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Updated: Dec 3, 2025

Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination
Published on: April 29, 2015
Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence
Ruihong Feng1, Fubo Yu1, Jing Xu1
1Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
Abstract:
Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gaps remain to be filled prior to clinical applications (e.g., immunotherapy). The lack of databases on interactions between the immune system and NMs affects the discovery of new NMs for immunotherapy. Complement activation and inhibition by NMs have been widely studied, but the general rules remain unclear. Biomimetic nanocoating to promote the clearance of NMs by the immune system is an alternative strategy for the immune response mediation of the biological corona. Immune response predictions based on NM properties can facilitate the design of NMs for immunotherapy, and artificial intelligences deserve much attention in the field. This review addresses the knowledge gaps regarding immune response and immunotherapy in relation to NMs, effective immunotherapy and material design without adverse immune responses.
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