WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 3Citation - Scopus: 4A Facile Method for Boosting the Graphitic Carbon Nitride's Photocatalytic Activity Based on 0d/2d S-Scheme Heterojunction Nanocomposite Architecture(Elsevier, 2024) Kahraman, Zeynep; Kartal, Uğur; Gent, Aziz; Alp, EmreGraphitic carbon nitride (g-C 3 N 4 ) has received significant interest as a metal -free photocatalyst. The S -scheme photocatalytic system has great potential to improve the charge separation in semiconductor photocatalysts. In this study, we have fabricated non-toxic and low-cost photocatalytic nanocomposites of 0D/2D S -scheme heterojunction composed of iron oxide and graphitic carbon nitride by a facile method. The developed facile method provides a sustainable way with a high atom economy to further enhance the photocatalytic performance of exfoliated g-C 3 N 4 . The 0D -iron oxide/2D-C 3 N 4 exhibited nearly 10 times better than bulk g-C 3 N 4 and almost 60 % better than exfoliated g-C 3 N 4 under simulated solar light irradiation. The experimental results demonstrated that the effective charge -carrier mechanism led to an improved generation of reactive oxygen species (ROSs), resulting in an impressive photocatalytic performance. A serial photocatalytic test was also conducted to understand photocatalytic reaction mechanisms with various scavengers.Article Citation - WoS: 3Citation - Scopus: 3Roadmap on Multifunctional Materials for Drug Delivery(IOP Publishing, 2024) Nottelet, Benjamin; Buwalda, Sytze; van Nostrum, Cornelus F.; Zhao, Xiaofei; Deng, Chao; Zhong, Zhiyuan; Cheah, Ernest; Kehr, Nermin SedaThis Roadmap on drug delivery aims to cover some of the most recent advances in the field of materials for drug delivery systems (DDSs) and emphasizes the role that multifunctional materials play in advancing the performance of modern DDSs in the context of the most current challenges presented. The Roadmap is comprised of multiple sections, each of which introduces the status of the field, the current and future challenges faced, and a perspective of the required advances necessary for biomaterial science to tackle these challenges. It is our hope that this collective vision will contribute to the initiation of conversation and collaboration across all areas of multifunctional materials for DDSs. We stress that this article is not meant to be a fully comprehensive review but rather an up-to-date snapshot of different areas of research, with a minimal number of references that focus upon the very latest research developments.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.Conference 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.Conference Object Development of Novel Nanotoxicity Assessment Method Utilizing 3d Printing System(Elsevier, 2022) Başlar, Muhammet Semih; Öksel Karakuş, Ceyda; Aldemir Dikici, BetülUnique physicochemical properties of nanomaterials (NMs) make them a material of choice in various applications but also raise concerns about their potential toxicity. While the commercial use of nano-enabled materials is growing rapidly, their interaction with biological systems and environment are not yet fully understood [1, 2]. Traditionally, toxicity of nano-sized materials are assessed by 2D cell culture models due to their time and cost-related advantages but their simplicity often comes at the cost of accuracy. While these methods are considered as the first step in toxicological assessment of both nanosized and bulk-form materials, they fall short in mimicking the complexity of in vivo physiological environments.Article Citation - WoS: 69Citation - Scopus: 73Nanoparticle-Protein Corona Complex: Understanding Multiple Interactions Between Environmental Factors, Corona Formation, and Biological Activity(Taylor & Francis, 2021) Öksel Karakuş, Ceyda; Tomak, Aysel; Çeşmeli, Selin; Hanoğlu, Berçem Dilan; Winkler, DavidThe surfaces of pristine nanoparticles become rapidly coated by proteins in biological fluids, forming the so-called protein corona. The corona modifies key physicochemical characteristics of nanoparticle surfaces that modulate its biological and pharmacokinetic activity, biodistribution, and safety. In the two decades since the protein corona was identified, the importance of nano particles surface properties in regulating biological responses have been recognized. However, there is still a lack of clarity about the relationships between physiological conditions and cor ona composition over time, and how this controls biological activities/interactions. Here we review recent progress in characterizing the structure and composition of protein corona as a function of biological fluid and time. We summarize the influence of nanoparticle characteristics on protein corona composition and discuss the relevance of protein corona to the biological activity and fate of nanoparticles. The aim is to provide a critical summary of the key factors that affect protein corona formation (e.g. characteristics of nanoparticles and biological environ ment) and how the corona modulates biological activity, cellular uptake, biodistribution, and drug delivery. In addition to a discussion on the importance of the characterization of protein corona adsorbed on nanoparticle surfaces under conditions that mimic relevant physiological environment, we discuss the unresolved technical issues related to the characterization of nano particle-protein corona complexes during their journey in the body. Lastly, the paper offers a perspective on how the existing nanomaterial toxicity data obtained from in vitro studies should be reconsidered in the light of the presence of a protein corona, and how recent advances in fields, such as proteomics and machine learning can be integrated into the quantitative analysis of protein corona components.