The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Optical tweezers reveal relationship between microstructure and nanoparticle penetration of pulmonary mucus
Open accessAbstract
In this study, the mobility of nanoparticles in mucus and similar hydrogels as model systems was assessed to elucidate the link between microscopic diffusion behavior and macroscopic penetration of such gels. Differences in particle adhesion to mucus components were strongly dependent on particle coating. Particles coated with 2 kDa PEG exhibited a decreased adhesion to mucus components, whereas chitosan strongly increased the adhesion. Despite such mucoinert properties of PEG, magnetic nanoparticles of both coatings did not penetrate through native respiratory mucus, resisting high magnetic forces (even for several hours). However, model hydrogels were, indeed, penetrated by both particles in dependency of particle coating, obeying the theory of particle mobility in an external force field. Comparison of penetration data with cryogenic scanning EM images of mucus and the applied model systems suggested particularly high rigidity of the mucin scaffold and a broad pore size distribution in mucus as reasons for the observed particle immobilization. Active probing of the rigidity of mucus and model gels with optical tweezers was used in this context to confirm such properties of mucus on the microscale, thus presenting the missing link between micro- and macroscopical observations. Because of high heterogeneity in the size of the voids and pores in mucus, on small scales, particle mobility will depend on adhesive or inert properties. However, particle translocation over distances larger than a few micrometers is restricted by highly rigid structures within the mucus mesh.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Filipe, V., Hawe, A., & Jiskoot, W. (2010) · Pharmaceutical Research · doi:10.1007/s11095-010-0073-2 · Cited by 1,885
The basics and underlying mechanisms of mucoadhesion
SMART, J. (2005) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2005.07.001 · Cited by 1,167
Rapid transport of large polymeric nanoparticles in fresh undiluted human mucus
Lai, S. K., O'Hanlon, D. E., Harrold, S., Man, S. T., Wang, Y.-Y., Cone, R., & Hanes, J. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0608611104 · Cited by 1,050
Biological hydrogels as selective diffusion barriers
Lieleg, O., & Ribbeck, K. (2011) · Trends in Cell Biology · doi:10.1016/j.tcb.2011.06.002 · Cited by 387 · cited 2×
“Current studies in this field either focus on pore size as limiting factor (10, 11) or suggest the more complex interaction filtering of mucus rather than size exclusion effects (6).”
Background
Cited by
Physicochemical properties of mucus and their impact on transmucosal drug delivery
Leal, J., Smyth, H. D. C., & Ghosh, D. (2017) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2017.09.018 · Cited by 560
Wu, Z., Li, L., Yang, Y., Hu, P., Li, Y., Yang, S.-Y., Wang, L. V., & Gao, W. (2019) · Science Robotics · doi:10.1126/scirobotics.aax0613 · Cited by 466
Mucus as a Barrier to Drug Delivery – Understanding and Mimicking the Barrier Properties
Boegh, M., & Nielsen, H. M. (2015) · Basic & Clinical Pharmacology & Toxicology · doi:10.1111/bcpt.12342 · Cited by 384
Enzymatically active biomimetic micropropellers for the penetration of mucin gels
Walker, D., Käsdorf, B. T., Jeong, H.-H., Lieleg, O., & Fischer, P. (2015) · Science Advances · doi:10.1126/sciadv.1500501 · Cited by 331
Billings, N., Ramirez Millan, M., Caldara, M., Rusconi, R., Tarasova, Y., Stocker, R., & Ribbeck, K. (2013) · PLoS Pathogens · doi:10.1371/journal.ppat.1003526 · Cited by 326
Metadata
- Authors
- Kirch, J., Schneider, A., Abou, B., Hopf, A., Schaefer, U. F., Schneider, M., Schall, C., Wagner, C., & Lehr, C.-M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2012-10-03
- Volume
- 109
- Issue
- 45
- Pages
- 18355-18360
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2096433675
- Cited by
- 190
- References
- 4
- FWCI
- 9.49
- Type
- journal article
- Language
- en
- Open access
- bronze
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Optical tweezers reveal relationship between microstructure and nanoparticle penetration of pulmonary mucus. https://app.cochat.ai/papers/10.1073/pnas.1214066109
- The paper
- Kirch, J., Schneider, A., Abou, B., Hopf, A., Schaefer, U. F., Schneider, M., Schall, C., Wagner, C., & Lehr, C.-M. (2012). Optical tweezers reveal relationship between microstructure and nanoparticle penetration of pulmonary mucus. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1214066109
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.