Search results for: D. C. M. Kulatunga

Authors: Sangyeop Shin, D. C. M. Kulatunga, S. H. S. Dananjaya, Chamilani Nikapitiya, Jehee Lee, Mahanama De Zoysa

Abstract:

Saprolegniasis is one of the most devastating fungal diseases in freshwater fish which is caused by species in the genus Saprolegnia including Saprolegnia parasitica. In this study, we isolated the strain of S. parasitica from diseased rainbow trout in Korea. Morphological and molecular based identification confirmed that isolated fungi belong to the member of S. parasitica, supported by its typical fungal features including cotton-like whitish mycelium, zoospores (primary and secondary) and phylogenetic analysis with internal transcribed spacer (ITS) region. Pathogenicity of isolated S. parasitica was developed in embryo, larvae, juvenile and adult zebrafish as a disease model. Up regulation of host genes encoding ZfTnf-α, Zfc-Rel, ZfIl-12, ZfLyz-c, Zfβ-def, and ZfHsp-70 was identified in zebrafish larvae after experimental challenge of S. parasitica showing the host immune responses against the S. parasitica. Survival of the juveniles upon fungal infection might be due to the increased immune protection in the host. Investigation of antifungal susceptibility of S. parasitica with natural lawsone (2-hydroxy-1,4-naphthoquinone) revealed the minimum inhibitory concentration (MIC) and percentage inhibition of radial growth (PIRG %) as 200 µg/mL and 31.8%, respectively. Lawsone was able to change the membrane permeability, and cause irreversible damage and disintegration to the cellular membranes of S. parasitica which might have effect on fungi growth inhibition. Moreover, the mycelium exposed to lawsone (MIC level) changed the transcriptional responses of S. parasitica genes. Overall results indicate that lawsone could be a potential and novel anti-S. parasitica agent for controlling S. parasitica infection.

Keywords: host-pathogen interactions, lawsone, rainbow trout, Saprolegnia parasitica, Saprolegniasis, zebrafish

Procedia PDF Downloads 248

Authors: Aparna Sengupta

Abstract:

The paper seeks to find answers to the question as to why India’s disaster management policies have been unable to deliver the desired results. Are the shortcomings in policy formulation, effective policy implementation or timely prevention mechanisms? Or is there a fundamental issue of policy formulation which sparsely takes into account the cultural specificities and uniqueness, technological know-how, educational, religious and attitudinal capacities of the target population into consideration? India was slow in legislating disaster policies but more than that the reason for lesser success of disaster polices seems to be the gap between policy and the people. We not only keep hearing about the failure of governmental efforts but also how the local communities deal far more efficaciously with disasters utilizing their traditional knowledge. The 2004 Indian Ocean tsunami which killed 250,000 people (approx.) could not kill the tribal communities who saved themselves due to their age-old traditional knowledge. This large scale disaster, considered as a landmark event in history of disasters in the twenty-first century, can be attributed in bringing and confirming the importance of Traditional Environmental Knowledge in managing disasters. This brings forth the importance of cultural and traditional know-how in dealing with natural disasters and one is forced to question as to why shouldn’t traditional environmental knowledge (TEK) be taken into consideration while formulating India’s disaster resilience policies? Though at the international level, many scholars have explored the connectedness of disaster to cultural dimensions and several research examined how culture acts as a stimuli in perceiving disasters and their management (Clifford, 1956; Mcluckie, 1970; Koentjaraningrat, 1985; Peacock, 1997; Elliot et.al, 2006; Aruntoi, 2008; Kulatunga, 2010). But in the Indian context, this field of inquiry i.e. linking disaster policies with tradition and generational understanding has seldom received attention of the government, decision- making authorities, disaster managers and even in the academia. The present study attempts to fill this gap in research and scholarship by presenting an historical analysis of disaster and its cognition by cultural communities in India. The paper seeks to interlink the cultural comprehension of Indian tribal communities with scientific-technology towards more constructive disaster policies in India.

Keywords: culture, disasters, local communities, traditional knowledge

Procedia PDF Downloads 105

Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

Abstract:

Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

Procedia PDF Downloads 126