An organotypic model of high-grade serous ovarian cancer to test the anti-metastatic potential of ROR2 targeted Polyion complex nanoparticles

Q: How does OCRA curate its research paper database?

OCRA indexes peer-reviewed papers from PubMed and CrossRef, enriched with MeSH terms, author profiles, and citation metrics. Papers are categorized by cancer type, research method, and clinical relevance.

Q: Can I search papers by MeSH term or author?

Yes. Use the search bar to filter papers by MeSH term, author name, journal, keyword, or cancer type. Each paper includes linked MeSH terms and author profiles for further exploration.

Q: How current is the paper database?

The database is updated regularly through automated ingestion from PubMed and CrossRef. Most papers appear within days of their PubMed indexing date.

Dongli Liu; Kristie-Ann Dickson; Martina H. Stenzel

doi:10.1039/d1tb01837j

An organotypic model of high-grade serous ovarian cancer to test the anti-metastatic potential of ROR2 targeted Polyion complex nanoparticles

Dongli Liu & Martina H. Stenzel et al. · 2021-11-17

A 3D co-cultured organotypic cancer model to evaluate the anti-metastatic ability of siRNA loaded BSA decorated PICs nanoparticles has been developed.

An organotypic model of high-grade serous ovarian cancer to test the anti-metastatic potential of ROR2 targeted Polyion complex nanoparticles

Links

Journal

Institutions

Authors

Funding