Search results for: Diabetic nephropathy

Authors: Aditya Arya, Hairin Taha, Ataul Karim Khan, Nayiar Shahid, Hapipah Mohd Ali, Mustafa Ali Mohd

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This study has investigated the antidiabetic and antioxidant potential of Pseudovaria macrophylla bark extract on streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF and NMR experiments were done to determine the chemical composition in the methanolic bark extract. For in vivo experiments, the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.) induced diabetic rats were treated with methanolic extract of Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and glibenclamide (2.5 mg/kg) as positive control respectively. Biochemical parameters were assayed in the blood samples of all groups of rats. The pro-inflammatory cytokines, antioxidant status and plasma transforming growth factor βeta-1 (TGF-β1) were evaluated. The histological study of the pancreas was examined and its expression level of insulin was observed by immunohistochemistry. In addition, the expression of glucose transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by western blot analysis. The outcomes of the study displayed that the bark methanol extract of Pseuduvaria macrophylla has potentially normalized the elevated blood glucose levels and improved serum insulin and C-peptide levels with significant increase in the antioxidant enzyme, reduced glutathione (GSH) and decrease in the level of lipid peroxidation (LPO). Additionally, the extract has markedly decreased the levels of serum pro-inflammatory cytokines and transforming growth factor beta-1 (TGF-β1). Histopathology analysis demonstrated that Pseuduvaria macrophylla has the potential to protect the pancreas of diabetic rats against peroxidation damage by downregulating oxidative stress and elevated hyperglycaemia. Furthermore, the expression of insulin protein, GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced. The findings of this study support the anti-diabetic claims of Pseudovaria macrophylla bark.

Keywords: Diabetes mellitus, Pseuduvaria macrophylla, alkaloids, caffeic acid.

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Authors: Murat Koklu, Yavuz Unal

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Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.

Keywords: Artificial Intelligence, Classifiers, Data Mining, Diabetic Patients.

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Authors: C. C. Okafor, E. E. Ugwu

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A comparative study on the feasibility of producing instant high fibre plantain flour for diabetic fufu by blending soy residence with different plantain (Musa spp) varieties (Horn, false Horn and French), all sieved at 60 mesh, mixed in ratio of 60:40 was analyzed for their passing properties using standard analytical method. Results show that VIIIS60 had the highest peak viscosity (303.75 RVU), Trough value (182.08 RVU), final viscosity (284.50 RVU), and lowest in breakdown viscosity (79.58 RVU), set back value (88.17 RVU), peak time (4.36min), pasting temperature (81.18°C) and differed significantly (p <0.05) from other samples. VIS60 had the lowest in peak viscosity (192.25 RVU), Trough value (112.67 RVU), final viscosity (211.92 RVU), but highest in breakdown viscosity (121.61 RVU), peak time (4.66min) pasting temperature (82.35°C), and differed significantly (p <0.05), from other samples. VIIS60 had the medium peak viscosity (236.67 RVU), Trough value (116.58 RVU), Break down viscosity (120:08 RVU), set back viscosity (167.92 RVU), peak time (4.39min), pasting temp (81.44°C) and differed significantly (p <0.05) from other samples. High final viscosity and low set back values of the French variety with soy residue blended at 60 mesh particle size recommends this french variety and fibre composition as optimum for production of instant plantain soy residue flour blend for production of diabetic fufu. 

Keywords: Plantain, soy residue pasting properties particle size.

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: Diabetic retinopathy, fundus, CHT, exudates, hemorrhages.

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Authors: Sh. Yasini, M. B. Naghibi-Sistani, A. Karimpour

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This paper employs a new approach to regulate the blood glucose level of type I diabetic patient under an intensive insulin treatment. The closed-loop control scheme incorporates expert knowledge about treatment by using reinforcement learning theory to maintain the normoglycemic average of 80 mg/dl and the normal condition for free plasma insulin concentration in severe initial state. The insulin delivery rate is obtained off-line by using Qlearning algorithm, without requiring an explicit model of the environment dynamics. The implementation of the insulin delivery rate, therefore, requires simple function evaluation and minimal online computations. Controller performance is assessed in terms of its ability to reject the effect of meal disturbance and to overcome the variability in the glucose-insulin dynamics from patient to patient. Computer simulations are used to evaluate the effectiveness of the proposed technique and to show its superiority in controlling hyperglycemia over other existing algorithms

Keywords: Insulin Delivery rate, Q-learning algorithm, Reinforcement learning, Type I diabetes.

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Authors: Muhammad Zeeshan UlHaque, Peng Du, Leo K. Cheng, Marc D. Jacobs

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Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.

Keywords: Diabetic neuropathy, Finite element modeling, Monte Carlo Algorithm, Somatosensory nerve networks

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Authors: Kalakotla Shanker, G. Krishna Mohan

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Nowadays, nanoparticles are being used in pharmacological studies for their exclusive properties such as small size, more surface area, biocompatibility and enhanced solubility. In view of this, the present study aimed to evaluate the antihyperglycemic potential of biologically synthesized silver nanoparticles (BSSNPs) and Gymnema sylvestre (GS) extract. The SEM and SEM analysis divulges that the BSSNPs were spherical in shape. EDAX spectrum exhibits peaks for the presence of silver, carbon, and oxygen atoms in the range of 1.0-3.1 keV. FT-IR reveals the binding properties of active bio-constituents responsible for capping and stabilizing BSSNPs. The results showed increased blood glucose, huge loss in body weight and downturn in plasma insulin. The GS extract (200 mg/kg, 400 mg/kg), BSSNPs (100 mg/kg, 200 mg/kg) and metformin 50 mg/kg were administered to the diabetic rats. BSSNPs at a dose level of 200 mg/kg (b.wt.p.o.) showed significant inhibition of (p<0.001) blood glucose levels as compared with GS extract treated group. The results obtained from study indicate that the BSSNP shows potent anti-diabetic activity.

Keywords: BSSNP, G.sylvetre, wistar rats, antihyperglycemic activity.

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Authors: Shanmugasundaram Krishnakumari, Paramasivam Rajeswari, Subramanian Kathiravan

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Mushrooms are a group of fleshy macroscopic fungi. They have been valued throughout the world as both edible and medicine. They are highly nutritious with good amount of quality proteins, vitamins and minerals. An edible mushroom, Calocybe indica was selected to validate its nutritional and medicinal properties. Since tissue damage in hyperglycemia has been related to oxidative stress, we evaluated the enzymatic and non-enzymatic antioxidant status in the serum, liver and kidney since they are the target organs in diabetic complications. From the results, increased oxidative stress and decreased antioxidants might be related to the causation of diabetes mellitus. The treatment in the diabetic rats with the Calocybe indica showed an increase in the antioxidant system and decrease in the production of free radicals. The mushrooms which contain antioxidant phytochemicals has potential free radical scavenging capacity and hence can induce the antioxidant system in the body significantly reduces the generated free radicals thereby maintaining the normal levels of the antioxidants

Keywords: Antioxidants, Calocybe indica, diabetes mellitus, edible mushroom, oxidative stress.

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Authors: Okolie Uchenna, Ehiemere Ijeoma, Ezenduka Pauline, Ogbu Sylvester

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A cross sectional survey design was used to collect data from 370 diabetic patients. Two instruments were used in obtaining data; in-depth interview guide and researchers- developed questionnaire. Fisher's exact test was used to investigate association between the identified factors and nonadherence. Factors identified were: socio-demographic factors such as: gender, age, marital status, educational level and occupation; psychosocial obstacles such as: non-affordability of prescribed diet, frustration due to the restriction, limited spousal support, feelings of deprivation, feeling that temptation is inevitable, difficulty in adhering in social gatherings and difficulty in revealing to host that one is diabetic; health care providers obstacles were: poor attitude of health workers, irregular diabetes education in clinics , limited number of nutrition education sessions/ inability of the patients to estimate the desired quantity of food, no reminder post cards or phone calls about upcoming patient appointments and delayed start of appointment / time wasting in clinics.

Keywords: Behavior change, diabetes mellitus, dietarymanagement, diet adherence.

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.

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Authors: Aljabryn Dalal Hamad

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The present explanatory study concerns with the relation between Diabetes Mellitus and Food Balance in the Kingdom of Saudi Arabia during 2005-2010, using published data. Results illustrated that Saudi citizen daily protein consumption (DPC) during 2005-2007 (g/capita/day) is higher than the average global consumption level of protein with 15.27%, daily fat consumption (DFC) with 24.56% and daily energy consumption (DEC) with 16.93% and increases than recommended level by International Nutrition Organizations (INO) with 56% for protein, 60.49% for fat and 27.37% for energy. On the other hand, DPC per capita in Saudi Arabia decreased during the period 2008-2010 from 88.3 to 82.36 gram/ day. Moreover, DFC per capita in Saudi Arabia decreased during the period 2008-2010 from 3247.90 to 3176.43 Cal/capita/ day, and daily energy consumption (DEC) of Saudi citizen increases than world consumption with 16.93%, whereas increases with 27.37% than INO. Despite this, DPC, DFC and DEC per capita in Saudi Arabia still higher than world mean. On the other side, results illustrated that the number of diabetic patients in Saudi Arabia during the same period (2005-2010). The curve of diabetic patient’s number in Saudi Arabia during 2005-2010 is regular ascending with increasing level ranged between 7.10% in 2005 and 12.44% in 2010. It is essential to devise Saudi National programs to educate the public about the relation of food balances and diabetes so it could be avoided, and provide citizens with healthy dietary balances tables.

Keywords: Diabetes Mellitus, Food Balance, Energy, Fat, Protein, Saudi Arabia.

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Authors: Srinivasan Aruchamy, Partha Bhattacharjee, Goutam Sanyal

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Optic disk segmentation plays a key role in the mass screening of individuals with diabetic retinopathy and glaucoma ailments. An efficient hardware-based algorithm for optic disk localization and segmentation would aid for developing an automated retinal image analysis system for real time applications. Herein, TMS320C6416DSK DSP board pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk is reported. The experiment has been performed on color and fluorescent angiography retinal fundus images. Initially, the images were pre-processed to reduce the noise and enhance the quality. The retinal vascular tree of the image was then extracted using canny edge detection technique. Finally, a pixel intensity based fractal analysis is performed to segment the optic disk by tracing the origin of the vascular tree. The proposed method is examined on three publicly available data sets of the retinal image and also with the data set obtained from an eye clinic. The average accuracy achieved is 96.2%. To the best of the knowledge, this is the first work reporting the use of TMS320C6416DSK DSP board and pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk. This will pave the way for developing devices for detection of retinal diseases in the future.

Keywords: Color retinal fundus images, Diabetic retinopathy, Fluorescein angiography retinal fundus images, Fractal analysis.

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Authors: Raad Nari, Maura Moriaty, Maha T. Barakat

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Introduction: Sodium-glucose co-transporter-2 (SGLT2) inhibitors are a new class of oral anti-diabetic drugs with a unique mechanism of action. They are used to improve glycaemic control in adults with type 2 diabetes by enhancing urinary glucose excretion. In the UAE, there has been certainly an increased use of these medications. As with any new medication, there are safety considerations related to their use in patients with type two diabetes. A retrospective study was conducted at the three main centres of the Imperial College London Diabetes Centre. Methodology: All patients in electronic database (Diamond) from October 2014 to October 2017 were included with a minimum of six months usage of sodium glucose co-transporter inhibitors that comprise canagliflozin, dapagliflozin and empagliflozin. There were 15 paired sample biochemical and clinical correlations. The analysis was done at the start of the study, three months and six months apart. SPSS version 24 was used for this study. Conclusion: This study of sodium glucose co-transporter-2 inhibitors used showed significant reductions in weight, glycated haemoglobin A1C, systolic and diastolic blood pressures. As the case with systematic reviews, there were similar changes in liver enzymes, raised total cholesterol, low density lipopoptein and high density lipoprotein. There was slight improvement in estimated glomerular filtration rate too. Our analysis also showed that they increased in the incidence of urinary tract symptoms and incidence of urinary tract infections.

Keywords: SGLT2 inhibitors dapagliflozin empagliflozin canagliflozin, adverse effects, amputation diabetic ketoacidosis DKA, urinary tract infection.

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Authors: Santosh Kumar, Anand Prakash, Kanak Sinha, Anita K Verma

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Vernonia divergens Benth., commonly known as “Insulin Plant” (Fam: Asteraceae) is a potent sugar killer. Locally the leaves of the plant, boiled in water are successfully administered to a large number of diabetic patients. The present study evaluates the putative anti-diabetic ingredients, isolated from the in vivo and in vitro grown plantlets of V. divergens for their antimicrobial and anticancer activities. Sterilized explants of nodal segments were cultured on MS (Musashige and Skoog, 1962) medium in presence of different combinations of hormones. Multiple shoots along with bunch of roots were regenerated at 1mg l-1 BAP and 0.5 mg l-1 NAA. Micro-plantlets were separated and sub-cultured on the double strength (2X) of the above combination of hormones leading to increased length of roots and shoots. These plantlets were successfully transferred to soil and survived well in nature. The ethanol extract of plantlets from both in vivo & in vitro sources were prepared in soxhlet extractor and then concentrated to dryness under reduced pressure in rotary evaporator. Thus obtainedconcentrated extracts showed significant inhibitory activity against gram negative bacteria like Escherichia coli and Pseudomonas aeruginosa but no inhibition was found against gram positive bacteria. Further, these ethanol extracts were screened for in vitro percentage cytotoxicity at different time periods (24 h, 48 h and 72 h) of different dilutions. The in vivo plant extract inhibited the growth of EAC mouse cell lines in the range of 65, 66, 78, and 88% at 100, 50, 25 & 12.5μg mL-1 but at 72 h of treatment. In case of the extract of in vitro origin, the inhibition was found against EAC cell lines even at 48h. During spectrophotometric scanning, the extracts exhibited different maxima (ʎ) - four peaks in in vitro extracts as against single in in vivo preparation suggesting the possible change in the nature of ingredients during micropropagation through tissue culture techniques.

Keywords: Anti-cancer, Anti-microbial, EAC mouse cell, Tissue culture, Vernonia divergens.

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: Bootstrap, diabetes risk groups, error rate, k-nearest neighbors.

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Authors: Yutaka Takaoka, Mika Ohta, Aki Sugano, Tsuyoshi Oda, Eiichi Maeda, Sumiyo Hanaoka, Masako Matsuura

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Along with the increased morbidity of glaucoma or diabetic retinitis pigmentosa, etc., number of people with vision loss is also increasing in Japan. It is difficult for the visually impaired to learn and acquire braille because most of them are middle-aged. In addition, number of braille teachers are not sufficient and reducing in Japan, and this situation makes more difficult for the visually impaired. Therefore, we research and develop a Web-based e-learning program for tactile braille, that cooperate with braille display and voice assistance.

Keywords: Acquired visually impaired, Braille, e-learning, Tactile braille

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Authors: M. Das Gupta, S. Banerjee

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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: Case based reasoning, Exudates, Retina image, Similarity based retrieval.

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Authors: V.Ashok, A.Nirmalkumar, N.Jeyashanthi

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A method and apparatus for noninvasive measurement of blood glucose concentration based on transilluminated laser beam via the Index Finger has been reported in this paper. This method depends on atomic gas (He-Ne) laser operating at 632.8nm wavelength. During measurement, the index finger is inserted into the glucose sensing unit, the transilluminated optical signal is converted into an electrical signal, compared with the reference electrical signal, and the obtained difference signal is processed by signal processing unit which presents the results in the form of blood glucose concentration. This method would enable the monitoring blood glucose level of the diabetic patient continuously, safely and noninvasively.

Keywords: Anisotropy factor, Blood glucose, Diabetes Mellitus, Noninvasive method, Photo detectors.

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Authors: Darren Thompson, Philip Morrow, Bryan Scotney, John Winder

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Patients with diabetes are susceptible to chronic foot wounds which may be difficult to manage and slow to heal. Diagnosis and treatment currently rely on the subjective judgement of experienced professionals. An objective method of tissue assessment is required. In this paper, a data fusion approach was taken to wound tissue classification. The supervised Maximum Likelihood and unsupervised Multi-Modal Expectation Maximisation algorithms were used to classify tissues within simulated wound models by weighting the contributions of both colour and 3D depth information. It was found that, at low weightings, depth information could show significant improvements in classification accuracy when compared to classification by colour alone, particularly when using the maximum likelihood method. However, larger weightings were found to have an entirely negative effect on accuracy.

Keywords: Classification, data fusion, diabetic foot, stereophotogrammetry, tissue colour.

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Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, A. Naseem, N. G. Karthick, T. K. Abdul Jaleel, Paul K.Joseph

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It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.

Keywords: Autonomic nervous system, diabetes mellitus, heart rate variability, pattern identification, sample entropy

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Authors: Pratibha Gupta, Satyawati Sharma, Sanjay Saxena

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Stevia rebaudiana Bertoni (natural sweetener) belongs to Asteraceae family and can be used as substitute of artificial sweeteners for diabetic patients. Conventionally, it is cultivated by seeds or stem cutting, but seed viability rate is poor. A protocol for callus induction and multiplication was developed to produce large no. of calli in short period. Surface sterilized nodal, leaf and root explants were cultured on Murashige and Skoog (MS) medium with different concentrations of plant hormone like, IBA, kinetin, NAA, 2,4-D, and NAA in combination with 2,4-D. 100% callusing was observed from leaf explants cultured on combination of NAA and 2,4-D after three weeks while with 2,4-D, only 10% callusing was observed. Calli obtained from leaf and root explants were shiny green while with nodal explants it was hard and brown. The present findings deal with induction of callusing in Stevia to achieve the rapid callus multiplication for study of steviol glycosides in callus culture.

Keywords: 2, 4-D, Callusing, NAA, Stevia, Steviol glycosides

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Authors: D.O. Omondi, M.K. Walingo, G.M. Mbagaya, L.O.A. Othuon

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This study applied the Theory of Planned Behavior model in predicting dietary behavior among Type 2 diabetics in a Kenyan environment. The study was conducted for three months within the diabetic clinic at Kisii Hospital in Nyanza Province in Kenya and adopted sequential mixed methods design combing both qualitative and quantitative phases. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The results based on the common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within dietary behavior {χ2 = 223.3, df = 77, p = .02, χ2/df = 2.9, n=237; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039, .146)}. This implies that the Theory of Planned Behavior holds and forms a framework for promoting dietary practice among Type 2 diabetics.

Keywords: Dietary practice, Kenya, Theory of PlannedBehavior, Type 2 diabetes, Mixed Methods Design.

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Authors: D. O. Omondi, M. K. Walingo, G. M. Mbagaya, L. O. A. Othuon

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Understanding patient factors related to physical activity behavior is important in the management of Type 2 Diabetes. This study applied the Theory of Planned Behavior model to understand physical activity behavior among sampled Type 2 diabetics in Kenya. The study was conducted within the diabetic clinic at Kisii Level 5 Hospital and adopted sequential mixed methods design beginning with qualitative phase and ending with quantitative phase. Qualitative data was analyzed using grounded theory analysis method. Structural equation modeling using maximum likelihood was used to analyze quantitative data. The common fit indices revealed that the theory of planned behavior fitted the data acceptably well among the Type 2 diabetes and within physical activity behavior {¤ç2 = 213, df = 84, n=230, p = .061, ¤ç2/df = 2.53; TLI = .97; CFI =.96; RMSEA (90CI) = .073(.029, .08)}. This theory proved to be useful in understanding physical activity behavior among Type 2 diabetics.

Keywords: Physical activity, Theory of Planned Behavior, Type2 diabetes, Kenya.

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Authors: Hala O. El-Mesallamy, Salwa M. Suwailem, Mae M. Seleem

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Visfatin and apelin are two new adipokines that recently gained a special interest in diabetes research. This study was conducted to study the interplay between these two adipokines and their correlation with other inflammatory and biochemical parameters in type 2 diabetic (T2D) postmenopausal women with CAD. Visfatin and apelin were measured by enzyme-linked immunoassay (ELISA). Visfatin was found to be significantly higher in the following groups: T2D patients without CAD, non-obese and obese T2D patients with CAD when compared to control group. Apelin was found to be significantly lower in non-obese and obese T2D patients with CAD when compared to control group. Visfatin and apelin were found to be significantly associated with each other and with other biochemical parameters. The current study provides evidence for the interplay between visfatin and apelin through the inflammatory milieu characteristic of T2D and their possible role in the pathogenesis of CAD complication of T2D. 

Keywords: Apelin, Coronary artery disease, Inflammation, Type 2 diabetes, Visfatin.

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Authors: S. Nurdiana, A. S. Nor Haziqah, M. K. Nur Ezwa Khairunnisa, S. Nurul `Izzati, Y. Siti Amna M. J. Norashirene, I. Nur Hilwani

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Azadirachta excelsa or locally known as sentang are frequently used as a traditional medicine by diabetes patients in Malaysia. However, less attention has been given to their toxicity effect. Thus, the study is an attempt to examine the protective effect of A. excelsa on the pancreas and to determine possible toxicity mediated by the extract. Diabetes was induced experimentally in rats by high-fat-diet for 16 weeks followed by intraperitoneal injection of streptozotocin at dosage of 35 mg/kg of body weight. Declination of the fasting blood glucose level was observed after continuous administration of A. excelsa for 14 days twice daily. This is due to the refining structure of the pancreas. However, surprisingly, the plant extract reduced the leukocytes, erythrocytes, hemoglobin, MCHC and lymphocytes. In addition, the rat treated with the plant extract exhibited increment in AST and eosinocytes level. Overall, the finding shows that A. excelsa possesses antidiabetic activity by improving the structure of pancreatic islet of Langerhans but involved in ameliorating of hematology and biochemical parameters.

Keywords: Azadirachta excelsa, diabetes, pancreas, hematobiochemical parameters.

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Authors: N. Haghjou, M. J. Abdekhodaie, Y. L. Cheng, M. Saadatmand

Abstract:

Intravitreal injection (IVI) is the most common treatment for eye posterior segment diseases such as endopthalmitis, retinitis, age-related macular degeneration, diabetic retinopathy, uveitis, and retinal detachment. Most of the drugs used to treat vitreoretinal diseases, have a narrow concentration range in which they are effective, and may be toxic at higher concentrations. Therefore, it is critical to know the drug distribution within the eye following intravitreal injection. Having knowledge of drug distribution, ophthalmologists can decide on drug injection frequency while minimizing damage to tissues. The goal of this study was to develop a computer model to predict intraocular concentrations and pharmacokinetics of intravitreally injected drugs. A finite volume model was created to predict distribution of two drugs with different physiochemical properties in the rabbit eye. The model parameters were obtained from literature review. To validate this numeric model, the in vivo data of spatial concentration profile from the lens to the retina were compared with the numeric data. The difference was less than 5% between the numerical and experimental data. This validation provides strong support for the numerical methodology and associated assumptions of the current study.

Keywords: Posterior segment, Intravitreal injection (IVI), Pharmacokinetic, Modelling, Finite volume method.

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Authors: Tsu-Yun Chiu, Tsung-Hsueh Lu, Tain-Junn Cheng

Abstract:

Background: Traditional chronic disease management did not pay attention to effects of geographic factors on the compliance of treatment regime, which resulted in geographic inequality in outcomes of chronic disease management. This study aims to examine the geographic distribution and clustering of quality indicators of diabetes care. Method: We first extracted address, demographic information and quality of care indicators (number of visits, complications, prescription and laboratory records) of patients with diabetes for 2014 from medical information system in a medical center in Tainan City, Taiwan, and the patients’ addresses were transformed into district- and village-level data. We then compared the differences of geographic distribution and clustering of quality of care indicators between districts and villages. Despite the descriptive results, rate ratios and 95% confidence intervals (CI) were estimated for indices of care in order to compare the quality of diabetes care among different areas. Results: A total of 23,588 patients with diabetes were extracted from the hospital data system; whereas 12,716 patients’ information and medical records were included to the following analysis. More than half of the subjects in this study were male and between 60-79 years old. Furthermore, the quality of diabetes care did indeed vary by geographical levels. Thru the smaller level, we could point out clustered areas more specifically. Fuguo Village (of Yongkang District) and Zhiyi Village (of Sinhua District) were found to be “hotspots” for nephropathy and cerebrovascular disease; while Wangliau Village and Erwang Village (of Yongkang District) would be “coldspots” for lowest proportion of ≥80% compliance to blood lipids examination. On the other hand, Yuping Village (in Anping District) was the area with the lowest proportion of ≥80% compliance to all laboratory examination. Conclusion: In spite of examining the geographic distribution, calculating rate ratios and their 95% CI could also be a useful and consistent method to test the association. This information is useful for health planners, diabetes case managers and other affiliate practitioners to organize care resources to the areas most needed.

Keywords: Geocoding, chronic disease management, quality of diabetes care, rate ratio.

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Authors: Fernando C. Monteiro, Vasco Cadavez

Abstract:

This paper presents a method for the detection of OD in the retina which takes advantage of the powerful preprocessing techniques such as the contrast enhancement, Gabor wavelet transform for vessel segmentation, mathematical morphology and Earth Mover-s distance (EMD) as the matching process. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Vessel segmentation method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel-s feature vector. Feature vectors are composed of the pixel-s intensity and 2D Gabor wavelet transform responses taken at multiple scales. A simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity using the EMD. The minimum distance provides an estimate of the OD center coordinates. The method-s performance is evaluated on publicly available DRIVE and STARE databases. On the DRIVE database the OD center was detected correctly in all of the 40 images (100%) and on the STARE database the OD was detected correctly in 76 out of the 81 images, even in rather difficult pathological situations.

Keywords: Diabetic retinopathy, Earth Mover's distance, Gabor wavelets, optic disc detection, retinal images

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Authors: Tayyab Hassan, Talha Rehman, Qasim Abdul Aziz, Ahmad Salman

Abstract:

The constant monitoring of blood glucose level is necessary for maintaining health of patients and to alert medical specialists to take preemptive measures before the onset of any complication as a result of diabetes. The current clinical monitoring of blood glucose uses invasive methods repeatedly which are uncomfortable and may result in infections in diabetic patients. Several attempts have been made to develop non-invasive techniques for blood glucose measurement. In this regard, the existing methods are not reliable and are less accurate. Other approaches claiming high accuracy have not been tested on extended dataset, and thus, results are not statistically significant. It is a well-known fact that acetone concentration in breath has a direct relation with blood glucose level. In this paper, we have developed the first of its kind, reliable and high accuracy breath analyzer for non-invasive blood glucose measurement. The acetone concentration in breath was measured using MQ 138 sensor in the samples collected from local hospitals in Pakistan involving one hundred patients. The blood glucose levels of these patients are determined using conventional invasive clinical method. We propose a linear regression classifier that is trained to map breath acetone level to the collected blood glucose level achieving high accuracy.

Keywords: Blood glucose level, breath acetone concentration, diabetes, linear regression.

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Authors: Chiung-Tsun Kuoa, Tzu-Hao Liu, Fang-Yi Lin, Tai-Hao Hsu, Hui-Yin Chen

Abstract:

Hyperglycemia-mediated accumulation of advanced glycation end-products (AGEs) play a pivotal role in the development of diabetic complications by inducing inflammation. In the present study, we evaluated the possible effects of water/ethanol (1/1, v/v) extracts (WEE) and its fractions from Canarium album Raeusch. (Chinese olive) which is a fruit used on AGEs-stimulated oxidative stress and inflammation in monocytes and vascular endothelial cells. Co-incubation of EA.hy926 endothelial cells with WEE and its fractions for 24h resulted in a significant decrease of monocyte–endothelial cell adhesion, the expression of ICAM-1, generation of intracellular ROS and depletion of GSH induced by AGEs. Chinese olive fruit extracts also reduced the expression of pro-inflammatory mediates, such as TNF-α, IL-1β and IL-6 in THP-1 cells. These findings suggested that Chinese olive fruit was able to protect vascular endothelium from dysfunction induced by AGEs. 

Keywords: Advanced glycation end-products (AGEs), Canarium album Raeusch, endothelial dysfunction, inflammation.

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