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: 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.Review Citation - WoS: 69Nanoparticle-Protein Corona Complex: Understanding Multiple Interactions Between Environmental Factors, Corona Formation, and Biological Activity(TAYLOR & FRANCIS LTD, 2021) Tomak, Aysel; Tomak, Aysel; Çesmeli, Selin; Öksel Karakuş, Ceyda; Hanoglu, Bercem D.; Winkler, David; Oksel Karakus, CeydaThe 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 nanoparticles surface properties in regulating biological responses have been recognized. However, there is still a lack of clarity about the relationships between physiological conditions and corona 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 environment) 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 nanoparticle-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.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: 4Citation - Scopus: 4Optimizing the Dispersion of Calcium Phosphate Nanoparticles for Cellular Studies Using Statistical Design of Experiments(Elsevier, 2023) Önder, Anıl Can; Tomak, Aysel; Öksel Karakuş, CeydaThe in vitro experimentation of ceramic nanoparticles often requires their dispersion in liquid media without causing particle clumps or deteriorating sample integrity. However, the dispersion of nanoparticles using the available protocols rarely leads to stable and uniform dispersions which, in turn, raises concerns about the validity, repeatability and comparability of the findings observed in vitro. Moreover, the ability to control the final dispersion quality of ceramic nanoparticles is an essential step to obtaining optimized nanoceramic materials with desired functionality and to enhancing their performance in subsequent applications. While the need to have a comprehensive guideline for the dispersion of nanoparticles has led to several published documents and protocols, the dispersion methodology of ceramic nanoparticles and the relative contribution of the experimental parameters to the quality of resulting dispersion are still not clear. Here, we employed the statistical design of experiment (DoE) approach to systematically assess the magnitude and source of variation in dispersion quality of two different ceramic nanoparticles, hydroxyapatite and tricalcium phosphate. Using the first-order Plackett-Burman Design (PBD), nanoparticle concentration, pH and the presence of an additive were identified as the most critical factors influencing the resulting hydrodynamic size and zeta potential of the ceramic nanoparticles. Optimization using a second-order Central Composite Design (CCD) yielded a set of quadratic regression equations that were used to predict the hydrodynamic size or zeta potential of ceramic nanoparticles with high accuracy (R2, 0.88–0.92). The results of PBD screening and CCD optimization experiments were employed to prepare nanoparticle dispersions of different quality, which were then used to compare the effect of aggregation on the viability of human osteosarcoma (SaOS-2) cells. Overall, the results of this study provided insight into the role that various experimental parameters play in the colloidal stability and dispersion of ceramic nanoparticles. © 2023Article Citation - WoS: 10Citation - Scopus: 13Overcoming Roadblocks in Computational Roadmaps To the Future for Safe Nanotechnology(IOP Publishing, 2021) Öksel Karakuş, Ceyda; Winkler, David A.The rapid rise of nanotechnology has resulted in a parallel rise in the number of products containing nanomaterials. The unusual properties that nano forms of materials exhibit relative to the bulk has driven intense research interest and relatively rapid adoption by industry. Regulatory agencies are charged with protecting workers, the public, and the environment from any adverse effects of nanomaterials that may also arise because of these novel physical and chemical properties. They need data and models that allow them to flag nanomaterials that may be of concern, while balancing potential stifling of commercial innovation. Roadmaps for the future of safe nanotechnology were defined more than a decade ago, but many roadblocks identified in these studies remain. Here, we discuss the roadblocks that are still hindering the effective application of informatics and predictive computational nanotoxicology methods from providing more effective guidance to nanomaterials regulatory agencies and safe-by-design rationale for industry. We describe how developments in high throughput synthesis, characterization, and biological assessment of nanomaterials will overcome many of these roadblocks, allowing a clearly defined roadmap for computational design of effective but safe-by-design nanomaterials to be realized.