PubMed İndeksli Yayınlar Koleksiyonu
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Article Citation - WoS: 12Citation - Scopus: 144D-QSAR Investigation and Pharmacophore Identification of Pyrrolo[2,1-C][1,4]Benzodiazepines Using Electron Conformational-Genetic Algorithm Method(Taylor & Francis Ltd, 2016) Ozalp, A.; Yavuz, S. C.; Sabanci, N.; Copur, F.; Kokbudak, Z.; Saripinar, E.; 01. Abdullah Gül UniversityIn this paper, we present the results of pharmacophore identification and bioactivity prediction for pyrrolo[2,1-c][1,4]benzodiazepine derivatives using the electron conformational-genetic algorithm (EC-GA) method as 4D-QSAR analysis. Using the data obtained from quantum chemical calculations at PM3/HF level, the electron conformational matrices of congruity (ECMC) were constructed by EMRE software. The ECMC of the lowest energy conformer of the compound with the highest activity was chosen as the template and compared with the ECMCs of the lowest energy conformer of the other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA, i.e. pharmacophore) by ECSP software. A descriptor pool was generated taking into account the obtained pharmacophore. To predict the theoretical activity and select the best subset of variables affecting bioactivities, the nonlinear least square regression method and genetic algorithm were performed. For four types of activity including the GI(50), TGI, LC50 and IC50 of the pyrrolo[2,1-c][1,4] benzodiazepine series, the r(train)(2), r(test)(2) and q(2) values were 0.858, 0.810, 0.771; 0.853, 0.848, 0.787; 0.703, 0.787, 0.600; and 0.776, 0.722, 0.687, respectively.Article Citation - WoS: 6Citation - Scopus: 8Anhedonia in Relation to Reward and Effort Learning in Young People With Depression Symptoms(MDPI, 2023) Frey, Anna-Lena; Kaya, M. Siyabend; Adeniyi, Irina; McCabe, Ciara; 01. Abdullah Gül University; 06. İnsan ve Toplum Bilimleri Fakültesi; 06.02. PsikolojiAnhedonia, a central depression symptom, is associated with impairments in reward processing. However, it is not well understood which sub-components of reward processing (anticipation, motivation, consummation, and learning) are impaired in association with anhedonia in depression. In particular, it is unclear how learning about different rewards and the effort needed to obtain them might be associated with anhedonia and depression symptoms. Therefore, we examined learning in young people (N = 132, mean age 20, range 17-25 yrs.) with a range of depression and anhedonia symptoms using a probabilistic instrumental learning task. The task required participants to learn which options to choose to maximize their reward outcomes across three conditions (chocolate taste, puppy images, or money) and to minimize the physical effort required to obtain the rewards. Additionally, we collected questionnaire measures of anticipatory and consummatory anhedonia, as well as subjective reports of "liking", "wanting" and "willingness to exert effort" for the rewards used in the task. We found that as anticipatory anhedonia increased, subjective liking and wanting of rewards decreased. Moreover, higher anticipatory anhedonia was significantly associated with lower reward learning accuracy, and participants demonstrated significantly higher reward learning than effort learning accuracy. To our knowledge, this is the first study observing an association of anhedonia with reward liking, wanting, and learning when reward and effort learning are measured simultaneously. Our findings suggest an impaired ability to learn from rewarding outcomes could contribute to anhedonia in young people. Future longitudinal research is needed to confirm this and reveal the specific aspects of reward learning that predict anhedonia. These aspects could then be targeted by novel anhedonia interventions.Article Citation - WoS: 9Citation - Scopus: 10An Answer to Colon Cancer Treatment by Mesenchymal Stem Cell Originated from Adipose Tissue(Mashhad Univ Med Sciences, 2018) Iplik, Elif Sinem; Ertugrul, Baris; Kozanoglu, Ilknur; Baran, Yusuf; Cakmakoglu, Bedia; 01. Abdullah Gül UniversityObjective(s): Colon cancer is risen up with its complex mechanism that directly impacts on its treatment as well as its common prevalence. Mesenchymal stem cells (MSCs) have been considered as a therapeutic candidate for conventional disease including cancer. In this research, we have focused on apoptotic effects of adipose tissue-derived MSCs in colon cancer. Materials and Methods: MSCs were obtained from adipose tissue and characterized by Flowcytometer using suitable antibodies. MSCs, HT-29, HCT-116, RKO and healthy cell line MRC5 were cultured by different seeding procedure. After cell viability assay, changes in caspase 3 enzyme activity and the level of phosphatidylserine were measured. Results: For cell viability assay, a 48 hr incubation period was chosen to seed all cells together. There was a 1.36-fold decrease in caspase 3 enzyme activity by co-treatment of RKO and MSCs in addition to 2.02-fold decrease in HT-29 and MSCs co-treatment, and 1.103-fold increase in HCT-116 and MSCs. The results demonstrated that HCT-116 led to the highest rate of apoptotic cell death (7.5%) compared with other cells. Conclusion: We suggest that MSCs might remain a new treatment option for cancer by its differentiation and repair capacity.Article Citation - WoS: 20Citation - Scopus: 23Apoptotic Effects of Non-Edible Parts of Punica Granatum on Human Multiple Myeloma Cells(Sage Publications Ltd, 2016) Kiraz, Yagmur; Neergheen-Bhujun, Vidushi S.; Rummun, Nawraj; Baran, Yusuf; 01. Abdullah Gül UniversityMultiple myeloma is of great concern since existing therapies are unable to cure this clinical condition. Alternative therapeutic approaches are mandatory, and the use of plant extracts is considered interesting. Punica granatum and its derived products were suggested as potential anticancer agents due to the presence of bioactive compounds. Thus, polypenolic-rich extracts of the non-edible parts of P. granatum were investigated for their antiproliferative and apoptotic effects on U266 multiple myeloma cells. We demonstrated that there were dose-dependent decreases in the proliferation of U266 cells in response to P. granatum extracts. Also, exposure to the extracts triggered apoptosis with significant increases in loss of mitochondrial membrane potential in U266 cells exposed to the leaves and stem extracts, while the flower extract resulted in slight increases in loss of MMP. These results were confirmed by Annexin-V analysis. These results documented the cytotoxic and apoptotic effects of P. granatum extracts on human U266 multiple myeloma cells via disruption of mitochondrial membrane potential and increasing cell cycle arrest. The data suggest that the extracts can be envisaged in cancer chemoprevention and call for further exploration into the potential application of these plant parts.Article Citation - WoS: 17Citation - Scopus: 27Blockchain for Genomics and Healthcare: A Literature Review, Current Status, Classification and Open Issues(PeerJ Inc, 2021) Dedeturk, Beyhan Adanur; Soran, Ahmet; Bakir-Gungor, Burcu; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik FakültesiThe tremendous boost in the next generation sequencing technologies and in the "omics"technologies resulted in the generation of hundreds of gigabytes of data per day. Nowadays, via integrating -omics data with other data types, such as imaging and electronic health record (EHR) data, panomics studies attempt to identify novel and potentially actionable biomarkers for personalized medicine applications. In this respect, for the accurate analysis of -omics data and EHR, there is a need to establish secure and robust pipelines that take the ethical aspects into consideration, regulate privacy and ownership issues, and data sharing. These days, blockchain technology has picked up significant attention in diverse fields, including genomics, since it offers a new solution for these problems from a different perspective. Blockchain is an immutable transaction ledger, which offers secure and distributed system without a central authority. Within the system, each transaction can be expressed with cryptographically signed blocks, and the verification of transactions is performed by the users of the network. In this review, firstly, we aim to highlight the challenges of EHR and genomic data sharing. Secondly, we attempt to answer "Why"or "Why not"the blockchain technology is suitable for genomics and healthcare applications in detail. Thirdly, we elucidate the general blockchain structure based on the Ethereum, which is a more suitable technology for the genomic data sharing platforms. Fourthly, we review current blockchain-based EHR and genomic data sharing platforms, evaluate the advantages and disadvantages of these applications, and classify these applications using different metrics. Finally, we conclude by discussing the open issues and introducing our suggestion on the topic. In summary, to facilitate the diagnosis, monitoring and therapy of diseases with the effective analysis of -omics data with other available data types, through this review, we put forward the possible implications of the blockchain technology to life sciences and healthcare.Article Citation - WoS: 11Citation - Scopus: 10Clinical and Molecular Evaluation of MEFV Gene Variants in the Turkish Population: A Study by the National Genetics Consortium(Springer Heidelberg, 2022) Dundar, Munis; Fahrioglu, Umut; Yildiz, Saliha Handan; Bakir-Gungor, Burcu; Temel, Sehime Gulsun; Akin, Haluk; Erdem, Levent; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik FakültesiFamilial Mediterranean fever (FMF) is a monogenic autoinflammatory disorder with recurrent fever, abdominal pain, serositis, articular manifestations, erysipelas-like erythema, and renal complications as its main features. Caused by the mutations in the MEditerranean FeVer (MEFV) gene, it mainly affects people of Mediterranean descent with a higher incidence in the Turkish, Jewish, Arabic, and Armenian populations. As our understanding of FMF improves, it becomes clearer that we are facing with a more complex picture of FMF with respect to its pathogenesis, penetrance, variant type (gain-of-function vs. loss-of-function), and inheritance. In this study, MEFV gene analysis results and clinical findings of 27,504 patients from 35 universities and institutions in Turkey and Northern Cyprus are combined in an effort to provide a better insight into the genotype-phenotype correlation and how a specific variant contributes to certain clinical findings in FMF patients. Our results may help better understand this complex disease and how the genotype may sometimes contribute to phenotype. Unlike many studies in the literature, our study investigated a broader symptomatic spectrum and the relationship between the genotype and phenotype data. In this sense, we aimed to guide all clinicians and academicians who work in this field to better establish a comprehensive data set for the patients. One of the biggest messages of our study is that lack of uniformity in some clinical and demographic data of participants may become an obstacle in approaching FMF patients and understanding this complex disease.Article Citation - WoS: 3Citation - Scopus: 4Clinical Probe Utilizing Surface Enhanced Raman Scattering(A V S Amer Inst Physics, 2014) Kim, Jeonghwan; Hah, Dooyoung; Daniels-Race, Theda; Feldman, Martin; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik MühendisliğiConventional Raman scattering is a well-known technique for detecting and identifying complex molecular samples. In surface enhanced Raman scattering, a nanorough metallic surface close to the sample enormously enhances the Raman signal. In previous work, the metallic surface was a thin layer of gold deposited on a rough transparent epoxy substrate. The advantage of the clear substrate was that the Raman signal could be obtained by passing light through the substrate, on to opaque samples simply placed against its surface. In this work, a commercially available Raman spectrometer was coupled to a distant probe. Raman signals were obtained from the surface, and from the interior, of a solid specimen located more than 1 m away from the spectrometer. The practical advantage of this arrangement is that it opens up surface enhanced Raman spectrometry to a clinical environment, with a patient simply sitting or lying near the spectrometer. (C) 2014 American Vacuum Society.Article Citation - WoS: 2Citation - Scopus: 2Comparative Analysis of Machine Learning Approaches for Predicting Respiratory Virus Infection and Symptom Severity(PeerJ Inc, 2023) Isik, Yunus Emre; Aydin, Zafer; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik FakültesiRespiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the spread and progression of the disease, especially in countries where health systems remain incapable. Personalized medicine studies involving statistics and computer technologies could help to address this need. In addition to individual studies, competitions are also held such as Dialogue for Reverse Engineering Assessment and Methods (DREAM) challenge which is a community-driven organization with a mission to research biology, bioinformatics, and biomedicine. One of these competitions was the Respiratory Viral DREAM Challenge, which aimed to develop early predictive biomarkers for respiratory virus infections. These efforts are promising, however, the prediction performance of the computational methods developed for detecting respiratory diseases still has room for improvement. In this study, we focused on improving the performance of predicting the infection and symptom severity of individuals infected with various respiratory viruses using gene expression data collected before and after exposure. The publicly available gene expression dataset in the Gene Expression Omnibus, named GSE73072, containing samples exposed to four respiratory viruses (H1N1, H3N2, human rhinovirus (HRV), and respiratory syncytial virus (RSV)) was used as input data. Various preprocessing methods and machine learning algorithms were implemented and compared to achieve the best prediction performance. The experimental results showed that the proposed approaches obtained a prediction performance of 0.9746 area under the precision-recall curve (AUPRC) for infection (i.e., shedding) prediction (SC-1), 0.9182 AUPRC for symptom class prediction (SC-2), and 0.6733 Pearson correlation for symptom score prediction (SC-3) by outperforming the best leaderboard scores of Respiratory Viral DREAM Challenge (a 4.48% improvement for SC-1, a 13.68% improvement for SC-2, and a 13.98% improvement for SC-3). Additionally, over-representation analysis (ORA), which is a statistical method for objectively determining whether certain genes are more prevalent in pre-defined sets such as pathways, was applied using the most significant genes selected by feature selection methods. The results show that pathways associated with the 'adaptive immune system' and 'immune disease' are strongly linked to pre-infection and symptom development. These findings contribute to our knowledge about predicting respiratory infections and are expected to facilitate the development of future studies that concentrate on predicting not only infections but also the associated symptoms.Article Citation - WoS: 151Citation - Scopus: 154Computational Analysis of MicroRNA-Mediated Interactions in SARS-CoV Infection(PeerJ Inc, 2020) Demirci, Muserref Duygu Sacar; Adan, Aysun; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.02. Moleküler Biyoloji ve Genetik; 04.01. BiyomühendislikMicroRNAs (miRNAs) are post-transcriptional regulators of gene expression found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs, there are examples of miRNA like sequences from RNA viruses with regulatory functions. In the case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with viral replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA-based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Overall, 950 hairpin structured sequences were extracted from the virus genome and based on the prediction results, 29 of them could be precursor miRNAs. Targeting analysis showed that 30 viral mature miRNA-like sequences could target 1,367 different human genes. PANTHER gene function analysis results indicated that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription, metabolism, defense system and several signaling pathways such as Wnt and EGFR signalings. Protein class-based grouping of targeted human genes showed that host transcription might be one of the main targets of the virus since 96 genes involved in transcriptional processes were potential targets of predicted viral miRNAs. For instance, basal transcription machinery elements including several components of human mediator complex (MED1, MED9, MED 12L, MED 19), basal transcription factors such as TAF4, TAF5, TAF7L and site-specific transcription factors such as STATI were found to be targeted. In addition, many known human miRNAs appeared to be able to target viral genes involved in viral life cycle such as S, M, N, E proteins and ORF lab, ORF3a, ORF8, ORF7a and ORF10. Considering the fact that miRNA-based therapies have been paid attention, based on the findings of this study, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics.Article Citation - WoS: 1Citation - Scopus: 1Concurrent Inhibition of FLT3 and Sphingosine Kinase-1 Triggers Synergistic Cytotoxicity in Midostaurin Resistant FLT3-ITD Positive Acute Myeloid Leukemia Cells via Blocking FLT3/TAT5A Signaling to Induce Apoptosis(Taylor & Francis Ltd, 2025) Tecik, Melisa; Adan, Aysun; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.02. Moleküler Biyoloji ve GenetikThe FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD) is one of the most frequent mutations observed in acute myeloid leukemia (AML) which contributes to disease progression and unfavorable prognosis. Midostaurin, a small FLT3 inhibitor (FLT3I), is clinically approved. However, patients generally possess acquired resistance when midostaurin used alone. Shifting the balance in the sphingolipid rheostat toward anti-apoptotic sphingosine kinase-1 (SK-1) or glucosylceramide synthase (GCS) is related to therapy resistance in cancer, however, their role in midostaurin resistant FLT3-ITD positive AML has not been previously investigated. We generated midostaurin resistant MV4-11 and MOLM-13 cell lines which showed increased IC50 values compared to their sensitive partner cells. SK-1 is overexpressed in resistant cells while GCS remains unchanged. Subsequent pharmacological targeting of SK-1 in resistant cells decreased SK-1 protein level, inhibited cell proliferation and showed additive or synergistic effect on cell growth, as confirmed by the Chou-Talalay combination index, and induced G0/G1 arrest (PI staining by flow cytometry). Cotreatment (SKI-II plus midostaurin) triggered apoptosis via phosphatidylserine exposure (annexin V/PI double staining). Mechanistically, induction of the intrinsic pathway of apoptosis was confirmed as increased activating cleavages of caspase-3 and PARP and increased Bax/Bcl-2 ratios. Activating phosphorylations of FLT3 (at tyrosine residue 591) and STAT5A (at tyrosine residue 694) dramatically inhibited in resistant cells treated with the combination. In conclusion, midostaurin resistance could be reversed by dual SK-1 and FLT3 inhibition in midostaurin resistant AML cell lines, providing the first evidence of a novel treatment approach to re-sensitize FLT3-ITD positive AML.Article Citation - WoS: 1Citation - Scopus: 1ConVarT: Search Engine for Missense Variants Between Humans and Other Organisms(Wiley, 2022) Pir, Mustafa S.; Cevik, Sebiha; Kaplan, Oktay I.; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.02. Moleküler Biyoloji ve Genetik; 04.01. BiyomühendislikConVarT (https://convart.org/) is a search engine for searching for conjugate variants between humans and other species. The search engine is based on matching conjugate variants called MatchVars between species. Matching equivalent variants requires correct alignment of orthologous proteins with the use of multiple sequence alignments (MSA). Indeed, the ConVarT pipeline has performed over a million MSAs and integrated variants and variant-specific annotations (pathogenicity, phenotypic variants; etc.) into the corresponding positions on MSAs. When a clinically relevant variant is discovered whose functional relevance is unknown, ConVarT offers clinician scientists the possibility to search for a MatchVar in other species and to look for functional data on that variant. Fortunately, ConVarT enables users to paste a protein sequence in FASTA format to search for human orthologous proteins. A pairwise sequence alignment (PSA) is then performed between the provided protein sequence and the human orthologous protein, allowing users to visualize human variants on the PSA. Here, we describe the step-by-step usage of ConVarT.Correction Correction: Engineering Novel Features for Diabetes Complication Prediction Using Synthetic Electronic Health Records(Frontiers Media S.A., 2025) Voskergian, Daniel; Bakir-Gungor, Burcu; Yousef, Malik; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik FakültesiArticle A Decision Support System for the Prediction of Mortality in Patients With Acute Kidney Injury Admitted in Intensive Care Unit(Univ South Bohemia, 2020) Kayaalti, Selda; Kayaalti, Omer; Aksebzeci, Bekir Hakan; 01. Abdullah Gül UniversityIntensive care unit (ICU) is a very special unit of a hospital, where healthcare professionals provide treatment and, later, close followup to the patients. It is crucial to estimate mortality in ICU patients from many viewpoints. The purpose of this study is to classify the status of patients with acute kidney injury (AKI) in ICU as early mortality, late mortality, and survival by the application of Classification and Regression Trees (CART) algorithm to the patients' attributes such as blood urea nitrogen, creatinine, serum and urine neutrophil gelatinase-associated lipocalin (NGAL), alkaline phosphatase, lactate dehydrogenase (LDH), gamma-glutamyl transferase, laboratory electrolytes, blood gas, mean arterial pressure, central venous pressure and demographic details of patients. This study was conducted 50 patients with AKI who were followed up in the ICU. The study also aims to determine the significance of relationship between the attributes used in the prediction of mortality in CART and patients' status by employing the Kruskal-Wallis H test. The classification accuracy, sensitivity, and specificity of CART for the tested attributes for the prediction of early mortality, late mortality, and survival of patients were 90.00%, 83.33%, and 91.67%, respectively. The values of both urine NGAL and LDH on day 7 showed a considerable difference according to the patients' status after being examined by the Kruskal-Wallis H test.Article Developing a Label Propagation Approach for Cancer Subtype Classification Problem(Tubitak Scientific & Technological Research Council Turkey, 2022) Guner, Pinar; Bakir-Gungor, Burcu; Coskun, Mustafa; 02. 04. Bilgisayar Mühendisliği; 01. Abdullah Gül University; 02. Mühendislik FakültesiCancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches.Article Citation - WoS: 4Citation - Scopus: 4Differential 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; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.02. Moleküler Biyoloji ve GenetikTreatment 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.Article Efficacy of Combinatorial Inhibition of Hedgehog and Autophagy Pathways on the Survival of AML Cell Lines(Academic Press inc Elsevier Science, 2025) Sansacar, Merve; Pepe, Nihan Aktas; Akcok, Emel Basak Gencer; El Khatib, Mona; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik; 04.02. Moleküler Biyoloji ve GenetikAcute myeloid leukemia (AML) is a common hematopoietic disease that results from diverse genetic abnormalities. Dysregulation of important signaling pathways, including the PI3K/AKT/mTOR, Wnt and Hedgehog pathways, plays crucial roles in the development of AML. Hedgehog pathway (Hh) is a conserved signaling pathway that is crucial throughout embryogenesis. Hh plays an important role in the regulation of autophagy, known as the cellular recycling process of organelles and unwanted proteins. Many studies have noted that the modulation of autophagy could act as a survival mechanism in AML. Considering the pivotal role of autophagy and Hh signaling in AML, understanding the relationship between these pathways is important for overcoming leukemia. Therefore, we examined the efficacy of Hh inhibition by GLI-ANTagonist 61 (GANT61) in MOLM-13 and CMK cells via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenil-2H-tetrazolium bromide (MTT) cell viability assays. GANT61 resulted in decreased cell viability in both cell lines. Therefore, we focused on the outcome of autophagy modulation in AML cells. We observed that the autophagy inhibitors ammonium chloride (NH4CI), chloroquine (CQ), and nocodazole led to a significant reduction in the proliferation of both cell lines. Cotreatment with autophagy pathway inhibitors and GANT61 synergistically affected both AML cell lines. Moreover, dual targeting of these pathways resulted in arrest at the G0/G1 phase in MOLM-13 cells but not in CMK cells. Furthermore, the combination of nocodazole and GANT61 increased the expression level of LC3B-II in both cell lines. Compared with that in the untreated control cells, the GLI1 gene expression level in both cell lines was significantly lower after GANT61 and autophagy cotreatment. In conclusion, targeting Hh and autophagy could be a favorable option to combat AML.Article Citation - Scopus: 1Engineering Novel Features for Diabetes Complication Prediction Using Synthetic Electronic Health Records(Frontiers Media S.A., 2025) Voskergian, Daniel; Bakir-Gungor, Burcu; Yousef, Malik; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik FakültesiDiabetes significantly affects millions of people worldwide, leading to substantial morbidity, disability, and mortality rates. Predicting diabetes-related complications from health records is crucial for early prevention and for the development of effective treatment plans. In order to predict four different complications of diabetes mellitus, i.e., retinopathy, chronic kidney disease, ischemic heart disease, and amputations, this study introduces a novel feature engineering approach. While developing the classification models, we utilize XGBoost feature selection method and various supervised machine learning algorithms, including Random Forest, XGBoost, LogitBoost, AdaBoost, and Decision Tree. These models were trained on synthetic electronic health records (EHR) generated by dual-adversarial autoencoders. These EHRs represent nearly 1 million synthetic patients derived from an authentic cohort of 979,308 individuals with diabetes. The variables considered in the models were the age range accompanied by chronic diseases that occur during patient visits starting from the onset of diabetes. Throughout the experiments, XGBoost and Random Forest demonstrated the best overall prediction performance. The final models, which are tailored to each complication and trained using our feature engineering approach, achieved an accuracy between 69% and 77% and an AUC between 77% and 84% using cross-validation, while the partitioned validation approach yielded an accuracy between 59% and 78% and an AUC between 66% and 85%. These findings imply that the performance of our method surpass the performance of the traditional Bag-of-Features approach, highlighting the effectiveness of our approach in enhancing model accuracy and robustness.Article Enlightening the Molecular Mechanisms of Type 2 Diabetes With a Novel Pathway Clustering and Pathway Subnetwork Approach(Tubitak Scientific & Technological Research Council Turkey, 2022) Bakir-Gungor, Burcu; Yazici, Miray Unlu; Goy, Gokhan; Temiz, Mustafa; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. BiyomühendislikType 2 diabetes mellitus (T2D) constitutes 90% of the diabetes cases, and it is a complex multifactorial disease. In the last decade, genome-wide association studies (GWASs) for T2D successfully pinpointed the genetic variants (typically single nucleotide polymorphisms, SNPs) that associate with disease risk. In order to diminish the burden of multiple testing in GWAS, researchers attempted to evaluate the collective effects of interesting variants. In this regard, pathway-based analyses of GWAS became popular to discover novel multigenic functional associations. Still, to reveal the unaccounted 85 to 90% of T2D variation, which lies hidden in GWAS datasets, new post-GWAS strategies need to be developed. In this respect, here we reanalyze three metaanalysis data of GWAS in T2D, using the methodology that we have developed to identify disease-associated pathways by combining nominally significant evidence of genetic association with the known biochemical pathways, protein-protein interaction (PPI) networks, and the functional information of selected SNPs. In this research effort, to enlighten the molecular mechanisms underlying T2D development and progress, we integrated different in silico approaches that proceed in top-down manner and bottom-up manner, and presented a comprehensive analysis at protein subnetwork, pathway, and pathway subnetwork levels. Using the mutual information based on the shared genes, the identified protein subnetworks and the affected pathways of each dataset were compared. While most of the identified pathways recapitulate the pathophysiology of T2D, our results show that incorporating SNP functional properties, PPI networks into GWAS can dissect leading molecular pathways, and it could offer improvement over traditional enrichment strategies.Article Citation - WoS: 12Citation - Scopus: 12Ethacrynic Acid and Cinnamic Acid Combination Exhibits Selective Anticancer Effects on K562 Chronic Myeloid Leukemia Cells(Springer, 2022) Yenigul, Munevver; Akcok, Ismail; Gencer Akcok, Emel Basak; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik; 04.02. Moleküler Biyoloji ve GenetikBackground Despite the recent advances in chemotherapy, the outcomes and the success of these treatments still remain insufficient. Novel combination treatments and treatment strategies need to be developed in order to achieve more effective treatment. This study was designed to investigate the combined effect of ethacrynic acid and cinnamic acid on cancer cell lines. Methods The anti-proliferative effect of ethacrynic acid and cinnamic acid was investigated by MTT cell viability assay in three different cancer cell lines. Combination indexes were calculated using CompuSyn software. Apoptosis was assessed by flow cytometric Annexin V-FITC/PI double-staining. The effect of the inhibitors on cell cycle distribution was measured by propidium iodide staining. Results The combination treatment of ethacrynic acid and cinnamic acid decreased cell proliferation significantly, by 63%, 75% and 70% for K562, HepG2 and TFK-1 cells, respectively. A 5.5-fold increase in the apoptotic cell population was observed after combination treatment of K562 cells. The population of apoptotic cells increased by 9.3 and 0.4% in HepG2 and TFK-1 cells, respectively. Furthermore, cell cycle analysis shows significant cell cycle arrest in S and G2/M phase for K562 cells and non-significant accumulation in G0/G1 phase for TFK-1 and HepG2 cells. Conclusions Although there is a need for further investigation, our results suggest that the inhibitors used in this study cause a decrease in cellular proliferation, induce apoptosis and cause cell cycle arrest.Article Citation - WoS: 3Citation - Scopus: 3Exploring Therapeutic Avenues: Mesenchymal Stem/Stromal Cells and Exosomes in Confronting Enigmatic Biofilm-Producing Fungi(Springer, 2024) Bicer, Mesude; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. BiyomühendislikFungal infections concomitant with biofilms can demonstrate an elevated capacity to withstand substantially higher concentrations of antifungal agents, contrasted with infectious diseases caused by planktonic cells. This inherent resilience intrinsic to biofilm-associated infections engenders a formidable impediment to effective therapeutic interventions. The different mechanisms that are associated with the intrinsic resistance of Candida species encompass drug sequestration by the matrix, drug efflux pumps, stress response cell density, and the presence of persister cells. These persisters, a subset of fungi capable of surviving hostile conditions, pose a remarkable challenge in clinical settings in virtue of their resistance to conventional antifungal therapies. Hence, an exigent imperative has arisen for the development of novel antifungal therapeutics with specific targeting capabilities focused on these pathogenic persisters. On a global scale, fungal persistence and their resistance within biofilms generate an urgent clinical need for investigating recently introduced therapeutic strategies. This review delves into the unique characteristics of Mesenchymal stem/stromal cells (MSCs) and their secreted exosomes, which notably exhibit immunomodulatory and regenerative properties. By comprehensively assessing the current literature and ongoing research in this field, this review sheds light on the plausible mechanisms by which MSCs and their exosomes can be harnessed to selectively target fungal persisters. Additionally, prospective approaches in the use of cell-based therapeutic modalities are examined, emphasizing the importance of further research to overcome the enigmatic fungal persistence.
