Ethnic differences in adipogenesis and the role of alkaline phosphatase in the control of adipogenesis in human preadipocytes and 3T3-L1 cells

A thesis submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in fulfilment of the requirement for the degree of Doctor of Philosophy. Johannesburg, 2004Alkaline phosphatase (ALP) is a ubiquitously expressed enzyme, that has been shown to play a role in cell differentiation and organogenesis. One study has also demonstrated ALP activity in rat adipocytes. The purpose of the present study was therefore to determine whether ALP is expressed in preadipocytes and what role it may have in adipogenesis. ALP activity was detected in the murine preadipocyte cell line, 3T3-L1, and in human preadipocytes isolated from mammary tissue, and from subcutaneous abdominal fat depots. In all the cell types studied ALP activity increased in parallel with adipogenesis. In the 3T3 -L1 cell line the tissue- non -specific ALP inhibitors, levamisole and histidine inhibited ALP activity, and adipogenesis, whereas the tissue specific ALP inhibitor Phe- Gly-Gly did not inhibit ALP or adipogenesis. In human preadipocytes, histidine inhibited adipogenesis and ALP activity, whereas levamisole inhibited adipogenesis, but did not block ALP activity in intact cells. However, levamisole did inhibit ALP activity by 50% in cell extracts. Levamisole was able to inhibit adipogenesis in human preadipocytes. The tissue specific ALP inhibitor, Phe Gly Gly, did not inhibit ALP activity or adipogenesis in human preadipocytes. ALP activity and adipogenesis, were compared in preadipocytes isolated from mammary tissue taken from black (13) and white (15) female subjects. Both ALP activity and adipogenesis, were lower in white compared to black female subjects. iii Immunocytochemical, analysis of the 3T3-L1 cell line and human preadipocytes demonstrated that ALP activity was restricted to the lipid droplets of these cells. ALP activity was also measured in serum samples obtained from 100 African subjects (74 females and 26 males) of varying BMI. ALP activity was found to be higher in obese than lean subjects, whereas, the other liver enzymes or products measured in serum were not. In fact these variables correlated to varying degrees with waist-hip ratio, whereas ALP levels did not. This suggest that liver function is predominantly influenced by abdominal obesity whereas serum ALP levels are more influenced by overall body adiposity. In conclusion, ALP, may be involved in the control of adipogenesis, in the 3T3- L1 preadipocyte cell line and in human preadipocytes isolated from mammary adipose tissue and subcutaneous abdominal adipose tisssue. The presence of ALP activity in lipid droplets in 3T3-L1 cells and human preadipocytes, and the ability of ALP inhibitors to block adipogenesis strongly suggest that ALP plays a role in the control of adipogenesis.IT201

Induced Resistance Using Nonpathogenic Fusarium Oxysporum for Biological Control of Banana Fusarium Wilt

Banana (Musa spp. Linn.) is the second most important fruit crops in Malaysia. It is easily attacked by the fungus Fusarium oxysporum Schlect. fsp. cubense (E.F.Smith) Snyder and Hansen (FOC), causing terminal wilt in the field. Chemical and cultural methods were not effective in controlling the disease. Therefore, alternative control measures have to be developed. In recent years, nonpathogenic Fusaria was being considered for plant disease control and could be the most promising approach for biological control of Fusarium wilt in banana through induced systemic resistance. Isolates of nonpathogenic F oxysporum (FO: F01, F02, F03, F04, F05 and F06) were isolated from healthy roots and rhizospheres of bananas vars. Berangan and Rastali, and were identified to the species level based on cultural and morphological characteristics. Random amplified polymorphic (RAPD-PCR) analysis was able to establish variability within F. oxy.\porom isolates and between saprophytic and pathogenic fonns (FOe race 1 and race 4), using ope 11 and ope 14 primers. All 6 isolates of FO were antagonistic to both pathogenic race 1 and race 4 of FOe with values of the % of inhibition of radial growth (PIRG) exceeding 50% in a series of dual culture test. F04 was found to be the most antagonistic against FOC' race 4 with PIRGof65%. Infectivity studies on six-weeks-old tissue cultured banana seedlings var. Berangan cv. intan, con finned that FO1, F02, F03, F04, F05 or F06 were not pathogenic to banana seedlings. No visible foliar or internal symptoms were observed both on inoculated and control seedlings. Seedlings inoculated with FOC' race 4 produced foliar symptoms as yellowing of the older leaves followed by necrosis and wilting. F04 conferred some degree of resistance to the host when challenged with FOe race I suggesting the possible role of induced resistance against Fusarium wilt

Monitoring Changes and Soil Characterization in Mangrove Forests of the United Arab Emirates Using the Canonical Correlation Forest Model by Multitemporal of Landsat Data

Mangrove forests are an important indicator of blue carbon storage and biodiversity and provide several benefits to the environment. This study showed the first attempt to apply the canonical correlation forest (CCF) model to classify mangroves and monitor changes in the mangrove forests of the entire region. The CCF model obtained a satisfactory accuracy with an F1 score of more than 0.90. Compared to Sentinel-2, Landsat 8 exhibited good temporal resolution with relatively little mangrove details. The resultant mangrove maps (1990–2020) were used to monitor changes in mangrove forests by applying a threshold value ranging from +1 to −1. The results showed a significant increase in the UAE mangroves over the period from 1990 to 2020. To characterize soil in mangrove forests, a set of interpolated maps for calcium carbonate, salinity concentration, nitrogen, and organic matter content was constructed. The results showed that there is a positive relationship between mangrove distribution and the calcium carbonate, nitrogen, salinity, and organic matter concentrations in the soil of the mangrove forests. Our results are of great importance to the ecological and research community. The new maps presented in this study will be a good reference and a useful source for the coastal management organization

Spatiotemporal Analysis of the Impacts of Climate Change on UAE Mangroves

Mangroves are imperative to coastal systems, providing security against extreme weather events by acting as natural barriers. These halophytic plants play a crucial role in mitigating global warming and act as an invaluable resource for consumption. Despite proving to be resilient, mangroves exhibit sensitivity to climatic (e.g., Land Surface Temperature, Salinity, etc.) and man-made factors (e.g., Land Use/Land Cover Changes). Numerous past studies recording the relationship between mangrove growth & development with the aforesaid constituents, but those were mostly restricted to visual observation/pattern recognition and single type of regression analysis. Also, the evaluation of simultaneous exploration of multiple aspects influencing mangrove evolution was not prominent. Therefore, the main objective of this study was to focus on the impact of both salinity and land surface temperature on mangrove biomass by the joint-venture of remote sensing, geographic information system and several machine learning algorithms. The study considered appropriate mangrove site selections with pre-processing of the acquired satellite images. Also, mathematical computations were performed on the raster layers to determine the previously mentioned natural aspects. Finally, several types of regression analysis were conducted to delineate potential patterns, governing mangrove vegetation health by virtue of temperature and salinity. Mangroves’ relationship with temperature and salinity showed insignificant coefficient of determination. However, the generated response curves postulated that high mangrove biomass could be achieved for a specific temperature window (30-33◦C) and vegetation health could deteriorate at increasing salinity. Overall, combined effects of surface temperature and salinity on mangrove vegetation were significantly more (i.e., Maximum coefficient of determination of 0.31) than individual component alone

SAR Image Denoising using MMSE Techniques

Synthetic aperture radar (SAR) provides many advantages over optical remote sensing, principally the all-weather and all-day acquisition capability. For this reason, SAR images have been exploited for many applications such as forestry, agriculture, disaster monitoring, sea/ice monitoring. However, the main limitation in SAR images is the contamination with the multiplicative speckle noise. The speckle damages the radiometric quality of SAR images and contracts the performance of information extraction techniques. Many methods have been proposed in the literature to reduce speckle noise. These methods, however, must avoid degrading the useful information in the SAR images, such as textures, local mean of backscatter, and point targets. The minimum mean square error (MMSE) techniques have been largely applied in SAR image speckle denoising. The objective of this chapter is to review and give new insights into the MMSE denoising of SAR images. In particular, the performances of three MMSE-based techniques which are the commonly applied Lee sigma filter and the newly introduced iterative MMSE (IMMSE) filter, and the infinite number of looks prediction (INLP) filter are studied

Um modelo de monitoração de pacientes na UTI usando micro servidor web

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação

Android based vehicle tracking system / Omer Ali Abubakr Abd Elrhman … [et al.]

Android, as an operating system, has provided users with great opportunity to innovate and get things done in a mobile device. This paper presents how to use the GPS technology in Android devices to complete an interactive application which can be used to monitor a fleet of vehicles and display their positions on Google Maps. By using SMS messages, this information can be transmitted to the server. It provides a telemonitoring system for distribution or transportation vehicles owned by a specific company. The whole system is made of two key parts. The first one is the client, which represents an Android application that is installed in the vehicle. During a vehicle’s motion, its location can be reported by SMS messages. The second is the server, which is a computer programme representing a map using Google Maps to show the last known locations of all tracked vehicles. The current system is able to provide the monitoring process from anywhere. The purpose of this system is to use the Android platform to provide the following features: i) Location information (longitude, latitude). ii) Real time tracking using SMS. iii) Map View of all vehicles’ locations. This system is needed by many companies to monitor illegal and unethical use of their vehicles. It also provides assurance that the location of the vehicle is known in the case of robbery

Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tree Models

© Copyright © 2020 Elmahdy, Ali, Mohamed, Howari, Abouleish and Simonet. Mangrove forests are acting as a green lung for the coastal cities of the United Arab Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting shoreline. Thus, the first step toward conservation and a better understanding of the ecological setting of mangroves is mapping and monitoring mangrove extent over multiple spatial scales. This study aims to develop a novel low-cost remote sensing approach for spatiotemporal mapping and monitoring mangrove forest extent in the northern part of the United Arab Emirates. The approach was developed based on random forest (RF), Kernel logistic regression (KLR), and Naive Bayes Tree machine learning algorithms which use multitemporal Landsat images. Our results of accuracy metrics include accuracy, precision, and recall, F1 score revealed that RF outperformed the KLR and NB with an F1 score of more than 0.90. Each pair of produced mangrove maps (1990–2000, 2000–2010, 2010–2019, and 1990–2019) was used to image difference algorithm to monitor mangrove extent by applying a threshold ranges from +1 to −1. Our results are of great importance to the ecological and research community. The new maps presented in this study will be a good reference and a useful source for the coastal management organization