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Abstract : Synthesis of Mannich Bases of 8-Hydroxyquinoline
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Abstract: In search of new potential therapeutic agents, 8-Hydroxyquinoline which is a highly active antifungal and antibacterial agent was subjected to Mannich reaction. Different combinations of aromatic aldehyde and aromatic amines were used for Mannich reaction on 8-Hydroxyquinoline from which one new 7-[α-(anilino)-3',4'-dimethoxybenzyl]-8-hydroxyquinoline (3) and two known Mannich bases (1,2) were obtained. Keywords: 8-Hydroxyquinoline, Oxine, Mannich Base, Mannich Reaction. |
Abstract : Analysis of Climatic Structure with Karachi Dengue Outbreak
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Abstract: Various studies have reported that global warming causes unstable climate and serious impact on physical environment and public health. The increasing incidence of dengue case is now a priority health issue and has become a health burden for Pakistan. In this study it has been investigated that spatial pattern of environment causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. The climatic or environmental and the Dengue Fever (DF) case data was processed by coding, editing, tabulating, recoding and restructuring and finally applying different statistical methods, techniques and procedures for the analysis and interpretation. Five climatic variables which we have studied are precipitation (P), Maximum temperature (Mx), Minimum temperature (Mn), Humidity (H) and Wind speed (W) collected from 1980-2012. The data on Dengue Fever cases in Karachi for the period 2010 to 2012 are available and reported on weekly basis. Principal Component 1 (PC1) for all groups of the period can be interpreted as the General atmospheric condition. PC2 the second important climate factor for dengue period (2010-2012) comes out contrast between precipitation and wind speed. PC3 is the weighted difference between maximum temperature and wind speed. PC4 is the contrast between maximum and wind speed. Negative Binomial and Poisson regression model are used to correlate the dengue fever incidence to climatic variable and principal component (PC) score. Due to the problems of over dispersion the Poisson models are not useful for interpretation through Negative Binomial model we found that relative humidity causes an increase on the chances of dengue occurrence by 1.71% times. While maximum temperature positively influence on the chances dengue occurrence by 19.48% times. Minimum temperature affects on the chances of dengue occurrence by 11.51% times. Wind speed is effecting negatively on the weekly occurrence of dengue fever by 7.41%times. Keywords: Principal component analysis, Dengue Fever, Negative Binomial Regression model, Poisson Regression model. |
Abstract : Development of Monoclonal Hybridoma Cell Lines and Extracting Antibody Against Fummonisin B1
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Abstract: Objective:To acquire monoclonal hybridoma cell lines against fummonisin B1(FB1) and extract monoclonal antibody against FB1. Methods: Coupling antigens of FB1-KLH and FB1-BSA with chemical methods and immune 6-8 weeks old female BALB/c mice with FB1-KLH. Integrating spleen cells with sp2/0 myeloma cells to acquire hybridoma cell lines secreting McAb against FB1. The method of multiple subclones was used to select cell lines stably secreting McAb. McAbs was got from ascites and purified. The subclass of antibody was measured and the molecular weight was identified. The specificity and sensitivity of McAb were identified with indirect competitive inhibition ELISA. Results:The results of serum from immuned mice showed that after five times of immunization the titer stables at 1×10-6, and the McAb belongs to IgG1 subclass, the light chain was κ, the molecular weight of heavy and light chain were 55kDa and 32kDa, respectively. ELISA results showed that McAb could react with FB1. The linear range indirect competitive inhibition ELISA is 10-500ng/ml. Conclusion:The monoclonal hybridoma cell lines and the high specificity,high sensitivity of FB1-McAb was Keywords: Fummonisin B1, hybridomacell lines, monoclonal antibody. Download Full Article |
Abstract : Analysis of Land Surface Temperature and NDVI Using Geo-Spatial Technique: A Case Study of Keti Bunder, Sindh, Pakistan
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Abstract:Keti Bunder is a small coastal community situated at about 200 km south east of Karachi. It has four major creeks namely Chann, Hajamro, Kangri (Turchhan) and Khober with an arid subtropical climate and temperature remaining moderate throughout the year. This paper reports the application of an integration of Remote Sensing (RS) and Geographic Information Systems (GIS) for analysis and monitoring of the relationship of land surface temperature (LST) with Normalized Difference Vegetation Index (NDVI) in the area. LST is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. [1-5]. Remote sensing in accord with tradition utilizes the NDVI to provide specific information on vegetation abundance to the LST–vegetation relationship. For mapping purposes, satellite images of Landsat-5 ETM+, Landsat-7 TM and Landsat-8 OLI / TIRS images, acquired on March 08, 2000, April 29, 2010 and April 08, 2014 respectively, were used. The results indicate that the maximum land surface temperature increased gradually from 39°C in 2000, to 42°C in 2010 and 45°C in 2014. Due to global warming and climatic changes. Keti Bunder of the Indus delta has experienced a serious condition over the past few years; the local communities have suffered badly from climate change impacts as heavy rainfalls, floods and cyclones have forced people to migrate to other places for their livelihood and shelter. However, mean NDVI value increased to -0.009 in 2014 as compared to 2010 (-0.165), due to several plantations of mangroves being established by the government. In the past, the mangrove forest was degraded due to lack of freshwater and seawater intrusion. The rate of degradation of mangrove forest in the delta was approximately 6 percent per year between 1980 and 1995 and only a small percentage of mangroves are now considered to be healthy [6-7]. Keywords: GIS, Remote Sensing, Land surface emissivity, vegetation abundance, Thermal Infrared, Atmospheric correction. Download Full Article |
