Rapid transport of large polymeric nanoparticles in fresh undiluted human mucus
Open accessAbstract
Nanoparticles larger than the reported mesh-pore size range (10–200 nm) in mucus have been thought to be much too large to undergo rapid diffusional transport through mucus barriers. However, large nanoparticles are preferred for higher drug encapsulation efficiency and the ability to provide sustained delivery of a wider array of drugs. We used high-speed multiple-particle tracking to quantify transport rates of individual polymeric particles of various sizes and surface chemistries in samples of fresh human cervicovaginal mucus. Both the mucin concentration and viscoelastic properties of these cervicovaginal samples are similar to those in many other human mucus secretions. Unexpectedly, we found that large nanoparticles, 500 and 200 nm in diameter, if coated with polyethylene glycol, diffused through mucus with an effective diffusion coefficient ( D eff ) only 4- and 6-fold lower than that for the same particles in water (at time scale τ = 1 s). In contrast, for smaller but otherwise identical 100-nm coated particles, D eff was 200-fold lower in mucus than in water. For uncoated particles 100–500 nm in diameter, D eff was 2,400- to 40,000-fold lower in mucus than in water. Much larger fractions of the 100-nm particles were immobilized or otherwise hindered by mucus than the large 200- to 500-nm particles. Thus, in contrast to the prevailing belief, these results demonstrate that large nanoparticles, if properly coated, can rapidly penetrate physiological human mucus, and they offer the prospect that large nanoparticles can be used for mucosal drug delivery.
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Improved tissue uptake of PEGylated nanoparticles may be attributed to their higher diffusivity through the mucous layer.
“Improved tissue uptake of PEGylated nanoparticles may be attributed to their higher diffusivity through the mucous layer-an observation shown using multiple particle tracking experiments by the Hanes lab 24 .”
From Nanotechnology approaches for global infectious diseases (2021) · cites this paper as [24]
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- Authors
- Lai, S. K., O'Hanlon, D. E., Harrold, S., Man, S. T., Wang, Y.-Y., Cone, R., & Hanes, J.
- Affiliations
- Johns Hopkins University (US)
- Biophysics and
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2007-01-30
- Volume
- 104
- Issue
- 5
- Pages
- 1482-1487
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC1785284
- OpenAlex
- W2102002215
- Cited by
- 1,050
- References
- 63
- Citations by year
- 2026: 50 · 2025: 48 · 2024: 53 · 2023: 52 · 2022: 53 · 2021: 56 · 2020: 78 · 2019: 71 · 2018: 60 · 2017: 68 · 2016: 75 · 2015: 73 · 2014: 66 · 2013: 51 · 2012: 47
- FWCI
- 23.33
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Johns Hopkins University
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Advanced Drug Delivery Systems
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Inhalation and Respiratory Drug Delivery
- Keywords
- polymeric nanoparticles, mucus transport, cervicovaginal mucus, diffusion coefficient, particle size effects, polyethylene glycol coating, mucin, mucus viscoelasticity, particle immobilization, mucosal drug delivery, multiple particle tracking
- MeSH terms
- Biological Transport, Cervix Mucus, Diffusion, Drug Carriers, Female, Humans, Mucus, Particle Size, Polyethylene Glycols, Polymers, Time Factors, Water, Drug Delivery Systems, Nanoparticles
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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