PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7645
Browse
2 results
Search Results
Article Citation - WoS: 2Citation - Scopus: 2Tuning Toxicity Profiles of Graphene Oxide Through Imidazole-Oxime Modification: Zebrafish as a Model System(Oxford Univ Press, 2025) Yildirim, Serkan; Kokturk, Mine; Yigit, Aybek; Sahin, Ayse; Kiliclioglu, Metin; Atamanalp, Muhammed; Alak, Gonca; 01. Izmir Institute of TechnologyThe increasing use of nanotechnology, especially in agriculture and the food industry, has raised concerns about the possible adverse effects of nanomaterials (NMs) on human health and the environment. This study investigates the effects of synthesized graphene oxide (GO) and its derivatives on zebrafish exposed for 96 hr, focusing on morphological changes in brain tissue, histopathology, and immunofluorescent markers such as 8-hydroxy-2'-deoxyguanosine (8-OHdG) and nucleolar protein 10 (NOP10). Exposure to GO resulted in malformations, DNA damage, and increased NOP10 expression, and it reduced hatching and survival rates. Our results demonstrated that exposure to GO, graphene oxide-oxime (GO-OX), and OX exerted dose-dependent inhibitory effects on hatching and promoted malformations in zebrafish larvae. Histopathological analysis revealed that higher doses led to more pronounced tissue damage, with GO 50 causing severe degeneration and necrosis, while high doses of GO-OX and OX resulted in moderate tissue changes. This was further supported by the increased expression levels of 8-OHdG (marker of oxidative DNA damage) and NOP10 (marker of nucleolar stress), which aligns with the histopathological findings and confirms the neurotoxic effects. Notably, GO-OX treatments consistently mitigated both morphological and neurotoxic effects at all doses, suggesting that oxime functionalization reduces the inherent toxicity of GO. In contrast, treatment with different concentrations of GO-OX derivatives mitigated these adverse effects, reducing them to mild or moderate levels.Article Citation - WoS: 5Citation - Scopus: 4Identifying Factors Controlling Cellular Uptake of Gold Nanoparticles by Machine Learning(TAYLOR & FRANCIS LTD, 2023) Bilgi, Eyüp; Bilgi, Eyüp; Öksel Karakuş, Ceyda; 03.01. Department of Bioengineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThere 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.