ReviewCurrent opinion in pharmacology2013
Porous silicon advances in drug delivery and immunotherapy.
Review in Current opinion in pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Regional immune mechanisms enhance efficacy of an autologous cellular cancer vaccine with intraperitoneal administration.Oncoimmunology · 2024Article
- Engineered tumor cell-derived vaccines against cancer: The art of combating poison with poison.Bioactive materials · 2023Review
- Particle-Based therapies for antigen specific treatment of type 1 diabetes.International journal of pharmaceutics · 2023Review
- Recent Developments in Porous Silicon Nanovectors with Various Imaging Modalities in the Framework of Theranostics.ChemMedChem · 2022Review
- Cancer vaccines from cryogenically silicified tumour cells functionalized with pathogen-associated molecular patterns.Nature biomedical engineering · 2022Article
- Embracing nanomaterials' interactions with the innate immune system.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2021Review
- Co-localization and confinement of ecto-nucleotidases modulate extracellular adenosine nucleotide distributions.PLoS computational biology · 2020Article
- Porous Si Microparticles Infiltrated with Magnetic Nanospheres.Nanomaterials (Basel, Switzerland) · 2020Article
- Site-SpecificPharmaceutics · 2019Article
- Systematic comparison of methods for determining the in vivo biodistribution of porous nanostructured injectable inorganic particles.Acta biomaterialia · 2019Article
- Mesoporous Silicon Particles Favor the Induction of Long-Lived Humoral Responses in Mice to a Peptide-Based Vaccine.Materials (Basel, Switzerland) · 2018Article
- Porous Silicon and Polymer Nanocomposites for Delivery of Peptide Nucleic Acids as Anti-MicroRNA Therapies.Advanced materials (Deerfield Beach, Fla.) · 2016Article
- Article
- Cefazolin-loaded mesoporous silicon microparticles show sustained bactericidal effect against Staphylococcus aureus.Journal of tissue engineering · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Biomedical applications of porous silicon include drug delivery, imaging, diagnostics and immunotherapy. This review summarizes new silicon particle fabrication techniques, dynamics of cellular transport, advances in the multistage vector approach to drug delivery, and the use of porous silicon as immune adjuvants. Recent findings support superior therapeutic efficacy of the multistage vector approach over single particle drug delivery systems in mouse models of ovarian and breast cancer. With respect to vaccine development, multivalent presentation of pathogen-associated molecular patterns on the particle surface creates powerful platforms for immunotherapy, with the porous matrix able to carry both antigens and immune modulators.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.