Preservation of Urban Fabric: Towards Sustainable Development of Tarim City in Hadhramout Valley, Yemen

The Old Hadhrami Cities such as Tarim are famous for many luxurious palaces whose buildings integrated both the Hadhrami architectural original style and the Asian one. Thus the use of local construction materials in the city\u27s luxurious palaces made of mud clearly indicates the concept of active participation of the inhabitants in determining the quality of the architectural heritage which emerged from their social and cultural traditions and customs. This special use of local construction materials in buildings gives the city a distinguished position among other cities in the region. The present study aims at highlighting mainly the source of available facilities of urban development as well as the preservation of the city with regard to the available land space for sustainable development and the possibility of including some new services and projects to meet the needs of inhabitants. The large number of mosques, clay houses and religious schools in Tarim, all these buildings together, constitute a unique identity in the architectural construction in the city which appear clearly in the availability of a network of main and secondary roads located in the city under study. Further, the study aims to find out if it is possible to link the palaces in Tarim with other surrounding buildings in the area of the city through the suggested roads and passageways there. Finally, the study seeks to investigate the instructions and guidelines necessary for the city\u27s sustainable development through making use of the empty spaces and areas which may be useful for the meeting of the city\u27s visitors. All these supporting facilities are necessary for the urban renovation of the city under study for they might help in improving the economic situation for this region. Moreover, they might provide the city with the necessary services as well as connecting it with the other surrounding regions for the sake of tourism investment as an alternative for the crafting and industrial ones in the heritage environment. The city inhabitants\u27 increasing awareness of the heritage environment supports the preservation of those historical cities and as a result, encourages the inhabitants to settle in that area

Hydrogel porosity controlling DNA-directed immobilization of gold nanoparticles revealed by DNA melting and scanning helium ion microscopy

Immobilization of nanomaterials is important for many applications, including sensor development, biomaterials design and catalysis. DNA-directed immobilization has been widely used because of its high specificity and programmability. While most previous work has been carried out using inorganic surfaces such as gold, silica, and carbon, we recently found that hydrogels are also useful for immobilization. For non-porous inorganic surfaces, DNA-directed immobilization is governed mainly by probe density, while porosity might play a major role for hydrogels. Herein, we test the effect of gel porosity on DNA-directed immobilization of gold nanoparticles (AuNPs). Porosity was varied by changing the hydrogel percentage and crosslinker density. The number of immobilized AuNPs and its binding strength were characterized by DNA melting experiments. Using scanning helium ion microscopy, the AuNP density on hydrogel was studied. The number of AuNP binding sites decreased with decreasing gel porosity or increasing AuNP size, implying that the associated AuNPs were inside the gel pores. Polyvalent binding is a key feature for nanoparticle immobilization. For a non-porous surface, polyvalent binding occurs only at one small spot. We found that hydrogels take advantage of its porous nature to establish 3-dimensional polyvalent binding. Even with a very low surface DNA density, effective AuNP immobilization can still be achieved.University of Waterloo || Canada Foundation for Innovation || Ontario Ministry of Research and Innovation || Natural Sciences and Engineering Research Council || Ministry of Higher Education of Saudi Arabia |

Identifying driver mutations in cancers

All cancers depend upon mutations in critical genes, which confer a selective advantage to the tumour cell. The key to understanding the contribution of a disease-associated mutation to the development and progression of cancer comes from an understanding of the consequences of that mutation on the function of the affected protein, and the impact on the pathways in which that protein is involved. Using data from over 30 different cancers from whole-exome sequencing cancer genomic projects, I analysed over one million somatic mutations. I identified mutational hotspots within domain families by mapping small mutations to equivalent positions in multiple sequence alignments of protein domains. I found that gain of function mutations from oncogenes and loss of function mutations from tumour suppressors are normally found in different domain families and when observed in the same domain families, hotspot mutations are located at different positions within the multiple sequence alignment of the domain. Next, I investigated the ability of seven prediction algorithms to discriminate between driver missense mutations in oncogenes and tumour suppressors. Using 19 features to describe these mutations, I then developed a random forest classifier, MOKCaRF, to distinguish between gain of function and loss of function missense mutations in cancer. MOKCaRF performs significantly better than existing algorithms. I then evaluated the ability of six existing prediction tools to distinguish between pathogenic and neutral mutations for both inframe insertion and inframe deletion mutations. I developed my own classifiers using 11 features that perform better than the current algorithms. Finally, using the algorithms that I developed, as well as changes in copy number and expression data for each gene, I analysed samples from 50 lung cancer patients to identify the actionable targets and potential new drug targets for each tumour

DNA-Functionalized Monolithic Hydrogels and Gold Nanoparticles for Colorimetric DNA Detection

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Applied Materials & Interfaces, copyright © American Chemical Society after peer review and technical editing by publisher. To access the final edited and published work see Baeissa, A., Dave, N., Smith, B. D., & Liu, J. (2010). DNA-Functionalized Monolithic Hydrogels and Gold Nanoparticles for Colorimetric DNA Detection. ACS Applied Materials & Interfaces, 2(12), 3594–3600. https://doi.org/10.1021/am100780dHighly sensitive and selective DNA detection plays a central role in many fields of research, and various assay platforms have been developed. Compared to homogeneous DNA detection, surface-immobilized probes allow washing steps and signal amplification to give higher sensitivity. Previously research was focused on developing glass or gold-based surfaces for DNA immobilization; we herein report hydrogel-immobilized DNA. Specifically, acrydite-modified DNA was covalently functionalized to the polyacrylamide hydrogel during gel formation. There are several advantages of these DNA-functionalized monolithic hydrogels. First, they can be easily handled in a way similar to that in homogeneous assays. Second, they have a low optical background where, in combination with DNA-functionalized gold nanoparticles, even ∼0.1 nM target DNA can be visually detected. By using the attached gold nanoparticles to catalyze the reduction of Ag+, as low as 1 pM target DNA can be detected. The gels can be regenerated by a simple thermal treatment, and the regenerated gels perform similarly to freshly prepared ones. The amount of gold nanoparticles adsorbed through DNA hybridization decreases with increasing gel percentage. Other parameters including the DNA concentration, DNA sequence, ionic strength of the solution, and temperature have also been systematically characterized in this study.University of Waterloo || Natural Sciences and Engineering Research Council || Ministry of Higher Education of Saudi Arabia |

Identification and analysis of mutational hotspots in oncogenes and tumour suppressors

Background: The key to interpreting the contribution of a disease-associated mutation in the development and progression of cancer is an understanding of the consequences of that mutation both on the function of the affected protein and on the pathways in which that protein is involved. Protein domains encapsulate function and position-specific domain based analysis of mutations have been shown to help elucidate their phenotypes. Results: In this paper we examine the domain biases in oncogenes and tumour suppressors, and find that their domain compositions substantially differ. Using data from over 30 different cancers from whole-exome sequencing cancer genomic projects we mapped over one million mutations to their respective Pfam domains to identify which domains are enriched in any of three different classes of mutation; missense, indels or truncations. Next, we identified the mutational hotspots within domain families by mapping small mutations to equivalent positions in multiple sequence alignments of protein domains We find that gain of function mutations from oncogenes and loss of function mutations from tumour suppressors are normally found in different domain families and when observed in the same domain families, hotspot mutations are located at different positions within the multiple sequence alignment of the domain. Conclusions: By considering hotspots in tumour suppressors and oncogenes independently, we find that there are different specific positions within domain families that are particularly suited to accommodate either a loss or a gain of function mutation. The position is also dependent on the class of mutation. We find rare mutations co-located with well-known functional mutation hotspots, in members of homologous domain superfamilies, and we detect novel mutation hotspots in domain families previously unconnected with cancer. The results of this analysis can be accessed through the MOKCa database (http://strubiol.icr.ac.uk/ extra/MOKCa)

An evaluation of space planning towards habitable house design for low-income group in Mukalla and Shibam, Yemen

The aim of this research is to evaluate the house design and its habitable the level of satisfaction of the low-income group in Mukalla and Shibam, Yemen The study focuses on the house design of the low-income group of Modern Mukalla, and uses the traditional house design in Shibam as the reference model because of its UNESCO's recognition listed under World Heritage Site. The study commences with the definitions of house, house design and habitability. The study finds that space planning and function, interior elements house-unit, interior house comfort level, interior house servtces, and indoor socio-cultural actives are important categories for definition of the house design and its habitability. It proceeds to provide qualitative and quantitative analyses of the data of these five categories as the check-list factors. A comparison of the responses under these five categories is made for Mukalla and Shibam. The outcome of the above steps is then subjected to a further analysis using triangulation method. The study finds that the respondents who live at modern houses are slightly satisfied with their house design in Modern Mukalla. It also observes that the house design in Shibam can serve as reference model of habitable house design for Hadhramout region, Yemen. The study finally provides several useful guidelines of habitable house design for the low-income group in Hadhramout region, Yemen

Mutational patterns in oncogenes and tumour suppressors

All cancers depend upon mutations in critical genes, which confer a selective advantage to the tumour cell. Knowledge of these mutations is crucial to understanding the biology of cancer initiation and progression, and to the development of targeted therapeutic strategies. The key to understanding the contribution of a disease-associated mutation to the development and progression of cancer, comes from an understanding of the consequences of that mutation on the function of the affected protein, and the impact on the pathways in which that protein is involved. In this paper we examine the mutation patterns observed in oncogenes and tumour suppressors, and discuss different approaches that have been developed to identify driver mutations within cancers that contribute to the disease progress. We also discuss the MOKCa database where we have developed an automatic pipeline that structurally and functionally annotates all proteins from the human proteome that are mutated in cancer

Identifying the impact of inframe insertions and deletions on protein function in cancer

Inframe insertion and deletion mutations (indels) are commonly observed in cancer samples accounting for over 1% of all reported mutations. Few somatic inframe indels have been clinically documented as pathogenic and at present there are few tools to predict which indels drive cancer development. However, indels are a common feature of hereditary disease and several tools have been developed to predict the impact of inframe indels on protein function. In this study, we test whether six of the popular prediction tools can be adapted to test for cancer driver mutations and then develop a new algorithm (IndelRF) that discriminates between recurrent indels in known cancer genes and indels not associated with disease. IndelRF was developed to try and identify somatic, driver, and inframe indel mutations. Using a random forest classifier with 11 features, IndelRF achieved accuracies of 0.995 and 0.968 for insertion and deletion mutations, respectively. Finally, we use IndelRF to classify the inframe indel cancer mutations in the MOKCa database

Photocatalytic Degradation of Methylene Blue by Fe/ZnO/SiO 2

The photocatalytic activity of Fe/ZnO/SiO2 catalysts under visible-light irradiation for the degradation of methylene blue was evaluated. The effect of pH, illumination time, amount of catalyst loaded, and initial dye concentration on the degradation efficiency of methylene blue was investigated. The results reveal that the optimum photocatalytic oxidation conditions of methylene blue are as follows: pH=4 and illumination time is 30 min, the amount of catalyst loading is 0.075 g/L and 50 ppm methylene blue dye concentration. Under these conditions, the removal efficiency of methylene blue was 100%

Bioinformatics in translational drug discovery

Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse ‘big data’ that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications