Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 296

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Clearance of pathological antibodies using biomimetic nanoparticles

Open access
Copp, Jonathan A., Fang, Ronnie H., Luk, Brian T., Hu, Che-Ming J., Gao, Weiwei, Zhang, Kang, Zhang, Liangfang·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: The selective depletion of disease-causing antibodies using nanoparticles offers a new model in the management of type II immune hypersensitivity reactions. The demonstration of pathophysiologically inspired nanoengineering serves as a valuable prototype for additional therapeutic improvements with the goal of minimizing therapy-related adverse effects. Through the use of cell membrane-cloaked nanoparticles, nanoscale decoys with strong affinity to pathological antibodies can be administered to disrupt disease processes in a minimally toxic manner. These biomimetic nanoparticles enable indiscriminate absorption of pathological antibodies regardless of their epitope specificities. This particular approach offers much promise in treating antibody-mediated autoimmune diseases, in which target antigens on susceptible cells can vary from patient to patient.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1073/pnas.1412420111

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 3 references

Cited by

See all 296

Metadata

Authors
Copp, J. A., Fang, R. H., Luk, B. T., Hu, C.-M. J., Gao, W., Zhang, K., & Zhang, L.
Venue
Proceedings of the National Academy of Sciences
Published
2014-09-02
Volume
111
Issue
37
Pages
13481-13486
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2105365201
Cited by
296
References
3
FWCI
5.60
Type
journal article
Language
en
Open access
green

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: Clearance of pathological antibodies using biomimetic nanoparticles. https://app.cochat.ai/papers/10.1073/pnas.1412420111
The paper
Copp, J. A., Fang, R. H., Luk, B. T., Hu, C.-M. J., Gao, W., Zhang, K., & Zhang, L. (2014). Clearance of pathological antibodies using biomimetic nanoparticles. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1412420111

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.