PubMed İndeksli Yayınlar Koleksiyonu

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

Browse

Now showing 1 - 20 of 260

An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
(Elsevier, 2024) Yengec-Tasdemir,Sena Busra; Aydin,Zafer; Akay,Ebru; Doğan,Serkan; Yilmaz,Bulent; 0000-0001-7686-6298; AGÜ, Fen Bilimleri Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı; Aydın, Zafer; Yilmaz, Bulent
Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic variants is crucial. This study introduces a cutting-edge computer-aided diagnosis system optimized for this task. Our system employs advanced Supervised Contrastive learning to ensure precise classification of colon histopathology images. Significantly, we have integrated the Big Transfer model, which has gained prominence for its exemplary adaptability to visual tasks in medical imaging. Our novel approach discerns between in-class and out-of-class images, thereby elevating its discriminatory power for polyp subtypes. We validated our system using two datasets: a specially curated one and the publicly accessible UniToPatho dataset. The results reveal that our model markedly surpasses traditional deep convolutional neural networks, registering classification accuracies of 87.1% and 70.3% for the custom and UniToPatho datasets, respectively. Such results emphasize the transformative potential of our model in polyp classification endeavors
Matching variants for functional characterization of genetic variants
(Oxford University Press, 2023) Cevik,Sabiha; Zhao,Pei; Zorluer,Atiyye; Pir, Mustafa S.; Bian, Wenyin; Kaplan, Oktay I.; 0000-0002-0935-1929; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Cevik, Sabiha; Zorluer, Atiye; Pir, Mustafa S.
Rapid and low-cost sequencing, as well as computer analysis, have facilitated the diagnosis of many genetic diseases, resulting in a substantial rise in the number of disease-associated genes. However, genetic diagnosis of many disorders remains problematic due to the lack of interpretation for many genetic variants, especially missenses, the infeasibility of high-throughput experiments on mammals, and the shortcomings of computational prediction technologies. Additionally, the available mutant databases are not well-utilized. Toward this end, we used Caenorhabditis elegans mutant resources to delineate the functions of eight missense variants (V444I, V517D, E610K, L732F, E817K, H873P, R1105K, and G1205E) and two stop codons (W937stop and Q1434stop), including several matching variants (MatchVar) with human in ciliopathy associated IFT-140 (also called CHE-11)//IFT140 (intraflagellar transport protein 140). Moreover, MatchVars carrying C. elegans mutants, including IFT-140(G680S) and IFT-140(P702A) for the human (G704S) (dbSNP: rs150745099) and P726A (dbSNP: rs1057518064 and a conflicting variation) were created using CRISPR/Cas9. IFT140 is a key component of IFT complex A (IFT-A), which is involved in the retrograde transport of IFT along cilia and the entrance of G protein-coupled receptors into cilia. Functional analysis of all 10 variants revealed that P702A and W937stop, but not others phenocopied the ciliary phenotypes (short cilia, IFT accumulations, mislocalization of membrane proteins, and cilia entry of nonciliary proteins) of the IFT-140 null mutant, indicating that both P702A and W937stop are phenotypic in C. elegans. Our functional data offered experimental support for interpreting human variants, by using ready-to-use mutants carrying MatchVars and generating MatchVars with CRISPR/Cas9.
Electrochemical and Optical Multi-Detection of Escherichia coli Through Magneto-Optic Nanoparticles: A Pencil-on-Paper Biosensor
(MDPI, 2024) Soysaldi, Furkan; Ekici, Derya Dincyurek; Soylu, Mehmet cagri; Mutlugun, Evren; 0000-0003-1120-5557; 0000-0001-5807-9944; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Ekici, Derya Dincyurek; Mutlugun, Evren
Escherichia coli (E. coli) detection suffers from slow analysis time and high costs, along with the need for specificity. While state-of-the-art electrochemical biosensors are cost-efficient and easy to implement, their sensitivity and analysis time still require improvement. In this work, we present a paper-based electrochemical biosensor utilizing magnetic core-shell Fe2O3@CdSe/ZnS quantum dots (MQDs) to achieve fast detection, low cost, and high sensitivity. Using electrochemical impedance spectroscopy (EIS) as the detection technique, the biosensor achieved a limit of detection of 2.7 x 10(2) CFU/mL for E. coli bacteria across a concentration range of 10(2)-10(8) CFU/mL, with a relative standard deviation (RSD) of 3.5781%. From an optical perspective, as E. coli concentration increased steadily from 10(4) to 10(7) CFU/mL, quantum dot fluorescence showed over 60% lifetime quenching. This hybrid biosensor thus provides rapid, highly sensitive E. coli detection with a fast analysis time of 30 min. This study, which combines the detection advantages of electrochemical and optical biosensor systems in a graphite-based paper sensor for the first time, has the potential to meet the needs of point-of-care applications. It is thought that future studies that will aim to examine the performance of the production-optimized, portable, graphite-based sensor system on real food samples, environmental samples, and especially medical clinical samples will be promising.
Discovery of a C-S lyase inhibitor for the prevention of human body malodor formation: tannic acid inhibits the thioalcohol production in Staphylococcus hominis
(SPRINGER NATURE LINK, 2025) Fidan, Ozkan; Karipcin, Ayse Doga; Kose, Ayse Hamide; Anaz, Ayse; Demirsoy, Beyza Nur; Arslansoy, Nuriye; Sun, Lei; Mujwar, Somdutt; 0000-0001-5312-4742; 0009-0005-7132-842X; 0009-0008-5514-8711; 0000-0003-4037-5475; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü; Fidan, Ozkan; Karipcin, Ayse Doga; Kose, Ayse Hamide; Anaz, Ayse; Demirsoy, Beyza Nur; Arslansoy, Nuriye
Human body odor is a result of the bacterial biotransformation of odorless precursor molecules secreted by the underarm sweat glands. In the human axilla, Staphylococcus hominis is the predominant bacterial species responsible for the biotransformation process of the odorless precursor molecule into the malodorous 3M3SH by two enzymes, a dipeptidase and a specific C-S lyase. The current solutions for malodor, such as deodorants and antiperspirants are known to block the apocrine glands or disrupt the skin microbiota. Additionally, these chemicals endanger both the environment and human health, and their long-term use can influence the function of sweat glands. Therefore, there is a need for the development of alternative, environmentally friendly, and natural solutions for the prevention of human body malodor. In this study, a library of secondary metabolites from various plants was screened to inhibit the C-S lyase, which metabolizes the odorless precursor sweat molecules, through molecular docking and molecular dynamics (MD) simulation. In silico studies revealed that tannic acid had the strongest affinity towards C-S lyase and was stably maintained in the binding pocket of the enzyme during 100-ns MD simulation. We found in the in vitro biotransformation assays that 1 mM tannic acid not only exhibited a significant reduction in malodor formation but also had quite low growth inhibition in S. hominis, indicating the minimum inhibitory effect of tannic acid on the skin microflora. This study paved the way for the development of a promising natural C-S lyase inhibitor to eliminate human body odor and can be used as a natural deodorizing molecule after further in vivo analysis.
Unravelling the moderating roles of environmental regulations on the impact of foreign direct investment on environmental sustainability
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2025) Ehigiamusoe, Kizito Uyi; Chen, Danqing; Dogan, Eyup; Binsaeed, Rima H.; 0000-0003-0476-5177; AGÜ, Yönetim Bilimleri Fakültesi, Ekonomi Bölümü; Dogan, Eyup
In the era of economic globalization, China attracts significant foreign direct investment (FDI) to accelerate economic prosperity. FDI inflows could have ramifications on environmental degradation (ED) despite the enactment of different environmental regulations (ERs) such as market-incentive, command-and-control as well as informal regulations. Though some studies have shown that FDI and ED have significant relationship, the moderating roles of different ERs on the environmental impact of FDI has not been empirically unraveled. This study fills this research gap by analyzing the direct impact of FDI on ED (i.e., carbon dioxide emissions, ecological footprint) using the provincial panel data. Second, it unravels the moderating roles of different ERs on the environmental impact of FDI in the provinces and regions. The results indicate that FDI directly mitigates ED, verifying the pollution halo hypothesis while ERs directly alleviate ED in China. However, the interaction between FDI and ERs do not alleviate ED in China albeit regional heterogeneity exist. The economic implication is that FDI is not a channel through which ERs enhance environmental sustainability in China. This study recommends some policy options arising from the findings.
Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation
(ACS Publications, 2024) Dangayach, Raghav; Jeong, Nohyeong; Demirel, Elif; Uzal, Nigmet; Fung, Victor; Chen, Yongsheng; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Nigmet
Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility and high tunability. Traditional trial-and-error methods for material synthesis are inadequate to meet the growing demands for high-performance membranes. Machine learning (ML) has demonstrated huge potential to accelerate design and discovery of membrane materials. In this review, we cover strengths and weaknesses of the traditional methods, followed by a discussion on the emergence of ML for developing advanced polymeric membranes. We describe methodologies for data collection, data preparation, the commonly used ML models, and the explainable artificial intelligence (XAI) tools implemented in membrane research. Furthermore, we explain the experimental and computational validation steps to verify the results provided by these ML models. Subsequently, we showcase successful case studies of polymeric membranes and emphasize inverse design methodology within a ML-driven structured framework. Finally, we conclude by highlighting the recent progress, challenges, and future research directions to advance ML research for next generation polymeric membranes. With this review, we aim to provide a comprehensive guideline to researchers, scientists, and engineers assisting in the implementation of ML to membrane research and to accelerate the membrane design and material discovery process.
Probabilistic assessment of wind power plant energy potential through a copula-deep learning approach in decision trees
(CELL PRESS, 2024) Şahin, Kübra Nur; Sutcu, Muhammed; 0000-0001-9786-6270; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Şahin, Kübra Nur
In the face of environmental degradation and diminished energy resources, there is an urgent need for clean, affordable, and sustainable energy solutions, which highlights the importance of wind energy. In the global transition to renewable energy sources, wind power has emerged as a key player that is in line with the Paris Agreement, the Net Zero Target by 2050, and the UN 2030 Goals, especially SDG-7. It is critical to consider the variable and intermittent nature of wind to efficiently harness wind energy and evaluate its potential. Nonetheless, since wind energy is inherently variable and intermittent, a comprehensive assessment of a prospective site's wind power generation potential is required. This analysis is crucial for stakeholders and policymakers to make well-informed decisions because it helps them assess financial risks and choose the best locations for wind power plant installations. In this study, we introduce a framework based on Copula-Deep Learning within the context of decision trees. The main objective is to enhance the assessment of the wind power potential of a site by exploiting the intricate and non-linear dependencies among meteorological variables through the fusion of copulas and deep learning techniques. An empirical study was carried out using wind power plant data from Turkey. This dataset includes hourly power output measurements as well as comprehensive meteorological data for 2021. The results show that acknowledging and addressing the non-independence of variables through innovative frameworks like the Copula-LSTM based decision tree approach can significantly improve the accuracy and reliability of wind power plant potential assessment and analysis in other real-world data scenarios. The implications of this research extend beyond wind energy to inform decision-making processes critical for a sustainable energy future.
Determination of promising inhibitors for N-SH2 domain of SHP2 tyrosine phosphatase: an in silico study
(SPRINGER NATURE LINK, 2024) Akcok, Emel Basak Gencer; Guner, Huseyin; Akcok, Ismail; 0000-0002-6559-9144; 0000-0002-5444-3929; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Akcok, Emel Basak Gencer; Akcok, Ismail
There are many genes that produce proteins related to diseases and these proteins can be targeted with drugs as a potential therapeutic approach. Recent advancement in drug discovery techniques have created new opportunities for treating variety of diseases by targeting disease-related proteins. Structure-based drug discovery is a faster and more cost-effective approach than traditional methods. SHP2 phosphatase, encoded by the PTPN11 gene, has been the focus of much attention due to its involvement in many types of diseases. The biological function of SHP2 is enabled mostly by protein-protein interaction through its SH2 domains. In this study, we report the identification of a potential small molecule inhibitor for the N-SH2 domain of SHP2 by structure-based drug discovery approach. We utilized molecular docking studies, followed by molecular dynamics simulations and MM/PBSA calculations, to analyze compounds retrieved from the Broad's Drug Repurposing Hub and ZINC15 databases. We selected 10 hit compounds with the best docking scores from the libraries and examined their binding properties in the N-SH2 domain. We found that compound CID 60838 (Irinotecan) was the most suitable compound with a binding free energy value of - 64.45 kcal/mol and significant interactions with the target residues in the domain.
CSA-DE-LR: enhancing cardiovascular disease diagnosis with a novel hybrid machine learning approach
(PEERJ INC, 2024) Dedeturk, Beyhan Adanur; Dedeturk, Bilge Kagan; Bakir-Gungor, Burcu; 0000-0003-4983-2417; 0000-0002-8026-5003; 0000-0002-2272-6270; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Beyhan Adanur, Dedeturk; Bakir-Gungor, Burcu
Cardiovascular diseases (CVD) are a leading cause of mortality globally, necessitating the development of efficient diagnostic tools. Machine learning (ML) and metaheuristic algorithms have become prevalent in addressing these challenges, providing promising solutions in medical diagnostics. However, traditional ML approaches often need to be improved in feature selection and optimization, leading to suboptimal performance in complex diagnostic tasks. To overcome these limitations, this study introduces a new hybrid method called CSA-DE-LR, which combines the clonal selection algorithm (CSA) and differential evolution (DE) with logistic regression. This integration is designed to optimize logistic regression weights efficiently for the accurate classification of CVD. The methodology employs three optimization strategies based on the F1 score, the Matthews correlation coefficient (MCC), and the mean absolute error (MAE). Extensive evaluations on benchmark datasets, namely Cleveland and Statlog, reveal that CSA-DELR outperforms state-of-the-art ML methods. In addition, generalization is evaluated using the Breast Cancer Wisconsin Original (WBCO) and Breast Cancer Wisconsin Diagnostic (WBCD) datasets. Significantly, the proposed model demonstrates superior efficacy compared to previous research studies in this domain. This study's findings highlight the potential of hybrid machine learning approaches for improving diagnostic accuracy, offering a significant advancement in the fields of medical data analysis and CVD diagnosis.
Role of pretty nanoflowers as novel versatile analytical tools for sensing in biomedical and bioanalytical applications
(Wiley-Online Library, 2024) Dadi,Seyma; Ocsoy,Ismail; 0000-0001-6280-3966; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Dadi, Seyma
In recent years, an encouraging breakthrough in the synthesis of immobilized enzymes in flower‐shaped called “organic‐inorganic hybrid nanoflowers (hNFs)” with greatly enhanced catalytic activity and stability were reported. Although, these hNFs were discovered by accident, the enzymes exhibited highly enhanced catalytic activities and stabilities in the hNFs compared with the free and conventionally immobilized enzymes. Herein, we rationally uti lized the catalytic activity of the hNFs for analytical applications. In this comprehensive review, we covered the design and use of the hNFs as novel versatile sensors for electrochemical, colorimetric/optical immunosensors‐based detection strategies in analytical perspective.
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.
Review of feature selection approaches based on grouping of features
(PeerJ, 2023) Kuzudisli,Cihan; Gungor-Bakır, Burcu; Bulut, Nurten; Qaqish, Behjat; Yousef, Malik; 0000-0002-1895-8749; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor-Bakır, Burcu; Bulut, Nurten
With the rapid development in technology, large amounts of high-dimensional data have been generated. This high dimensionality including redundancy and irrelevancy poses a great challenge in data analysis and decision making. Feature selection (FS) is an effective way to reduce dimensionality by eliminating redundant and irrelevant data. Most traditional FS approaches score and rank each feature individually; and then perform FS either by eliminating lower ranked features or by retaining highly ranked features. In this review, we discuss an emerging approach to FS that is based on initially grouping features, then scoring groups of features rather than scoring individual features. Despite the presence of reviews on clustering and FS algorithms, to the best of our knowledge, this is the first review focusing on FS techniques based on grouping. The typical idea behind FS through grouping is to generate groups of similar features with dissimilarity between groups, then select representative features from each cluster. Approaches under supervised, unsupervised, semi supervised and integrative frameworks are explored. The comparison of experimental results indicates the effectiveness of sequential, optimization-based (i.e., fuzzy or evolutionary), hybrid and multi-method approaches. When it comes to biological data, the involvement of external biological sources can improve analysis results. We hope this works findings can guide effective design of new FS approaches using feature grouping.
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.
Highly Potent New Probiotic Strains from Traditional Turkish Fermented Foods
(SPRINGER NATURE LINK, 2025) Yigit, Mehmet Burak; Cebeci, Aysun; 0000-0002-6158-8798; 0000-0002-6777-6773; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Cebeci, Aysun; Yigit, Mehmet Burak
Traditional Turkish fermented foods like boza, pickles, and tarhana are recognized for their nutritional and health benefits, yet the probiotic potential of lactic acid bacteria (LAB) strains isolated from them remains underexplored. Sixty-six LAB strains were isolated from fermented foods using bacterial morphology, Gram staining, and catalase activity. The isolates were differentiated at strain level by RAPD-PCR (Random Amplification of Polymorphic DNA-Polymerase Chain Reaction) and twenty-five strains were selected for further evaluation of acid and bile salt tolerance. Among these, ten strains exhibited high tolerance and were subsequently assessed for adhesion to Caco-2 colorectal carcinoma cells, antimicrobial activity, exopolysaccharide (EPS) production, lysozyme resistance, and hemolytic activity. Using k-means clustering, three strains: Lactiplantibacillus plantarum ES-3, Pediococcus pentosaceus N-1, and Enterococcus faecium N-2 demonstrated superior probiotic characteristics, including significant acid (100% survival at pH3.0) and 0.3% bile salt tolerance (57%, 64%, 67%), strong adhesion to intestinal cells (65%, 88%, 91%), high lysozyme resistance (88%, 88%, 77%), and produced high amounts of EPS. These strains show promising potential as probiotics and warrant further investigation to confirm their functional properties and potential applications.
Aguhyper: a hyperledger-based electronic health record management framework
(PEERJ INC, 2024) Dedeturk, Beyhan Adanur; Bakir-Gungor, Burcu; 0000-0003-4983-2417; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Dedeturk, Beyhan Adanur; Bakir-Gungor, Burcu
The increasing importance of healthcare records, particularly given the emergence of new diseases, emphasizes the need for secure electronic storage and dissemination. With these records dispersed across diverse healthcare entities, their physical maintenance proves to be excessively time-consuming. The prevalent management of electronic healthcare records (EHRs) presents inherent security vulnerabilities, including susceptibility to attacks and potential breaches orchestrated by malicious actors. To tackle these challenges, this article introduces AguHyper, a secure storage and sharing solution for EHRs built on a permissioned blockchain framework. AguHyper utilizes Hyperledger Fabric and the InterPlanetary Distributed File System (IPFS). Hyperledger Fabric establishes the blockchain network, while IPFS manages the off-chain storage of encrypted data, with hash values securely stored within the blockchain. Focusing on security, privacy, scalability, and data integrity, AguHyper’s decentralized architecture eliminates single points of failure and ensures transparency for all network participants. The study develops a prototype to address gaps identified in prior research, providing insights into blockchain technology applications in healthcare. Detailed analyses of system architecture, AguHyper’s implementation configurations, and performance assessments with diverse datasets are provided. The experimental setup incorporates CouchDB and the Raft consensus mechanism, enabling a thorough comparison of system performance against existing studies in terms of throughput and latency. This contributes significantly to a comprehensive evaluation of the proposed solution and offers a unique perspective on existing literature in the field.
ARL13B regulates juxtaposed cilia-cilia elongation in BBSome dependent manner in Caenorhabditis elegans
(CELL PRESS, 2025) Turan, Merve Gul; Kantarci, Hanife; Cevik, Sebiha; Kaplan, Oktay I.; 0000-0002-0935-1929; 0000-0002-8733-0920; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Turan, Merve Gul; Kantarci, Hanife; Cevik, Sebiha; Kaplan, Oktay I.
The interaction of cilia with various cellular compartments, such as axons, has emerged as a new form of cellular communication. Cilia often extend in proximity to cilia from neighboring cells. However, the mechanisms driving this process termed juxtaposed cilia-cilia elongation (JCE) remain unclear. We use fluorescence-based visualization to study the mechanisms of coordinated cilia elongation in sensory neurons of Caenorhabditis elegans. Conducting a selective gene-based screening strategy reveals that ARL-13/ARL13B and MKS-5/RPGRIP1L are essential for JCE. We demonstrate that ARL-13 modulates JCE independently of cilia length. Loss of NPHP-2/inversin along with HDAC-6 enhances the cilia misdirection phenotype of arl-13 mutants, while disruption of the BBSome complex, but not microtubule components, partially suppresses the JCE defects in arl-13 mutants. We further show changes in the phospholipid compositions in arl-13 mutants. We suggest that ARL-13 contributes to JCE, in part, through the modulation of the ciliary membrane.
Aurora Kinases: Their Role in Cancer and Cellular Processes
(Bingöl Üniversitesi Fen Bilimleri Enstitüsü, 2024) Sarı, Sibel; Özsoy, Elif Rumeysa; 0000-0002-2505-5804; 0009-0008-6040-9875; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Sarı, Sibel; Özsoy, Elif Rumeysa
Aurora kinases, belonging to a highly conserved family of serine/threonine kinases with critical roles in the regulation of the cell cycle, comprise three members: Aurora kinase A, B, and C, which serve as key mitotic regulators essential for maintaining chromosome stability. Aurora kinases play crucial roles in multiple events in mitotic such as the coordination of chromosomal and cytoskeletal events, regulation of the spindle assembly checkpoint pathway and cytokinesis to ensure the smooth progression of the cell cycle. Besides their mitotic functions, Aurora kinases are also involved in the regulation of meiosis. Gene amplification/mutation and overexpression of Aurora kinases have been detected in various solid and haematological cancers. In human tumours, Aurora kinases exhibit oncogenic roles associated with their mitotic roles, which drive the cancer cell proliferation and survival. Deregulation of Aurora kinase activity causes failure in centrosome function, spindle assembly, chromosomal alignment, and cytokinesis, eventually resulting in the mitotic abnormalities and genetic instability. These findings emphasize the crucial functions of Aurora kinases in cancer, prompting their recognition as valuable targets for cancer therapy. This review provides an overview of the structures and functions of Aurora kinases and sheds light on their oncogenic roles in cancer.
Computational Fluid Dynamics (CFD) Analysis of Bioprinting
(John Wiley and Sons Inc, 2024) Fareez, Umar Naseef Mohamed; Naqvi, Syed Ali Arsal; Mahmud, Makame; Temirel, Mikail; 0000-0002-8199-0100; AGÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümü; Fareez, Umar Naseef Mohamed; Naqvi, Syed Ali Arsal; Mahmud, Makame; Temirel, Mikail
Regenerative medicine has evolved with the rise of tissue engineering due to advancements in healthcare and technology. In recent years, bioprinting has been an upcoming approach to traditional tissue engineering practices, through the fabrication of functional tissue by its layer-by-layer deposition process. This overcomes challenges such as irregular cell distribution and limited cell density, and it can potentially address organ shortages, increasing transplant options. Bioprinting fully functional organs is a long stretch but the advancement is rapidly growing due to its precision and compatibility with complex geometries. Computational Fluid Dynamics (CFD), a carestone of computer-aided engineering, has been instrumental in assisting bioprinting research and development by cutting costs and saving time. CFD optimizes bioprinting by testing parameters such as shear stress, diffusivity, and cell viability, reducing repetitive experiments and aiding in material selection and bioprinter nozzle design. This review discusses the current application of CFD in bioprinting and its potential to enhance the technology that can contribute to the evolution of regenerative medicine.
Tomatidine, a Steroidal Alkaloid, Synergizes with Cisplatin to Inhibit Cell Viability and Induce Cell Death Selectively on FLT3-ITD+ Acute Myeloid Leukemia Cells
(SPRINGER NATURE Link, 2024) Ayvaz, Havva Berre; Yenigül, Münevver; Gencer Akçok, Emel Başak; 0000-0002-5873-7879; 0000-0003-0468-721X; 0000-0002-6559-9144; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü; Ayvaz, Havva Berre; Yenigül, Münevver; Gencer Akçok, Emel Başak
Background: Acute Myeloid Leukemia (AML) is a hematological cancer that frequently presents with a range of side effects and drug resistance during anticancer drug treatment. The current study aims to achieve increased efficacy by combining lower doses of cisplatin with increasing concentrations of tomatidine in AML cells to increase efficacy. Methods: Anti-proliferative effects of single and combination of cisplatin and tomatidine were assessed via MTT cell viability assay. The Annexin V/Propidium Iodide Double Staining method was used to measure the apoptotic effects of combined tomatidine and cisplatin treatment. Then, Western Blot analysis was performed to measure Poly (ADP-ribose) polymerase (PARP) and Caspase-3 protein expression levels. Results: Cisplatin treatment with lower concentrations displayed high cytotoxic effects on AML cells, compared with tomatidine. The combination of the Inhibitory Concentration (IC) 20 value of cisplatin and increasing doses of tomatidine exhibited a significant decrease in cell viability relative to single treatments. The combination index analysis revealed a mild synergistic effect of cisplatin IC20 and varying tomatidine doses. The apoptosis induced when cisplatin was combined with 500 µM tomatidine by almost 20%, while the percentage of apoptosis in combination with 1 mM tomatidine was measured by 50% for both cell lines. The upregulation of proapoptotic cleaved-PARP (3.2 and 1.08-fold for THP-1 and MOLM-13, respectively) and downregulation in Caspase-3 (0.23 and 0.13-fold for THP-1 and MOLM-13, respectively) was detected. Conclusions: Together, the study indicated that when tomatidine combined with cisplatin on AML cell lines, a combinatorial anti-proliferative and apoptotic effect is observed. The combination of cisplatin with tomatidine may be a promising approach.
Sustainability assessment of denim fabric made of PET fiber and recycled fiber from postconsumer PET bottles using LCA and LCC approach with the EDAS method
(John Wiley and Sons Inc, 2024) Fidan, Fatma Şener; Aydoğan, Emel Kızılkaya; Uzal, Niğmet; 0000-0002-2397-3628; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fidan, Fatma Şener; Uzal, Niğmet
The textile industry is under pressure to adopt sustainable production methods because its contribution to global warming is expected to rise by 50% by 2030. One solution is to increase the use of recycled raw material. The use of recycled raw material must be considered holistically, including its environmental and economic impacts. This study examined eight scenarios for sustainable denim fabric made from recycled polyethylene terephthalate (PET) fiber, conventional PET fiber, and cotton fiber. The evaluation based on the distance from average solution (EDAS) multicriteria decision‐making method was used to rank scenarios according to their environmental and economic impacts, which are assessed using life cycle assessment and life cycle costing. Allocation, a crucial part of evaluating the environmental impact of recycled products, was done using cut‐off and waste value. Life cycle assessments reveal that recycled PET fiber has lower freshwater ecotoxicity and fewer eutrophication and acidification impacts. Cotton outperformed PET fibers in human toxicity. Only the cut‐off method reduces potential global warming with recycled PET. These findings indicated that recycled raw‐material life cycle assessment requires allocation. Life cycle cost analysis revealed that conventional PET is less economically damaging than cotton and recycled PET. The scenarios were ranked by environmental and economic impacts using EDAS. This ranking demonstrated that sustainable denim fabric production must consider both economic and environmental impacts. Integr Environ Assess Manag 2024;20:2347–2365. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Browse

Recent Submissions