Antimicrobial studies on three Hypericum species from Turkey

The antimicrobial activity of several extracts and fractions of some Hypericum species (H. rupestre Jaub. & Spach, H. vacciniifolium Hayek & Siehe and H. imbricatum Poulter) was investigated using the disc diffusion method against Escherichia coli ATCC 11230, Staphylococcus aureus ATCC 6538P, Klebsiella pneumoniae UC57, Micrococcus luteus La 2971, Bordetella bronchiseptica ATCC 19395, Proteus vulgaris ATCC 8427, Pseudomonas aeruginosa ATCC 27853, Corynebacterium xerosis CCM 7064, Mycobacterium smegmatis CCM 2067, Bacillus subtilis ATCC 6633, Aeromonas hydrophila ATCC 49803, Candida albicans ATCC 10231, Saccharomyces cerevisiae ATCC 9730, Kluyveromyces fragilis NRRL 2415 and Rhodotorula rubra CCY. The methanol extract and chloroform fraction of H. vacciniifolium, as well as the methanol extracts, butanol and chloroform fractions of both H. rupestre and H. imbricatum, showed good antimicrobial activity against especially Gram-positive bacteria and the Gram-negative bacterium Bordetella bronchiseptica. The methanol extracts and fractions did not have antifungal activity. The results of the study support the use of these specimens in Turkish traditional medicine to treat skin and eye infections

Connexin 43 mediated gap junctional communication enhances breast tumor cell diapedesis in culture

INTRODUCTION: Metastasis involves the emigration of tumor cells through the vascular endothelium, a process also known as diapedesis. The molecular mechanisms regulating tumor cell diapedesis are poorly understood, but may involve heterocellular gap junctional intercellular communication (GJIC) between tumor cells and endothelial cells. METHOD: To test this hypothesis we expressed connexin 43 (Cx43) in GJIC-deficient mammary epithelial tumor cells (HBL100) and examined their ability to form gap junctions, establish heterocellular GJIC and migrate through monolayers of human microvascular endothelial cells (HMVEC) grown on matrigel-coated coverslips. RESULTS: HBL100 cells expressing Cx43 formed functional heterocellular gap junctions with HMVEC monolayers within 30 minutes. In addition, immunocytochemistry revealed Cx43 localized to contact sites between Cx43 expressing tumor cells and endothelial cells. Quantitative analysis of diapedesis revealed a two-fold increase in diapedesis of Cx43 expressing cells compared to empty vector control cells. The expression of a functionally inactive Cx43 chimeric protein in HBL100 cells failed to increase migration efficiency, suggesting that the observed up-regulation of diapedesis in Cx43 expressing cells required heterocellular GJIC. This finding is further supported by the observation that blocking homocellular and heterocellular GJIC with carbenoxolone in co-cultures also reduced diapedesis of Cx43 expressing HBL100 tumor cells. CONCLUSION: Collectively, our results suggest that heterocellular GJIC between breast tumor cells and endothelial cells may be an important regulatory step during metastasis

Contribution of the resampling stage to the execution time of particle filter Yeniden örnekleme adiminin parçacik süzgecinin çalişma zamanina katkisi

© 2019 IEEE.Particle filter is a serial Monte Carlo estimation algorithm. It represents the posterior probability density function with particles and their weights. As time progresses, the normalized weight of one of particles becomes nearly one, while the normalized weights of the remaining ones get close to zero. A common way to solve this problem, known as the degeneracy problem, is resampling. In resampling, the particles with larger weights are replicated, and the particles with smaller weights are eliminated. To tackle the numerical instability problem that is encountered by some of the resampling methods, the Metropolis resampling method is proposed by Murray and his co-workers. Unfortunately, Metropolis is liable to non-coalesced global memory access patterns on the GPU. In this work, we point to the Metropolis-C1 and Metropolis-C2 resampling methods which are proposed earlier. Then we examine the contribution of the stages of the particle filter to the total execution time by increasing the number of particles on a tracking application on the GPU. We use the Sampling Importance Resampling (SIR) method, which is a common particle filter. In the experiments, Metropolis resampling consumes the biggest portion of the execution time of the SIR particle filter. The share of Metropolis increases as the number of particles grows. It can be argued that this is because of non-coalesced global memory access patterns. To reach this conclusion it is sufficient to i) Compare the results of Metropolis, which has non-coalesced access patterns, with Metropolis-C1 and Metropolis-C2, which have confined non-coalesced access patterns, ii) See that the previous stages of the SIR particle filter are not subject to non-coalesced access patterns

MEASURING STRATEGIC BIG DATA MANAGEMENT ON INVESTMENTS, PARTICULARLY ON UNIVERSITY INVESTMENTS

In the changing environment of the 21st century, universities should develop very innovative ecosystems by doing right investments on human capital, research and development, buildings, laboratories, dorms, and other facilities on the campus while decreasing their costs and expenses in order to increase scientific and technological oriented innovations and outputs. For that reason, most of them are looking toward Big Data Management (BDM), which is a very new and dynamic subject to conduct properly and to make right decisions at the universities. Data analytics and data mining have increased and attracted the attention of most of the leaders, managers, administrators, researchers, and even educators who try to make massive data-related investments and decisions. More importantly, since the funding of higher education has become important issues for most of the governments and higher education management, the importance of BDM will increase in higher education much more than ever before. However, not all the universities are so successful in managing their small or medium-sized data. In this research, how universities are investing by improving their data was analyzed in three different universities in Istanbul. More strategically, how data analytics and mining can make changes and transformation higher education institutions by investing right resources under the promise of Big Data Management was critically studied. In this study, the impacts of big data mining and management on higher education institutions' sustainable funding, financing, planning, success, research and development, and innovation were critically studied. By taking into account the perceptions and the experiences of the experienced experts (6), faculty members (12), managers (4), and technical people (12), who were charged in using data analytics and mining at two state and one private universities, the investment of the universities had analyzed in order to understand critically the effects of the BDM. In the study, the phenomenological analysis was used by asking thirty-one research questions in the semi-structured interviews. While taking into account the observations of the researchers, the collected data of this study were systematically studied in data analysis software-program NVivo 10. The results showed that a few number of the investments had correctly done by using data mining and data analysis. As the participants had mentioned that the data would not have done anything if the higher education management had not taken into account and applied. So, according to the participants (75%), the university management understanding and policies should be changed in order to take in consideration the results of the big data. Even though a great amount of data had produced through the systems of the universities, the analysis, the segmentation, and the selected attention of the data had become dependent on the higher education management. The participants (28%), who were active in planning, funding, and investing, agreed that the investments done according to the results of the big data had better educational, financial, socio-economic, cultural, technological, environmental, and even individual benefits and outcomes. In conclusion, although a little data mining and analysis has properly used in making right investments, the universities are highly convinced on the positive effects of the BDM in their short-term and long-term investments in order to increase their impacts

What hospitality and tourism higher educators learned from COVID-19: A case of Turkiye

Among all the sectors, the hospitality and tourism sector has been detrimentally affected by the impact of the COVID-19 pandemic. This research aimed to determine how changes have been experienced specifically in the Turkish tourism higher education and tourism sector. Twenty-seven academics from the hospitality and tourism education departments were interviewed. Most agreed that restrictions have limited student access to hands-on practical courses and internships, which are crucial to developing necessary competencies. Moreover, the results showed the curriculum does not always meet the needs of the hospitality industry for a trained and skilled workforce. The challenge is to decide what else should be taught and what methods and teaching approaches should be used. As a result, industry-academia cooperation is necessary to reassess the curriculum programs to meet sector needs considering the pandemic impacts