Macrophages play a central role in orchestrating immune responses to foreign materials, which are often responsible for the failure of implanted medical devices. Material topography is known to influence macrophage attachment and phenotype, providing opportunities for the rational design of “immune‐instructive” topographies to modulate macrophage function and thus foreign body responses to biomaterials. However, no generalizable understanding of the inter‐relationship between topography and cell response exists. A high throughput screening approach is therefore utilized to investigate the relationship between topography and human monocyte–derived macrophage attachment and phenotype, using a diverse library of 2176 micropatterns generated by an algorithm. This reveals that micropillars 5–10 µm in diameter play a dominant role in driving macrophage attachment compared to the many other topographies screened, an observation that aligns with studies of the interaction of macrophages with particles. Combining the pillar size with the micropillar density is found to be key in modulation of cell phenotype from pro to anti‐inflammatory states. Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices.

Mesenchymal stromal cells (MSC) secrete factors that contribute to organ homeostasis and repair in a tissue specific manner. For instance, kidney perivascular mesenchymal stromal cells (kPSCs) can facilitate renal epithelial repair through secretion of hepatocyte growth factor (HGF) while the secretome of bone marrow MSCs gives rise to immunosuppression. Stromal cells function in a complex 3-dimensional (3D) connective tissue architecture that induces conformational adaptation. Here we tested the hypothesis that surface topography and associated cell adaptations dictate stromal cell function through tuning of the cytokines released. To this end, we cultured human bone marrow and kidney perivascular stromal cells in the TopoWell plate, a custom-fabricated multi-well plate containing 76 unique bioactive surface topographies. Using fluorescent imaging, we observed profound changes in cell shape, accompanied by major quantitative changes in the secretory capacity of the MSCs. The cytokine secretion profile was closely related to cell morphology and was stromal cell type specific. Our data demonstrate that stromal cell function is determined by microenvironment structure and can be manipulated in an engineered setting. Our data also have implications for the clinical manufacturing of mesenchymal stromal cell therapy, where surface topography during bioreactor expansion should be taken into account to preserve therapeutic properties.

Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated.

People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

The nanotopography of biomaterial surfaces can be modified to influence adhering cells with the aim to improve the performance of medical implants and tissue culture substrates. However, the necessary knowledge of the underlying mechanisms remains incomplete. One reason for this is the limited availability of high-resolution nanotopographies on relevant biomaterials, suitable to conduct systematic biological studies. The present study shows the fabrication of a library of nano-sized surface topographies with high fidelity. The potential of this library, called the 'NanoTopoChip' is shown in a proof of principle HTS study which demonstrates how cells are affected by nanotopographies. The large dataset, acquired by quantitative high-content imaging, allowed us to use predictive modeling to describe how feature dimensions affect cell morphology.