ArticleDrug delivery and translational research2023
Nanoparticle pre-treatment for enhancing the survival and activation of pulmonary macrophage transplant.
Article in Drug delivery and translational research, 2023. 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
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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, 6 citations in OpenAlex.
- Nanoparticle-Based Pulmonary Immune Engineering.Annual review of chemical and biomolecular engineering · 2025Review
- Age-dependent changes in phagocytic activity: in vivo response of mouse pulmonary antigen presenting cells to direct lung delivery of charged PEGDA nanoparticles.Journal of nanobiotechnology · 2024Article
- Macrophage variance: investigating how macrophage origin influences responses to soluble and physical cues with immortalized vs. primary cells in 2D and 3D culture.Frontiers in biomaterials science · 2024Article
- Aerosol pulmonary immune engineering.Advanced drug delivery reviews · 2023Review
- Emerging immunotherapeutics for immune activation and tolerance.Drug delivery and translational research · 2023Article
- An Analysis of Monitoring Solutions for CAR T Cell Production.Healthcare technology lettersReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Despite recent clinical successes of chimeric antigen receptor T cell therapies in treating liquid cancers, many lingering challenges stand in the way of therapeutic translation to broader types of malignancies. Macrophages have been proposed as alternatives to T cells given macrophages' advantages in promoting tumor infiltration, acquiring diverse antigens, and possessing the ability to continuously stimulate adaptive responses. However, the poor survival of macrophages upon transplantation in addition to transient anti-tumor phenotypical states have been major obstacles standing in the way of macrophage-based cell therapies. Given recent discoveries of nanoparticle strategies in improving macrophage survival and promoting phenotype retention, we herein report the ability to extend the survival and phenotype of macrophage transplants in murine lungs via pre-treatment with nanoparticles of varying degradation rates. Macrophages pre-treated with 100 µg/ml dose of poly(ethylene glycol) diacrylate nanoparticle formulations improve pulmonary macrophage transplant survival over untreated cells beyond 7 days, where degradable nanoparticle formulations result in over a 50% increase in retention of transplanted cell counts relative to untreated cells. Furthermore, pre-treated macrophages more efficiently retain an imposed pro-inflammatory-like polarization state following transplantation out to 7 days compared to macrophages pre-treated with a classical pro-inflammatory stimulus, interferon-gamma, where CD86 costimulatory molecule expression is greater than 150% higher in pre-treated macrophage transplants compared to untreated counterparts. These findings provide an avenue for a major improvement in the lifespan and efficacy of macrophage-based cell therapies and have broader implications to other phagocyte-based cellular therapeutics and administration routes.
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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.