Cell-scaffold interaction quantitatively investigated using fluorescently labeled PLGA from PolySciTech

A powerful technique commonly applied in tissue engineering is cell-scaffolding in which a highly-porous, biocompatible material is implanted into a patient. This mesh allows for cells to grow inside of its structure to repair damaged or lost tissue. There still remains a great deal to learn about exactly how cells interact with the substrate they are growing on, as the structure and chemistry of the mesh is critical to how the cells grow. One common problem with growing roughly translucent microscopic cells on an opaque microfiber mesh is visualizing what is going on with the cells. This is where fluorescent imaging comes in to play. In this method, each component is bound to a specific dye that emits light when excited by a specific wavelength of light. This allows researchers to image each component of the system, separately. Recently, researchers from National institute of Standards and Technology (NIST) and National Institute of Health (NIH) utilized fluorescently conjugated PLGA-FKR648 (PolyVivo AV015) from PolySciTech (www.polyscitech.com) to make a series of cell-scaffolds and test their interactions with cells. The fluorescent nature of this polymer allowed for direct imaging of the mesh by fluorescence techniques, so they could investigate cell-interactions in fine detail. This research provides a valuable tool for tissue-engineering researchers looking to optimize their mesh designs. Read more: Bajcsy, Peter, Soweon Yoon, Stephen J. Florczyk, Nathan A. Hotaling, Mylene Simon, Piotr M. Szczypinski, Nicholas J. Schaub, Carl G. Simon, Mary Brady, and Ram D. Sriram. "Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images." BMC Bioinformatics 18, no. 1 (2017): 526. https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1928-x

“Background: Cell-scaffold contact measurements are derived from pairs of co-registered volumetric fluorescent confocal laser scanning microscopy (CLSM) images (z-stacks) of stained cells and three types of scaffolds (i.e., spun coat, large microfiber, and medium microfiber). Our analysis of the acquired terabyte-sized collection is motivated by the need to understand the nature of the shape dimensionality (1D vs 2D vs 3D) of cell-scaffold interactions relevant to tissue engineers that grow cells on biomaterial scaffolds. Results: We designed five statistical and three geometrical contact models, and then down-selected them to one from each category using a validation approach based on physically orthogonal measurements to CLSM. The two selected models were applied to 414 z-stacks with three scaffold types and all contact results were visually verified. A planar geometrical model for the spun coat scaffold type was validated from atomic force microscopy images by computing surface roughness of 52.35 nm ±31.76 nm which was 2 to 8 times smaller than the CLSM resolution. A cylindrical model for fiber scaffolds was validated from multi-view 2D scanning electron microscopy (SEM) images. The fiber scaffold segmentation error was assessed by comparing fiber diameters from SEM and CLSM to be between 0.46% to 3.8% of the SEM reference values. For contact verification, we constructed a web-based visual verification system with 414 pairs of images with cells and their segmentation results, and with 4968 movies with animated cell, scaffold, and contact overlays. Based on visual verification by three experts, we report the accuracy of cell segmentation to be 96.4% with 94.3% precision, and the accuracy of cell-scaffold contact for a statistical model to be 62.6% with 76.7% precision and for a geometrical model to be 93.5% with 87.6% precision. Conclusions: The novelty of our approach lies in (1) representing cell-scaffold contact sites with statistical intensity and geometrical shape models, (2) designing a methodology for validating 3D geometrical contact models and (3) devising a mechanism for visual verification of hundreds of 3D measurements. The raw and processed data are publicly available from https://isg.nist.gov/deepzoomweb/data/ together with the web -based verification system. Keywords: Co-localization Cellular measurements Cell-scaffold contact Segmentation models Contact evaluation Web-based verification Large-volume 3D image processing”