Pub Date : 2021-02-20DOI: 10.18466/CBAYARFBE.752495
S. Ilhan
Docetaxel (DOC) is a chemotherapeutic that induces microtubule stabilization. It is often used in breast, prostate, lung and gastric cancers but severe side effects such as cardiotoxicity, neurotoxicity, hepatotoxicity, and nephrotoxicity limit its usage. Curcumin (CUR), a natural bioactive compound derived from turmeric. Here, the possible preventive effect of CUR against DOC-induced oxidative stress and apoptosis on HEK-293 immortalized human embryonic kidney cells. Viability was assessed via MTT assay. The generation of ROS was measured by CM-H2DCFDA dye. Phosphatidylserine externalization and caspase 3/7 activity were used to measure apoptosis. CUR pretreatment remarkably inhibited DOC-induced cell viability reduction, ROS generation, and cell apoptosis in HEK-293 cells. Moreover, this study revealed that CUR pretreatment decreased the caspase-3 activity. Thus, this study highlights the novel pharmacological mechanisms of CUR and understanding the detailed mechanisms of CUR action could lead to novel renoprotective interventions.
{"title":"Attenuation of Docetaxel-induced Oxidative Stress and Apoptosis in HEK 293 Human Embryonic Kidney Cells by Curcumin Treatment","authors":"S. Ilhan","doi":"10.18466/CBAYARFBE.752495","DOIUrl":"https://doi.org/10.18466/CBAYARFBE.752495","url":null,"abstract":"Docetaxel (DOC) is a chemotherapeutic that induces microtubule stabilization. It is often used in breast, prostate, lung and gastric cancers but severe side effects such as cardiotoxicity, neurotoxicity, hepatotoxicity, and nephrotoxicity limit its usage. Curcumin (CUR), a natural bioactive compound derived from turmeric. Here, the possible preventive effect of CUR against DOC-induced oxidative stress and apoptosis on HEK-293 immortalized human embryonic kidney cells. Viability was assessed via MTT assay. The generation of ROS was measured by CM-H2DCFDA dye. Phosphatidylserine externalization and caspase 3/7 activity were used to measure apoptosis. CUR pretreatment remarkably inhibited DOC-induced cell viability reduction, ROS generation, and cell apoptosis in HEK-293 cells. Moreover, this study revealed that CUR pretreatment decreased the caspase-3 activity. Thus, this study highlights the novel pharmacological mechanisms of CUR and understanding the detailed mechanisms of CUR action could lead to novel renoprotective interventions.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"6 1","pages":"73-78"},"PeriodicalIF":0.0,"publicationDate":"2021-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90048550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-30DOI: 10.18466/CBAYARFBE.811643
Burcu Somtürk Yılmaz, Serkan Dayan, C. Altinkaynak, N. Ozpozan, N. Özdemir
In this study, flower shape hybrid protein-inorganic hybrid nanostructures were synthesized using a common protein (bovine serum albumin, BSA) and metal ion (Cu2+) at different protein concentrations (0.01, 0.02, 0.05, and 0.1mg mL-1) and pHs (PBS pH:6-9) at +4 oC for investigation of thermal properties the first time in detail. These synthesized protein-inorganic hybrid nanostructures (BSA-Cu3(PO4)2. 3H2O hNFs) were defined using SEM, EDX, elemental mapping XRD, FTIR, etc. Morphologies of BSA-Cu3(PO4)2.3H2O hNFs were characterized by SEM. Element analysis of BSA-Cu3(PO4)2.3H2O hNFs was achieved by EDX. Peak positions of BSA-Cu3(PO4)2. 3H2O hNFs were investigated using XRD. And, the FTIR technique was used to substantiate the creation of hNFs. Also, the thermal behavior such as glass transition and crystallization of BSA-Cu3(PO4)2.3H2O hNFs were investigated in detail using thermal gravimetric analysis (TGA).
{"title":"Thermal Behaviours of Flower Shape BSA@Cu(II) Hybrid Nanostructures","authors":"Burcu Somtürk Yılmaz, Serkan Dayan, C. Altinkaynak, N. Ozpozan, N. Özdemir","doi":"10.18466/CBAYARFBE.811643","DOIUrl":"https://doi.org/10.18466/CBAYARFBE.811643","url":null,"abstract":"In this study, flower shape hybrid protein-inorganic hybrid nanostructures were synthesized using a common protein (bovine serum albumin, BSA) and metal ion (Cu2+) at different protein concentrations (0.01, 0.02, 0.05, and 0.1mg mL-1) and pHs (PBS pH:6-9) at +4 oC for investigation of thermal properties the first time in detail. These synthesized protein-inorganic hybrid nanostructures (BSA-Cu3(PO4)2. 3H2O hNFs) were defined using SEM, EDX, elemental mapping XRD, FTIR, etc. Morphologies of BSA-Cu3(PO4)2.3H2O hNFs were characterized by SEM. Element analysis of BSA-Cu3(PO4)2.3H2O hNFs was achieved by EDX. Peak positions of BSA-Cu3(PO4)2. 3H2O hNFs were investigated using XRD. And, the FTIR technique was used to substantiate the creation of hNFs. Also, the thermal behavior such as glass transition and crystallization of BSA-Cu3(PO4)2.3H2O hNFs were investigated in detail using thermal gravimetric analysis (TGA).","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"156 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84676508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-29DOI: 10.18466/CBAYARFBE.705653
Emrah Dagli, Ömer Çapar
In the present study, the bearing capacities of coarse graded soils beneath the strip foundations were calculated by means of analytical and numerical methods. First all necessary geotechnical properties of the soil were achieved at seven different relative density values of the soil in terms of correlations between friction angle () and dry density (d). Second, 63 bearing capacity analyses of strip foundation systems were conducted by changing the soil parameters and the width of the foundations with analytical and finite element methods (FEM). The Mohr-Coulomb, elastic-plastic, model was chosen for this research. Although explicit analytic solutions were obtained without any difficulty, FEM provided only the load-deformation response at the base of the footing from the models. Because of that, some prediction methods were used to evaluate and find the bearing capacity of the soils beneath the foundation from the load-deformation responses. The results of analytic and numerical analyses of strip foundation laying on loose soil models gave very similar values. Although, very similar bearing capacity values of the foundations laying on dense soil models were calculated from the analytical methods, the results of numerical methods were very divergent and scattered at the same conditions. The reason for this is due to some limitations of the elastic-plastic model and prediction methods.
{"title":"Evaluation of the Bearing Capacity of Sandy Soils with Analytical and Numerical Methods","authors":"Emrah Dagli, Ömer Çapar","doi":"10.18466/CBAYARFBE.705653","DOIUrl":"https://doi.org/10.18466/CBAYARFBE.705653","url":null,"abstract":"In the present study, the bearing capacities of coarse graded soils beneath the strip foundations were calculated by means of analytical and numerical methods. First all necessary geotechnical properties of the soil were achieved at seven different relative density values of the soil in terms of correlations between friction angle () and dry density (d). Second, 63 bearing capacity analyses of strip foundation systems were conducted by changing the soil parameters and the width of the foundations with analytical and finite element methods (FEM). The Mohr-Coulomb, elastic-plastic, model was chosen for this research. Although explicit analytic solutions were obtained without any difficulty, FEM provided only the load-deformation response at the base of the footing from the models. Because of that, some prediction methods were used to evaluate and find the bearing capacity of the soils beneath the foundation from the load-deformation responses. The results of analytic and numerical analyses of strip foundation laying on loose soil models gave very similar values. Although, very similar bearing capacity values of the foundations laying on dense soil models were calculated from the analytical methods, the results of numerical methods were very divergent and scattered at the same conditions. The reason for this is due to some limitations of the elastic-plastic model and prediction methods.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"108 1","pages":"91-100"},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87648478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-14DOI: 10.18466/CBAYARFBE.716691
B. Uzilday
Aim of this work was to investigate effects of Cu, Zn and Fe treatments on small ubiquitin-like modifier (SUMO) machinery of Arabidopsis thaliana. SUMO is a 100-115 amino acid post-translational modifier that can regulate stability, activity or sub-cellular localization of target proteins. A. thaliana plants were treated with 50 µM Cu, 700 µM Zn and 400 µM Fe for 7 d and then expressions of genes related to SUMOylation and deSUMOylation of target proteins were measured with qRT-PCR. Only Cu treatment was able to induce genes related to SUMOylation (SUM3, SAE2, SIZ1) of target proteins, while all of the three metal used in this study was effective in inducing a deSUMOylation related gene. Results of this study indicated that deSUMOylation of proteins might be a part of plant response to metal toxicity.
{"title":"The Expressions of Small Ubiquitin-like Modifier (SUMO) Related Genes Under Metal (Cu, Zn and Fe) Stress in Arabidopsis thaliana","authors":"B. Uzilday","doi":"10.18466/CBAYARFBE.716691","DOIUrl":"https://doi.org/10.18466/CBAYARFBE.716691","url":null,"abstract":"Aim of this work was to investigate effects of Cu, Zn and Fe treatments on small ubiquitin-like modifier (SUMO) machinery of Arabidopsis thaliana. SUMO is a 100-115 amino acid post-translational modifier that can regulate stability, activity or sub-cellular localization of target proteins. A. thaliana plants were treated with 50 µM Cu, 700 µM Zn and 400 µM Fe for 7 d and then expressions of genes related to SUMOylation and deSUMOylation of target proteins were measured with qRT-PCR. Only Cu treatment was able to induce genes related to SUMOylation (SUM3, SAE2, SIZ1) of target proteins, while all of the three metal used in this study was effective in inducing a deSUMOylation related gene. Results of this study indicated that deSUMOylation of proteins might be a part of plant response to metal toxicity.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"40 1","pages":"301-305"},"PeriodicalIF":0.0,"publicationDate":"2020-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81569164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-07DOI: 10.18466/cbayarfbe.770565
Gozde Basak Ozturk, Mert Tunca
The intense association of the architecture, engineering, construction, operation, and facility management (AECO/FM) industry with cognitive and behavioral technologies leads to the increase in productivity of industry activities. In light of these thoughts, the building information modeling (BIM) platform is included in the AECO/FM industry to further increase efficiency and deliver construction projects economically, timely, and safely. While the BIM platform can work integrated with many programs and systems, concepts that offer innovative and fast solutions such as artificial intelligence (AI) benefit the AECO/FM industry. The main aim of this study is to understand the tendency of AI in BIM research carried out in different countries and by various scholars. This study adopts a bibliometric search, and a scientometric analysis and mapping approach with applying document-based citation analysis, country-based citation analysis, and country-based bibliographic coupling analysis of scientific research of AI and BIM integration. Data on the use of AI and BIM has been collected by reviewing and screening articles selected from the Scopus database. The results reveal that information management, decision support systems, genetic algorithms, neural networks, knowledge-based systems, machine learning, and deep learning effect AI in BIM research. This article contributes to the AECO/FM literature by analyzing and visualizing the current status and relationship between AI and BIM. Therefore, the findings highlight the gaps and trends in AI and BIM studies and provide new recommendations for future studies.
{"title":"Artificial Intelligence in Building Information Modeling Research: Country and Document-based Citation and Bibliographic Coupling Analysis","authors":"Gozde Basak Ozturk, Mert Tunca","doi":"10.18466/cbayarfbe.770565","DOIUrl":"https://doi.org/10.18466/cbayarfbe.770565","url":null,"abstract":"The intense association of the architecture, engineering, construction, operation, and facility management (AECO/FM) industry with cognitive and behavioral technologies leads to the increase in productivity of industry activities. In light of these thoughts, the building information modeling (BIM) platform is included in the AECO/FM industry to further increase efficiency and deliver construction projects economically, timely, and safely. While the BIM platform can work integrated with many programs and systems, concepts that offer innovative and fast solutions such as artificial intelligence (AI) benefit the AECO/FM industry. The main aim of this study is to understand the tendency of AI in BIM research carried out in different countries and by various scholars. This study adopts a bibliometric search, and a scientometric analysis and mapping approach with applying document-based citation analysis, country-based citation analysis, and country-based bibliographic coupling analysis of scientific research of AI and BIM integration. Data on the use of AI and BIM has been collected by reviewing and screening articles selected from the Scopus database. The results reveal that information management, decision support systems, genetic algorithms, neural networks, knowledge-based systems, machine learning, and deep learning effect AI in BIM research. This article contributes to the AECO/FM literature by analyzing and visualizing the current status and relationship between AI and BIM. Therefore, the findings highlight the gaps and trends in AI and BIM studies and provide new recommendations for future studies.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"26 1","pages":"269-279"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87668837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-07DOI: 10.18466/cbayarfbe.729586
E. Erdem
Microfluidic reactors are advantageous for nanomaterial synthesis due to their capability to provide controlled reaction environment. In this work, a droplet based microfluidic reactor is designed for the synthesis of silica nanoparticles. The synthesis is carried out in a very controlled environment and a uniform size and shape distribution is achieved. The classical synthesis protocol for silica nanoparticles is modified to use nonpolar solvents in the reaction so that this platform can later be used for coating hydrophobic nanomaterials. Therefore, this study not only presents a new device but also a new synthesis method. The results are compared with conventional batch wise synthesis methods and the obtained nanoparticles showed better size distribution.
{"title":"Droplet-based Microfluidic Device for the Synthesis of Silica Nanoparticles","authors":"E. Erdem","doi":"10.18466/cbayarfbe.729586","DOIUrl":"https://doi.org/10.18466/cbayarfbe.729586","url":null,"abstract":"Microfluidic reactors are advantageous for nanomaterial synthesis due to their capability to provide controlled reaction environment. In this work, a droplet based microfluidic reactor is designed for the synthesis of silica nanoparticles. The synthesis is carried out in a very controlled environment and a uniform size and shape distribution is achieved. The classical synthesis protocol for silica nanoparticles is modified to use nonpolar solvents in the reaction so that this platform can later be used for coating hydrophobic nanomaterials. Therefore, this study not only presents a new device but also a new synthesis method. The results are compared with conventional batch wise synthesis methods and the obtained nanoparticles showed better size distribution.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"39 1","pages":"245-249"},"PeriodicalIF":0.0,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77960114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.18466/cbayarfbe.742889
Emrah Dönmez
Analysis of agricultural products is an important area that is widely emphasized today. In this context, with the development of technology, computer-aided analysis systems are also being developed. In this study, a system has been proposed for classifying maize seeds as haploid and diploid using pre-trained convolutional neural networks. For this purpose, AlexNet, GoogLeNet, ResNet-18, ResNet-50, and VGG16 pre-trained models have been used as feature extractors for the haploid and diploid seed classification process. In the first stage, the deep features of haploid and diploid maize seeds have been obtained in these models. The features have been taken from different layers of network architecture. Instead of softmax classifier in the last layer of the network, classifiers based on decision tree, k-nearest neighbor, and support vector machine have been used. According to the classification results with these features, the achievements in network architectures and classifier methods have been observed. The experiments have been carried out on a publicly available dataset consisting of 3000 haploid and diploid maize seed images. The experimental results revealed that the developed classification systems demonstrate a remarkable performance.
{"title":"Classification of Haploid and Diploid Maize Seeds based on Pre-Trained Convolutional Neural Networks","authors":"Emrah Dönmez","doi":"10.18466/cbayarfbe.742889","DOIUrl":"https://doi.org/10.18466/cbayarfbe.742889","url":null,"abstract":"Analysis of agricultural products is an important area that is widely emphasized today. In this context, with the development of technology, computer-aided analysis systems are also being developed. In this study, a system has been proposed for classifying maize seeds as haploid and diploid using pre-trained convolutional neural networks. For this purpose, AlexNet, GoogLeNet, ResNet-18, ResNet-50, and VGG16 pre-trained models have been used as feature extractors for the haploid and diploid seed classification process. In the first stage, the deep features of haploid and diploid maize seeds have been obtained in these models. The features have been taken from different layers of network architecture. Instead of softmax classifier in the last layer of the network, classifiers based on decision tree, k-nearest neighbor, and support vector machine have been used. According to the classification results with these features, the achievements in network architectures and classifier methods have been observed. The experiments have been carried out on a publicly available dataset consisting of 3000 haploid and diploid maize seed images. The experimental results revealed that the developed classification systems demonstrate a remarkable performance.","PeriodicalId":9652,"journal":{"name":"Celal Bayar Universitesi Fen Bilimleri Dergisi","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90769939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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