Role of the ABC transporter ABCG2 in human haematopoiesis

ABCG2 is a transporter protein that has the ability to efflux many drugs and fluorescent dyes. Primitive haematopoietic stem cells highly express ABCG2 and the expression level decreases as these cells differentiate indicating a possible role of this transporter in HSC. In the present study, we have analyzed the role of ABCG2 in early haematopoietic stem cells by constitutively expressing ABCG2 in human CB derived CD133+ cells. This constitutive expression of ABCG2 demonstrated an enhancement of primary CFCs in vitro, including the most primitive clonogenic cells the CFU-GEMM (n=12, p<0.002). ABCG2 enhances the replating capacity of primary colonies with a mean 3.0 fold increase in the number of 2nd colonies (n=9, p<0.01), indicating a substantial enhancement of the proliferative potential of clonogenic progenitors by constitutive ABCG2 expression. Overexpression of ABCG2 did not have any positive effect on cell expansion in liquid culture as well as the frequency of LTC-IC, however, the production of CFC per LTC-IC was found to be enhanced, again supporting the fact that ABCG2 might play an important role in the differentiation and proliferation of clonogenic progenitors. Using the NOD/SCID mouse model, we were able to demonstrate that enforced expression of ABCG2 in human primitive haematopoietic cells leads to inversion of lymphoid-myeloid ratio, suggesting that ABCG2 perhaps alters the cell fate decisions of multipotent cells with myeloid and lymphoid differentiation capacity. An enhanced production of differentiated myeloid cells was observed on ABCG2 overexpression. In order to analyze the effect of ABCG2 on early haematopoietic cells, NOD/SCID mice transplanted with CB cells either expressing ABCG2 or the empty viral vector, were analyzed for the presence of HSC. Although the number of human CD34+ CD38- cells did not show any difference, the number of CD34+ CD38+ progenitor cells was significantly increased (n=5, p<0.05), indicating that ABCG2 plays a role in the differentiation of clonogenic progenitors. CRU assays were performed to detect the effect of ABCG2 expression on the frequency of SRC and did not show any significant increase in the frequency of SRC. Taken together, these results indicate that ABCG2 is a potent positive regulator of human hematopoiesis at the level of early haematopoietic development

TOLEARATION OR RECOGNITION. TOWARDS A NEW ACCOUNT OF RELIGIOUS DIVERSITY IN CONTEMPORARY EGYPT

If we portrait Egyptian socio-cultural context in the last few years, we can remarkably find out an avoidable form of contradiction which attaches to daily religious aspects. Now we can see a wide distance of intolerance currently exists in Egyptian's practical which reflect on their daily and formal; religious and cultural dialogues. This case of intolerance dramatically led to various acts of violence and hatred between Muslim and Christian. How can we understand the nature of that contradiction and how possibly can we raise it? Therefore the present study suggests a new theoretical frame of reference aims to recognize the world as characterized by different identities rather than different beliefs and values. This research through anthropological method seeks to describe all forms of tolerance in Egyptian daily life, determining the all forms of relationships between tolerance and other variables like religious pattern, educational status, gender and finally socio-economic class

Artificial neural networks for diagnosis and survival prediction in colon cancer

ANNs are nonlinear regression computational devices that have been used for over 45 years in classification and survival prediction in several biomedical systems, including colon cancer. Described in this article is the theory behind the three-layer free forward artificial neural networks with backpropagation error, which is widely used in biomedical fields, and a methodological approach to its application for cancer research, as exemplified by colon cancer. Review of the literature shows that applications of these networks have improved the accuracy of colon cancer classification and survival prediction when compared to other statistical or clinicopathological methods. Accuracy, however, must be exercised when designing, using and publishing biomedical results employing machine-learning devices such as ANNs in worldwide literature in order to enhance confidence in the quality and reliability of reported data

Temporal Issues in Market Inefficiency in asset prices with an emphasis on commodities

This summary provides an overview of the contributions made in this thesis to the literature. No references are included in the summary; these can be found in the Bibliography on page 156. This dissertation consists of 6 chapters. The first chapter acts as an introduction to the thesis and discusses the central theme of the dissertation along with providing a preview of what to expect in the following chapters. The contributions of the different chapters vary. Chapter 2 is a more introductory chapter and its contributions are perhaps less consequential than those in Chapters 3-5. Chapter 2 makes contributions to the literature on testing for explosive roots or bubbles. By modifying the Bhargava test statistic, we show in Chapter 2 that the Bhargava test can address earlier criticisms that had been cited against it; namely that it has low power when multiple bubbles are present in a particular series. Through introducing a rolling window approach, we are able to address that criticism and show that the modified Bhargava test statistic achieves better power. We compare and contrast the power of the modified test with the popular GSADF test statistic which has recently become popular in bubble testing literature. Another contribution made in this chapter is the application of these tests to a data set comprising of 25 commodities. As at the writing of the chapter this was believed to be a first attempt to perform bubble testing on a comprehensive commodity data set. Since commodities are often deemed to be targets of speculative behaviour, they are a natural universe for testing notions of market efficiency as they tend to go through different regimes through natural economic processes. Using both tests we are able to detect bubbles in similar periods with most of them being concentrated around the two oil price crises (1972-73 and 1979-80) and the financial crisis (2005-2007). Our conclusion is that the modified Bhargava statistic works better than the original statistic and can be used to complement the results of other statistics. The major contributions of Chapter 3 and 4 are the introduction of different methodologies that enable the user to assess how often asset markets are efficient. In Chapter 3 we argue that commodity prices can be estimated using switching-regression models including hidden Markov state-switching models. Instead of estimating Markov transition matrices directly from the estimation procedure, we estimate the transition matrix separately using unit root tests. By restricting the transition matrix to our estimated matrix and then estimating a Markov state-switching regression we show that we get more accurate smoothed probabilities i.e. a high probability is assigned to explosive states when the price was actually explosive and a high probability is assigned to the random walk/efficient state when the price exhibited efficient behaviour. This methodology is then extended to the three state case and it is argued that the transition matrices estimated this way will inform us of how often commodity markets are efficient. The methodology is empirically applied to non-ferrous metals with particular attention to Copper; we believe this is an additional contribution of the article. Chapter 3 also presents a partial equilibrium model which leads to an estimable reduced form expression for commodities and thereby motivates estimation by Markov switching-regressions. Three major contributions are made in Chapter 4. Firstly, we make a theoretical contribution to the literature on threshold auto-regressive models with exogenous triggers. Conditions for the existence of a mean and variance when a series follows a threshold auto-regressive (TAR) process with an exogenous trigger are derived. The second contribution is the use of TAR simulations to show that the tests which try to detect bubbles in asset prices lose a substantial amount of power when the asset price spends some time in the mean reverting state in addition to being in the explosive and random walk states. The third contribution of this article is the provision of a framework using TAR models which acts as a metric for market efficiency. By considering three states, an efficient/random walk state, a mean reverting state and an explosive state, we show that estimating asset prices as TARs with exogenous triggers can allow us to measure how often an asset market is efficient. This methodology uses a different class of models from those used in Chapter 4. The methodology is then applied to the S&P500 and FTSE100 process and it is shown that under the most general model specification, the indices primarily exhibit market efficiency. Chapter 5 looks deeper into how commodity prices are determined and thereby the main contribution is to the literature on commodity market pricing. By making three important changes to the commodity storage model of William and Wright (1991), we are able to show that our model is able to capture essential features of commodity prices that have not been captured by previous iterations. The numerical solution for the model is obtained using the Parameterized Expectations Algorithm (PEA) and simulated series based on this solution are able to reproduce some statistical features of real commodity price series including a high degree of first order auto-correlation, skewness and kurtosis. A second contribution is with regards to the application of the model; we calibrate the model to match five real commodities and show that the model’s solution is able to match real life data. The model is also able to explain why we observe spikes (bubbles) in commodity prices and cites the impact of storage as a probable contributor. Chapter 6 provides concluding remarks on the dissertation.Higher Education Commission of Pakistan, Cambridge Commonwealth Trus

Ripening of the AlSi9Cu3ZnMg alloy - mechanical and microstructural characterisation

Recovered aluminium has poor mechanical properties, to improve them considerably, three main factors have been considered. The first is to add four very low-density elements to the recovered aluminium, including 9% silicon, 3% copper and some traces of zinc and magnesium less than 1% (≤ 1% Zinc, ≤ 1% Mg), which produces the non-standardized casting alloy AlSi9Cu3ZnMg. Then, in order to obtain a fine microstructure, a gravity die-casting is carried out in the as-cast state noted: F. Finally, to further increase the strength of the F-state and essentially obtain high elasticity stresses, high rigidity modulus with low deformations, the AlSi9Cu3ZnMg alloy composed of 60% scrap and 40% new ingots, is subjected to structural hardening by varying the ripening time for 24 hours in increments of 2 hours, thus giving rise to precipitates of various kinds which impede the dislocations sliding.The results thus obtained show that the cured state for 12 hours (M12h) is a good compromise between good strength and maximum ductility.

Modified Value of Rock Quality Designation Index RQD in Rock Formation

The rock quality designation, RQD, is a commonly index used in the description of rock mass quality. This RQD, index value is used to predict the engineering properties of the rock strata under study. The RQD index value was introduced for the engineering applications, such as mining and geotechnical engineering. Calculating of RQD index for rock formation is a great part due to its simplicity. However, this also leads to a number of limitations, including among other, a dependency of RQDm value on the borehole orientation and on the selected threshold value for the minimum intact core length. In this paper, a new modified RQDm index is introduced to overcome the limitations when assessing the ordinary RQD index value. This modified and corrected value of RQDm index will be more conservative to use for predicting the rock properties than the ordinary RQD

Ripening of the AlSi9Cu3ZnMg alloy - mechanical and microstructural characterisation

Recovered aluminium has poor mechanical properties, to improve them considerably, three main factors have been considered. The first is to add four very low-density elements to the recovered aluminium, including 9% silicon, 3% copper and some traces of zinc and magnesium less than 1% (≤ 1% Zinc, ≤ 1% Mg), which produces the non-standardized casting alloy AlSi9Cu3ZnMg. Then, in order to obtain a fine microstructure, a gravity die-casting is carried out in the as-cast state noted: F. Finally, to further increase the strength of the F-state and essentially obtain high elasticity stresses, high rigidity modulus with low deformations, the AlSi9Cu3ZnMg alloy composed of 60% scrap and 40% new ingots, is subjected to structural hardening by varying the ripening time for 24 hours in increments of 2 hours, thus giving rise to precipitates of various kinds which impede the dislocations sliding.The results thus obtained show that the cured state for 12 hours (M12h) is a good compromise between good strength and maximum ductility.

Dependence Between Report Lag and Claim Amounts in Property and Casualty Insurance

An essential tool for comprehending the variable of interest is possessing a variable that can interpret the behavior of another. The concept of dependency has been intensively researched throughout the years, with numerous models. Copulas are a comprehensive tool for simulating the interdependence of the variables. They provide alternative interpretations of the linear and non-linear relationship between associated random variables and their marginal. In Insurance sector, one of the most risks that the insurers face is holding inefficient provision amounts for claims. This paper explains the dependence structure between the claim amount and the report lag period for claims in the insurance companies