PH regulation of amphotericin B channels activity in the bilayer lipid membrane

Background: Amphotericin B (AmB) is a polyene antibiotic frequently applied in the treatment of systemic fungal infections in spite of its secondary effects. The pH plays a crucial role in modulating biophysical features of ion channels in the bilayer lipid membranes. Aim: In this study, the role of pH in the regulation of AmB channel was assessed by single channel recording of ion channel incorporated in the artificial membrane. Materials and Methods: Bilayer lipid membrane was formed by phosphatidylcholine in a 350 m diameter aperture between two chambers, cis and trans contained 200/50 mMKCl solutions, respectively; then AmB was incorporated into the bilayer lipid membrane. Single channel recordings were used to indicate the effects of pH changes on AmB channels activity. The records were analyzed by Clamp fit 10 software. Results: A kinetic analysis of single channel currents indicated a cation ion channel with 500 pS conductance and voltage-dependence of the open probability of the AmB channel (Po ). A reduction of cis pH to 6 decreased Po and conductance. This effect was also voltage-dependent, being greater at a more positive above -40. The pH changes in the range of 6-8 had no effect on the reversal potential and ion selectivity. Conclusion: Our data indicated that extracellular acidity can reduce AmB activity. © 2016 Journal of Natural Science, Biology and Medicine | Published by Wolters Kluwer - Medknow

Electrophysiological characteristics of cationic single-channel formed by incorporation of amphotericin b in bilayer lipid membrane

BACKGROUND AND OBJECTIVE: Amphotericin B (AmB) is the main antibiotic of polyene type, which is widely used in the treatment of systemic fungal infections. One of the key mechanisms of this drug is the formation of ion channels and increasing permeability of the host cell membranes. This study was conducted to evaluate some of the electrophysiological characteristics of cationic single-channel formed by the incorporation of AmB in bilayer lipid membrane (BLM). METHODS: In this experimental study, phosphatidyl choline was extracted from fresh egg yolk. After the formation of BLM and the incorporation of AmB in the membrane, the channel activity was recorded through +40 to -40 millivolt (mV) voltages. Data analysis was conducted using PClamp10 software to determine the electrophysiological characteristics of the channel. FINDINGS: Reverse potential of Amphotericin B ion Channel was-36 mV. The Channel activity was more in such positive voltages. This means that in voltage -40 mV the current amplitude was 2 Pico Ampère but in voltage +40 mV reach to 30 Pico Ampère. In addition, the channel open probability at voltage -30 mV voltage was low (less than 0.15) but increased to 0.75 in voltage +40 mV. The channel conductance was also 157±4.9 Picoseimence. CONCLUSION: AmB forms cationic channels in BLMs with phosphatidylcholine and without cholesterol. This channel has voltage-dependent electrophysiological characteristics and behaviors. © 2016, Babol University of Medical Sciences. All rights reserved

Conceptual framework for developing a diabetes information network

Objective: To provide a conceptual framework for managing diabetic patient care, and creating an information network for clinical research. Background: A wide range of information technology (IT) based interventions such as distance learning, diabetes registries, personal or electronic health record systems, clinical information systems, and clinical decision support systems have so far been used in supporting diabetic care. Previous studies demonstrated that IT could improve diabetes care at its different aspects. There is however no comprehensive conceptual framework that defines how different IT applications can support diverse aspects of this care. Therefore, a conceptual framework that combines different IT solutions into a wide information network for improving care processes and for research purposes is widely lacking. In this study we describe the theoretical underpin of a big project aiming at building a wide diabetic information network namely DIANET. Research design and methods: A literature review and a survey of national programs and existing regulations for diabetes management was conducted in order to define different aspects of diabetic care that should be supported by IT solutions. Both qualitative and quantitative research methods were used in this study. In addition to the results of a previous systematic literature review, two brainstorming and three expert panel sessions were conducted to identify requirements of a comprehensive information technology solution. Based on these inputs, the requirements for creating a diabetes information network were identified and used to create a questionnaire based on 9-point Likert scale. The questionnaire was finalized after removing some items based on calculated content validity ratio and content validity index coefficients. Cronbach's alpha reliability coefficient was also calculated (α Total= 0.98, P < 0.05, CI=0.95). The final questionnaire was containing 45 items. It was sent to 13 clinicians at two diabetes clinics of endocrine and metabolism research institute in order to assess the necessity level of the requirements for diabetes information network conceptual framework. The questionnaires were returned by 10 clinicians. Each requirement item was labeled as essential, semi-essential, or non-essential based on the mean of its scores. Results: All requirement items were identified as essential or semi-essential. Thus, all of them were used to build the conceptual framework. The requirements were allocated into 11 groups each one representing a module in the conceptual framework. Each module was described separately. Conclusion: We proposed a conceptual framework for supporting diabetes care and research. Integrating different and heterogeneous clinical information systems of healthcare facilities and creating a comprehensive diabetics data warehouse for research purposes, would be possible by using the DIANET framework. � 2016 Hossein Riazi, Mostafa Langarizadeh, Bagher Larijani, and Leila Shahmoradi

Determination of minimum data set (MSD) in echocardiography reporting system to exchange with Iran's electronic health record (EHR) system

Background: Determination of minimum data set (MDS) in echocardiography reports is necessary for documentation and putting information in a standard way, and leads to the enhancement of electrocardiographic studies through having access to precise and perfect reports and also to the development of a standard database for electrocardiographic reports. Aim: To determine the minimum data set of echocardiography reporting system to exchange with Iran's electronic health record (EHR) system. Methods: First, a list of minimum data set was prepared after reviewing texts and studying cardiac patients' records. Then, to determine the content validity of the prepared MDS, the expert views of 10 cardiologists and 10 health information management (HIM) specialists were obtained; to estimate the reliability of the set, test-retest method was employed. Finally, the data were analyzed using SPSS software. Results: The highest degree of consensus was found for the following MDSs: Patient's name and family name (5), accepting doctor's name and family name, familial death records due to cardiac disorders, the image identification code, mitral valve, aortic valve, tricuspid valve, pulmonary valve, left ventricle, hole, atrium valve, Doppler examination of ventricular and atrial movement models and diagnoses with an average of. Conclusions: To prepare a model of echocardiography reporting system to exchange with EHR system, creation a standard data set is the vital point. Therefore, based on the research findings, the minimum reporting system data to exchange with Iran's electronic health record system include information on entity, management, medical record, carried-out acts, and the main content of the echocardiography report, which the planners of reporting system should consider. © 2016 Zahra Mahmoudvand, Mehran Kamkar, Leila Shahmoradi, Ahmadreza Farzaneh Nejad

Managing diabetes mellitus using information technology: A systematic review

Objective: To review published evidences about using information technology interventions in diabetes care and determine their effects on managing diabetes. Design: Systematic review of information technology based interventions. Research design and methods: MEDLINE®/PubMed were electronically searched for articles published between 2004/07/01 and 2014/07/01. A comprehensive, electronic search strategy was used to identify eligible articles. Inclusion criteria were defined based on type of study and effect of information technology based intervention in relation to glucose control and other clinical outcomes in diabetic patients. Studies must have used a controlled design to evaluate an information technology based intervention. A total of 3613 articles were identified based on the searches conducted in MEDLINE from PubMed. After excluding duplicates (n = 6), we screened titles and abstracts of 3607 articles based on inclusion criteria. The remaining articles matched with inclusion criteria (n = 277) were reviewed in full text, and 210 articles were excluded based on exclusion criteria. Finally, 67 articles complied with our eligibility criteria and were included in this study. Results: In this study, the effect of various information technology based interventions on clinical outcomes in diabetic patients extracted and measured from selected articles is described and compared to each other. Conclusion: Information technology based interventions combined with the usual care are associated with improved glycemic control with different efficacy on various clinical outcomes in diabetic patients. © 2015 Riazi et al

Differential diagnosis of Erythmato-Squamous Diseases using classification and regression tree

Introduction: Differential diagnosis of Erythmato-Squamous Diseases (ESD) is a major challenge in the field of dermatology. The ESD diseases are placed into six different classes. Data mining is the process for detection of hidden patterns. In the case of ESD, data mining help us to predict the diseases. Different algorithms were developed for this purpose. Objective: we aimed to use the Classification and Regression Tree (CART) to predict differential diagnosis of ESD. Methods: we used the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. For this purpose, the dermatology data set from machine learning repository, UCI was obtained. The Clementine 12.0 software from IBM Company was used for modelling. In order to evaluation of the model we calculate the accuracy, sensitivity and specificity of the model. Results: The proposed model had an accuracy of 94.84 (Standard Deviation: 24.42) in order to correct prediction of the ESD disease. Conclusions: Results indicated that using of this classifier could be useful. But, it would be strongly recommended that the combination of machine learning methods could be more useful in terms of prediction of ESD. © 2016 Keivan Maghooli, Mostafa Langarizadeh, Leila Shahmoradi, Mahdi Habibi-koolaee, Mohamad Jebraeily, and Hamid Bouraghi

Comparing Three Data Mining Methods to Predict Kidney Transplant Survival

Introduction: One of the most important complications of post-transplant is rejection. Analyzing survival is one of the areas of medical prognosis and data mining, as an effective approach, has the capacity of analyzing and estimating outcomes in advance through discovering appropriate models among data. The present study aims at comparing the effectiveness of C5.0 algorithms, neural network and C & RTree to predict kidney transplant survival before transplant. Method: To detect factors effective in predicting transplant survival, information needs analysis was performed via a researcher-made questionnaire. A checklist was prepared and data of 513 kidney disease patient files were extracted from Sina Urology Research Center. Following CRISP methodology for data mining, IBM SPSS Modeler 14.2, C5.0, C&RTree algorithms and neural network were used. Results: Body Mass Index (BMI), cause of renal dysfunction and duration of dialysis were evaluated in all three models as the most effective factors in transplant survival. C5.0 algorithm with the highest validity (96.77) was the first in estimating kidney transplant survival in patients followed by C&RTree (83.7) and neural network (79.5) models. Conclusion: Among the three models, C5.0 algorithm was the top model with high validity that confirms its strength in predicting survival. The most effective kidney transplant survival factors were detected in this study; therefore, duration of transplant survival (year) can be determined considering the regulations set for a new sample with specific characteristics. © 2016 Leila Shahmoradi, Mostafa Langarizadeh, Gholamreza Pourmand, Ziba Aghsaei fard, and Alireza Borhani

The evolution of food security: where are we now, where should we go next?

Food security is one of the most challenging topics globally; however, the concept of food security has taken on additional dimensions that are general and are less detailed. This study aims to identify the intellectual structure of food security research and the changes in this structure. This paper analyzed 3169 documents from the Web of Science database through a bibliometric review. A review of the published documents shows an increasing trend over the past 46 years. In accordance with co-occurrence analysis, 125 keywords were grouped into five clusters: food security and sustainable development; food security and socioeconomic factors; food security policy and governance; coping strategies for poverty, inequality, and hunger; and modern food security management. This study identifies four streams within food security research: sustainability and environmental, socioeconomic, cultural, and political factors. The paper concludes that even though food security might investigate many significant areas, other new dimensions should still be considered. Further gaps in the literature emerge that present avenues for future research directions. Reviewing indicators and techniques of food security assessment and identifying high-risk groups should be a priority

Quality improvement of liver ultrasound images using fuzzy techniques

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. © 2016 Azadeh Bayani, Leila Shahmoradi, Mostafa Langarizadeh, Amir Reza Radmard, and Ahmadreza Farzaneh Nejad

The Temporal and Spectral Characteristics of "Fast Rise and Exponential Decay" Gamma-Ray Burst Pulses

In this paper we have analyzed the temporal and spectral behavior of 52 Fast Rise and Exponential Decay (FRED) pulses in 48 long-duration gamma-ray bursts (GRBs) observed by the CGRO/BATSE, using a pulse model with two shape parameters and the Band model with three shape parameters, respectively. It is found that these FRED pulses are distinguished both temporally and spectrally from those in long-lag pulses. Different from these long-lag pulses only one parameter pair indicates an evident correlation among the five parameters, which suggests that at least $\sim$4 parameters are needed to model burst temporal and spectral behavior. In addition, our studies reveal that these FRED pulses have correlated properties: (i) long-duration pulses have harder spectra and are less luminous than short-duration pulses; (ii) the more asymmetric the pulses are the steeper the evolutionary curves of the peak energy ($E_{p}$) in the $\nu f_{\nu}$ spectrum within pulse decay phase are. Our statistical results give some constrains on the current GRB models.Comment: 18 pages, 7 figures, accepted for publication in the Astrophysical Journa