The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Latest Advances in Cryogel Technology for Biomedical Applications
Abstract
There exists a technological need for advanced materials with improved properties for emerging biomedical applications. Recent developments in macroporous materials have demonstrated their applicability as indispensable tools in biomedical research. Cryogels, which are materials with a macroporous 3D structure, are produced as a result of controlled freezing during polymerization with a highly interconnected polymer network. Cryogels’ interest lies in their ability to address some of the limitations of their hydrogel analogues. In this review, hydrogel and cryogel basic concepts are discussed as a short primer for readers unfamiliar with the cryogels literature. Next, a general overview of the methods for synthesis and characterization of cryogels is provided, highlighting key concepts relevant to cryogels and explaining their unique properties. Finally an in‐depth overview of specific technologies and fields where cryogels have been applied is given. It is argued that the latest advances in cryogel technologies are able to address challenges in bioseparation, tissue engineering, and other emerging bioengineering disciplines.
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
Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
Nishita, M., Park, S.-Y., Nishio, T., Kamizaki, K., Wang, Z., Tamada, K., Takumi, T., Hashimoto, R., Otani, H., Pazour, G. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-016-0028-x · Cited by 15,947
Matrix elasticity directs stem cell lineage specification
Engler, A. J., Sen, S., Sweeney, H. L., & Discher, D. E. (2006) · Cell · doi:10.1016/j.cell.2006.06.044 · Cited by 13,915
Tissue Cells Feel and Respond to the Stiffness of Their Substrate
Discher, D. E., Janmey, P., & Wang, Y.-L. (2005) · Science · doi:10.1126/science.1116995 · Cited by 6,382
Biomedical applications of biodegradable polymers
Ulery, B. D., Nair, L. S., & Laurencin, C. T. (2011) · Journal of Polymer Science Part B: Polymer Physics · doi:10.1002/polb.22259 · Cited by 2,206
Adoptive immunotherapy for cancer: harnessing the T cell response
Restifo, N. P., Dudley, M. E., & Rosenberg, S. A. (2012) · Nature Reviews Immunology · doi:10.1038/nri3191 · Cited by 1,688
Three-dimensional culture systems in cancer research: Focus on tumor spheroid model
Nath, S., & Devi, G. R. (2016) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2016.03.013 · Cited by 919
Amine coupling through EDC/NHS: a practical approach
Fischer, M. J. E. (2010) · Methods in Molecular Biology · doi:10.1007/978-1-60761-670-2_3 · Cited by 492
Soft Materials in Neuroengineering for Hard Problems in Neuroscience
Jeong, J.-W., Shin, G., Park, S. I., Yu, K. J., Xu, L., & Rogers, J. A. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.035 · Cited by 333
Chitosan–alginate 3D scaffolds as a mimic of the glioma tumor microenvironment
Kievit, F. M., Florczyk, S. J., Leung, M. C., Veiseh, O., Park, J. O., Disis, M. L., & Zhang, M. (2010) · Biomaterials · doi:10.1016/j.biomaterials.2010.03.062 · Cited by 209
Akbarzadeh, R., & Yousefi, A. (2014) · Journal of Biomedical Materials Research Part B: Applied Biomaterials · doi:10.1002/jbm.b.33101 · Cited by 208
Cited by
Xu, X., Jiang, F., Lin, K., Fang, J., Chen, F., Ru, Y., Weng, H., Xiao, Q., Yang, Q., & Xiao, A. (2024) · Food Hydrocolloids · doi:10.1016/j.foodhyd.2023.109726 · Cited by 29
Metadata
- Authors
- Memic, A., Colombani, T., Eggermont, L. J., Rezaeeyazdi, M., Steingold, J., Rogers, Z. J., Navare, K. J., Mohammed, H. S., & Bencherif, S. A.
- Venue
- Advanced Therapeutics
- Publisher
- Wiley
- Published
- 2019-02-10
- Volume
- 2
- Issue
- 4
- ISSN
- 2366-3987 (ISSN-L)
- OpenAlex
- W2913545421
- Cited by
- 310
- References
- 11
- FWCI
- 10.82
- 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
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.