual pre-trained deep networks for DF extraction with machine learning classifiers. A novel pipeline consisting of ResNet-50 for DF computation and ensemble of subspace discriminant classifier was the best performer in the classification of the five classes, achieving a detection accuracy of 91.6 ± 0.57% (± Confidence Interval, CI) at 95% confidence level). Furthermore, the same pipeline achieved accuracies of 98.6 ± 0.34% (± CI) and 99.9% in three-class and two-class problems focused on distinguishing COVID-19, TB and healthy cases; and COVID-19 and healthy images; respectively. The pipeline was computationally efficient requiring just 0.19 s to extract DF per X-ray image and 2 min for training a classifier on a CPU machine. The results suggest the potential benefits of using our pipeline in the detection of COVID-19, particularly in resource-limited settings as it relies in accessible X-rays and limited computational resources. The final constructed dataset, named COVID-19 five-class dataset and codes, are available from https://drive.google.com/drive/folders/1toMymyHTy0DR_fyE7hjO3LSBGWtVoPNf?usp=sharing.

Dyslipidemia is a risk factor for cardiovascular disease, steatohepatitis, and progression of liver disorders. This study investigated the protective effect of farnesol (FAR), a sesquiterpene alcohol, against liver injury in high cholesterol diet (HCD)-fed rats, and its modulatory effect on fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC). HCD was supplemented for 10 weeks, and the rats were concurrently treated with FAR. Rats that received HCD exhibited significant elevation of serum cholesterol, triacylglycerols, LDL and vLDL cholesterol, CRP, and pro-inflammatory cytokines and increased values of the cardiovascular risk indices. Serum transaminases, ALP, LDH and CK-MB, and hepatic lipid peroxidation (LPO), cholesterol, and triacylglycerols were increased in HCD-fed rats. Treatment with FAR greatly ameliorated dyslipidemia and liver function, reduced inflammatory mediators, LPO, and hepatic lipid infiltration and enhanced anti-oxidant defenses. FAR suppressed hepatic FAS, ACC, and SREPB-1c mRNA abundance and FAS activity in HDC-fed rats. In addition, molecular docking simulations pinpointed the binding modes of FAR to the active pocket residues of FAS and ACC. In conclusion, FAR possesses a strong anti-hyperlipidemic/anti-hypercholesterolemic activity mediated through its ability to modulate hepatic FAS, ACC, and SREPB-1c. FAR prevented oxidative stress, inflammation, and liver injury induced by HCD. Thus, FAR may represent a promising lipid-lowering agent that can protect against dyslipidemia and its linked metabolic deregulations.

We report here the fabrication and validation of a novel 3D-printed, automated immunoarray to detect multiple proteins with ultralow detection limits. This low cost, miniature immunoarray employs electrochemiluminescent (ECL) detection measured with a CCD camera and employs touch-screen control of a micropump to facilitate automated use. The miniaturized array features prefilled reservoirs to deliver sample and reagents to a paper-thin pyrolytic graphite microwell detection chip to complete sandwich immunoassays. The detection chip achieves high sensitivity by using single-wall carbon nanotube—antibody conjugates in the microwells and employing massively labeled antibody-decorated RuBPY—silica nanoparticles to generate ECL. The total cost of an array is $0.65, and an eight-protein assay can be done in duplicate for $0.14 per protein with limits of detection (LOD) as low as 78–110 fg mL(−1) in diluted serum. The electronic control system costs $210 in components. Utility of the automated immunoarray was demonstrated by detecting an eight-protein prostate cancer biomarker panel in human serum samples in 25 min. The system is well suited to future clinical and point-of-care diagnostic testing and could be used in resource-limited environments.

Classification of satellite images is an important key for ground features extraction and thematic maps production. Satellite images with multi-spectral bands provide rich data which is useful for features extraction and description. Many supervised classification methods have been developed for classifying the multispectral images. Each method has its own advantages and disadvantages (limitations). In this paper the performance of four of the common used supervised classification techniques is compared. The techniques considered here are: Parallelepiped (PP), Minimum Distance (MD), Mahalanobies (MA), and Maximum Likelihood (ML). They are applied on a set of multispectral images acquired by Worldview-2 satellite. The classification results accuracy are analyzed and evaluated The research work flow is processed by using ENVI. The developed maps are then visually compared with each other and accuracy assessments utilizing ground-truths. The assessment of classification results is represented in confusion matrix format and determination of Kappa coefficients. The preliminary results show that Maximum Likelihood (ML) gives accurate classification result for the area of study with overall accuracy 91.5741% and it is evaluated by Kappa coefficient which is 0.8846

Objectives The current study aims to investigate the analgesic effect of oral hyoscine-N-butyl bromide (HBB) for alleviating pain during hysterosalpingography (HSG). Study design Randomized, double-blind, placebo-controlled study. Study setting Assiut University Hospital, Egypt. Materials and methods The study was conducted between March and May 2016. Infertile women scheduled for HSG were randomized (1:1) to HBB or Placebo group. All women received oral 20 mg HBB or placebo tablets 30 min before the procedure. The primary outcome was the participant's self-rated pain perception utilizing a 10-cm Visual Analogue Scale (VAS) with 0 = no pain, and 10 = worst imaginable pain during the HSG procedure. Results Ninety-four women were enrolled (n = 47 in each group). No difference in the baseline characteristics. Oral HBB does not reduce the median VAS pain scores during injection of the dye (3.75 vs. 4.5, p = 0.195), immediately post-procedure (3 vs. 3, p = 0.102) and 30 min post-procedure (2 vs. 2.5, P = 0.745). No significant differences in women satisfaction score (p = 0.302). The rate of side effects was higher in the HBB group especially nausea (14.9%) and dizziness (10.6%) (p = 0.0001). Conclusion Utility of oral HBB 30 min before HSG has no benefit in alleviating the induced pain during and 30 min after the HSG procedure.

The main objective of this investigation was carried out to study the ability of utilizing greenhouse solar dryers for drying of corn in order to obtain the best quality of dried grains for using it as seeds with the least drying time, and comparing with the natural sun drying method. Thus, contributing to increase the productivity. Corn cv. (Giza 168) was used for the experimental work at initial moisture content of 31.73% on dry basis (d.b). Two different drying methods of corn were tested for drying of ear and shelled corn. The two methods were natural sun drying and solar drying using greenhouse type solar dryers at different air velocities (0.5, 1.0 and 1.5 m/s). The experiments were carried out in rice mechanization center at Meet El- Dyba, Kafr El-Sheikh Governorate, Egypt during September 2016. Experiment included the flowing variables Two different drying methods (Solar drying method using greenhouse type solar dryer and natural sun drying method). Two different conditions of corn (complete ear-shelled corn). Three different air velocity (0.5, 1.0 and 1.5 m/s). High moisture ear and shelled corn was dried by using solar energy for heating air inside a greenhouse and compared with natural sun drying method. The results of quality tests that included standard germination test, vigor test and tetrazolium test for both drying methods for ear and shelled corn recorded high percentages for all treatments except solar drying of ear corn at air velocities 0.5 and 1.0 m/s. The average air temperature inside the solar dryer at air velocities 0.5 and 1.0 m/s reached to 43.9 and 42.4 ˚C respectively. High temperatures killed the germ of corn so the quality tests were reduced. Germination percentage of natural sun dried ear corn was 97 % and for solar dried samples at air velocities 0.5, 1.0 and 1.5 m/s was 79, 81, and 89%, respectively. The corresponding values for shelled corn were 93, 97 and 98 %.and 95 % for natural sun dried ones. The vigor test of dried ear corn recorded 90 for natural sun drying method and 34, 45, and 66% for solar drying at air velocities of 0.5, 1.0 and 1.5 m/s, respectively. The corresponding values for shelled corn were 86, 96 and 97% respectively, and 82 for natural sun dried samples. The recorded drying times were 26, 24 and 28 hours to reduce the moisture content from an initial level of 31.73 to final level of 14.07% (d.b.) for ear corn and for shelled corn were 20, 16 and 24 hours to reduce the moisture content from an initial level of an initial level of 31.73 to final level of 14.07% (d.b.) for ear corn and for shelled corn were 20, 16 and 24 hours to reduce the moisture content from an initial level of 27.23% to 14.12% compared with 46 and 38 hours for ear and shelled corn dried by natural sun drying method. Hourly costs of ear corn drying were 0.95, 0.88, 1.00 and 1.03 L.E/ kg for solar drying at air velocities 0.5, 1.0 , 1.5m/s and natural sun drying respectively. The corresponding values for shelled corn were 0.74, 0.58, 0.89 and 0.96 L.E/ kg.

Olive oil and leaf extract have several health benefits; however, their beneficial effect against fluoxetine-induced liver injury has not been investigated. The present study aimed to scrutinize the impact of fluoxetine on the liver of rats and to evaluate the protective effects of olive oil and leaf extract. Rats received fluoxetine orally at dose of 10 mg/kg body weight for 7 consecutive days. The fluoxetine-induced rats were concurrently treated with olive oil or leaf extract. At the end of the experiment, blood and liver samples were collected for analysis. Fluoxetine administration significantly increased circulating ALT, AST, ALP and the pro-inflammatory cytokines TNF-α and IL-1β levels in rats. Histological analysis showed several alterations, such as inflammatory cells infiltration, hepatocyte vacuolation and dilated sinusoids in the liver of fluoxetine-induced rats. Concurrent supplementation of olive oil and olive leaf extract significantly reduced circulating liver function marker enzymes and pro-inflammatory cytokines, and prevented fluoxetine-induced histological alterations. Both olive oil and leaf extract significantly decreased liver lipid peroxidation and nitric oxide, and ameliorated liver glutathione, superoxide dismutase, catalase and glutathione peroxidase. In addition, olive oil and leaf extract prevented fluoxetine-induced apoptosis in the liver of rats as evidenced by decreased expression of Bax and caspase-3, and up-regulated expression of Bcl-2. In conclusion, olive oil and leaf extract protect against fluoxetine-induced liver injury in rats through attenuation of oxidative stress, inflammation and apoptosis.

Structurally diverse piperazine-based compounds hybrid with thiadiazole, isatin or with sulfur/nitrogen, functionalities were synthesized. The structures of the new compounds were established based on their spectral data and elemental analysis. The physicochemical, bioactivity scores and pharmacokinetic behavior of all the prepared ligands were evaluated using in silico computational tools. The new piperazine ligands have been screened for their inhibition activity against SARS-CoV-2 protease enzyme using molecular docking analysis. The docking studies showed that all the ligands have been docked with negative dock energy onto the target protease protein. Moreover, Molecular interaction studies revealed that SARS-CoV-2 protease enzyme had strong hydrogen bonding interactions with piperazine ligands. The present in silico study thus, provided some guidance to facilitate drug design targeting the SARS-CoV-2 main protease., Graphical abstract Image, graphical abstract

Low cost, miniaturized assay platforms that work with small sample volumes, high sensitivity and rapid detection will have high value in future biomolecular diagnostics. Herein we report an automated, 3D printed electrochemiluminescent (ECL) immunoarray integrated with a nanostructured pyrolytic graphite sheet (PGS) microwell chip configured to detect 2 proteins simultaneously from complex liquid samples with high sensitivity and selectivity. Assays are done in 18 min at cost of < $1.00 using 1–2 microliters of sample. 3D printed microfluidic array design integrates reagent and sample chambers with rapid ECL detection. A commercial programmable syringe pump used with a preset program allows pump to pause and resume reagent delivery as required for completion of the sandwich immunoassays. Nanostructured surfaces feature antibody-decorated single wall carbon nanotube forests on PGS chip microwells, and sensitivity is amplified via massively labeled RuBPY-silica nanoparticles for detection. Prostate specific antigen (PSA) and prostate specific membrane antigen (PSMA) were measured simultaneously from human serum on the immunoarray with detection limits 150 fg mL(−1) for PSA and 230 fg mL(−1) for PSMA, with dynamic ranges up to 5 ng mL(−1). Validation of the immunoarray by measuring these proteins in human serum showed good correlation with single protein ELISA. These 3D printed platforms can be easily adapted to multiple applications and configurable CAD files for the immunoarray can be downloaded from our lab’s website.

This research aimed to determine the change of cutting knives decision depending on knife wear phenomena, anditseffect on hammer mill productivity and product quality. It can be done by tracing the knives wear stages and determine its safe time range to replace the knives. The experiments were done in El-Serw village Damietta Governorate from 2014 to 2016, by grinding both of corn ear and dough as popular agricultural productive using the traditional hammer mill. The studied variables also are four concaves hole diameters (2.5, 4.0, 8.0 and 12.0 mm), five operating hours of new knife, 150, 200, 250 and 300 h for corn ear. While, for dough, are used two concaves hole diameters (2.5 and 4.0 mm) and operating hours of new knife, 200, 400, 600 and 800 h. The measurement includes specifications of knives, product quality and hammer mill performance. The research recommended that the hammer mill knives must replacement after 220 operating hours to grind corn ear and 600 operating hours to grind dough which represents the safe limit time to keep product quantity and quality in accepted state.

Rapid population growth and agricultural intensification have been directly associated with land degradation and with visible deterioration in water quality in the Ethiopian lakes. Assessing the extent and origin of pollution is cumbersome because of the lack of measurements for water quality parameters. This paper reports on the dissolved phosphorus (DP) concentrations in Lake Tana and its tributaries during 3 years from 2010 to 2012 and the four rainy months in 2014. Concentrations in the headwaters, at the gaging station, at the river mouth, near shore (littoral), and in the open lake (pelagic) were measured for the four major rivers. DP concentration in the rivers was on the average 0·32 mg l−1, and DP in the lake was much lower with an average concentration of 0·10 mg l−1. Temporally, DP concentrations were greater in the rainy phase of the monsoon than in the dry phase from November through March. Moreover, an upward trend in DP concentrations is coinciding with the area expansion of water hyacinths in the lake. Copyright © 2017 John Wiley & Sons, Ltd.

Background and Objective: Diabetes Mellitus (DM) is a major healthcare problem worldwide and considerable evidence proved its negative impact on the male reproductive system. Adenium obesum is an interesting medicinal plant with a wide range of bioactivities. The current study examined the protective effects of A. obesum flower extract (AOE) on testicular injury in streptozotocin (STZ)-induced type I diabetic rats. Materials and Methods: Diabetes was induced by a single injection of 50 mg kg(-1) STZ. Diabetic rats received 250 and 500 mg kg(-1) AOE for 21 days and samples were collected for analysis. Results: As compared to the diabetic control rats, treatment with AOE increased serum testosterone, Follicle-Stimulating Hormone (FSH) and Luteinizing Hormone (LH) levels, decreased testicular thiobarbituric acid reactive substances (TBARS) content, effectively enhanced reduced glutathione (GSH) content and superoxide dismutase (SOD) activity. Additionally, AGE effectively inhibited diabetes-induced testicular tissue injuryand prevented inflammatoryand apoptotic responses manifested by decreased TNF-alpha, IL-6 and Bax and increased Bcl-2. Conclusion: These results demonstrated that AGE mitigates testicular injury, oxidative stress, inflammatory response and apoptotic cell death in STZ-induced diabetic rats.