The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Artificial Super Neutrophils for Inflammation Targeting and HClO Generation against Tumors and Infections
Abstract
Neutrophils are powerful effector leukocytes that play an important role in innate immune systems for opposing tumor progression and ameliorating pathogen infections. Inspired by their distinct functions against tumors and infections, the artificial “super neutrophils” are proposed with excellent inflammation targeting and hypochlorous acid (HClO) generation characteristics for targeting and eliminating malignant tumor cells and pathogens. The “super neutrophils” are fabricated by embedding glucose oxidase (GOx) and chloroperoxidase (CPO) into zeolitic imidazolate framework‐8 (ZIF‐8) for HClO generation via enzymatic cascades, and then encapsulating them with the neutrophil membrane (NM) for inflammation targeting. In vitro and in vivo results indicate that these artificial “super neutrophils” can generate seven times higher reactive HClO than the natural neutrophils for eradicating tumors and infections. The “super neutrophils” demonstrated here with easy fabrication and good neutrophil‐mimicking property exhibit great potential for biomedical applications.
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
Neutrophil recruitment and function in health and inflammation
Kolaczkowska, E., & Kubes, P. (2013) · Nature Reviews Immunology · doi:10.1038/nri3399 · Cited by 5,472
Getting to the site of inflammation: the leukocyte adhesion cascade updated
Ley, K., Laudanna, C., Cybulsky, M. I., & Nourshargh, S. (2007) · Nature Reviews Immunology · doi:10.1038/nri2156 · Cited by 4,354
Microenvironmental regulation of metastasis
Joyce, J. A., & Pollard, J. W. (2009) · Nature Reviews Cancer · doi:10.1038/nrc2618 · Cited by 3,684
Rodenhizer, D., Gaude, E., Cojocari, D., Mahadevan, R., Frezza, C., Wouters, B. G., & McGuigan, A. P. (2016) · Nature Materials · doi:10.1038/nmat4482 · Cited by 132
Cited by
Targeting drugs to tumours using cell membrane-coated nanoparticles
Fang, R. H., Gao, W., & Zhang, L. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00699-x · Cited by 980
Self-citationWang, J., Tang, W., Yang, M., Yin, Y., Li, H., Hu, F., Tang, L., Ma, X., Zhang, Y., & Wang, Y. (2021) · Biomaterials · doi:10.1016/j.biomaterials.2021.120784 · Cited by 317
Metal–Organic‐Framework‐Engineered Enzyme‐Mimetic Catalysts
Ma, L., Jiang, F., Fan, X., Wang, L., He, C., Zhou, M., Li, S., Luo, H., Cheng, C., & Qiu, L. (2020) · Advanced Materials · doi:10.1002/adma.202003065 · Cited by 298
Liu, B., Bian, Y., Liang, S., Yuan, M., Dong, S., He, F., Gai, S., Yang, P., Cheng, Z., & Lin, J. (2022) · ACS Nano · doi:10.1021/acsnano.1c07893 · Cited by 257
Endogenous Hydrogen Sulfide-Triggered MOF-Based Nanoenzyme for Synergic Cancer Therapy
Li, Y., Zhou, J., Wang, L., & Xie, Z. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c08659 · Cited by 125
Metadata
- Authors
- Zhang, C., Zhang, L., Wu, W., Gao, F., Li, R., Song, W., Zhuang, Z., Liu, C., & Zhang, X.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2019-03-29
- Volume
- 31
- Issue
- 19
- Pages
- e1901179-e1901179
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W2928674156
- Cited by
- 192
- References
- 4
- FWCI
- 8.77
- Type
- journal article
- Language
- en
- Open access
- closed
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: Artificial Super Neutrophils for Inflammation Targeting and HClO Generation against Tumors and Infections. https://app.cochat.ai/papers/10.1002/adma.201901179
- The paper
- Zhang, C., Zhang, L., Wu, W., Gao, F., Li, R., Song, W., Zhuang, Z., Liu, C., & Zhang, X. (2019). Artificial Super Neutrophils for Inflammation Targeting and HClO Generation against Tumors and Infections. Advanced Materials. https://doi.org/10.1002/adma.201901179
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.