Scopus İndeksli Yayınlar / Scopus Indexed Publications

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Browsing Scopus İndeksli Yayınlar / Scopus Indexed Publications by Rights "Attribution-NoDerivs 3.0 United States"

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    PublicationOpen Access
    CRISPR/Cas9-Mediated Bag-1 Knockout Increased Mesenchymal Characteristics of MCF-7 Cells Via Akt Hyperactivation-Mediated Actin Cytoskeleton Remodeling
    (Public Library of Science, 2022) KILBAŞ, PELİN ÖZFİLİZ; Can, Nisan Denizce; Kızılboğa, Tuğba; Ezberci, Fikret; Doğanay, Hamdi Levent; Doğanay, Gizem Dinler; ARISAN, ELİF DAMLA
    Bag-1 protein is a crucial target in cancer to increase the survival and proliferation of cells. The Bag-1 expression is significantly upregulated in primary and metastatic cancer patients compared to normal breast tissue. Overexpression of Bag-1 decreases the efficiency of conventional chemotherapeutic drugs, whereas Bag-1 silencing enhances the apoptotic efficiency of therapeutics, mostly in hormone-positive breast cancer subtypes. In this study, we generated stable Bag-1 knockout (KO) MCF-7 breast cancer cells to monitor stress-mediated cellular alterations in comparison to wild type (wt) and Bag-1 overexpressing (Bag-1 OE) MCF-7 cells. Validation and characterization studies of Bag-1 KO cells showed different cellular morphology with hyperactive Akt signaling, which caused stress-mediated actin reorganization, focal adhesion decrease and led to mesenchymal characteristics in MCF-7 cells. A potent Akt inhibitor, MK-2206, suppressed mesenchymal transition in Bag-1 KO cells. Similar results were obtained following the recovery of Bag-1 isoforms (Bag-1S, M, or L) in Bag-1 KO cells. The findings of this study emphasized that Bag-1 is a mediator of actin-mediated cytoskeleton organization through regulating Akt activation. © 2022 Kilbas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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    PublicationOpen Access
    Deep Learning-Based Defect Prediction for Mobile Applications
    (MPDI, 2022) JORAYEVA, MANZURA; AKBULUT, AKHAN; Çatal, Çağatay; Mishra, Alok
    Smartphones have enabled the widespread use of mobile applications. However, there are unrecognized defects of mobile applications that can affect businesses due to a negative user experience. To avoid this, the defects of applications should be detected and removed before release. This study aims to develop a defect prediction model for mobile applications. We performed cross-project and within-project experiments and also used deep learning algorithms, such as convolutional neural networks (CNN) and long short term memory (LSTM) to develop a defect prediction model for Android-based applications. Based on our within-project experimental results, the CNN-based model provides the best performance for mobile application defect prediction with a 0.933 average area under ROC curve (AUC) value. For cross-project mobile application defect prediction, there is still room for improvement when deep learning algorithms are preferred.
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    PublicationOpen Access
    Development of Pre-Service Early Childhood Teachers' Technology Integrations Skills Through a Praxeological Approach
    (Springer, 2022) Kulaksız, Taibe; TORAN, MEHMET
    How to improve and what should be carried out for pre-service teachers' technological competencies for teaching purposes is still an important issue on the agenda of the higher education field. In light of this, we aimed to reflect the individual and collective technology integration knowledge and skills construction process of pre-service early childhood education teachers with democratic participation. We utilized the praxeological approach as a method and learning approach to reveal the reflections of the instructional technologies course. The participants in this study were 52 sophomore pre-service teachers in the early childhood education department. We collected the data from various sources such as interviews, portfolios, researchers' field notes, e-mails, online course evaluation form. We carried out the thematic analysis method to analyze the data. The findings indicated that three main themes emerged as initial challenges, learning process, and learning outcomes during enhancement of pre-service early childhood teachers' technology integration knowledge and skills. As a result, the praxeological approach used in instructional technologies courses in teacher education programs leads to a crucial digital transformation to be ready to become future teachers.
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    PublicationUnknown
    Identification of Phantom Movements With an Ensemble Learning Approach
    (Pergamon-Elsevier Science Ltd., 2022) AKBULUT, AKHAN; Güngör, Feray; Tarakçı, Ela; Aydın, Muhammed Ali; Zaim, Abdul Halim; Çatal, Çağatay
    Phantom limb pain after amputation is a debilitating condition that negatively affects activities of daily life and the quality of life of amputees. Most amputees are able to control the movement of the missing limb, which is called the phantom limb movement. Recognition of these movements is crucial for both technology-based amputee rehabilitation and prosthetic control. The aim of the current study is to classify and recognize the phantom movements in four different amputation levels of the upper and lower extremities. In the current study, we utilized ensemble learning algorithms for the recognition and classification of phantom movements of the different amputation levels of the upper and lower extremity. In this context, sEMG signals obtained from 38 amputees and 25 healthy individuals were collected and the dataset was created. Studies of processing sEMG signals in amputees are rather limited, and studies are generally on the classification of upper extremity and hand movements. Our study demonstrated that the ensemble learning-based models resulted in higher accuracy in the detection of phantom movements. The ensemble learning-based approaches outperformed the SVM, Decision tree, and kNN methods. The accuracy of the movement pattern recognition in healthy people was up to 96.33%, this was at most 79.16% in amputees.
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    PublicationUnknown
    Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review
    (MDPI, 2022) JORAYEVA, MANZURA; AKBULUT, AKHAN; Çatal, Çağatay; Mishra, Alok
    Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be allocated to fault-prone modules effectively. While a few software defect prediction models have been developed for mobile applications, a systematic overview of these studies is still missing. Therefore, we carried out a Systematic Literature Review (SLR) study to evaluate how machine learning has been applied to predict faults in mobile applications. This study defined nine research questions, and 47 relevant studies were selected from scientific databases to respond to these research questions. Results show that most studies focused on Android applications (i.e., 48%), supervised machine learning has been applied in most studies (i.e., 92%), and object-oriented metrics were mainly preferred. The top five most preferred machine learning algorithms are Naive Bayes, Support Vector Machines, Logistic Regression, Artificial Neural Networks, and Decision Trees. Researchers mostly preferred Object-Oriented metrics. Only a few studies applied deep learning algorithms including Long Short-Term Memory (LSTM), Deep Belief Networks (DBN), and Deep Neural Networks (DNN). This is the first study that systematically reviews software defect prediction research focused on mobile applications. It will pave the way for further research in mobile software fault prediction and help both researchers and practitioners in this field.
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    PublicationUnknown
    Minimal Generators of Annihilators of Even Neat Elements in the Exterior Algebra
    (Scientific Technical Research Council Turkey-TUBITAK, 2022) ESİN, SONGÜL
    This paper deals with an exterior algebra of a vector space whose base field is of positive characteristic. In this work, a minimal set of generators forming the annihilator of even neat elements of such an exterior algebra is exhibited. The annihilator of some special type of even neat elements is determined to prove the conjecture established in [3]. Moreover, a vector space basis for the annihilators under consideration is calculated.
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    PublicationUnknown
    Prediction of University Students' Subjective Well-Being with Sleep and Physical Activity Data using Classification Algorithms
    (Elsevier B.V., 2022) KILIÇ, AKİF CAN; Karakuş, Ahmet; Alptekin, Emre
    Daily activities affect mental health. One of the most used scales is "subjective well-being (SWB)", which is a self-reported questionnaire. This study aimed to predict SWBs using step count, heart rate and sleep duration data from sensors instead of questionnaires. NetHealth data from the University of Notre Dame1 has been used. Attributes included average daily steps, average heart rate, heartbeat standard deviation, average sleep duration, and sleep duration deviation. Preprocessing, processing, classification, and evaluation followed. Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Ensemble classifiers were used. Performance metrics include accuracy, precision, recall, F1-Score, and ROC (Receiver Operating Characteristic) curves. Model accuracy was 62%. This indicates that machine learning could be beneficial in detecting SWB levels using sensor data. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022).
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    PublicationUnknown
    The Protective Impact of Growth Hormone Against Rotenone-Induced Apoptotic Cell Death via Acting on Endoplasmic Reticulum Stress and Autophagy Axis
    (Scientific and Technological Research Council Turkey, 2023) RENCÜZOĞULLARI, ÖZGE; TORNACI, SELAY; ÇELİK, YAĞMUR; TAŞ, NAYAT NAROT; YERLİKAYA, PINAR OBAKAN; Arısan, Elif Damla; Gürkan, Ajda Çoker
    Human growth hormone (GH) is crucial modulator of cellular metabolisms, including cell proliferation and organ development, by stimulating insulin-like growth factor-1 (IGF-1), which has various functions such as cell proliferation, tissue growth, survival, or neuroprotection. Therefore, GH is implicated as a critical player in the cell and can enhance neurogenesis and provide neuroprotection during the treatment of neurological diseases such as Parkinson's disease (PD). In this study, the neuroprotective role of GH was investigated in rotenone-induced PD models for the first time. Both SH-SY5Y and SK-N-AS neuroblastoma cells were exposed to rotenone to mimic PD pathogenesis as stated in previous studies. Our data demonstrated that overexpression of GH led to the resistance of the SH-SY5Y and SK-N-AS cell lines to rotenone treatment. The levels of ER stress markers, CHOP, PERK, XBP-1, and ATF6, were higher in wt cells than GH+ SH-SY5Y cells. However, the level of autophagy markers LC3 increased and the levels of reactive oxygen species (ROS) decreased with the overexpression of GH. Furthermore, while rotenone significantly increased the SubG1 population in the cell cycle of SH-SY5Y wt cells, there was a minor alteration in GH+ cell population. Concomitantly, the levels of the proapoptotic marker, cleaved-PARP, and positive staining of Annexin V in SH-SY5Y wt cells were higher after rotenone treatment. Together, these results revealed that overexpression of GH enhanced the autophagy response by triggering the ER stress of SH-SY5Y cells to rotenone exposure and showed a neuroprotective effect in vitro PD models.
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    PublicationUnknown
    A Randomized-Controlled Trial of EMDR Flash Technique on Traumatic Symptoms, Depression, Anxiety, Stress, and Life of Quality With Individuals Who Have Experienced a Traffic Accident
    (Frontiers Media SA, 2022) Yaşar, Alişan Burak; Konuk, Emre; KAVAKCI, ÖNDER; Uygun, Ersin; Gündoğmuş, İbrahim; Taygar, Afra Selma; Uludağ, Esra
    The Flash Technique of Eye Movement Desensitization and Reprocessing (EMDR) is widely recognized for its effectiveness in reducing the effects of emotional responses associated with traumatic memories. Using a randomized-controlled trial methodology, this study attempts to establish the efficacy of the EMDR Flash Technique. This study's sample includes volunteers who were involved in traffic accidents and were given the randomized EMDR Flash Technique and Improving Mental Health Training for Primary Care Residents (mhGAP) Stress management module. The participants were given a socio-demographic data form, the Depression-Anxiety-Stress 21 scale (DASS-21), the Impact of Event Scale-Revised (IES-R), and the WHOQOL Quality of Life scale. Participants were evaluated using measurements taken before and after the application, as well as a one-month follow-up. The mean age of the participants was 36.20 (11.41) years and 82.1% (n = 32) were female. The DASS-21 Anxiety (eta(2) = 0.085), IES-R Intrusion (eta(2) = 0.101), Avoidance (eta(2) = 0.124), Total (eta(2) = 0.147), and WHOQOL-BREF Psychological (eta(2) = 0.106) score improvements of the EMDR Flash Technique group were shown to be statistically significant when compared to the mhGAP group. However, no statistically significant difference in the DASS-21 Depression, Stress, Impact of Event Scale-Revised Hyperarousal WHOQOL-BREF General Health, Physical, Social Relationships, and Environment component scores was reported between the two groups. The present study's findings clearly demonstrate that the EMDR Flash technique, when applied to persons involved in traffic accidents, is successful in improving anxiety, intrusion, avoidance, total traumatic stress, and mental quality of life symptoms for at least 1 month. We believe that these findings will improve the reliability and applicability of the EMDR Flash Technique, which was tested for the first time in a clinical randomized-controlled trial (RCT).
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    PublicationOpen Access
    Structure, Vibrational Spectra, and Cryogenic MatrixPhotochemistry of 6-Bromopyridine-2-Carbaldehyde: From the Single Molecule of the Compound to the Neat Crystalline Material
    (MDPI, 2023) Brito, Anna Luiza B.; Lopes, Susy; ILDIZ, GÜLCE ÖĞRÜÇ; Fausto, Rui
    6-Bromopyridine-2-carbaldehyde (abbreviated as BPCA) is used both as a building block in supramolecular chemistry and as a ligand for transition metal catalysts and luminescent complexes. In this study, the structure and vibrational spectra of BPCA were investigated in both the room temperature neat crystalline phase and for the compound isolated in cryogenic Ar, Kr and Xe matrices. The experimental studies were complemented by quantum chemical DFT(B3LYP)/6-311++G(d,p) calculations. For the crystalline compound, infrared and Raman spectra were obtained and interpreted. Comparison of the obtained infrared spectrum of the crystal with those obtained for the isolated molecules of BPCA in the studied cryomatrices helped to conclude that the intermolecular interactions in the crystal do not significantly perturb the intramolecular vibrational potential. Structural analysis further supports the existence of weak coupling between the intermolecular interactions and the structure of the constituting molecular units in crystalline state. The intermolecular interactions in the BPCA crystal were also evaluated by means of Hirshfeld analysis, which revealed that the most important interactions are weak and of the (HN)-N- horizontal ellipsis , (HO)-O- horizontal ellipsis , (HH)-H- horizontal ellipsis , (HBr)-Br- horizontal ellipsis and (BrBr)-Br- horizontal ellipsis types. The conformer of BPCA present in the crystal was found to correspond to the most stable form of the isolated molecule (trans), which bears stabilizing C-(HO)-O- horizontal ellipsis =C and C(=O)(HN)-N- horizontal ellipsis interactions. This conformer was shown to be the single conformer present in the as-deposited cryogenic matrices prepared from the room temperature gaseous compound. Broadband UV irradiation of matrix-isolated BPCA (lambda >= 235 nm) resulted in the conversion of the trans conformer into the higher-energy cis conformer, where repulsive C-(HH)-H- horizontal ellipsis -C(=O) and C=(OLPLPN)-N- horizontal ellipsis (where LP designates a lone electron pair) interactions are present, and decarbonylation of the compound with formation of 2-bromopyridine (plus CO). The decarbonylation reaction was found to be more efficient in the more polarizable Xe matrix, indicating stabilization of the radicals initially formed upon breaking of the C-C(HO) and C-H (aldehyde) bonds in this medium, and testifying the occurrence of the decarbonylation reaction with involvement of radical species. TD-DFT calculations were used to access the nature of the excited states associated with the observed UV-induced reactions. As a whole, this study provides fundamental data to understand the physicochemical behavior of the compound, bridging the properties of the isolated molecule to those of the neat crystalline com-pound. Such information is of fundamental importance for the understanding of the role of BPCA in supramolecular chemistry and to potentiate its applications in synthesis and as a ligand for transition metal catalysts and luminescent complexes.