Bilgi, Eyüp
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Bilgi, E
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03.01. Department of Bioengineering
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Former Staff
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Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
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3GOOD HEALTH AND WELL-BEING
5
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4QUALITY EDUCATION
1
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5GENDER EQUALITY
0
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6CLEAN WATER AND SANITATION
0
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7AFFORDABLE AND CLEAN ENERGY
2
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8DECENT WORK AND ECONOMIC GROWTH
1
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
0
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
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13CLIMATE ACTION
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14LIFE BELOW WATER
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Scholarly Output
12
Articles
8
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20330/1926
Supervised MSc Theses
0
Supervised PhD Theses
1
WoS Citation Count
103
Scopus Citation Count
114
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0
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0
WoS Citations per Publication
8.58
Scopus Citations per Publication
9.50
Open Access Source
5
Supervised Theses
1
| Journal | Count |
|---|---|
| Planta Medica | 2 |
| Biomedical Microdevices | 1 |
| Cellulose | 1 |
| International Archives of Allergy and Immunology | 1 |
| Journal of Drug Targeting | 1 |
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12 results
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Now showing 1 - 10 of 12
Conference Object Induction of Secondary Metabolism of Marine Derived Streptomyces Cacaoi(Georg Thieme Verlag, 2019) Gezer, Erkin; Bilgi, Eyüp; Küçüksolak, Melis; Bedir, ErdalMicrobial natural products have an adaptive role as signal molecules or defense tools in ecological interactions. Biosynthesis of these molecules is suppressed in standard laboratory conditions where there are no ecological triggers. Thus, only a portion of the chemical diversity of a microbial strain is discovered by standard fermentation protocols. However, using different fermentation conditions or different approaches such as co-culture, biosynthesis of these suppressed molecules can be triggered, and new natural products can be isolated.Article Citation - WoS: 19Citation - Scopus: 21Bacterial Cellulose Based Facial Mask With Antioxidant Property and High Moisturizing Capacity(Springer, 2021) Bilgi, Eyüp; Homan Gökçe, Evren; Bayır, Ece; Şendemir, Aylin; Özgen Özer, Kevser; Hames Tuna, Elif EsinBacterial cellulose (BC) produced by certain bacteria has the potential to be used in many different areas. Despite its advantageous properties compared to plant cellulose, such as high purity, mechanical strength, nanofiber mesh structure, and high-water holding capacity, its production through a biotechnological process prevents it from competing with plant counterparts in terms of cost-effectiveness. Therefore, studies have focused on the development of culture media with cost-effective BC production methods and the production of high value-added products from BC. In this study, it was aimed to develop a taurine-loaded moisturizing facial mask with antioxidant properties based on BC's high-water retention and chemical retention capacity. BC facial mask samples were characterized by Scanning Electron Microscopy (SEM) imaging, Fourier Transform Infrared (FTIR) Spectroscopy, Differential Scanning Calorimetry (DSC), Liquid Chromatography-Mass spectrometry (LC-MS), microbial and mechanical stability tests, as well as cytotoxicity tests. According to our results, produced facial mask samples did not show any cytotoxic effect on human keratinocyte (HS2) or mouse fibroblast (L-929) cell lines; it has high thermal stability, which makes it suitable for different sterilization techniques including sterilization by heat treatment. Taurine release (over 2 mu g/mL in 5 min) and microbial stability tests (no bacterial growth observed) of packaged products kept at 40 and 25 degrees C for 6 months have shown that the product preserves its characteristics for a long time. In conclusion bacterial cellulose-based facial masks are suitable for use as a facial mask, and they can be used for moisturizing and antioxidant properties by means of taurine.Article Citation - WoS: 37Citation - Scopus: 40Biomedical Nanomaterials: Applications, Toxicological Concerns, and Regulatory Needs(Informa Healthcare, 2020) Öksel Karakuş, Ceyda; Bilgi, Eyüp; Winkler, DavidAdvances in cutting-edge technologies such as nano- and biotechnology have created an opportunity for re-engineering existing materials and generating new nano-scale products that can function beyond the limits of conventional ones. While the step change in the properties and functionalities of these new materials opens up new possibilities for a broad range of applications, it also calls for structural modifications to existing safety assessment processes that are primarily focused on bulk material properties. Decades after the need to modify existing risk management practices to include nano-specific behaviors and exposure pathways was recognized, relevant policies for evaluating, and controlling health risks of nano-enabled materials is still lacking. This review provides an overview of current progress in the field of nanobiotechnology rather than intentions and aspirations, summarizes long-recognized but still unresolved issues surrounding materials safety at the nanoscale, and discusses key barriers preventing generation and integration of reliable data in bio/nano-safety domain. Particular attention is given to nanostructured materials that are commonly used in biomedical applications. © 2020 Informa UK Limited, trading as Taylor & Francis Group.Article Citation - WoS: 13Citation - Scopus: 17Machine Learning-Assisted Prediction of the Toxicity of Silver Nanoparticles: a Meta-Analysis(Springer, 2023) Bilgi, Eyüp; Öksel Karakuş, CeydaSilver nanoparticles are likely to be more dangerous than other forms of silver due to the intracellular release of silver ions upon dissolution and the formation of mixed ion-containing complexes. Such concerns have resulted in an ever-growing pile of scientific evaluations addressing the safety aspects of nanosilver with widely varying methodological approaches. The substantial differences in the conduct/design of nanotoxicity screening have led to the generation of conflicting findings that may be accurate in their narrative but fail to provide a complete picture. One strategy to maximize the use of individual risk assessments with potentially biased estimates of toxicological effects is to homogenize results across several studies and to increase the generalizability and human relevance of their findings. Here, we collected a large pool of data (n=162 independent studies) on the cytotoxicity of nanosilver and unrevealed potential triggers of toxicity. Two different machine learning approaches, decision tree (DT) and artificial neural network (ANN), were primarily employed to develop models that can predict the cytotoxic potential of nanosilver based on material- and assay-related parameters. Other machine learning algorithms (logistic regression, Gaussian Naive Bayes, k-nearest neighbor, and random forest classifiers) were also applied. Among several attributes compared, exposure concentration, duration, zeta potential, particle size, and coating were found to have the most substantial impact on nanotoxicity, with biomolecule- and microorganism-assisted surface modifications having the most beneficial and detrimental effects on cell survival, respectively. Such machine learning-assisted efforts are critical to developing commercially viable and safe nanosilver-containing products in the ever-expanding nanobiomaterial market.Article Citation - WoS: 1Citation - Scopus: 1Exploring the Heterogeneity of Ige-Mediated Food Allergy Through Latent Class Analysis(S. Karger AG, 2022) Akarsu, Ayşegül; Öksel Karakuş, Ceyda; Ocak, Melike; Oral, Nihan; Bilgi, Eyüp; Şahiner, Ümit Murat; Soyer, Özge; Şekerel, Bülent EnisIntroduction: Food allergy (FA) is a heterogeneous disease with multiple morbidities and a huge burden for patients and healthcare systems. Variable manifestations, comorbidities (atopic dermatitis [AD], asthma, and/or allergic rhinitis [AR]), severity (anaphylaxis), and outcomes suggest the existence of different endotypes that cluster analyses may reveal. In this study, we aimed to investigate distinct subgroups among patients with FAs using data from 524 children/adolescents. Methods: 524 patients with IgE-mediated FA (353 male [67%]; median age 4.4 years [IQR:3.0-6.8]), 354 (68%) had multiple FA. The history of AD, asthma, AR, and anaphylaxis was recorded in 59.4%, 35.5%, 24.2%, and 51.2% of the patients, respectively. Latent class analysis was carried out to distinguish clinical FA phenotypes using five potential markers of allergy severity (single/multiple FA, never/inactive/current asthma and AD, AR, and anaphylaxis). Results: Three distinct phenotypes were identified: (1) multiple FA with eczema and respiratory multimorbidity (42%), (2) multiple FA with persistent eczema (34%), and (3) single FA with respiratory multimorbidity without eczema (24%). Compared with the single FA cluster, the prevalence of AD was significantly higher in multiple FA groups. Cluster 1 had the highest frequency of AR and allergic asthma, and the lowest rate of total tolerance of FA. Discussion: We put forward the hypothesis of underlying pathogenesis according to the clinical phenotypes. While skin barrier defect may play a dominant role in the pathogenesis in Cluster 2, immune dysregulation may be dominant in Cluster 3. In Cluster 1, the most severe group, a combination of both skin barrier defects and immune dysregulation may be responsible for the clinical features.Article Citation - WoS: 5Citation - Scopus: 4Identifying Factors Controlling Cellular Uptake of Gold Nanoparticles by Machine Learning(TAYLOR & FRANCIS LTD, 2023) Bilgi, Eyüp; Winkler, David A.; Öksel Karakuş, CeydaThere is strong interest to improve the therapeutic potential of gold nanoparticles (GNPs) while ensuring their safe development. The utility of GNPs in medicine requires a molecular-level understanding of how GNPs interact with biological systems. Despite considerable research efforts devoted to monitoring the internalisation of GNPs, there is still insufficient understanding of the factors responsible for the variability in GNP uptake in different cell types. Data-driven models are useful for identifying the sources of this variability. Here, we trained multiple machine learning models on 2077 data points for 193 individual nanoparticles from 59 independent studies to predict cellular uptake level of GNPs and compared different algorithms for their efficacies of prediction. The five ensemble learners (Xgboost, random forest, bootstrap aggregation, gradient boosting, light gradient boosting machine) made the best predictions of GNP uptake, accounting for 80-90% of the variance in the test data. The models identified particle size, zeta potential, GNP concentration and exposure duration as the most important drivers of cellular uptake. We expect this proof-of-concept study will foster the more effective use of accumulated cellular uptake data for GNPs and minimise any methodological bias in individual studies that may lead to under- or over-estimation of cellular internalisation rates.Article Citation - WoS: 5Citation - Scopus: 7Five New Cardenolides Transformed From Oleandrin and Nerigoside by Alternaria Eureka 1e1bl1 and Phaeosphaeriasp. 1e4cs-1 and Their Cytotoxic Activities(Elsevier Ltd., 2021) Karakoyun, Çiğdem; Küçüksolak, Melis; Bilgi, Eyüp; Doğan, Gamze; Çömlekçi, Yiğit Ege; Bedir, ErdalBiotransformation of oleandrin (1) and nerigoside (2) by endophytic fungi; Alternaria eureka 1E1BL1 and Phaeospheria sp. 1E4CS-1, has led to the isolation of five new metabolites (3, 5, 6, 7 and 8) together with a known compound (4). The structures of the biotransformation products were elucidated by 1D-, 2D NMR and HR-MS. Phaeospheria sp. mainly provided monooxygenation reactions on the A and B rings, whereas A. eureka afforded both monooxygenated and desacetylated derivatives of the substrates. Cytotoxic activity of the compounds was tested against a non-cancerous (HEK-293) and four cancer (PANC-1, MIA PaCa-2, DU 145 and A549) cell lines by MTT cell viability assay. All compounds were less cytotoxic than oleandrin, which had IC50 values ranging between 2.7 and 41.9 nM. Two of the monohydroxylated metabolites, viz. 7(?)-hydroxy oleandrin (3) and 1(?)-hydroxy oleandrin (7), were also potent with IC50 values from 18.45 to 39.0 nM, while desacetylated + monohydroxylated, or dihydroxylated products had much lower cytotoxicity. Additionally, the lesser activity of 2 and its metabolite (6) possessing diginose as sugar residue inferred that oleandrose moiety is important for the toxicity of oleandrin as well as hydrophobicity of the steroid core. © 2020 Phytochemical Society of EuropeConference Object Computational Nanotoxicology: a Case Study With Silver and Zinc Nanomaterials(Elsevier, 2022) Bilgi, Eyüp; Öksel Karakuş, CeydaNanomaterials (NMs) have been the focus of basic and applied research for more than two decades. According to the updated consumer materials inventory, over 1800 commercial NMs have taken their place in the market, 42% of which are in health and wellness category1. The widespread use of NMs in health-related products made not only the human exposure to the (residues of) NMs inevitable but also the long-recognized concerns over their safety a priority. Despite this pressing need, more than 70% of commercially available nano-containing products do not include sufficient information about their physicochemical and/or toxicological characteristics.Review Citation - WoS: 23Citation - Scopus: 24Microfluidic-Based Technologies for Diagnosis, Prevention, and Treatment of Covid-19: Recent Advances and Future Directions(Springer, 2023) Tarım, Ergün Alperay; Anıl İnevi, Müge; Özkan, İlayda; Keçili, Seren; Bilgi, Eyüp; Başlar, Muhammet Semih; Özçivici, Engin; Öksel Karakuş, Ceyda; Tekin, Hüseyin CumhurThe COVID-19 pandemic has posed significant challenges to existing healthcare systems around the world. The urgent need for the development of diagnostic and therapeutic strategies for COVID-19 has boomed the demand for new technologies that can improve current healthcare approaches, moving towards more advanced, digitalized, personalized, and patient-oriented systems. Microfluidic-based technologies involve the miniaturization of large-scale devices and laboratory-based procedures, enabling complex chemical and biological operations that are conventionally performed at the macro-scale to be carried out on the microscale or less. The advantages microfluidic systems offer such as rapid, low-cost, accurate, and on-site solutions make these tools extremely useful and effective in the fight against COVID-19. In particular, microfluidic-assisted systems are of great interest in different COVID-19-related domains, varying from direct and indirect detection of COVID-19 infections to drug and vaccine discovery and their targeted delivery. Here, we review recent advances in the use of microfluidic platforms to diagnose, treat or prevent COVID-19. We start by summarizing recent microfluidic-based diagnostic solutions applicable to COVID-19. We then highlight the key roles microfluidics play in developing COVID-19 vaccines and testing how vaccine candidates perform, with a focus on RNA-delivery technologies and nano-carriers. Next, microfluidic-based efforts devoted to assessing the efficacy of potential COVID-19 drugs, either repurposed or new, and their targeted delivery to infected sites are summarized. We conclude by providing future perspectives and research directions that are critical to effectively prevent or respond to future pandemics.Doctoral Thesis Development of Computational Models To Predict the Toxicity of Advanced Materials(01. Izmir Institute of Technology, 2023) Bilgi, Eyüp; Karakuş, Ceyda Öksel; Bedir, ErdalThe aim of this study is to harness computational power to enhance existing knowledge on NM safety and to optimize the use of existing nanotoxicity data. The primary goal is to support the safe(r)-by-design concept, necessitating early integration of safety considerations into NM design through structural manipulation strategies. This thesis focuses on three case studies: zinc oxide, silver, and gold NP, using data manually collected from the literature. Analyses with zinc oxide and silver NP revealed a correlation between their toxicity and both internal (intrinsic properties, size, shape, surface charge) and external (cell and analysis-related properties) factors. For zinc oxide, it was found that coating had significant influence on cell viability, with a critical threshold identified at 20 µg/ml concentration and 10 nm size. Similarly, for silver NPs, concentration, size, and exposure time were significant factors. Coating with organic macromolecules increased cell viability, whereas green-synthesized NPs (using bacteria, plant extracts, algae) decreased it. The gold NP study highlighted that ensemble methods were more effective in elucidating complex relationships, with cellular uptake linked to particle size, zeta potential, concentration, and exposure time. Overall, this thesis contributes to safer-by-design strategies, crucial for developing commercially viable and safe NMs. The findings advocate for a broader toxicity evaluation approach, considering various physicochemical aspects and experimental procedures. The complex interactions observed suggest that advanced algorithms are necessary for accurate modeling, supporting the optimization of experimental parameters in NP engineering for biomedical applications.