ArticleAdvanced healthcare materials2020
Polymeric Nanoparticles Controlled by On-Chip Self-Assembly Enhance Cancer Treatment Effectiveness.
Article in Advanced healthcare materials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 10 citations in OpenAlex.
- Cutting-edge nanotechnology: unveiling the role of zinc oxide nanoparticles in combating deadly gastrointestinal tumors.Frontiers in bioengineering and biotechnology · 2025Review
- 3D Bioprinting in Cancer Modeling and Biomedicine: From Print Categories to Biological Applications.ACS omega · 2024Review
- Microfluidic-Assisted Production of Gastro-Resistant Active-Targeted Diatomite Nanoparticles for the Local Release of Galunisertib in Metastatic Colorectal Cancer Cells.Advanced healthcare materials · 2023Article
- Brain organoid-on-a-chip: A next-generation human brain avatar for recapitulating human brain physiology and pathology.Biomicrofluidics · 2022Article
- Targeted Cancer Therapy via pH-Functionalized Nanoparticles: A Scoping Review of Methods and Outcomes.Gels (Basel, Switzerland) · 2022Article
- Nanodispersions of Polyelectrolytes Based on Humic Substances: Isolation, Physico-Chemical Characterization and Evaluation of Biological Activity.Pharmaceutics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Nanoparticle (NP)-based drug delivery systems or nanomedicines have broadened the horizon of translational research for decades. Conventional bulk mixing synthesis methods have impeded successful clinical translations of nanomedicines due to the limited ability of the controlled, scalable production with high uniformity. Herein, an on-chip preparation of self-assembled, drug-encapsulated polymeric NPs is presented for their improved uniformity and homogeneity that results in enhanced anti-cancer effect in vitro and in vivo. The NPs are formulated through rapid convective mixing of two aqueous solutions of a hydrophilic polymer and an anti-cancer drug, doxorubicin (DOX), in the swirling microvortex reactor (SMR). Compared to conventional bulk-mixed NPs (BMPs), the microvortex-synthesized NPs (MVPs) exhibit narrower size distributions and better size tunability. It is found that the improved uniformity and homogeneity of the MVPs not only enhance cellular uptake and anti-cancer effect with pH-responsive drug release in vitro, but also result in an improved tumor regression and decreased side effects at off-targeted organs in vivo. The findings demonstrate that uniformly designed NPs with more homogeneous properties can induce a significant enhancement of an anti-cancer effect in vivo. The results show the potential of a high-speed on-chip synthesis as a scalable manufacturing platform for reliable clinical translations of nanomedicines.
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.