Anti-inflammatory and analgesic effects of Coriandrum sativum L. in animal models

An important part of ethnopharmacology is study of pharmacological effects of medicinal plants and natural compounds in animal models. In this study the anti-inflammatory and analgesic effects of Coriandrum sativum L. seeds were evaluated. The total hydroalcoholic and flavonoid extract of the seeds were prepared and concentrated. Essential oil of coriander was obtained by soxhlet extractor, using pentane as solvent. Carrageenan (CAR) test was used for evaluation of anti-inflammatory effect. In this test 100ml of CAR suspension (1%w/v) was injected into subplantar space of rat hind paw and volume of paw was measured at 0 and 3 hrs after injection. For evaluation of analgesic effect writhing and formalin tests were used. For Writhing test, acetic acid (1%v/v) at a dose of 10 ml/kg was injected intraperitonealy (i.p.) and 10 min later the number of writhes was counted during a 10 minutes period. In formalin test, the paw licking time was measured during phase 1(0-5 min) and phase 2 (20-25min) after injection of 50 ml of formalin (2.5%v/v). Gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS) analysis showed that linalool (83.1%) is the major constituent of coriander essential oil. Our results showed that Coriander had no anti-inflammatory effect in CAR test. In writhing test, only the essential oil (4ml/100g,P.O) had a significant effect (P<0.01). Total extract, polyphenolic extract and essential oil of coriander, had significant effect in both phases of formalin test. Since the major constituent of coriander essential oil is linalool, it seems that it may be responsible for the effects

Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images

Noisy data and the similarity in the ocular appearances caused by different ophthalmic pathologies pose significant challenges for an automated expert system to accurately detect retinal diseases. In addition, the lack of knowledge transferability and the need for unreasonably large datasets limit clinical application of current machine learning systems. To increase robustness, a better understanding of how the retinal subspace deformations lead to various levels of disease severity needs to be utilized for prioritizing disease-specific model details. In this paper we propose the use of disease-specific feature representation as a novel architecture comprised of two joint networks -- one for supervised encoding of disease model and the other for producing attention maps in an unsupervised manner to retain disease specific spatial information. Our experimental results on publicly available datasets show the proposed joint-network significantly improves the accuracy and robustness of state-of-the-art retinal disease classification networks on unseen datasets.Comment: \c{opyright} 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images

Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processing, machine learning and deep learning algorithms have been used for early detection and diagnosis of retinal diseases. Unfortunately, these are prone to error and computational inefficiency, which requires further intervention from human experts. In this paper, we propose a novel convolution neural network architecture to successfully distinguish between different degeneration of retinal layers and their underlying causes. The proposed novel architecture outperforms other classification models while addressing the issue of gradient explosion. Our approach reaches near perfect accuracy of 99.8% and 100% for two separately available Retinal SD-OCT data-set respectively. Additionally, our architecture predicts retinal diseases in real time while outperforming human diagnosticians.Comment: 8 pages. Accepted to 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019

Effect of Pullback Speed and the Distance between the Skin and Vein on the Performance of Endovenous Laser Treatment by Numerical Simulation

Introduction: Endovenous laser treatment (ELT) is a new treatment method for the reflux of the great saphenous vein. A successful ELT is dependent on the selection of optimum parameters required to achieve optimal vein damage while avoiding side effects including skin burns. The mathematical modeling of ELT can be used to understand the process of ELT. This study was conducted to examine the effect of laser pullback speed and the distance between the vein and skin on the performance of ELT. Material and Methods: The finite element method was used to develop optical-thermal damage models and simulate the process of ELT process. Firstly, light distribution was modeled using the diffusion approximation of the transport theory. On the second step, temperature rise was determined by solving the bioheat equation. Considering the temperature field, the extension of laser-induced tissue damage was estimated using Arrhenius model. Results: Regarding the results, pullback speed and the distance between the vein and the skin distance can affect the process of ELT. Moreover, the pullback speed of 1 mm/s, 2 mm/s, and 4mm/s were suitable for the treatment of varicose veins located in a depth of 15 mm, 10 mm, and 5 mm, respectively. Conclusion: In the ELT method, the pullback speed should be determined considering the geometry of the varicose vein segments, especially the distance between the skin and vein

A Randomized Comparative Trial on the Therapeutic Efficacy of Topical Aloe vera and Calendula officinalis on Diaper Dermatitis in Children

Introduction. Diaper dermatitis (DD) is a common inflammatory disorder among children and infants. The objective of the present randomized and double-blind trial was to compare the therapeutic efficacies of Aloe vera cream and Calendula officinalis ointment on the frequency and severity of DD in children. Methods. Sixty-six infants with DD (aged < 3 years) were randomized to receive either Aloe cream (n = 32) or Calendula ointment (n = 34). Infants were treated with these drugs 3 times a day for 10 days. The severity of dermatitis was graded at baseline as well as at the end of trial using a 5-point scale. The adverse effects of study medications were assessed during the trial. Results. Although improvement in the severity of DD was observed in both treatment groups (P < 0.001), patients receiving Calendula ointment had significantly fewer rash sites compared to Aloe group (P = 0.001). No adverse effect was reported from either of the medications. Discussion. The evidence from this study suggests that topical Aloe and in particular Calendula could serve as safe and effective treatment for the treatment of diaper dermatitis in infants

Enhancing the performance of residential construction project through stakeholder satisfaction: the application of structural equation modelling (SEM)

Project-based companies require a proactive approach so that the needs and interests of stakeholders can be satisfied. In line with the stakeholder theory, Project Management Body of Knowledge (PMBOK) is a guideline, which has been developed to enhance residential construction project performance by fulfilling stakeholder needs and interests. In accordance to the literature review, studies which highlight the effects of guidelines on project performance are few and far in between. In investigating the association between this study's variables, a quantitative methodology, where cross-sectional survey method is involved, was applied. The collected data, which consisted of a random sample of 384 buyers and developers from the residential sectors of construction project in Iran, was categorized Subsequently, the response rate generally amounted to 44.1%. Structural Equation Modelling (SEM) technique was used through SmartPLS software to investigate the relationship of variables. Based on the results, the positive relation between project performance, stakeholder satisfaction, and project stakeholder management are prominent It is also revealed by the results that positive project performance, buyers' satisfaction, and project stakeholder management is also prominent. Moreover, the results show that the implementation of PMBOK standard through the mediating variables of buyers' satisfaction provides a positive impact on project performance. Additionally, resource-based theory, along with resource dependence and stakeholder theories were incorporated in this study in order to create a new theoretical framework, where the significance of social capital in enhancing project performance is evident. © Vilnius University, 2002-2018