ArticleChemical communications (Cambridge, England)2015
Gene delivery polymer structure-function relationships elucidated via principal component analysis.
Article in Chemical communications (Cambridge, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Polymeric Vehicles for Nucleic Acid Delivery: Enhancing the Therapeutic Efficacy and Cellular Uptake.Recent advances in drug delivery and formulation · 2024Review
- Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows.ACS polymers Au · 2023Review
- Machine learning guided structure function predictions enable in silico nanoparticle screening for polymeric gene delivery.Acta biomaterialia · 2022Article
- Nonviral delivery systems for antisense oligonucleotide therapeutics.Biomaterials research · 2022Review
- Advances in the polymeric delivery of nucleic acid vaccines.Theranostics · 2022Review
- High-throughput evaluation of polymeric nanoparticles for tissue-targeted gene expression using barcoded plasmid DNA.Journal of controlled release : official journal of the Controlled Release Society · 2021Article
- Automation and data-driven design of polymer therapeutics.Advanced drug delivery reviews · 2021Review
- Optimisation and feature selection of poly-beta-amino-ester as a drug delivery system for cartilage.Journal of materials chemistry. B · 2020Article
- Polymeric vehicles for nucleic acid delivery.Advanced drug delivery reviews · 2020Review
- Engineering DNA vaccines against infectious diseases.Acta biomaterialia · 2018Review
- Polymeric nanoparticles as cancer-specific DNA delivery vectors to human hepatocellular carcinoma.Journal of controlled release : official journal of the Controlled Release Society · 2017Article
- Gene delivery nanoparticles to modulate angiogenesis.Advanced drug delivery reviews · 2017Review
- Influence of Substituent Chain Branching on the Transfection Efficacy of Cyclopropenium-Based Polymers.Polymers · 2017Article
- Article
- Quantification of cellular and nuclear uptake rates of polymeric gene delivery nanoparticles and DNA plasmids via flow cytometry.Acta biomaterialia · 2016Article
- Exploring the role of polymer structure on intracellular nucleic acid delivery via polymeric nanoparticles.Journal of controlled release : official journal of the Controlled Release Society · 2015Review
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
Principal component analysis was applied to a biomaterial library of poly(beta-amino ester)s, useful for non-viral gene delivery, to elucidate chemical parameters that drive biological function. Correlative relationships and principal components were analyzed between 24 physico-chemical polymer properties and 3 cell-based functional variables in human glioblastoma cells (transfection, uptake, and viability).
Indexed as
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.