WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Apatinib Sensitizes Human Breast Cancer Cells Against Navitoclax and Venetoclax Despite Up-Regulated Bcl-2 and Mcl-1 Gene Expressions
(Kare Publ, 2021) Kavakcioglu Yardimci, Berna; Ozgun Acar, Ozden; Semiz, Asli; Sen, Alaattin
OBJECTIVE Defects in apoptotic cell death which restrict the success of conventional cytotoxic therapies have pivotal roles in a number of pathological conditions including cancer. However, a novel drug class targeting pro-survival Bcl-2 protein family members has been developed with the understanding of the structures and interactions of Bcl-2 proteins. Within this new class, Bcl-2/Bcl-xL inhibitor Navitoclax and Bcl-2 specific inhibitor Venetoclax have been shown to demonstrate strong anticancer activities on several types of cancers. But their low affinity to other anti-apoptotic proteins limits their clinical usage. Here, we investigated the cytotoxic and apoptotic effects of Navitoclax/Venetoclax and their combinations with specific tyrosine kinase inhibitor Apatinib on estrogen receptor (ER)-positive MCF-7 and ER-negative MDA-MB-231 breast cancer cell lines. METHODS MTT assay was used for the evaluation of the inhibition of cancer cell proliferation. ELISA test and Quantitative real-time PCR assay was performed to determine the role of caspase-3, Bak, Bax, Bcl-2, Bcl-xL and Mcl-1 proteins in the inhibition of cell proliferation triggered by the tested agents. RESULTS We found that aggressive MDA-MB-231 cell line was more sensitive to all tested agents. Apatinib significantly enhanced Navitoclax/Venetoclax mediated inhibition of cell viability in both cancer cell lines despite up-regulation in the expression levels of Bcl-2 and Mcl-1 genes. We further demonstrated significant Bak/Bax and caspase-3 expression in less aggressive MCF-7 cells. CONCLUSION Our findings have impacts on Navitoclax/Venetoclax plus Apatinib based therapy for breast adenocarcinoma. On the other hand, further studies should be conducted to elucidate the mechanisms underlying synergistic effects of Navitoclax/Venetoclax plus Apatinib combinations.
A New Approach for Numerical Solution of Linear and Non-Linear Systems
(Korean Soc Computational & Applied Mathematics & Korean Sigcam, 2017) Zeybek, Halil; Dolapci, Ihsan Timucin
In this study, Taylor matrix algorithm is designed for the approximate solution of linear and non-linear differential equation systems. The algorithm is essentially based on the expansion of the functions in differential equation systems to Taylor series and substituting the matrix forms of these expansions into the given equation systems. Using the Mathematica program, the matrix equations are solved and the unknown Taylor coefficients are found approximately. The presented numerical approach is discussed on samples from various linear and non-linear differential equation systems as well as stiff systems. The computational data are then compared with those of some earlier numerical or exact results. As a result, this comparison demonstrates that the proposed method is accurate and reliable.
Text Classification Experiments on Contextual Graphs Built by N-Gram Series
(Springer International Publishing AG, 2025) Sen, Tarik Uveys; Yakit, Mehmet Can; Gumus, Mehmet Semih; Abar, Orhan; Bakal, Gokhan
Traditional n-gram textual features, commonly employed in conventional machine learning models, offer lower performance rates on high-volume datasets compared to modern deep learning algorithms, which have been intensively studied for the past decade. The main reason for this performance disparity is that deep learning approaches handle textual data through the word vector space representation by catching the contextually hidden information in a better way. Nonetheless, the potential of the n-gram feature set to reflect the context is open to further investigation. In this sense, creating graphs using discriminative ngram series with high classification power has never been fully exploited by researchers. Hence, the main goal of this study is to contribute to the classification power by including the long-range neighborhood relationships for each word in the word embedding representations. To achieve this goal, we transformed the textual data by employing n-gram series into a graph structure and then trained a graph convolution network model. Consequently, we obtained contextually enriched word embeddings and observed F1-score performance improvements from 0.78 to 0.80 when we integrated those convolution-based word embeddings into an LSTM model. This research contributes to improving classification capabilities by leveraging graph structures derived from discriminative n-gram series.
Citation - WoS: 3
Citation - Scopus: 3
Template Scoring Methods for Protein Torsion Angle Prediction
(Springer-Verlag Berlin, 2015) Aydin, Zafer; Baker, David; Noble, William Stafford
Prediction of backbone torsion angles provides important constraints about the 3D structure of a protein and is receiving a growing interest in the structure prediction community. In this paper, we introduce a three-stage machine learning classifier to predict the 7-state torsion angles of a protein. The first two stages employ dynamic Bayesian and neural networks to produce an ab-initio prediction of torsion angle states starting from sequence profiles. The third stage is a committee classifier, which combines the ab-initio prediction with a structural frequency profile derived from templates obtained by HHsearch. We develop several structural profile models and obtain significant improvements over the Laplacian scoring technique through: (1) scaling templates by integer powers of sequence identity score, (2) incorporating other alignment scores as multiplicative factors (3) adjusting or optimizing parameters of the profile models with respect to the similarity interval of the target. We also demonstrate that the torsion angle prediction accuracy improves at all levels of target-template similarity even when templates are distant from the target. The improvement is at significantly higher rates as template structures gradually get closer to target.
Citation - WoS: 1
Citation - Scopus: 2
Experimental Study on Increase of Bonding Strength of FRP Reinforcement in Concrete
(Springer-Verlag Singapore Pte Ltd, 2022) Taskin, Furkan; Ciftci, Cihan
In the last two decades, the use of fiber-reinforced polymer (FRP) bars is of great interest to reinforce concrete beam structures due to its high specific strength, effective corrosion resistance, and low cost fabrication. Therefore, the flexural performance of these reinforced concrete beams containing FRP bars has been investigated by researchers for years with great interest. According to these investigations, one of the major problems is weak bonding strength between these bars and concrete material. Since, this major problem causes low flexural capacity, high deflection, and high crack widths for the reinforced concrete beams. Hence, the use of FRP bars by engineers does not sufficiently become widespread and also the engineering applications of these useful materials are still limited today. In this study, it is aimed to present an applicable solution regarding the bonding failures of the FRP bars in structurally reinforced concrete beams. For this solution, reinforced concrete beam samples were produced by using FRP materials on which knotted structures were formed. Then these samples were tested under 3-point bending tests. Furthermore, smooth-surfaced FRP bars and traditional deformed steel rebars were also used as reinforcing materials in the concrete beam samples for the comparison of the flexural capacities of each sample in order to investigate the effects of the reinforcing materials on the bonding strength. To conclude, the knotted FRP bars provide a significant contribution on the flexural capacity due to the increase of the bonding strength between the reinforcing material and the concrete in the beams.
Normal Mixture Model-Based Clustering of Data Using Genetic Algorithm
(Springer International Publishing AG, 2020) Gogebakan, Maruf; Erol, Hamza
In this study, a new algorithm was developed for clustering multivariate big data. Normal mixture distributions are used to determine the partitions of variables. Normal mixture models obtained from the partitions of variables are generated using Genetic Algorithms (GA). Each partition in the variables corresponds to a clustering center in the normal mixture model. The best model that fits the data structure from normal mixture models is obtained by using the information criteria obtained from normal mixture distributions.
Citation - WoS: 4
Citation - Scopus: 4
Differential in Vitro Anti-Leukemic Activity of Resveratrol Combined With Serine Palmitoyltransferase Inhibitor Myriocin in FMS-Like Tyrosine Kinase 3-Internal Tandem Duplication (FLT3-LTD) Carrying AML Cells
(Springer, 2022) Ersoz, Nur Sebnem; Adan, Aysun
Treatment of FMS-like tyrosine kinase 3 (FLT3)-internal tandem duplication (ITD) AML is restricted due to toxicity, drug resistance and relapse eventhough targeted therapies are clinically available. Resveratrol with its multi-targeted nature is a promising chemopreventive remaining limitedly studied in FLT3-ITD AML regarding to ceramide metabolism. Here, its cytotoxic, cytostatic and apoptotic effects are investigated in combination with serine palmitoyltransferase (SPT), the first enzyme of de novo pathway of ceramide production, inhibitor myriocin on MOLM-13 and MV4-11 cells. We assessed dose-dependent cell viability, flow cytometric cell death and cell cycle profiles of resveratrol in combination with myriocin by MTT assay, annexin-V/PI staining and PI staining respectively. Resveratrol's dose-dependent effect on SPT protein expression was also checked by western blot. Resveratrol decreased cell viability in a dose- dependent manner whereas myriocin did not affect cell proliferation effectively in both cell lines after 48h treatments. Although resveratrol induced both apoptosis and a significant S phase arrest in MV4-11 cells, it triggered apoptosis and non-significant S phase accumulation in MOLM-13 cells. Co-administrations reduced cell viability. Increased cytotoxic effect of co-treatments was further proved mechanistically through induction of apoptosis via phosphatidylserine relocalization. The cell cycle alteration in co-treatment was significant with an S phase arrest in MV4-11 cells, however, it was not effective on cell cycle progression of MOLM-13 cells. Resveratrol also increased SPT expression. Overall, modulation of SPT together with resveratrol might be the possible explanation for resveratrol's action. It could be an integrative medicine for FLT3-ITD AML after investigating its detailed mechanism of action in relation to de novo pathway of ceramide production.
Citation - WoS: 1
Motion Artifact Detection in Colonoscopy Images
(Sciendo, 2018) Kacmaz, Rukiye Nur; Yilmaz, Bulent; Dundar, Mehmet Sait; Dogan, Serkan
Computer-aided detection is an integral part of medical image evaluation process because examination of each image takes a long time and generally experts' do not have enough time for the elimination of images with motion artifact (blurred images). Computer-aided detection is required for both increasing accuracy rate and saving experts' time. Large intestine does not have straight structure thus camera of the colonoscopy should be moved continuously to examine inside of the large intestine and this movement causes motion artifact on colonoscopy images. In this study, images were selected from open-source colonoscopy videos and obtained at Kayseri Training and Research Hospital. Totally 100 images were analyzed half of which were clear. Firstly, a modified version of histogram equalization was applied in the pre-processing step to all images in our dataset, and then, used Laplacian, wavelet transform (WT), and discrete cosine transform-based (DCT) approaches to extract features for the discrimination of images with no artifact (clear) and images with motion artifact. The Laplacian-based feature extraction method was used for the first time in the literature on colonoscopy images. The comparison between Laplacian-based features and previously used methods such as WT and DCT has been performed. In the classification phase of our study, support vector machines (SVM), linear discriminant analysis (LDA), and k nearest neighbors (k-NN) were used as the classifiers. The results showed that Laplacian-based features were more successful in the detection of images with motion artifact when compared to popular methods used in the literature. As a result, a combination of features extracted using already existing approaches (WT and DCT) and the Laplacian-based methods reached 85% accuracy levels with SVM classification approach.
Citation - Scopus: 1
Correlation of PAPP-A Values With Maternal Characteristics, Biochemical and Ultrasonographic Markers of Pregnancy
(Marmara Univ, Fac Medicine, 2021) Kaymakcalan, Hande; Uzut, Ommu Gulsum; Harkonen, Juho; Bakir Gungor, Burcu
Objective: Our aim is to investigate whether there is a correlation of pregnancy-associated plasma protein A (PAPP-A) values with other variables in pregnancy and maternal characteristics. Materials and Methods: We retrospectively analyzed the relation between the PAPP-A levels, demographics, biochemical and ultrasonographic markers of the first trimester screening of 11,842 pregnant women seen at a tertiary hospital between November 2002 and November 2008. Results: A significant difference between PAPP-A values of the diabetic and non-diabetic pregnant women were observed (p=0.0005, Mann-Whitney U test). In terms of weight, crown-rump length, Beta-hCG values, significant differences were observed between low and medium level PAPP-A subgroups and between low and high level PAPP-A subgroups. PAPP-A levels were found to differ significantly between the pregnant women of Caucasian origin and other racial origins. Conclusions: Pregnant women with different ethnic and medical backgrounds have different PAPP-A values and other markers of the aneuploidy screening. 'lb make patient specific risk predictions, understanding these interactions and differences is important. Future studies are needed to understand the pathopyhsiology behind these differences.
Citation - Scopus: 5
Distribution Automation Effects on Reliability During Major Contingencies
(IEEE Computer Society help@computer.org, 2018) Yoldaş, Yeliz; Onen, Ahmet; Alan, İrfan; Broadwater, Robert P.
Distribution automation affects reliability by providing faster restoration ability. In this study, the effect of distribution automation on radial distribution circuits during substation failures at peak load is investigated. The ultimate goal is to compare circuit automation to manual operation, where the comparison evaluates planning criteria reliability for customer interruption hours. The results show that distribution automation can improve reliability measurements such as SAIDI, SAIFI and CAIDI. © 2018 Elsevier B.V., All rights reserved.
Use of Confocal Microscopy to Monitor Structural Transformations in Nanopillars Based on DNA and CdSe/CdZnSe Quantum Dots
(Springer, 2023) Motevich, I. G.; Erdem, T.; Akrema, A.; Maskevich, S. A.; Strekal, N. D.
Chip system prototypes in the form of nanopillars were created from DNA complexes with CdSe/CdZnSe/ZnS quantum dots immobilized on a plasmonic gold fi lm by the use of vacuum deposition technology and inorganic synthesis. The design and presence of terminal DNA labeled with Cy3 cyanine dyes makes it possible to carry out the hybridization reaction of this terminal strand with complementary DNA and to control the process by variation of the giant Raman scattering (GRS) and the fluorescence signal. The effect of molecular recognition of complementary DNA is accompanied by a change in the GRS spectrum, a 20-fold increase in the fluorescence intensity, and a decrease in the duration of fluorescence decay.
Citation - WoS: 2
Citation - Scopus: 2
Analysis of the Motion of a Rigid Rod on a Circular Surface Using Interpolated Variational Iteration Method
(Yildiz Technical Univ, 2022) Coskun, Safa Bozkurt; Senturk, Erman; Atay, Mehmet Tarik
In this paper, interpolated variational iteration method (IVIM) is applied to investigate the vibration period and steady-state response for the motion of rigid rod rocking back and forth on a circular surface without slipping. The problem can be considered as a strongly nonlinear oscillator. In this solution procedure, analytical variational iteration technique is utilized by evaluating the integrals numerically. The approximate analytical results produced by the presented method are compared with the other existing solutions available in the literature. The advantage of using numerical evaluation of integrals, the method becomes fast convergent and a highly accurate solution can be obtained within seconds. The authors believe that the presented technique has potentially wide application in the other nonlinear oscillation problems.
What Does the Bibliometrics of an Interdisciplinary Field Tell Us?: The Case of Cognitive Science
(Seoul Natl Univ, inst Cognitive Science, 2023) Arik, Beril T.; Arik, Engin
This study investigated the bibliometric characteristics of an interdisciplinary field, Cognitive Science, which consists of contributions from diverse fields such as psychology, computer science, philosophy, linguistics, and anthropology, among others. The results showed that there were 4,711 publications in Web of Science between 1900 and 2017, with an exponential increase in the number of publications in recent years. About two-thirds of publications were classified as social science, of which 41% were in the field of psychology. Seventy percent of the publications were journal articles, half of the publications were written by researchers in the USA, and 95% of the publications were in English. Corpus analyses of abstracts and keywords showed that frequently used words included cognitive, science, research, theory, model, cognition, information, learning, and psychology. These analyses also showed that research in this field centered on the common themes of cognition, information, psychology, language, learning, representation, artificial intelligence, and mind before 2010 and focused on more restricted themes such as embodied and extended cognition, morality and religion, quantum, and music after 2010.
Citation - WoS: 5
Citation - Scopus: 5
Rings With Modules Having a Restricted Injectivity Domain
(Springer International Publishing AG, 2020) Demirci, Yilmaz Mehmet; Turkmen, Burcu Nisanci; Turkmen, Ergul
We introduce modules whose injectivity domains are contained in the class of modules with zero radical and call them working-class. This notion gives a generalization of poor modules that have minimal injectivity domain. Semisimple working-class modules always exist for arbitrary rings whereas their predecessors do not. We investigate the rings over which every module is either injective or working-class. Right weakly V-rings are examples of these rings. Moreover, we study the existence of working-class simple modules and show that if there is a projective working-class simple right module, then the ring is a right GV-ring.
Leveraging MicroRNA-Gene Associations With Mirgedinet: An Intelligent Approach for Enhanced Classification of Breast Cancer Molecular Subtypes
(Springer International Publishing AG, 2025) Qumsiyeh, Emma; Bakir-Gungor, Burcu; Yousef, Malik
Understanding the molecular subtypes of breast cancer is crucial for advancing targeted therapies and precision medicine. For the BRCA molecular subtype prediction problem, this study employs miRGediNET, a machinelearning approach that integrates data from miRTarBase, DisGeNET, and HMDD databases to investigate shared gene associations between microRNA (miRNA) activity and disease mechanisms. Using the BRCA LumAB_Her2Basal dataset, we evaluate miRGediNET's performance against traditional feature selection methods, including CMIM, mRmR, Information Gain (IG), SelectKBest (SKB), Fast Correlation-Based Filter (FCBF), and XGBoost (XGB). These feature selection techniques were assessed using various classification algorithms including Random Forest (RF), Support Vector Machine (SVM), LogitBoost, Decision Tree, and AdaBoost, all executed with default parameters. The feature selection methods were tested using Monte Carlo Cross-Validation, where performance metrics obtained for each iteration were averaged to ensure robustness. Our findings reveal that miRGediNET outperforms traditional methods in accuracy and Area Under the Curve (AUC), emphasizing its superior capability to identify key genes that bridge miRNA interactions and breast cancer mechanisms. Notably, both miRGediNET and Information Gain (IG) feature selection consistently identified ESR1, a critical biomarker frequently reported in recent research associated with breast cancer prognosis and resistance to endocrine therapies. This integrative approach provides deeper biological insights into miRNA-disease interactions, paving the way for enhanced patient stratification, biomarker discovery, and personalized medicine strategies. The miRGediNET tool, developed on the KNIME platform, offers a practical resource for further exploration in the field of bioinformatics and oncology.
Citation - WoS: 3
Citation - Scopus: 3
Artificial Cells: A Potentially Groundbreaking Field of Research and Therapy
(Sciendo, 2024) Dundar, Mehmet Sait; Yildirim, A. Baki; Yildirim, Duygu T.; Akalin, Hilal; Dundar, Munis
Artificial cells are synthetic constructs that mimic the architecture and functions of biological cells. Artificial cells are designed to replicate the fundamental principles of biological systems while also have the ability to exhibit novel features and functionalities that have not been achieved before. Mainly, Artificial cells are made up of a basic structure like a cell membrane, nucleus, cytoplasm and cellular organelles. Nanotechnology has been used to make substances that possess accurate performance in these structures. There are many roles that artificial cells can play such as drug delivery, bio-sensors, medical applications and energy storage. An additional prominent facet of this technology is interaction with biological systems. The possibility of synthetic cells being compatible with living organisms opens up the potential for interfering with specific biological activities. This element is one of the key areas of research in medicine, aimed at developing novel therapies and comprehending life processes. Nevertheless, artificial cell technology is not exempt from ethical and safety concerns. The interplay between these structures and biological systems may give rise to questions regarding their controllability and safety. Hence, the pursuit of artificial cell research seeks to reconcile ethical and safety concerns with the potential advantages of this technology.
Influence of Silica Nanoparticles on the Stability of Paraffin Wax Emulsion
(Yildiz Technical Univ, 2023) Ibrahim, Aliu Pennah; Erdem, Ilker; Gonen, Mehmet
Paraffin wax emulsions have been used widely in various areas. However, the basic problem faced in all areas is instability of emulsion. Different methods and emulsifiers have been proposed to overcome this problem. This study focuses on using a commercial emulsifier, (IK8000) and aqueous silica nanoparticles to formulate paraffin wax emulsions and investigate their effects on the stability and mean diameter of paraffin wax emulsions. For comparison purpose, different emulsifier, PEG-7 Glyceryl Cocoate was used to stabilize one of 20 % (wt./ wt.) paraffin wax emulsions. The PEG-7-Glyceryl Cocoate stabilized emulsion phase -separated after 3 days while the IK-8000 stabilized remained stable for more than a month. The effect of the silica nanoparticles on the emulsion's stability was studied by observing samples stored for over 2 months. It was seen that aqueous silica nanoparticles helped to increase the stability of the paraffin wax emulsions. Emulsions prepared without silica nanoparticles (only IK-8000) were stable for just a month (1 month) whereas those which were formulated with silica nanoparticles and IK-8000 remained stable for more than 2 months (> 2 months). However, the addition of aqueous silica nanoparticles did not have a significant effect on the mean particle size of the emulsion. It was observed that the addition of 0.5 mL aqueous silica nanoparticles to the paraffin wax emulsion first increased the mean particle size from 1.142 mu m to 2.680 mu m. Nonetheless, further increasing the amount of the aqueous silica nanoparticles from 1.0-5.0 mL decreased the mean particles size of the paraffin wax emulsion from 2.680 mu m to 0.942 mu m. The contact angle formed by water drop on the surfaces coated with different emulsion samples of 30%wt. PWE, 40%wt. PWE, 50%wt. PWE and 60 %wt. PWE were measured. The higher the degree of solid content in emulsion, the greater the contact angle measured thus higher hydrophobicity.
Target Attractor Formed via Fractional Feedback Control
(Yildiz Technical Univ, 2021) Borisenok, Sergey
We discuss here the stabilization problem for an ordinary differential equation (ODE) dynamical model. To make such a control, one can form a Kolesnikov's subset attracting the phase trajectories to its neighborhood in the phase space via defining the appropriate feedback signal. Kolesnikov's target attractor algorithm provides the exponential convergence, but at the same time it demands the permanent power supply pumping the energy to the system even if the control goal is achieved. To decrease the power cost of Kolesnikov's control, we re-formulate the feedback in the form of Caputo's fractional derivative. In this case the solution to the ODE together with the feedback control signal could be found with the Rida-Arafa method based on the generalized Mittag-Leffler function. We prove that for the certain constraints over the initial condition and the target stabilization level, the integer-dimensional Kolesnikov algorithm can be replaced with the fractional target attractor feedback to provide the minimal power cost.
Investigation of the Antitumor Effect of Targeting PI3K-AKT-mTOR Pathway and Histone Deacetylase Enzymes on Acute Myeloid Leukemia Cells
(Cig Media Group, Lp, 2021) Sansacar, Merve; Sagir, Helin; Akcok, Emel Gencer
Citation - WoS: 1
Citation - Scopus: 1
RPI-1 (Human DCDC2) Displays Functional Redundancy With Nephronophthisis 4 in Regulating Cilia Biogenesis in C. Elegans
(Tubitak Scientific & Technological Research Council Turkey, 2023) Kaplan, Oktay I.
Projecting from most cell surfaces, cilia serve as important hubs for sensory and signaling processes and have been linked to a variety of human disorders, including Bardet-Biedl Syndrome (BBS), Meckel-Gruber Syndrome (MKS), Nephronophthisis (NPHP), and Joubert Syndrome, and these diseases are collectively known as a ciliopathy. DCDC2 is a ciliopathy protein that localizes to cilia; nevertheless, our understanding of the role of DCDC2 in cilia is still limited. We employed C. elegans to investigate the function of C. elegans RPI-1, a Caenorhabditis elegans ortholog of human DCDC2, in cilia and found that C. elegans RPI-1 localizes to the entire ciliary axoneme, but is not present in the transition zone and basal body. We generated a null mutant of C. elegans rpi-1, and our analysis with a range of fluorescence-based ciliary markers revealed that DCDC2 and nephronophthisis 4 (NPHP-4/NPHP4) display functional redundant roles in regulating cilia length and cilia positions. Taken together, our analysis discovered a novel genetic interaction between two ciliopathy disease genes (RPI-1/DCDC2 and NPHP-4/NPHP4) in C. elegans.

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