MATIJEVIć E. Fine particles in medicine and pharmacy[M]. New York:Springer, 2012:57-100.
|
CHAVALI M S, NIKOLOVA M P. Metal oxide nanoparticles and their applications in nanotechnology[J]. SN applied sciences, 2019, 1(6):607.
|
NAVROTSKY A. Thermochemistry of nanomaterials[J]. Reviews in mineralogy and geochemistry, 2001, 44(1):73-103.
|
CAI X, LIU X, JIANG J, et al. Molecular mechanisms, characterization methods, and utilities of nanoparticle biotransformation in nanosafety assessments[J]. Small, 2020, 16(36):1907663.
|
HOLDER A L, GOTH-GOLDSTEIN R, LUCAS D, et al. Particle-induced artifacts in the MTT and LDH viability assays[J]. Chemical research in toxicology, 2012, 25(9):1885-1892.
|
ANDREESCU S, ORNATSKA M, ERLICHMAN J S, et al. Biomedical applications of metal oxide nanoparticles[J]. Fine particles in medicine and pharmacy, 2012, 2012:57-100.
|
YOUNIS S A, EL-FAWAL E M, SERP P. Nano-wastes and the environment:potential challenges and opportunities of nano-waste management paradigm for greener nanotechnologies[J]. Handbook of environmental materials management, 2018:1-72.
|
AHAMED M, AKHTAR M J, ALHADLAQ H A, et al. Assessment of the lung toxicity of copper oxide nanoparticles:current status[J]. Nanomedicine, 2015, 10(15):2365-2377.
|
YAN X, SEDYKH A, WANG W, et al. In silico profiling nanoparticles:predictive nanomodeling using universal nanodescriptors and various machine learning approaches[J]. Nanoscale, 2019, 11(17):8352-8362.
|
GRASSIAN V H, O'SHAUGHNESSY P T, ADAMCAKOVA-DODD A, et al. Inhalation exposure study of titanium dioxide nanoparticles with a primary particle size of 2 to 5 nm[J]. Environmental health perspectives, 2007, 115(3):397-402.
|
ERLICHMAN J S, LEITER J C. Complexity of the nano-bio interface and the tortuous path of metal oxides in biological systems[J]. Antioxidants, 2021, 10(4):547.
|
GOLBAMAKI A, GOLBAMAKI N, SIZOCHENKO N, et al. Genotoxicity induced by metal oxide nanoparticles:a weight of evidence study and effect of particle surface and electronic properties[J]. Nanotoxicology, 2018, 12(10):1113-1129.
|
SHIN H K, KIM K Y, PARK J W, et al. Use of metal/metal oxide spherical cluster and hydroxyl metal coordination complex for descriptor calculation in development of nanoparticle cytotoxicity classification model[J]. SAR and QSAR in environmental research, 2017, 28(11):875-888.
|
PAL A K, BELLO D, COHEN J, et al. Implications of in vitro dosimetry on toxicological ranking of low aspect ratio engineered nanomaterials[J]. Nanotoxicology, 2015, 9(7):871-885.
|
LIU R, LIU H H, JI Z, et al. Evaluation of toxicity ranking for metal oxide nanoparticles via an in vitro dosimetry model[J]. ACS nano, 2015, 9(9):9303-9313.
|
黄杨,吴雨宣,伍天翔,等.计算毒理学工具解码纳米毒性评估和毒性机理[J].环境化学, 2024.(2024-04-28). https://kns.cnki.net/kcms2
/article/abstract?v=DMKM_QUxZ7BCTazGKhED58GWZZ_5pAF31pxzZQNdLP6w-UBOiyRkjd3rXgGO4cV4BrVbS6ZmQPa5iin0CBdOTtM-YI7MB9pPlphMHz68zKIlGWZuMEzp1F9cHh_OXRktHajEmHgz7FBhMBpC47UYrL_xDxysDwrSZFlEN9UG-93oTLQQ04V3_yU8Nd0Z5oZoKWR&uniplatform=NZKPT&language=CHS. HUANG Y, WU Y X, WU T X, et al. In silico tools in computational toxicology decode risk assessment and mechanism interpretation of nanomaterials[J]. Environmental chemistry, 2024.(2024-04-28). https://kns.cnki.net/kcms2/article/abstract?v=DMKM_QUxZ7BCTaz-GKhED58GWZZ_5pAF31pxzZQNdLP6wUBOiyRkjd3r-XgGO4cV4BrVbS6ZmQPa5iin0CBdOTtMYI7MB9pPlp-hMHz68zKIlGWZuMEzp1F9cHh_OXRktHajEmHgz7FB-hMBpC47UYrL_xDxysDwrSZFlEN9UG93oTLQQ04V3_yU8Nd0Z5oZoKWR&uniplatform=NZKPT&language=CHS.
|
HALAPPANAVAR S, NYMARK P, KRUG H F, et al. Non-animal strategies for toxicity assessment of nanoscale materials:role of adverse outcome pathways in the selection of endpoints[J]. Small, 2021, 17(15):2007628.
|
WANG Z, CHEN J, HONG H. Developing QSAR models with defined applicability domains on PPARγ binding affinity using large data sets and machine learning algorithms[J]. Environmental science&technology, 2021, 55(10):6857-6866.
|
ZHANG H, JI Z, XIA T, et al. Use of metal oxide nanoparticle band gap to develop a predictive paradigm for oxidative stress and acute pulmonary inflammation[J]. ACS nano, 2012, 6(5):4349-4368.
|
YU F, WEI C, DENG P, et al. Deep exploration of random forest model boosts the interpretability of machine learning studies of complicated immune responses and lung burden of nanoparticles[J]. Science advances, 2021, 7(22):4130.
|
徐淑君,李瑞香,伍天翔.工程纳米颗粒生物负荷量的机器学习预测模型[J].环境化学, 2024, 43(10):3406-3415.
|
AHMADI S. Mathematical modeling of cytotoxicity of metal oxide nanoparticles using the index of ideality correlation criteria[J]. Chemosphere, 2020, 242:125192.
|
SHARMA M, NIKOTA J, HALAPPANAVAR S, et al. Predicting pulmonary fibrosis in humans after exposure to multi-walled carbon nanotubes (MWCNTs)[J]. Archives of toxicology, 2016, 90(7):1605-1622.
|
SHATKIN J, ONG K. Alternative testing strategies for nanomaterials:state of the science and considerations for risk analysis[J]. Risk analysis, 2016, 36(8):1564-1580.
|
AREECHEEWAKUL S, ADAMCAKOVA-DODD A, GIVENS B E, et al. Toxicity assessment of metal oxide nanomaterials using in vitro screening and murine acute inhalation studies[J]. NanoImpact, 2020, 18:100214.
|
ZAKHAROV A V, PEACH M L, SITZMANN M, et al. QSAR modeling of imbalanced high-throughput screening data in PubChem[J]. Journal of chemical information and modeling, 2014, 54(3):705-712.
|
IDAKWO G, THANGAPANDIAN S, LUTTRELL J, et al. Structure-activity relationship-based chemical classification of highly imbalanced Tox21 datasets[J]. Journal of cheminformatics, 2020, 12(1):1-19.
|
CHAWLA N V, BOWYER K W, HALL L O, et al. SMOTE:synthetic minority over-sampling technique[J]. Journal of artificial intelligence research, 2002, 16:321-357.
|
ZHU T, LIN Y, LIU Y. Synthetic minority oversampling technique for multiclass imbalance problems[J]. Pattern recognition, 2017, 72:327-340.
|
HOSMER JR D W, LEMESHOW S, STURDIVANT R X. Applied logistic regression[M]//Wiley Series in probability and statistics. John Wiley&Sons, 2013:153-225.
|
ROY K, KAR S, AMBURE P. On a simple approach for determining applicability domain of QSAR models[J]. Chemometrics and intelligent laboratory systems, 2015, 145:22-29.
|
LI M, SUN H, HUANG Y, et al. Shapley value:from cooperative game to explainable artificial intelligence[J]. Autonomous intelligent systems, 2024, 4(1):2-14.
|
DE ALMEIDA M S, SUSNIK E, DRASLER B, et al. Understanding nanoparticle endocytosis to improve targeting strategies in nanomedicine[J]. Chemical society reviews, 2021, 50(9):5397-5434.
|
KHEDER W, SOUMYA S, SAMSUDIN A. Impact of titanium dioxide particle size on macrophage production of intracellular reactive oxygen species[J]. Archives of oral biology, 2021, 127:105133.
|
KUMARI M, RAJAK S, SINGH S P, et al. Repeated oral dose toxicity of iron oxide nanoparticles:biochemical and histopathological alterations in different tissues of rats[J]. Journal of nanoscience and nanotechnology, 2012, 12(3):2149-2159.
|
PETOSA A R, JAISI D P, QUEVEDO I R, et al. Aggregation and deposition of engineered nanomaterials in aquatic environments:role of physicochemical interactions[J]. Environmental science&technology, 2010, 44(17):6532-6549.
|
GEVARIYA D, PRIYA L, MEHTA S, et al. Bio-functional mesoporous silica nanoparticles as nano-structured carriers in cancer theranostic review on recent advancements[J]. Current drug targets, 2023, 24(12):934-944.
|
肖九逸.具有降低毒性的介孔二氧化硅纳米棒用于精确癌症治疗[J].科学, 2017, 69(6):21-29.
XIAO J Y. Mesoporous silica nanorods with reduced toxicity for precise cancer treatment[J]. Science, 2017, 69(6):21.
|
HUANG Y, LI X, CAO J, et al. Use of dissociation degree in lysosomes to predict metal oxide nanoparticle toxicity in immune cells:machine learning boosts nano-safety assessment[J]. Environment international, 2022, 164:107258.
|