Ahmadi Amirsadra, Sokunbi Moses, Patel Trisha, Chang Ming-Wei, Ahmad Zeeshan, Singh Neenu
Leicester School of Allied Health Sciences, De Montfort University, The Gateway, Leicester LE1 9BH, UK.
Nanotechnology and Integrated Bioengineering Centre, Jordanstown Campus, University of Ulster, Newtownabbey BT37 0QB, UK.
Nanomaterials (Basel). 2022 Jun 11;12(12):2016. doi: 10.3390/nano12122016.
Mesoporous Silica Nanoparticles (MSNs) have received increasing attention in biomedical applications due to their tuneable pore size, surface area, size, surface chemistry, and thermal stability. The biocompatibility of MSNs, although generally believed to be satisfactory, is unclear. Physicochemical properties of MSNs, such as diameter size, morphology, and surface charge, control their biological interactions and toxicity. Experimental conditions also play an essential role in influencing toxicological results. Therefore, the present study includes studies from the last five years to statistically analyse the effect of various physicochemical features on MSN-induced in-vitro cytotoxicity profiles. Due to non-normally distributed data and the presence of outliers, a Kruskal-Wallis H test was conducted on different physicochemical characteristics, including diameter sizes, zeta-potential measurements, and functionalisation of MSNs, based on the viability results, and statistical differences were obtained. Subsequently, pairwise comparisons were performed using Dunn's procedure with a Bonferroni correction for multiple comparisons. Other experimental parameters, such as type of cell line used, cell viability measurement assay, and incubation time, were also explored and analysed for statistically significant results.
介孔二氧化硅纳米颗粒（MSNs）因其可调节的孔径、表面积、尺寸、表面化学性质和热稳定性，在生物医学应用中受到越来越多的关注。尽管人们普遍认为MSNs的生物相容性令人满意，但其仍不明确。MSNs的物理化学性质，如直径大小、形态和表面电荷，控制着它们的生物相互作用和毒性。实验条件在影响毒理学结果方面也起着至关重要的作用。因此，本研究纳入了过去五年的研究，以统计分析各种物理化学特征对MSN诱导的体外细胞毒性概况的影响。由于数据呈非正态分布且存在异常值，基于活力结果，对不同的物理化学特征，包括直径大小、zeta电位测量和MSNs的功能化，进行了Kruskal-Wallis H检验，并获得了统计学差异。随后，使用Dunn程序进行两两比较，并采用Bonferroni校正进行多重比较。还对其他实验参数，如所用细胞系的类型、细胞活力测量方法和孵育时间，进行了探索和分析，以获得具有统计学意义的结果。
