TR Dizin İndeksli Yayınlar / TR Dizin Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7149
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Article Citation - WoS: 2Citation - Scopus: 1Dynamics of Co2 Consumption, and Biomass and Lipid Carbon Production During Photobioreactor Cultivation of the Diatom Cyclotella(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2023) Ökten, HaticeUnderstanding of CO2 delivery and consumption dynamics in algal photobioreactors are critical to unravel microalgae’s full potential for bioproduct generation and carbon capture from flue gas streams. This study aims to expand our current understanding by cultivating the diatom Cyclotella under controlled process conditions of a bubble column photobioreactor and analyzing CO2 consumption dynamics in real time using results from an online CO2 sensor connected to the reactor exhaust. Two sets of experiments were conducted: they served to contrast the influence of silicon and nitrate (Si&N colimitation) and Si limitation, and the light availability, respectively. CO2 consumption was calculated based on the mass balance around the reactor inlet and outlet gas streams. Biomass samples and lipid extracts were analyzed for carbon (C) content to determine biomass-C and lipid-C concentrations. The outlet CO2 concentrations varied significantly with cultivation time and process conditions. More than 15% to 65% of the CO2 introduced left the reactor in the exhaust at any instance based on the set CO2 transfer rates. The highest average daily capturing efficiency was 60%. Nutrient limitation regimes imposed generated unique CO2 consumption profiles undiscernible by the biomass-C analysis, i.e. unlike Si limitation, N limitation had more immediate detrimental effects on C consumption. Final biomass-C concentration increased with increasing N and light availability, 275 mg/L vs. 336 mg/L, and 270 mg/L vs. 501 mg/L, respectively. Biomass-C based capturing efficiency approximations resulted in 20% to 40% underestimation. Under Si-limited conditions, the higher light intensity increased the final lipid-C to biomass-C ratio by two times (from 20% to 40%) and the final lipid-C concentration and peak productivity by four times (from 56 mg/L to 216 mg/L, from 7 to 30 mg/L-day, respectively). This study demonstrates online exhaust CO2 concentration-based analysis’s unique capabilities for assessing carbon availability and capture, organic-C production, and its diversion to biomass and lipid production.Article Citation - WoS: 1Citation - Scopus: 2A Molecularly Imprinted Polymer as Solid Phase Extraction Sorbent for Ketoprofen Determination in Water and Artificial Serum Prior To Hplc(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Shahwan, Talal; Gürel Özyurt, Elif; Özyurt, Ömer; Ölçer, Yekta Arya; Eroğlu, Ahmet Emin; Boyacı, EzelKetoprofen (KET) is an active pharmaceutical compound that has pain relieving and antipyretic effects. Its determination in body fluids and environmental waters is important due to widespread use of the compound. In this study, a selective and reliable method has been developed for the determination of ketoprofen in water and artificial serum using molecularly imprinted polymers (MIPs) as a solid phase extraction sorbent prior to HPLC-DAD detection. The MIP was synthesized by copolymerization of methacrylic acid (MAA) and trimethylpropane trimethacrylate (TRIM) in the presence of ketoprofen as the template. For the sake of comparison, nonimprinted polymer (NIP) was also synthesized under the same experimental conditions without the addition of ketoprofen under the same experimental conditions. Critical extraction parameters such as sample pH, shaking time and sorbent amount were optimized and adjusted to 8.0, 24 h, and 10.0 mg, respectively, for a sample volume of 10.0 mL. MIP showed higher selectivity than NIP towards ketoprofen in an artificial matrix containing another pain relieving drug, ibuprofen, and a cardiovascular drug, metoprolol. The proposed method was successfully applied for the detection of ketoprofen in spiked drinking water, tap water, and artificial serum samples, and showed satisfactory results with respective recoveries of 96.8 % (± 0.8), 93.7% (± 0.6), 62.2% (± 0.6), and 69.9% (± 0.6).Article Asking the Right Questions To Solve Algebraic Word Problems(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Çelik, Ege Yiğit; Orulluoğlu, Zeynel; Mertoğlu, Rıdvan; Tekir, SelmaWord algebra problems are among challenging AI tasks as they combine natural language understanding with a formal equation system. Traditional approaches to the problem work with equation templates and frame the task as a template selection and number assignment to the selected template. The recent deep learning-based solutions exploit contextual language models like BERT and encode the natural language text to decode the corresponding equation system. The proposed approach is similar to the template-based methods as it works with a template and fills in the number slots. Nevertheless, it has contextual understanding because it adopts a question generation and answering pipeline to create tuples of numbers, to finally perform the number assignment task by custom sets of rules. The inspiring idea is that by asking the right questions and answering them using a state-of-the-art language model-based system, one can learn the correct values for the number slots in an equation system. The empirical results show that the proposed approach outperforms the other methods significantly on the word algebra benchmark dataset alg514 and performs the second best on the AI2 corpus for arithmetic word problems. It also has superior performance on the challenging SVAMP dataset. Though it is a rule-based system, simple rule sets and relatively slight differences between rules for different templates indicate that it is highly probable to develop a system that can learn the patterns for the collection of all possible templates, and produce the correct equations for an example instance.Data Paper Knockdown of Death Receptor 5 Antisense Long Noncoding Rna and Cisplatin Treatment Modulate Similar Macromolecular and Metabolic Changes in Hela Cells(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Gürer, Dilek Cansu; Erdoğan Vatansever, İpek; Ceylan, Çağatay; Akgül, BünyaminBackground/aim: Despite great progress in complex gene regulatory mechanisms in the dynamic tumor microenvironment, the potential contribution of long noncoding RNAs (lncRNAs) to cancer cell metabolism is poorly understood. Death receptor 5 antisense (DR5-AS) is a cisplatin inducible lncRNA whose knockdown modulates cell morphology. However, its effect on cell metabolism is unknown. The aim of this study is to examine metabolic changes modulated by cisplatin and DR5-AS lncRNA in HeLa cells. Materials and methods: We used cisplatin as a universal cancer therapeutic drug to modulate metabolic changes in HeLa cervix cancer cells. We then examined the extent of metabolic changes by Fourier transform infrared spectroscopy (FTIR). We also performed transcriptomics analyses by generating new RNA-seq data with total RNAs isolated from cisplatin-treated HeLa cells. Then, we compared cisplatin-mediated transcriptomics and macromolecular changes with those mediated by DR5-AS knockdown. Results: Cisplatin treatment caused changes in the unsaturated fatty acid and lipid-to-protein ratios and the glycogen content. These observations in altered cellular metabolism were supported by transcriptomics analyses. FTIR spectroscopy analyses have revealed that DR5-AS knockdown causes a 20.9% elevation in the lipid/protein ratio and a 76.6% decrease in lipid peroxidation. Furthermore, we detected a 3.42% increase in the chain length of the aliphatic lipids, a higher content of RNA, and a lower amount of glycogen indicating relatively lower metabolic activity in the DR5-AS knockdown HeLa cells. Interestingly, we observed a similar gene expression pattern under cisplatin treatment and DR5-AS knockdown HeLa cells. Conclusion: These results suggest that DR5-AS lncRNA appears to account for a fraction of cisplatin-mediated macromolecular ametabolic changes in HeLa cervix cancer cells.Article Citation - WoS: 3Citation - Scopus: 4Photocatalytic Degradation of Aquatic Organic Pollutants With Zn- and Zr-Based Metalorganic Frameworks: Zif-8 and Uio-66(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Çalık, Fatma Defne; Erdoğan, Bilgesu; Yılmaz, Esra; Saygı, Gizem; Çakıcıoğlu-Özkan, FehimeWater treatment has been an essential issue with the increasing population over 40 years. Researchers center on the major organic pollutants, such as dyes, pesticides, and pharmaceutical products. Photocatalytic degradation is one of the promising methods for aquatic organic pollutant treatment. Over the years, scientists have been working on developments for photocatalysts to enhance their pollutant degradation performances. From the reviewed studies, it is seen that properties like surface area, chemical, mechanical, and thermal stability, and uniform distribution of active sites are crucial, and an increase in these properties provides better degradation efficiency. In this sense, metal-organic frameworks as photocatalysts can be considered more advantageous. This study focuses on the organic aquatic pollutant degradation studies by using well-known MOFs like ZIF-8 and UiO-66 photocatalysts. Mainly the organic dye (RhB, MB, MO, etc.) degradation efficiencies of ZIF-8 and UiO-66 have been achieved to 100%. Recently, the degradation capacities of various pharmaceuticals such as diazinon, acetaminophen, levofloxacin, and sulfamethoxazole have also been investigated. According to the reviewed studies, ZIF-8 and UiO-66 can be considered remarkable photocatalysts for the degradation of organic pollutants.Article Citation - WoS: 4Citation - Scopus: 5Co2 Absorption Into Primary and Secondary Amine Aqueous Solutions With and Without Copper Ions in a Bubble Column(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Yousefzadeh, Hamed; Güler, Cansu; Erkey, Can; Uzunlar, ErdalChemical absorption of CO2 into aqueous amine solutions using a nonstirred bubble column was experimentally investigated. The performance of CO2 absorption of four different primary and secondary amines including monoethanolamine (MEA), piperazine (PZ), 2-piperidineethanol (2PE), and homopiperazine (HPZ) were compared. The effects of initial concentration of amine, the inlet mole fraction of CO2, and solution temperature on the rate of CO2 absorption and CO2 loading (mol CO2/mol amine) were studied in the range of 0.02–1 M, 0.10–0.15, and 25–40 °C, respectively. The effect of the presence of copper ions in the amine solution on CO2 loading was also studied. By comparison of the breakthrough curves of the amines at different operational conditions, it was revealed that the shortest and longest time for the appearance of the breakthrough point was observed for MEA and HPZ solutions, respectively. CO2 loading of MEA, 2PE, PZ, and HPZ aqueous solutions at 25 °C, 0.2 M of initial concentration of amine, and 0.15 of inlet mole fraction of CO2 were 1.06, 1.14, 1.13, and 1.18 mol CO2/mol amine, respectively. By decreasing the inlet mole fraction of CO2 from 0.15 to 0.10, CO2 loading slightly decreased. As the initial concentration of amine and temperature decreased, CO2 loading increased. Also, the presence of copper ions in the absorbent solution resulted in a decrease in the CO2 loading of MEA and HPZ aqueous solutions. In case of PZ and 2PE amines, adding copper ions led to precipitation even at low copper ion concentrations.Article Citation - WoS: 1Citation - Scopus: 1Cytoplasmically Localized Trna-Derived Fragments Inhibit Translation in Drosophila S2 Cells(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Hamid, Syed Muhammad; Akgül, BünyaminTransfer ribonucleic acids (tRNAs) serve not only as amino acid carriers during translation but also as a template for the biogenesis of short fragments that can regulate gene expression. Despite recent progress in the function of tRNA-derived fragments (tRFs), their intracellular localization, protein partners, and role in regulating translation are not well understood. We used synthetic tRFs to investigate their localization and function in Drosophila S2 cells. Under our experimental setting, all synthetic tRFs tested were localized at distinct sites within the cytoplasm in a similar manner in Drosophila S2 cells. Cytoplasmically-localized tRFs were positioned in close proximity to GW182 and XRN1 proteins. Functionally, tRFs, which slightly suppressed proliferation in S2 cells, inhibited translation without any major shift in the polysome profile. These results suggest that 5???-tRFs are cytoplasmically-localized and regulate gene expression through inhibition of translation in Drosophila.Article Citation - WoS: 3Citation - Scopus: 6Improved Cell Segmentation Using Deep Learning in Label-Free Optical Microscopy Images(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2021) Ayanzadeh, Aydın; Yalçın Özuysal, Özden; Pesen Okvur, Devrim; Önal, Sevgi; Töreyin, Behçet Uğur; Ünay, DevrimThe recently popular deep neural networks (DNNs) have a significant effect on the improvement of segmentation accuracy from various perspectives, including robustness and completeness in comparison to conventional methods. We determined that the naive U-Net has some lacks in specific perspectives and there is high potential for further enhancements on the model. Therefore, we employed some modifications in different folds of the U-Net to overcome this problem. Based on the probable opportunity for improvement, we develop a novel architecture by using an alternative feature extractor in the encoder of U-Net and replacing the plain blocks with residual blocks in the decoder. This alteration makes the model superconvergent yielding improved performance results on two challenging optical microscopy image series: a phase-contrast dataset of our own (MDA-MB-231) and a brightfield dataset from a well-known challenge (DSB2018). We utilized the U-Net with pretrained ResNet-18 as the encoder for the segmentation task. Hence, following the modifications, we redesign a novel skip-connection to reduce the semantic gap between the encoder and the decoder. The proposed skip-connection increases the accuracy of the model on both datasets. The proposed segmentation approach results in Jaccard Index values of 85.0% and 89.2% on the DSB2018 and MDA-MB-231 datasets, respectively. The results reveal that our method achieves competitive results compared to the state-of-the-art approaches and surpasses the performance of baseline approaches.Article Citation - WoS: 1Citation - Scopus: 2Information Retrieval-Based Bug Localization Approach With Adaptive Attribute Weighting(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2021) ErşahIn, Mustafa; Utku, Semih; Kılınç, Deniz; ErşahIn, BuketSoftware quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development standards. The aim of this study is to build an adaptive IRBL tool and make it usable by more companies. BugSTAiR solves the aforementioned problem by means of the adaptive attribute weighting (AAW) algorithm and is evaluated on four open-source projects which are well-known benchmark datasets on BL. One of them is BLIA which is the state of the art in bug localization area and another is BLUIR which is a well-known BL tool. According to the promising results of experiments, Top1 rank of BugSTAiR is 2% and MAP is 10% better than BLIA's results on AspectJ and it has localized 4.6% of all bugs in Top1 and its precision is 6.1% better than BLIA on SWT, respectively. On the other side, it is 20% better in the Top1 metric and 30% in precision than BLUIR.Article Citation - WoS: 1Citation - Scopus: 2Reactive Wetting of Metallic/Ceramic (al/Α-al2 O3 ) Systems: a Parallel Molecular Dynamics Simulation Study(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2020) Aral, GürcanThe reactive wetting process of a flat solid alumina (?-Al2 O3) ceramic surface by metallic aluminum (Al) nanodroplets with different shapes (spherical, cylindrical, and layer) is studied using parallel molecular dynamics (MD) simulations based on a variable charge MD method, with focuses on heat transfer, mass transfer, and the structure of the reactive region at the Al/?-Al2 O3 interface. We find that the diffusion of oxygen (O) atoms from the substrate into the droplet leads to the formation of a continuous layer of reaction product at the interface. The diffusion length of oxygen atoms into the spherical Al droplet is found to be ~7.3 Å, and the number density of O atoms at the ~5 top layers of the substrate decreases substantially. As a result, the structural correlations near the reactive region differ considerably from those in the solid substrate. Heat generated by the exothermic reactions in the reactive region is transferred to both the substrate and the droplet. The heat transfer is found to be sensitive to droplet shape.