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For: Meneses J, González-Durruthy M, Fernandez-de-Gortari E, Toropova AP, Toropov AA, Alfaro-Moreno E. A Nano-QSTR model to predict nano-cytotoxicity: an approach using human lung cells data. Part Fibre Toxicol 2023;20:21. [PMID: 37211608 DOI: 10.1186/s12989-023-00530-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 05/01/2023] [Indexed: 05/23/2023]  Open
Number Cited by Other Article(s)
1
Qi Q, Wang Z. Machine learning-based models to predict aquatic ecological risk for engineered nanoparticles: using hazard concentration for 5% of species as an endpoint. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024;31:25114-25128. [PMID: 38467999 DOI: 10.1007/s11356-024-32723-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/27/2024] [Indexed: 03/13/2024]
2
Feng X, Shi Y, Zhang Y, Lei F, Ren R, Tang X. Opportunities and Challenges for Inhalable Nanomedicine Formulations in Respiratory Diseases: A Review. Int J Nanomedicine 2024;19:1509-1538. [PMID: 38384321 PMCID: PMC10880554 DOI: 10.2147/ijn.s446919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/24/2024] [Indexed: 02/23/2024]  Open
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