Chromium(VI) Biosorption and Bioaccumulation by Live and Acid-Modified Biomass of a Novel Morganella morganii Isolate

Conventional methods of chromium removal are often insufficient for the remediation of chromium-contaminated natural environments, necessitating the development of alternative strategies. In this paper, we report the isolation of a novel Morganella morganii strain capable of reducing hexavalent chromium to its less-toxic and less-soluble trivalent form. Cr(VI) reduction by this strain was evaluated in both acidic environments and conditions reflecting natural freshwater sources. The isolate achieved equilibrium within 3 h and displayed a specific uptake rate of 24.30 ± 1.67 mg Cr(VI)/g biomass following HCl treatment. Without acid treatment, a reduction of over 90% was recorded within 72 h for an initial Cr(VI) concentration 20 mg/L, corresponding to a Cr(VI) removal capacity of 19.36 ± 1.89 mg/g. Absorption data of acid-treated STB5 biomass most closely followed the Toth and Langmuir models. FTIR results indicate that hydroxyl groups and extracellular or cell membrane polysaccharides may be potential adsorption sites for hexavalent chromium. Our results suggest that the isolate may be used in situ for treatment of polluted freshwater environments. Copyright © Taylor & Francis Group, LLC

Decreased Cerebrovascular Brain-Derived Neurotrophic Factor–Mediated Neuroprotection in the Diabetic Brain

Objective: Diabetes is an independent risk factor for stroke. However, the underlying mechanism of how diabetes confers that this risk is not fully understood. We hypothesize that secretion of neurotrophic factors by the cerebral endothelium, such as brain-derived neurotrophic factor (BDNF), is suppressed in diabetes. Consequently, such accrued neuroprotective deficits make neurons more vulnerable to injury. Research Design and Methods: We examined BDNF protein levels in a streptozotocin-induced rat model of diabetes by Western blotting and immunohistochemistry. Levels of total and secreted BDNF protein were quantified in human brain microvascular endothelial cells after exposure to advanced glycation end product (AGE)-BSA by enzyme-linked immunosorbent assay and immunocytochemistry. In media transfer experiments, the neuroprotective efficacy of conditioned media from normal healthy endothelial cells was compared with AGE-treated endothelial cells in an in vitro hypoxic injury model. Results: Cerebrovascular BDNF protein was reduced in the cortical endothelium in 6-month diabetic rats. Immunohistochemical analysis of 6-week diabetic brain sections showed that the reduction of BDNF occurs early after induction of diabetes. Treatment of brain microvascular endothelial cells with AGE caused a similar reduction in BDNF protein and secretion in an extracellular signal–related kinase-dependent manner. In media transfer experiments, conditioned media from AGE-treated endothelial cells were less neuroprotective against hypoxic injury because of a decrease in secreted BDNF. Conclusions: Taken together, our findings suggest that a progressive depletion of microvascular neuroprotection in diabetes elevates the risk of neuronal injury for a variety of central nervous system diseases, including stroke and neurodegeneration

Understanding How Social Entrepreneurs Fit into the Tourism Discourse

This chapter discusses how social entrepreneurs fit into the existing tourism discourse. It examines four areas of literature in particular, tourism entrepreneurs, sustainability, destination development and intrapreneurship, and analyzes how introducing the concept of social entrepreneurs into these discussions is useful, and contributes to our understanding. Furthermore the paper illustrates that as social entrepreneurs are relevant to a broad range of issues in the tourism literature this should prevent the development of research silos where social entrepreneurship scholars seek out their own vein of research. The nexus of common ground and interests, as displayed in this chapter, should enhance the development of research, thought and understanding of social entrepreneurs within the field as a whole The key argument is that research on social entrepreneurs is not just relevant for those interested in entrepreneurs it also effects our thinking on issues such as destination development, relationships between stakeholders, tourism policy and sustainability. The chapter concludes with a wide range of questions for further research

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

<p>Abstract</p> <p>Background</p> <p>Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.</p> <p>Methods</p> <p>A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis.</p> <p>Results</p> <p>The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results.</p> <p>Conclusion</p> <p>The proposed meta-analysis approach has the ability to detect a set of differentially expressed genes with the least amount of within-group variability, thus providing highly stable gene lists for class prediction. Increased statistical power and stringent filtering criteria used in the present study also make identification of novel candidate genes possible and may provide further insight to improve our understanding of breast cancer development.</p

A New Mathematical Model for Multisession Exams-Building Assignment

The educational timetabling problem has been extensively investigated in timetabling literature. However, the problem of assigning exams to examination buildings has not been studied intensively by researchers. We were inspired by Open and Distance Education System exams of Anadolu University. Anadolu University Open and Distance Education System, which is used by approximately two millions of students and has more than two millions of graduates, is a well-known institution in Turkey. In this study, we propose a multi-objective mathematical model for multisession exam-building assignment problem. Objective functions of this model are to minimize the distance between consecutive session buildings for a given student, to maximize the number of occupants of buildings in every session and to minimize the variety of booklets for building in every session. Mathematical model has been found inadequate because students-examination building assignment in the Anadolu University Open Education system is a large size real life problem. Starting from this point of view, an order-based multi-objective heuristic algorithm is developed to solve this problem. The solutions obtained by the proposed algorithm are compared with the solution obtained by the mathematical modelling and the current state of the existing system

Sentiment Analysis: an Application to Anadolu University

Social media is a Web 2.0 platform that allows to share content and information without the limitations of time and space. Social media networks have managed to become a part of today's lifestyle and are increasingly gaining importance when viewed from a state perspective. Sentiment analysis refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. In this study, we focus on social media mining and sentiment analysis for students of an open and distance education system. Anadolu University which has approximately two million students and more than two million graduates, is a well-known institution in Turkey, that offers higher education through contemporary distance education model. Firstly, we have fetched Tweets related to Anadolu University open and distance education system. To perform sentiment analysis, these tweets were analysed by statistical and data mining techniques. Finally, results were visualized