PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article The Joubert syndrome protein CEP41 is excluded from the distal segment of cilia in C. elegans(2021) Sebiha Cevik; Oktay I KaplanRare diseases are a fundamental issue in today's world, affecting more than 300 million individuals worldwide. According to data from Orphanet and OMIM, about 50-60 new conditions are added to the list of over 6,000 clinically distinct diseases each year, rendering disease diagnosis and treatment even more challenging. Ciliopathies comprise a heterogeneous category of rare diseases made up of over 35 distinct diseases, including Joubert syndrome (JBTS; OMIM 213300), that are caused by functional and structural defects in cilia. JBTS is an autosomal recessive condition characterized by a range of symptoms, including cerebellar vermis hypoplasia and poor muscle tone. There are now a total of 38 genes that cause JBTS, almost all of which encode protein products that are found in cilia and cilia-associated compartments, such as the basal body and transition zone. CEP41 is a JBTS-associated protein that is found in cilia and the basal body of mammals, but its localization in other ciliary organisms remains elusive. C. elegans is an excellent model organism for studying the molecular mechanisms of rare diseases like JBTS. We, therefore, decided to use C. elegans to identify the localization of CEP41. Our microscopy analysis revealed that CEPH-41(CEntrosomal Protein Homolog 41) not only localizes to cilia but is excluded from the distal segment of the amphid and phasmid cilia in C. elegans. Furthermore, we discovered a putative X-box motif located in the promoter of ceph-41 and the expression of ceph-41 is regulated by DAF-19, a sole Regulatory Factor X (RFX) transcription factor.Article Subcellular localization of the voltage-gated K+ channel EGL-36 , a member of the KV3 subfamily, in the ciliated sensory neurons in C. elegans(2021) Sebiha Cevik; Oktay I KaplanDelineated as the first cellular organelle in 1675 by Antonie van Leeuwenhoek, cilia did not receive much attention until the 2000s, when it became apparent that cilia played a key role in the development of embryos, a variety of signaling pathways. Therefore, collective efforts by many scientists have led to the identification of many novel ciliopathy and cilia genes, while we are still far from disclosing the complete components of cilia.Here we used the ciliated sensory neurons in C. elegans as a model system that revealed the voltage-gated K+ channel EGL-36 (a member of the Shaw subfamily) as a new component associated with cilia. The confocal microscopy examination of fluorescence tagged EGL-36 together with ciliary (IFT-140) or transition zone (MKS-6) markers reveal that EGL-36 is only expressed in subsets of the ciliated sensory neurons, where it partially overlaps with the basal body signals and predominantly localizes to the periciliary membrane compartment. This expression pattern along with studies of egl-36 gain-of-function variants indicates that egl-36 is not essential for ciliogenesis in C. elegans. Our data identify the voltage-gated K+ channel EGL-36 as a new cilia-associated protein, and future studies should reveal the functional significance of EGL-36 in cilia biogenesis.Review Aerial Swarms: Recent Applications and Challenges(Springer, 2021) Mohamed Abdelkader; Samet GülerPurpose of review: Currently, there is a large body of research on multi-agent systems addressing their different system theoretic aspects. Aerial swarms as one type of multi-agent robotic systems have recently gained huge interest due to their potential applications. However, aerial robot groups are complex multi-disciplinary systems and usually research works focus on specific system aspects for particular applications. The purpose of this review is to provide an overview of the main motivating applications that drive the majority of research works in this field, and summarize fundamental and common algorithmic components required for their development._x000D_ _x000D_ Recent findings: Most system demonstrations of current aerial swarms are based on simulations, some have shown experiments using few 10 s of robots in controlled indoor environment, and limited number of works have reported outdoor experiments with small number of autonomous aerial vehicles. This indicates scalability issues of current swarm systems in real world environments. This is mainly due to the limited confidence on the individual robot's localization, swarm-level relative localization, and the rate of exchanged information between the robots that is required for planning safe coordinated motions._x000D_ _x000D_ Summary: This paper summarizes the main motivating aerial swarm applications and the associated research works. In addition, the main research findings of the core elements of any aerial swarm system, state estimation and mission planning, are also presented. Finally, this paper presents a proposed abstraction of an aerial swarm system architecture that can help developers understand the main required modules of such systems.Article Citation - WoS: 26Citation - Scopus: 33miRmoduleNet: Detecting miRNA-mRNA Regulatory Modules(Frontiers Media S.A., 2022-04-12) Yousef, Malik; Goy, Gokhan; Bakir-Gungor, BurcuIncreasing evidence that MicroRNAs (miRNAs) play a key role in carcinogenesis has revealed the need for elucidating the mechanisms of miRNA regulation and the roles of miRNAs in gene-regulatory networks. A better understanding of the interactions between miRNAs and their mRNA targets will provide a better understanding of the complex biological processes that occur during carcinogenesis. Increased efforts to reveal these interactions have led to the development of a variety of tools to detect and understand these interactions. We have recently described a machine learning approach miRcorrNet, based on grouping and scoring (ranking) groups of genes, where each group is associated with a miRNA and the group members are genes with expression patterns that are correlated with this specific miRNA. The miRcorrNet tool requires two types of -omics data, miRNA and mRNA expression profiles, as an input file. In this study we describe miRModuleNet, which groups mRNA (genes) that are correlated with each miRNA to form a star shape, which we identify as a miRNA-mRNA regulatory module. A scoring procedure is then applied to each module to further assess their contribution in terms of classification. An important output of miRModuleNet is that it provides a hierarchical list of significant miRNA-mRNA regulatory modules. miRModuleNet was further validated on external datasets for their disease associations, and functional enrichment analysis was also performed. The application of miRModuleNet aids the identification of functional relationships between significant biomarkers and reveals essential pathways involved in cancer pathogenesis.Article Citation - WoS: 20Citation - Scopus: 24miRdisNET: Discovering MicroRNA Biomarkers That Are Associated With Diseases Utilizing Biological Knowledge-Based Machine Learning(Frontiers Media S.A., 2023-01-12) Jabeer, Amhar; Temiz, Mustafa; Bakir-Gungor, Burcu; Yousef, MalikDuring recent years, biological experiments and increasing evidence have shown that MicroRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex diseases, it is necessary to reveal the associations between a specific disease and related miRNAs. Although current computational models based on machine learning attempt to determine miRNA-disease associations, the accuracy of these models need to be improved, and candidate miRNA-disease relations need to be evaluated from a biological perspective. In this paper, we propose a computational model named miRdisNET to predict potential miRNA-disease associations. Specifically, miRdisNET requires two types of data, i.e., miRNA expression profiles and known disease-miRNA associations as input files. First, we generate subsets of specific diseases by applying the grouping component. These subsets contain miRNA expressions with class labels associated with each specific disease. Then, we assign an importance score to each group by using a machine learning method for classification. Finally, we apply a modeling component and obtain outputs. One of the most important outputs of miRdisNET is the performance of miRNA-disease prediction. Compared with the existing methods, miRdisNET obtained the highest AUC value of .9998. Another output of miRdisNET is a list of significant miRNAs for disease under study. The miRNAs identified by miRdisNET are validated via referring to the gold-standard databases which hold information on experimentally verified MicroRNA-disease associations. miRdisNET has been developed to predict candidate miRNAs for new diseases, where miRNA-disease relation is not yet known. In addition, miRdisNET presents candidate disease-disease associations based on shared miRNA knowledge. The miRdisNET tool and other supplementary files are publicly available at: .Article Citation - WoS: 26Citation - Scopus: 31miRcorrNet: Machine Learning-Based Integration of miRNA and mRNA Expression Profiles, Combined with Feature Grouping and Ranking(PeerJ Inc., 2021-05-19) Yousef, M.; Göy, G.; Mitra, R.; Eischen, C.M.; Jabeer, A.; Bakir-Güngör, B.A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high throughput technologies allowed to generate mRNA and microRNA (miRNA) expression profiles; and the integrative analysis of these profiles allowed to uncover the functional effects of RNA expression in complex diseases, such as cancer. Several researches attempt to integrate miRNA and mRNA expression profiles using statistical methods such as Pearson correlation, and then combine it with enrichment analysis. In this study, we developed a novel tool called miRcorrNet, which performs machine learning-based integration to analyze miRNA and mRNA gene expression profiles. miRcorrNet groups mRNAs based on their correlation to miRNA expression levels and hence it generates groups of target genes associated with each miRNA. Then, these groups are subject to a rank function for classification. We have evaluated our tool using miRNA and mRNA expression profiling data downloaded from The Cancer Genome Atlas (TCGA), and performed comparative evaluation with existing tools. In our experiments we show that miRcorrNet performs as good as other tools in terms of accuracy (reaching more than 95% AUC value). Additionally, miRcorrNet includes ranking steps to separate two classes, namely case and control, which is not available in other tools. We have also evaluated the performance of miRcorrNet using a completely independent dataset. Moreover, we conducted a comprehensive literature search to explore the biological functions of the identified miRNAs. We have validated our significantly identified miRNA groups against known databases, which yielded about 90% accuracy. Our results suggest that miRcorrNet is able to accurately prioritize pan-cancer regulating high-confidence miRNAs. miRcorrNet tool and all other supplementary files are available at https://github.com/ malikyousef/miRcorrNet. © 2021 Elsevier B.V., All rights reserved.Letter Citation - WoS: 18Yemen's Triple Emergency: Food Crisis Amid a Civil War and COVID-19 Pandemic(Elsevier, 2021-11) Hashim, Hashim Talib; Miranda, Adriana Viola; Babar, Maryam Salma; Essar, Mohammad Yasir; Hussain, Hasham; Ahmad, Shoaib; Basalilah, Ashraf Fhed MohammedYemen has been termed as the world's worst humanitarian crisis by the United Nations. About 20.1 million (more than 50% of population) Yemenis are facing hunger and 10 million are severely food insecure according to reports by the World Food Programme. With the spread of COVID-19, the situation in Yemen has worsened and humanitarian aid from other countries has become the basis of life for hundreds of thousands of Yemenis after the threat of famine. Yemen is practically one of the poorest countries in the world. It has structural vulnerabilities that have developed over a protracted period of conflict and poor governance and more than 50% live in starving, they suffer for getting one meal a day. To prevent a total collapse of Yemen's food crises, the government and the international community should act now more decisively.Article Citation - WoS: 8Citation - Scopus: 8Writing Chemical Patterns Using Electrospun Fibers as Nanoscale Inkpots for Directed Assembly of Colloidal Nanocrystals(Royal Soc Chemistry, 2020) Kiremitler, N. Burak; Torun, Ilker; Altintas, Yemliha; Patarroyo, Javier; Demir, Hilmi Volkan; Puntes, Victor F.; Onses, M. SerdarApplications that range from electronics to biotechnology will greatly benefit from low-cost, scalable and multiplex fabrication of spatially defined arrays of colloidal inorganic nanocrystals. In this work, we present a novel additive patterning approach based on the use of electrospun nanofibers (NFs) as inkpots for end-functional polymers. The localized grafting of end-functional polymers from spatially defined nanofibers results in covalently bound chemical patterns. The main factors that determine the width of the nanopatterns are the diameter of the NF and the extent of spreading during the thermal annealing process. Lowering the surface energy of the substrates via silanization and a proper choice of the grafting conditions enable the fabrication of nanoscale patterns over centimeter length scales. The fabricated patterns of end-grafted polymers serve as the templates for spatially defined assembly of colloidal metal and metal oxide nanocrystals of varying sizes (15 to 100 nm), shapes (spherical, cube, rod), and compositions (Au, Ag, Pt, TiO2), as well as semiconductor quantum dots, including the assembly of semiconductor nanoplatelets.Article Citation - WoS: 13Citation - Scopus: 13Why Do Muse Stem Cells Present an Enduring Stress Capacity? Hints From a Comparative Proteome Analysis(MDPI, 2021-02-19) Acar, Mustafa B.; Aprile, Domenico; Ayaz-Guner, Serife; Guner, Huseyin; Tez, Coskun; Di Bernardo, Giovanni; Galderisi, UmbertoMuse cells are adult stem cells that are present in the stroma of several organs and possess an enduring capacity to cope with endogenous and exogenous genotoxic stress. In cell therapy, the peculiar biological properties of Muse cells render them a possible natural alternative to mesenchymal stromal cells (MSCs) or to in vitro-generated pluripotent stem cells (iPSCs). Indeed, some studies have proved that Muse cells can survive in adverse microenvironments, such as those present in damaged/injured tissues. We performed an evaluation of Muse cells' proteome under basic conditions and followed oxidative stress treatment in order to identify ontologies, pathways, and networks that can be related to their enduring stress capacity. We executed the same analysis on iPSCs and MSCs, as a comparison. The Muse cells are enriched in several ontologies and pathways, such as endosomal vacuolar trafficking related to stress response, ubiquitin and proteasome degradation, and reactive oxygen scavenging. In Muse cells, the protein-protein interacting network has two key nodes with a high connectivity degree and betweenness: NFKB and CRKL. The protein NFKB is an almost-ubiquitous transcription factor related to many biological processes and can also have a role in protecting cells from apoptosis during exposure to a variety of stressors. CRKL is an adaptor protein and constitutes an integral part of the stress-activated protein kinase (SAPK) pathway. The identified pathways and networks are all involved in the quality control of cell components and may explain the stress resistance of Muse cells.Article Citation - WoS: 39Citation - Scopus: 51What Are the Key Success Factors for Strategy Formulation and Implementation? Perspectives of Managers in the Hotel Industry(Elsevier Sci Ltd, 2020-08) Koseoglu, Mehmet Ali; Altin, Mehmet; Chan, Eric; Aladag, Omer FarukThis study investigates how hotel managers describe strategy and identify key success factors for its formulation and implementation. The study analyzes qualitative data collected through semi-structured interviews with property level top managers of hotels in Hong Kong. The findings show that hotel managers prioritize competition analysis and macro-environmental conditions over internal characteristics such as teamwork in strategy formulation. In the implementation phase, however, internal considerations such as employee involvement and strategic consensus are given prominence. This study provides a significant contribution by examining how top level practitioners in the industry interpret success factors in their strategic management efforts, and it highlights a largely neglected area in the hospitality and tourism management literature.