The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
An algorithm-based topographical biomaterials library to instruct cell fate
Open accessAbstract
It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.
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
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
Nearest neighbor pattern classification
Cover, T., & Hart, P. (1967) · IEEE Transactions on Information Theory · doi:10.1109/tit.1967.1053964 · Cited by 16,936
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., et al. (2006) · Genome Biology · doi:10.1186/gb-2006-7-10-r100 · Cited by 5,157
Self-citationCell Shape, Cytoskeletal Tension, and RhoA Regulate Stem Cell Lineage Commitment
McBeath, R., Pirone, D. M., Nelson, C. M., Bhadriraju, K., & Chen, C. S. (2004) · Developmental Cell · doi:10.1016/s1534-5807(04)00075-9 · Cited by 4,180
Exploring and Engineering the Cell Surface Interface
Stevens, M. M., & George, J. H. (2005) · Science · doi:10.1126/science.1106587 · Cited by 2,607
Role of cell shape in growth control
Folkman, J., & Moscona, A. (1978) · Nature · doi:10.1038/273345a0 · Cited by 2,422
The control of human mesenchymal cell differentiation using nanoscale symmetry and disorder
Dalby, M. J., Gadegaard, N., Tare, R., Andar, A., Riehle, M. O., Herzyk, P., Wilkinson, C. D. W., & Oreffo, R. O. C. (2007) · Nature Materials · doi:10.1038/nmat2013 · Cited by 2,416
Harnessing traction-mediated manipulation of the cell/matrix interface to control stem-cell fate
Huebsch, N., Arany, P. R., Mao, A. S., Shvartsman, D., Ali, O. A., Bencherif, S. A., Rivera-Feliciano, J., & Mooney, D. J. (2010) · Nature Materials · doi:10.1038/nmat2732 · Cited by 1,569
Biomaterials: Where We Have Been and Where We Are Going
Ratner, B. D., & Bryant, S. J. (2004) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.6.040803.140027 · Cited by 1,507
Topographical control of cells
Curtis, A., & Wilkinson, C. (1997) · Biomaterials · doi:10.1016/s0142-9612(97)00144-0 · Cited by 1,405
Cited by
Extracellular matrix: A dynamic microenvironment for stem cell niche
Gattazzo, F., Urciuolo, A., & Bonaldo, P. (2014) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2014.01.010 · Cited by 1,294
Harnessing nanotopography and integrin–matrix interactions to influence stem cell fate
Dalby, M. J., Gadegaard, N., & Oreffo, R. O. C. (2014) · Nature Materials · doi:10.1038/nmat3980 · Cited by 1,082
Materials as stem cell regulators
Murphy, W. L., McDevitt, T. C., & Engler, A. J. (2014) · Nature Materials · doi:10.1038/nmat3937 · Cited by 947
Role of the extracellular matrix in regulating stem cell fate
Watt, F. M., & Huck, W. T. S. (2013) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3620 · Cited by 861
Image-based profiling for drug discovery: due for a machine-learning upgrade?
Chandrasekaran, S. N., Ceulemans, H., Boyd, J. D., & Carpenter, A. E. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-00117-w · Cited by 389
Self-citation
Metadata
- Authors
- Unadkat, H. V., Hulsman, M., Cornelissen, K., Papenburg, B. J., Truckenmüller, R. K., Carpenter, A. E., Wessling, M., Post, G. F., Uetz, M., Reinders, M. J. T., Stamatialis, D., van Blitterswijk, C. A., & de Boer, J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2011-09-26
- Volume
- 108
- Issue
- 40
- Pages
- 16565-16570
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2047961352
- Cited by
- 379
- References
- 28
- FWCI
- 15.11
- 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: An algorithm-based topographical biomaterials library to instruct cell fate. https://app.cochat.ai/papers/10.1073/pnas.1109861108
- The paper
- Unadkat, H. V., Hulsman, M., Cornelissen, K., Papenburg, B. J., Truckenmüller, R. K., Carpenter, A. E., Wessling, M., Post, G. F., Uetz, M., Reinders, M. J. T., Stamatialis, D., van Blitterswijk, C. A., & de Boer, J. (2011). An algorithm-based topographical biomaterials library to instruct cell fate. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1109861108
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.