PubMed İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397

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Aerial Swarms: Recent Applications and Challenges
(Springer, 2021) Mohamed Abdelkader; Samet Güler; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Güler, Samet
Purpose 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. 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. 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.
Application of Biological Domain Knowledge Based Feature Selection on Gene Expression Data
(MDPIST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2021) Yousef, Malik; Kumar, Abhishek; Bakir-Gungor, Burcu; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Bakir-Gungor, Burcu
In the last two decades, there have been massive advancements in high throughput technologies, which resulted in the exponential growth of public repositories of gene expression datasets for various phenotypes. It is possible to unravel biomarkers by comparing the gene expression levels under different conditions, such as disease vs. control, treated vs. not treated, drug A vs. drug B, etc. This problem refers to a well-studied problem in the machine learning domain, i.e., the feature selection problem. In biological data analysis, most of the computational feature selection methodologies were taken from other fields, without considering the nature of the biological data. Thus, integrative approaches that utilize the biological knowledge while performing feature selection are necessary for this kind of data. The main idea behind the integrative gene selection process is to generate a ranked list of genes considering both the statistical metrics that are applied to the gene expression data, and the biological background information which is provided as external datasets. One of the main goals of this review is to explore the existing methods that integrate different types of information in order to improve the identification of the biomolecular signatures of diseases and the discovery of new potential targets for treatment. These integrative approaches are expected to aid the prediction, diagnosis, and treatment of diseases, as well as to enlighten us on disease state dynamics, mechanisms of their onset and progression. The integration of various types of biological information will necessitate the development of novel techniques for integration and data analysis. Another aim of this review is to boost the bioinformatics community to develop new approaches for searching and determining significant groups/clusters of features based on one or more biological grouping functions.
Blockchain for genomics and healthcare: a literature review, current status, classification and open issues
(PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021) Dedeturk, Beyhan Adanur; Soran, Ahmet; Bakir Gungor, Burcu; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Dedeturk, Beyhan Adanur; Soran, Ahmet; Bakir Gungor, Burcu
The 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.
Cell Proliferation and Cytotoxicity Assays
(BENTHAM SCIENCE PUBL LTDEXECUTIVE STE Y-2, PO BOX 7917, SAIF ZONE, 1200 BR SHARJAH, U ARAB EMIRATES, 2016) Adan, Aysun; Kiraz, Yagmur; Baran, Yusuf; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Adan, Aysun; Kiraz, Yagmur; Baran, Yusuf
Cell viability is defined as the number of healthy cells in a sample and proliferation of cells is a vital indicator for understanding the mechanisms in action of certain genes, proteins and pathways involved cell survival or death after exposing to toxic agents. Generally, methods used to determine viability are also common for the detection of cell proliferation. Cell cytotoxicity and proliferation assays are generally used for drug screening to detect whether the test molecules have effects on cell proliferation or display direct cytotoxic effects. Regardless of the type of cell-based assay being used, it is important to know how many viable cells are remaining at the end of the experiment. There are a variety of assay methods based on various cell functions such as enzyme activity, cell membrane permeability, cell adherence, ATP production, co-enzyme production, and nucleotide uptake activity. These methods could be basically classified into different categories: (I) dye exclusion methods such as trypan blue dye exclusion assay, (II) methods based on metabolic activity, (III) ATP assay, (IV) sulforhodamine B assay, (V) protease viability marker assay, (VI) clonogenic cell survival assay, (VII) DNA synthesis cell proliferation assays and (V) raman micro-spectroscopy. In order to choose the optimal viability assay, the cell type, applied culture conditions, and the specific questions being asked should be considered in detail. This particular review aims to provide an overview of common cell proliferation and cytotoxicity assays together with their own advantages and disadvantages, their methodologies, comparisons and intended purposes.
Flow cytometry: basic principles and applications
(TAYLOR & FRANCIS LTD2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND, 2017) Adan, Aysun; Alizada, Gunel; Kiraz, Yagmur; Baran, Yusuf; Nalbant, Ayten; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü
Flow cytometry is a sophisticated instrument measuring multiple physical characteristics of a single cell such as size and granularity simultaneously as the cell flows in suspension through a measuring device. Its working depends on the light scattering features of the cells under investigation, which may be derived from dyes or monoclonal antibodies targeting either extracellular molecules located on the surface or intracellular molecules inside the cell. This approach makes flow cytometry a powerful tool for detailed analysis of complex populations in a short period of time. This review covers the general principles and selected applications of flow cytometry such as immunophenotyping of peripheral blood cells, analysis of apoptosis and detection of cytokines. Additionally, this report provides a basic understanding of flow cytometry technology essential for all users as well as the methods used to analyze and interpret the data. Moreover, recent progresses in flow cytometry have been discussed in order to give an opinion about the future importance of this technology.
Major apoptotic mechanisms and genes involved in apoptosis
(SAGE PUBLICATIONS LTD1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND, 2016) Kiraz, Yagmur; Adan, Aysun; Yandim, Melis Kartal; Baran, Yusuf; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Baran, Yusuf; Kiraz, Yagmur
As much as the cellular viability is important for the living organisms, the elimination of unnecessary or damaged cells has the opposite necessity for the maintenance of homeostasis in tissues, organs and the whole organism. Apoptosis, a type of cell death mechanism, is controlled by the interactions between several molecules and responsible for the elimination of unwanted cells from the body. Apoptosis can be triggered by intrinsically or extrinsically through death signals from the outside of the cell. Any abnormality in apoptosis process can cause various types of diseases from cancer to auto-immune diseases. Different gene families such as caspases, inhibitor of apoptosis proteins, B cell lymphoma (Bcl)-2 family of genes, tumor necrosis factor (TNF) receptor gene superfamily, or p53 gene are involved and/or collaborate in the process of apoptosis. In this review, we discuss the basic features of apoptosis and have focused on the gene families playing critical roles, activation/inactivation mechanisms, upstream/downstream effectors, and signaling pathways in apoptosis on the basis of cancer studies. In addition, novel apoptotic players such as miRNAs and sphingolipid family members in various kind of cancer are discussed.
Reply to Stoimenis et al
(Nature Publishing Group, 2015) Bakir Güngör, Burcu; Remmers, Elaine F.; Meguro, Akira; Mizuki, Nobuhisa; Kästner, Daniel L.; Gul, Ahmet; Sezerman, Ugur; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü;
[Özet Yok]
Revolutionizing dermatology: harnessing mesenchymal stem/stromal cells and exosomes in 3D platform for skin regeneration
(SPRINGER NATURE LINK, 2024) Bicer, Mesude; 0000-0001-7089-5661; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü; Bicer, Mesude
Contemporary trends reveal an escalating interest in regenerative medicine-based interventions for addressing refractory skin defects. Conventional wound healing treatments, characterized by high costs and limited efficacy, necessitate a more efficient therapeutic paradigm to alleviate the economic and psychological burdens associated with chronic wounds. Mesenchymal stem/stromal cells (MSCs) constitute cell-based therapies, whereas cell-free approaches predominantly involve the utilization of MSC-derived extracellular vesicles or exosomes, both purportedly safe and effective. Exploiting the impact of MSCs by paracrine signaling, exosomes have emerged as a novel avenue capable of positively impacting wound healing and skin regeneration. MSC-exosomes confer several advantages, including the facilitation of angiogenesis, augmentation of cell proliferation, elevation of collagen production, and enhancement of tissue regenerative capacity. Despite these merits, challenges persist in clinical applications due to issues such as poor targeting and facile removal of MSC-derived exosomes from skin wounds. Addressing these concerns, a three-dimensional (3D) platform has been implemented to emend exosomes, allowing for elevated levels, and constructing more stable granules possessing distinct therapeutic capabilities. Incorporating biomaterials to encapsulate MSC-exosomes emerges as a favorable approach, concentrating doses, achieving intended therapeutic effectiveness, and ensuring continual release. While the therapeutic potential of MSC-exosomes in skin repair is broadly recognized, their application with 3D biomaterial scenarios remains underexplored. This review synthesizes the therapeutic purposes of MSCs and exosomes in 3D for the skin restoration, underscoring their promising role in diverse dermatological conditions. Further research may establish MSCs and their exosomes in 3D as a viable therapeutic option for various skin conditions.
Uncovering Membrane-Bound Models of Coagulation Factors by Combined Experimental and Computational Approaches
(GEORG THIEME VERLAG KGRUDIGERSTR 14, D-70469 STUTTGART, GERMANY, 2021) Ohkubo, Y. Zenmei; Madsen, Jesper J.; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü; Ohkubo, Y. Zenmei
In the life sciences, including hemostasis and thrombosis, methods of structural biology have become indispensable tools for shedding light on underlying mechanisms that govern complex biological processes. Advancements of the relatively young field of computational biology have matured to a point where it is increasingly recognized as trustworthy and useful, in part due to their high space-time resolution that is unparalleled by most experimental techniques to date. In concert with biochemical and biophysical approaches, computational studies have therefore proven time and again in recent years to be key assets in building or suggesting structural models for membrane-bound forms of coagulation factors and their supramolecular complexes on membrane surfaces where they are activated. Such endeavors and the proposed models arising from them are of fundamental importance in describing and understanding the molecular basis of hemostasis under both health and disease conditions. We summarize the body of work done in this important area of research to drive forward both experimental and computational studies toward new discoveries and potential future therapeutic strategies.
An update on molecular biology and drug resistance mechanisms of multiple myeloma
(ELSEVIER SCIENCE INC, 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA, 2015) Mutlu, Pelin; Kiraz, Yagmur; Gunduz, Ufuk; Baran, Yusuf; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü;
Multiple myeloma (MM), a neoplasm of plasma cells, is the second most common hematological malignancy. Incidance rates increase after age 40. MM is most commonly seen in men and African-American population. There are several factors to this, such as obesity, environmental factors, family history, genetic factors and monoclonal gammopathies of undetermined significance (MGUS) that have been implicated as potentially etiologic. Development of MM involves a series of complex molecular events, including chromosomal abnormalities, oncogene activation and growth factor dysregulation. Chemotherapy is the most commonly used treatment strategy in MM. However, MM is a difficult disease to treat because of its marked resistance to chemotherapy. MM has been shown to be commonly multidrug resistance (MDR)-negative at diagnosis and associated with a high incidence of MDR expression at relapse. This review deals with the molecular aspects of MM, drug resistance mechanisms during treatment and also possible new applications for overcoming drug resistance. (C) 2015 Elsevier Ireland Ltd. All rights reserved.

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