Browsing by Author "Gunasekara, K.A.D.C."

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Detection of Dengue Co Infections Using a Novel Single Tube Multiplex Reverse Transcription Polymerase Chain Reaction.
(In: Proceedings of the International Postgraduate Research Conference 2017 (IPRC – 2017), Faculty of Graduate Studies, University of Kelaniya, Sri Lanka., 2017) Jayathilake, E.K.S.; Jayarathne, J.A.J.C.; Muhandiramlage, T.P.; Fujii, Y.; Gunasekara, K.A.D.C.
Co-infection in individuals by more than one Dengue Virus (DENV) serotype has been reported in regions where multiple serotypes co-circulate. Co-infections can be detected using Polymerase Chain Reaction (PCR). Semi-nested multiplex PCR with Lanciotti’s primers is a widely used PCR method for serotyping DENV and it has also been used for detecting coinfections. Despite of being widely used, Lanciotti’s method may be sub-optimal in detecting co-infections as overlapping primer targets will create a bias in the amplification of the serotype with a low viral load. This could lead to underreporting of co-infections. Nine new non- overlapping primers were designed to independently amplify each serotype with minimal competition between primers to their target.In mixed infections, novel PCR assay exhibited higher sensitivity in detecting the minor serotype compared to Lanciotti’s method. The new method can also detect all four serotypes in viral RNA isolated from viral cultures and patient samples in a single tube multiplex PCR. This enables rapid and cost-effective serotyping with improved sensitivity indetection ofco-infections in clinical samples.
Determination of current lead concentration in human blood by human biomonitoring in selected Sri Lankan population
(Faculty of Graduate Studies, University of Kelaniya, 2015) Amaranayaka, K.K.K.H.; Deeyamulla, M.P.; Gunasekara, K.A.D.C.
Lead contamination of human blood from occupational origin and vehicle emission is a cause for concern because of its potential accumulation ability in the environment and in living organisms leading to long term toxic effects. This study was aimed to assess the concentration of lead in blood of different groups exposed to different occupational conditions. Groups were selected based on the hypothesis that concentration of lead in blood may vary according to the type of exposure. Blood lead levels in students, drivers and workers of University of Kelaniya, motorcyclists and fuel station attendants in Kiribathgoda city area were studied. All other groups except fuel station attendants expose to vehicle smoke during their occupation and travelling. But fuel station attendants expose to vehicle smoke and gasoline vapors excessively during their duration of occupation than others. Some of the general population selected from a rural area who are least exposed to vehicle emissions and any occupational condition were used as the control group. A questionnaire was given to each volunteer that participated in the study to obtain the type and duration of exposure to check whether there is any correlation with lead level in blood to that parameters. Venous blood was obtained by a trained nurse and concentration of lead was determined by graphite furnace atomic absorption spectrophotometer after a microwave digestion. All analyzed groups except control group contained elevated level of lead in blood than the WHO recommended maximum level. Statistical analysis were carried out to identify the correlation between elevated level of lead in blood with the type of the exposure and the duration of the exposure. Statistical analysis revealed that lead level in blood is significantly different in each study group. Blood lead levels are found to be in, students (102.58 ± 18.50 μg L-1), drivers (208.50 ± 86.70 μg L-1) and workers (124.18 ± 27.05 μg L-1) of University of Kelaniya, motorcyclists (115.34 ± 15.30 μg L-1) and fuel station attendants (220.00 ± 65.90 μg L-1). It was also observed that individuals who smoke cigarettes had extremely high levels of lead in blood with respect to non-smokers within a same study group.
The validity of body mass index in predicting body fat percentage
(University of Kelaniya, 2013) Piyasena, W.B.A.I.; Jayasena, R.S.S.; Subasinghe, Wasantha; Gunasekara, K.A.D.C.
Introduction: Obesity has become a leading health concern worldwide. It has become a foremost factor for morbidity and mortality due to non communicable diseases. (Eg: Ischemic Heart Disease, Diabetes Mellitus). Body Mass Index (BMI) is commonly used to define obesity, which is mainly the high body fat content. However, prediction of body fat content using BMI is somewhat controversial. On the other hand, methods like Bio-Impedance Analysis (BIA) is more accurate in predicting body fat content, but lacks population level data for Sri Lanka. This study was designed to fulfill those shortcomings in body fat measurements. Objectives: To determine the relationship between body fat percentage and gender To determine the validity of body mass index in predicting body fat percentage Method: 46 participants including 25 obese (Asian cut off value for obesity >25 kg/m2) and 21 healthy volunteers (non-obese) were recruited in a preliminary cross –sectional study in the Obesity Clinic at North Colombo Teaching Hospital and Family Medicine Clinic, Faculty of Medicine, Ragama. A pre-tested, interviewer-administered questionnaire was distributed to collect data. Height and weight were measured for BMI calculation and percentage body fat was measured using BIA analyzer (MOTEX, 060607-U-01). Results: The obese group had 68% women and 32% men. 86 % of the non-obese group was female. 12% of obese group and 9.5% of non-obese group were suffering from chronic diseases such as hypertension and bronchial asthma in our sample.72% of obese group and 42 % of non-obese group had a family history of obesity. In the obese group mean BMI values were calculated as 31.76kg/m2 (SD=4.36) and 28.575kg/m2 (SD=3.27) for females and males respectively. According to the results, mean values of body fat percentage were 40.8% and 25.82 % for obese women and men respectively. Asian cut off values of obesity according to the 2004 WHO Expert Committee corresponded to 31-39% (mean 35%) body fat in females and 18-27% (mean 22%) body fat in males. Both BMI and body fat percentage data recorded for the non-obese group were within the WHO Asian standards. Relationship of the BMI to body fat percentage was tested by regression analysis. The correlation coefficient of BMI to body fat percentage for females is 0.94 and for the males it is 0.98, which suggests that BMI is a stronger predictor of body fat percentage for both females and males, within the limits of the current study. Conclusion: The results suggest that BMI is a stronger predictor of body fat percentage for both sexes. Even though the body fat percentage of females was higher than males, it was compatible with WHO Asian values.