Effect of Aescin in Psoriatic-Induced Animal Model: Immunohistochemical and Pathological Study

Background: Aescin is a mixture of the triterpene saponins extracted from the seeds of the horse chestnut tree Aesculus hippocastanum. Aescin has a venotonic, anti-inflammatory, antioxidant and anti-edematous characteristics that are mostly connected to the agent molecular mechanism. Objective: The present study aim to investigate the potential effects of Aescin on psoriasis induced by Imiquimod in male rats, ncluding its effect on the level of tumor necrosis factor alpha, Ki-67 and the histopathologic features of the psoriatic skin. Methods: Thirty-six albino male rats were divided into six groups each group containing 6 animals, psoriasis was induced by Imiquimod to five of the groups, while for the last group vasaline was applied and the group served as a control group. The animals were then treated with topical Aescin, topical clobetasol, combination of topical Aescin and clobetasol and oral Aescin, finally all animals were sacrificed and the dorsal back skin was taken to perform histopathological and immunohistochemical analysis. Results: regarding the level of Ki-67, Strong expression of Ki-67 was seen in the group who received Imiquimod only, where the scoring of Ki-67 was notably lowered among the other groups. However, the lowest expression was noticed in the group that were treated with the combination of topical Aescin and clobetasol. While the number of TNF-α positive cells and the intensity of immunostaining were higher in the induction group who received Imiquimod only and the lowest among the group who received the combination of topical Aescin and Clobetasol. Lastly the histopathologic analysis shows that the histopathologic features of psoriasis was markedly affected by the anti-inflammatory effect of Aescin and clobetasol, which was noticed through inhibition of proinflammatory markers, and the decrease in capillary permeability. Conclusion: Topical Aescin alone or in combination with clobetasol reduced Ki-67 expression successfully; furthermore, the combination of topical Aescin and Clobetasol decreased TNF- score and had the strongest anti-inflammatory activity more than the other groups. Lastly Aescin was able to alter the histopathologic features of the psoriatic skin through its anti-inflammatory, venotonic and anti-edematous activity

Aptamer Validation by Western Blot–an overview

Western blot is the main and basic technique in cellular and molecular biology. The principle of the western blot is the isolation and detection of the target molecule usually from a cellular extract. The whole process of western blot consists of three stages and can be described briefly as separation of   protein. followed by transportation to a solid membrane and finally detection of the target by an antibody. Western blot technique is usually used for the detection of proteins but also can be used to detect other molecules such as aptamers. Aptamers can be defined as a short-stranded DNA or RNA that bind with the target with high specificity and affinity. Aptamers highly resemble antibodies with many advantages. In this review, there is a focus on the aptamers that had validated by western blot technique other than other methods. This method has the advantage of   less time required, no antibodies needed, and introducing the possibility of multiplexing detection

Oxidative Stress and Antioxidant Status in Human InfectedWith Kala-azar

Malondialdehyde (MDA) is the most commonly marker that is used to investigate the presence of oxidative stress in biological system, and glutathione redox cycle is a major antioxidant defense system for the detoxification of reactive oxygen species (ROS) within erythrocyte. In the present study, we aimed to evaluate erythrocyte malondialdehyde (MDA) as an indicator for the oxidative status and erythrocyte reduced glutathione (GSH) level as indicators for the antioxidative status in Kala-azar patients. The study included sixty patient with Kala-azar and they were followedup after their complete chemotherapy with antileishmanial drug (sodium stibogluconate) for (4) weeks. Seventy normal healthy individuals of age and sex match who served as control. After data analysis the following observations were obtained, erythrocyte (MDA) and (GSH) level were significantly increased in Kala-azar patients as compared with normal healthy controls. After treatment, erythrocyte (MDA) and (GSH) level had decreased significantly as compared to patients before treatment groups. The results suggest that Kala-azar patients are in oxidative stress which most likely induces the endogenous antioxidant such as (GSH)

Optimum Median Filter Based on Crow Optimization Algorithm

يُقترح مرشح متوسط ​​جديد يعتمد على خوارزميات تحسين الغراب (OMF) لتقليل ضوضاء الملح والفلفل العشوائية وتحسين جودة الصور ذات اللون الرمادي والملونة . الفكرة الرئيسية لهذا النهج هي أن أولاً ، تقوم خوارزمية تحسين الأداء بالكشف عن وحدات البكسل الخاصة بالضوضاء ، واستبدالها بقيمة وسيطة مثالية تبعًا لدالة الأداء. أخيرًا ، تم استخدام نسبة القياس القصوى لنسبة الإشارة إلى الضوضاء (PSNR) ، والتشابه الهيكلي والخطأ المربع المطلق والخطأ التربيعي المتوسط ​​لاختبار أداء المرشحات المقترحة (المرشح الوسيط الأصلي والمحسّن) المستخدمة في الكشف عن الضوضاء وإزالتها من الصور. يحقق المحاكاة استنادًا إلى MATLAB R2019b والنتائج الحالية التي تفيد بأن المرشح المتوسط ​​المحسّن مع خوارزمية تحسين الغراب أكثر فعالية من خوارزمية المرشح المتوسط ​​الأصلية ومرشحات لطرق حديثة ؛ أنها تبين أن العملية المقترحة قوية للحد من مشكلة الخطأ وإزالة الضوضاء بسبب مرشح عامل التصفية المتوسط ​​؛ ستظهر النتائج عن طريق تقليل الخطأ التربيعي المتوسط ​​إلى أدنى أو أقل من (1.5) ، والخطأ المطلق للتساوي (0.22) ,والتشابه الهيكلي اكثر من ( 95%) والحصول على PSNR أكثر من 45dB).) وبنسبة تحسين ( 25%) .          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the results present that the improved median filter with crow optimization algorithm is more effective than the original median filter algorithm and some recently methods; they show that the suggested process is robust to reduce the error problem and remove noise because of a candidate of the median filter; the results will show by the minimized mean square error to equal or less than (1.38), absolute error to equal or less than (0.22) ,Structural Similarity (SSIM) to equal (0.9856) and getting PSNR more than (46 dB). Thus, the percentage of improvement in work is (25%)

SIRT1 activators as novel therapy for cancer

Sirutins 1-7 (SIRT1-7) is an enzyme that depends on NAD+ to be activated, making it a member of the 3rd class of Deacetylase enzymes. SIRT1-7’s activity is involved with metabolism, cell survival and/or death as well as DNA repair, gene repression, inflammatory responses, the   aging process, neuroprotection in addition to possibly helping with the treatment of cancer. Molecules that could have a modifying effect on SIRT1-7’s activity has caught a great attention recently, owing to the fact of how beneficial this enzyme could be. In this review, we attempt to shed a light on these activator compounds and their use in Sirutin activation therapy, particularly SIRT1, for it is the most researched type. One of these compounds is Resveratrol, a natural compound that –due to its SIRT 1 activation potential – could help in the treatment of obesity, prevention of tumor formation as well as decrease in heart function and neuronal loss related to aging; however, Resveratrol has poor bioavailability, which is why structurally reformulated compounds and molecules have been developed. Other molecules that are different from Resveratrol such as SRT1720, SRT2104 and SRT2379 in addition to others, have been used and shown greater activation potential for SIRT1 than Resveratrol

Systematic review of flaxseed (Linum usitatissimum L.) extract and formulation in wound healing

Context: Flaxseed constituents provide to antioxidant, anti-inflammatory, antimicrobial and wound healing benefits. Aims: To systematically review the experimental evidence on the wound healing ability of flaxseed extracts and formulations. Methods: Comprehensive searches in six databases (Scopus, Science Direct, Web of Science, PubMed, Google Scholar and Dimensions) were carried out from the beginning of databases until December 2020, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The terms used in searches were (Linum usitatissimum L., flaxseed, linseed, flax) AND (extract) AND (wound heal, heal, heal type, wound) for collection of articles, with only articles in English and research articles were included. Transgenic term were excluded. AXIS tool was chosen to assess the quality and risk of bias. The data were then categorised in term of extracts, laboratory formulation, and wound healing. Results: In total, 999 articles were collected and screened based on the pre-determined inclusion and exclusion criteria. Finally, 10 articles were included in the review. The majority of publications reported significant findings of flaxseed oil on wound healing regardless of extraction method and formulation. Healing parameters on excision, incision, and burn wound models were studied. Lack of laboratory formulation mentioned in the collected articles gave limitation impact on this study. Conclusions: Flaxseed oil formulation appears to exert a positive effect on wound healing. Therefore, extensive studies needed to evaluate the transportation of flaxseed phytochemicals into skin dermis by advanced drug formulation

A REVIEW PAPER: ANALYSIS OF WEKA DATA MINING TECHNIQUES FOR HEART DISEASE PREDICTION SYSTEM

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is a cardiovascular disease that causes death. Health problems are enormous in this recent situation because of the prediction and the classification of health problems in different situations. The data mining area included the prediction and identification of abnormality and its risk rate in these domains. Today the health industry holds hidden information essential for decision-making. For predicting heart problems, data extraction algorithms like K-star, J48, SMO, Naïve Bayes, MLP, Random Forest, Bayes Net, and REPTREE are used for this study (Weka 3.8.3) software. The results of the predictive accuracy, the ROC curve, and the AUC value are combined using a standard set of data and a collected dataset. By applying different data mining algorithms, the patient data can be used for diagnosis as training samples. The main drawbacks of the previous studies are that they need accurate and the number of features. This paper surveys recent data mining techniques applied to predict heart diseases. And Identifying the major risk factors of Heart Disease categorizing the risk factors in an order which causes damages to the heart such as high blood cholesterol, diabetes, smoking, poor diet, obesity, hypertension, stress, etc. Data mining functions and techniques are used to identify the level of risk factors to help the patients in taking precautions in advance to save their life

Preventive treatment of coronavirus disease-2019 virus using coronavirus disease-2019-receptor-binding domain 1C aptamer by suppress the expression of angiotensin-converting enzyme 2 receptor

The cause of the worldwide coronavirus disease-2019 (COVID-19) pandemic is the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). It is known to employ the same entry portal as SARS-CoV, which is the type 1 transmembrane angiotensin-converting enzyme 2 (ACE2) receptor. The receptor-binding domain (RBD) is located on the spike S-protein's S1 subunit of the spike glycoprotein. The most important and effective therapy method is inhibiting the interaction between the ACE2 receptor and the S-spike RBD. An aptamer is a small, single-chain oligonucleotide that binds strongly to the target molecule. Recently, a CoV-2-RBD-1C aptamer-based system with a 51-base hairpin structure was discovered to have substantial binding affinity against the SARS-CoV-2RBD with similar binding sites at ACE. In the current study, we will study the aptamer's effect as a SARS-CoV-2 spike blocker and inhibit its ACE2 receptors' binding by studying the toxicity of aptamer for this cell line by calcein assay and the inhibition test of CoV-2-RBD-1C aptamers on spike RBD–ACE2 binding. The results show the half-maximum inhibitory concentration of CoV-2-RBD-1C aptamer is 0.08188 μM. The inhibition effect of CoV-2-RBD-1C aptamer on spike RBD–ACE2 binding was determined at half-maximal effective concentration of 0.5 μM concentration. The percentage of spike-ACE2 binding inhibition in A549-hACE2 cells in the D614G variant after 30 s was 77%. This percentage is higher than D614 and N501Y and equals 55% and 65%, respectively, at 0.15 μM of CoV-2-RBD-1C aptamer. The CoV-2-RBD-1C aptamer prevents virus entrance through spike inhibition, which results in a 90% reduction in spike D614 virus transduction at 1.28 μM. In conclusion, the CoV-2-RBD-1C aptamer might be an effective treatment against COVID-19 infection because it directly affects the virus by blocking the S-spike of SARS-CoV-2 and preventing ACE2 receptor binding

Knockdown of α-Enolase (ENO1) to Suppress Glycolytic Pathway in Human Hepatocellular Carcinoma Cell Line (HepG2)

ABSTRACT Hepatocellular carcinoma therapies which are potentially curative depend on early diagnosis, but unfortunately only 20% is the 5-year survival rate of liver cancer despite of various treatment methods which progress continuously. Patients with hepatocellular carcinoma presenting with late stage disease despite established screening guidelines for patients at risk because of asymptomatic nature of this disease so finding effective treatments are imperative. Alpha-enolase has been noticed to be commonly over-expressed in tumors including hepatocellular carcinoma, it is one of the leading regulators of the Warburg effect, so plays an important role in carcinogenesis and tumor maintenance. In this study the cell line α-enolase short interference RNA was successfully constructed. In the α-enolase short interference RNA cell lines, messenger RNA and protein expression of α-enolase were lower than those in negative control and blank control groups. The pyruvate level was significantly inhibited, the proliferation ability was significantly suppressed. Our data provide strong evidence that α-enolase short interference RNA can efficiently suppress glycolysis pathway and thus the proliferation of Hep G2, which may provide a novel gene therapy for hepatocellular carcinoma

A REVIEW PAPER: ANALYSIS OF WEKA DATA MINING TECHNIQUES FOR HEART DISEASE PREDICTION SYSTEM

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is a cardiovascular disease that causes death. Health problems are enormous in this recent situation because of the prediction and the classification of health problems in different situations. The data mining area included the prediction and identification of abnormality and its risk rate in these domains. Today the health industry holds hidden information essential for decision-making. For predicting heart problems, data extraction algorithms like K-star, J48, SMO, Naïve Bayes, MLP, Random Forest, Bayes Net, and REPTREE are used for this study (Weka 3.8.3) software. The results of the predictive accuracy, the ROC curve, and the AUC value are combined using a standard set of data and a collected dataset. By applying different data mining algorithms, the patient data can be used for diagnosis as training samples. The main drawbacks of the previous studies are that they need accurate and the number of features. This paper surveys recent data mining techniques applied to predict heart diseases. And Identifying the major risk factors of Heart Disease categorizing the risk factors in an order which causes damages to the heart such as high blood cholesterol, diabetes, smoking, poor diet, obesity, hypertension, stress, etc. Data mining functions and techniques are used to identify the level of risk factors to help the patients in taking precautions in advance to save their life