Establishing a reference focal plane using beads for trypan-blue-based viability measurements.

Trypan blue dye exclusion-based cell viability measurements are highly dependent upon image quality and consistency. In order to make measurements repeatable, one must be able to reliably capture images at a consistent focal plane, and with signal-to-noise ratio within appropriate limits to support proper execution of image analysis routines. Imaging chambers and imaging systems used for trypan blue analysis can be inconsistent or can drift over time, leading to a need to assure the acquisition of images prior to automated image analysis. Although cell-based autofocus techniques can be applied, the heterogeneity and complexity of the cell samples can make it difficult to assure the effectiveness, repeatability and accuracy of the routine for each measurement. Instead of auto-focusing on cells in our images, we add control beads to the images, and use them to repeatedly return to a reference focal plane. We use bead image features that have stable profiles across a wide range of focal values and exposure levels. We created a predictive model based on image quality features computed over reference datasets. Because the beads have little variation, we can determine the reference plane from bead image features computed over a single-shot image and can reproducibly return to that reference plane with each sample. The achieved accuracy (over 95%) is within the limits of the actuator repeatability. We demonstrate that a small number of beads (less than 3 beads per image) is needed to achieve this accuracy. We have also developed an open-source Graphical User Interface called Bead Benchmarking-Focus And Intensity Tool (BB-FAIT) to implement these methods for a semi-automated cell viability analyser.

It is critical for the manufacturing and release of living cell-based therapies to determine the viability, the ratio of living cells to the total number of cells (live and dead), in the therapy. Dead cells can be a safety concern for the patient, and dosing is often based on the number of living cells which are the active ingredient of the drug product. Currently, the most common approach to evaluating cell viability is based on the staining of cell samples with the trypan blue marker of cell membrane integrity: a loss in cell membrane integrity with cell death allows the dye into the cell, which can be seen using brightfield microscopy. To classify cells as live/dead, the brightness of the cells is evaluated and cells with bright centres are considered live, while those with dark centres are considered dead. Unfortunately, this approach of staining, imaging and classification is very sensitive to image acquisition settings, including image focus and brightness. This paper introduces a method to establish the required image quality for image viability analysis, providing a tool to return to image acquisition settings that will ensure image quality even when there is variability from sample to sample. In this method, polymeric beads are added to each cell sample prior to cell viability analysis. Using image processing, we extract key features from the beads in the image such as sharpness of the edges of the beads. The image features of the cells can vary significantly from sample to sample and under different cell conditions, but image features of beads have proved to be consistent across samples. We are thus able to collect reference datasets quantifying bead features over a wide range of image acquisition settings (brightness and focus), allowing us to establish a reference focal plan for image acquisition for any cell sample based on bead features. We show that with as few as three beads per image, the reference focal plane can be found from a single acquisition of beads image data over a wide range of image focuses and brightness, allowing users to consistently acquire images for cell viability that meet pre-defined quality requirements.

Summary of the National Institute of Standards and Technology and US Food And Drug Administration cell counting workshop: Sharing practices in cell counting measurements.

The emergence of cell-based therapeutics has increased the need for high-quality, robust and validated measurements for cell characterization. Cell count, being one of the most fundamental measures for cell-based therapeutics, now requires increased levels of measurement confidence. The National Institute of Standards and Technology (NIST) and the US Food and Drug Administration (FDA) jointly hosted a workshop focused on cell counting in April 2017 entitled "NIST-FDA Cell Counting Workshop: Sharing Practices in Cell Counting Measurements." The focus of the workshop was on approaches for selecting, designing and validating cell counting methods and overcoming gaps in obtaining sufficient measurement assurance for cell counting. Key workshop discussion points, representing approximately 50 subject matter experts from industry, academia and government agencies, are summarized here. A key conclusion is the need to design the most appropriate cell counting method, including control/measurement assurance strategies, for a specific counting purposes. There remains a need for documentary standards for streamlining the process to develop, qualify and validate cell counting measurements as well as community-driven efforts to develop new or improved biological and non-biological reference materials.

FDA and NIST collaboration on standards development activities supporting innovation and translation of regenerative medicine products.

The development of standards for the field of regenerative medicine has been noted as a high priority by several road-mapping activities. Additionally, the U.S. Congress recognizes the importance of standards in the 21st Century Cure Act. Standards will help to accelerate and streamline cell and gene therapy product development, ensure the quality and consistency of processes and products, and facilitate their regulatory approval. Although there is general agreement for the need of additional standards for regenerative medicine products, a shared understanding of standards is required for real progress toward the development of standards to advance regenerative medicine. Here, we describe the roles of standards in regenerative medicine as well as the process for standards development and the interactions of different entities in the standards development process. Highlighted are recent coordinated efforts between the U.S. Food and Drug Administration and the National Institute of Standards and Technology to facilitate standards development and foster science that underpins standards development.

Evaluating the quality of a cell counting measurement process via a dilution series experimental design.

BACKGROUND AIMS: Cell counting measurements are critical in the research, development and manufacturing of cell-based products, yet determining cell quantity with accuracy and precision remains a challenge. Validating and evaluating a cell counting measurement process can be difficult because of the lack of appropriate reference material. Here we describe an experimental design and statistical analysis approach to evaluate the quality of a cell counting measurement process in the absence of appropriate reference materials or reference methods. METHODS: The experimental design is based on a dilution series study with replicate samples and observations as well as measurement process controls. The statistical analysis evaluates the precision and proportionality of the cell counting measurement process and can be used to compare the quality of two or more counting methods. As an illustration of this approach, cell counting measurement processes (automated and manual methods) were compared for a human mesenchymal stromal cell (hMSC) preparation. RESULTS: For the hMSC preparation investigated, results indicated that the automated method performed better than the manual counting methods in terms of precision and proportionality. DISCUSSION: By conducting well controlled dilution series experimental designs coupled with appropriate statistical analysis, quantitative indicators of repeatability and proportionality can be calculated to provide an assessment of cell counting measurement quality. This approach does not rely on the use of a reference material or comparison to "gold standard" methods known to have limited assurance of accuracy and precision. The approach presented here may help the selection, optimization, and/or validation of a cell counting measurement process.

Experimental and computational approach to establish fit-for-purpose cell viability assays.

Aim: Cell viability assays are critical for cell-based products. Here, we demonstrate a combined experimental and computational approach to identify fit-for-purpose cell assays that can predict changes in cell proliferation, a critical biological response in cell expansion. Materials & methods: Jurkat cells were systematically injured using heat (45 ± 1°C). Cell viability was measured at 0 h and 24 h after treatment using assays for membrane integrity, metabolic function and apoptosis. Proliferation kinetics for longer term cultures were modeled using the Gompertz distribution to establish predictive models between cell viability results and proliferation. Results & conclusion: We demonstrate an approach for ranking these assays as predictors of cell proliferation and for setting cell viability specifications when a particular proliferation response is required.

In recent years, there has been a surge in the amount of cellular therapy products which have been engineered to treat patients with severe diseases. These cellular products use living cells to treat the disease, and the quality of these cell products is critical for ensuring product safety and effectiveness. Throughout the process of engineering and manufacturing these cell products, many cells can die or be in the process of dying, and the amount of dead cells in the product can impact product yield and quality. In any given cell product at any given time during the manufacturing process, cells are exposed to stresses, and these stresses can injure the cells through several mechanisms, leading to a range of cell death events that can follow different timelines. There are many existing assays which evaluate the health of the cells, known as cell viability assays, and these assays can be based on many different cell features that indicate a cell has been injured (i.e., cell membrane permeability, changes in cell metabolism, molecular markers for cell death). These cell viability assays provide different insights into the state of cell health/injury based on what cell features are being evaluated and the timing at which the viability measurements are taken, and some viability assays may be more appropriate than others for specific applications. Therefore, a method is needed to appropriately select cell viability assays that are designed to evaluate injuries to cells that occur in specific bioprocess. In this series of studies, we used a range of analytical methods to study the number of living and dead cells in a series of cell populations that we treated to induce damage to the cells, reducing their ability to grow. We then used mathematical models to determine the relationship between cell viability measurements and cell growth over time, and used the results to determine the sensitivity of the viability assays to changes in cell growth. We used a specific cell line in this example, but this technique can be applied to any cell line or cell sample population and different types of injuries can be applied to the cells. This approach can be used by manufacturers of cell-based products and therapies to identify cell viability assays that are meaningful for monitoring the production of cells and characterizing product quality.

Establishing a reference focal plane using convolutional neural networks and beads for brightfield imaging.

Repeatability of measurements from image analytics is difficult, due to the heterogeneity and complexity of cell samples, exact microscope stage positioning, and slide thickness. We present a method to define and use a reference focal plane that provides repeatable measurements with very high accuracy, by relying on control beads as reference material and a convolutional neural network focused on the control bead images. Previously we defined a reference effective focal plane (REFP) based on the image gradient of bead edges and three specific bead image features. This paper both generalizes and improves on this previous work. First, we refine the definition of the REFP by fitting a cubic spline to describe the relationship between the distance from a bead's center and pixel intensity and by sharing information across experiments, exposures, and fields of view. Second, we remove our reliance on image features that behave differently from one instrument to another. Instead, we apply a convolutional regression neural network (ResNet 18) trained on cropped bead images that is generalizable to multiple microscopes. Our ResNet 18 network predicts the location of the REFP with only a single inferenced image acquisition that can be taken across a wide range of focal planes and exposure times. We illustrate the different strategies and hyperparameter optimization of the ResNet 18 to achieve a high prediction accuracy with an uncertainty for every image tested coming within the microscope repeatability measure of 7.5 µm from the desired focal plane. We demonstrate the generalizability of this methodology by applying it to two different optical systems and show that this level of accuracy can be achieved using only 6 beads per image.

Assessing the suitability of cell counting methods during different stages of a cell processing workflow using an ISO 20391-2 guided study design and analysis.

Cell counting is a fundamental measurement for determining viable cell numbers in biomanufacturing processes. The properties of different cell types and the range of intended uses for cell counts within a biomanufacturing process can lead to challenges in identifying suitable counting methods for each potential application. This is further amplified by user subjectivity in identifying the cells of interest and further identifying viable cells. Replacement of traditionally used manual counting methods with automated systems has alleviated some of these issues. However, a single cell type can exhibit different physical properties at various stages of cell processing which is further compounded by process impurities such as cell debris or magnetic beads. These factors make it challenging to develop a robust cell counting method that offers a high level of confidence in the results. Several initiatives from standards development organizations have attempted to address this critical need for standardization in cell counting. This study utilizes flow-based and image-based methods for the quantitative measurement of cell concentration and viability in the absence of a reference material, based on the tools and guidance provided by the International of Standards (ISO) and the US National Institute of Standards and Technology (NIST). Primary cells were examined at different stages of cell processing in a cell therapy workflow. Results from this study define a systematic approach that enables the identification of counting methods and parameters that are best suited for specific cell types and workflows to ensure accuracy and consistency. Cell counting is a foundational method used extensively along various steps of cell and gene therapy. The standard used in this study may be applied to other cell and gene therapy processes to enable accurate measurement of parameters required to guide critical decisions throughout the development and production process. Using a framework that confirms the suitability of the cell counting method used can minimize variability in the process and final product.

Quantitative, traceable determination of cell viability using absorbance microscopy.

Cell viability, an essential measurement for cell therapy products, lacks traceability. One of the most common cell viability tests is trypan blue dye exclusion where blue-stained cells are counted via brightfield imaging. Typically, live and dead cells are classified based on their pixel intensities which may vary arbitrarily making it difficult to compare results. Herein, a traceable absorbance microscopy method to determine the intracellular uptake of trypan blue is demonstrated. The intensity pixels of the brightfield images are converted to absorbance images which are used to calculate moles of trypan blue per cell. Trypan blue cell viability measurements, where trypan blue content in each cell is quantified, enable traceable live-dead classifications. To implement the absorbance microscopy method, we developed an open-source AbsorbanceQ application that generates quantitative absorbance images. The validation of absorbance microscopy is demonstrated using neutral density filters. Results from four different microscopes demonstrate a mean absolute deviation of 3% from the expected optical density values. When assessing trypan blue-stained Jurkat cells, the difference in intracellular uptake of trypan blue in heat-shock-killed cells using two different microscopes is 3.8%. Cells killed with formaldehyde take up ~50% less trypan blue as compared to the heat-shock-killed cells, suggesting that the killing mechanism affects trypan blue uptake. In a test mixture of approximately 50% live and 50% dead cells, 53% of cells were identified as dead (±6% standard deviation). Finally, to mimic batches of low-viability cells that may be encountered during a cell manufacturing process, viability was assessed for cells that were 1) overgrown in the cell culture incubator for five days or 2) incubated in DPBS at room temperature for five days. Instead of making live-dead classifications using arbitrary intensity values, absorbance imaging yields traceable units of moles that can be compared, which is useful for assuring quality for biomanufacturing processes.

Sensor technologies for quality control in engineered tissue manufacturing.

The use of engineered cells, tissues, and organs has the opportunity to change the way injuries and diseases are treated. Commercialization of these groundbreaking technologies has been limited in part by the complex and costly nature of their manufacture. Process-related variability and even small changes in the manufacturing process of a living product will impact its quality. Without real-time integrated detection, the magnitude and mechanism of that impact are largely unknown. Real-time and non-destructive sensor technologies are key for in-process insight and ensuring a consistent product throughout commercial scale-up and/or scale-out. The application of a measurement technology into a manufacturing process requires cell and tissue developers to understand the best way to apply a sensor to their process, and for sensor manufacturers to understand the design requirements and end-user needs. Furthermore, sensors to monitor component cells' health and phenotype need to be compatible with novel integrated and automated manufacturing equipment. This review summarizes commercially relevant sensor technologies that can detect meaningful quality attributes during the manufacturing of regenerative medicine products, the gaps within each technology, and sensor considerations for manufacturing.

Early time-point cell morphology classifiers successfully predict human bone marrow stromal cell differentiation modulated by fiber density in nanofiber scaffolds.

Nanofiber scaffolds can induce osteogenic differentiation and cell morphology alterations of human bone marrow stromal cells (hBMSCs) without introduction of chemical cues. In this study, we investigate the predictive power of day 1 cell morphology, quantified by a machine learning based method, as an indicator of osteogenic differentiation modulated by nanofiber density. Nanofiber scaffolds are fabricated via electrospinning. Microscopy, quantitative image processing and clustering analysis are used to systematically quantify scaffold properties as a function of fiber density. hBMSC osteogenic differentiation potential is evaluated after 14 days using osteogenic marker gene expression and after 50 days using calcium mineralization, showing enhanced osteogenic differentiation with an increase in nanofiber density. Cell morphology measurements at day 1 successfully predict differentiation potential when analyzed with the support vector machine (SVM)/supercell tools previously developed and trained on cells from a different donor. A correlation is observed between differentiation potential and cell morphology, demonstrating sensitivity of the morphology measurement to varying degrees of differentiation potential. To further understand how nanofiber density determines hBMSC morphology, both full 3-D morphology measurements as well as other measurements of the 2-D projected morphology are investigated in this study. To achieve predictive power on hBMSC osteogenic differentiation, at least two morphology metrics need to be considered together for each cell, with the majority of metric pairs including one 3-D morphology metric. Analysis of the local nanofiber structure surrounding each cell reveals a correlation with single-cell morphology and indicates that the osteogenic differentiation phenotype may be predictive at the single-cell level.

Synthesis of macromolecular mimics of small leucine-rich proteoglycans with a poly(ethylene glycol) core and chondroitin sulphate bristles.

Small leucine-rich proteoglycans (SLRPs) are a class of molecules prevalent in almost all tissues types and are thought to be responsible for collagen organization and macro-scale biological properties. However, when they are dysfunctional or degraded, severe pathological phenotypes are observed. Here we investigate macromolecular mimics to SLRPs using poly(ethylene glycol) (PEG) as a core (replacing the protein core of natural SLRPs) and chondroitin sulphate (CS) bristle(s) in an end-on attachment (via epoxide-amine reactions), mimicking the physical structure of the natural SLRPs. Poly(ethylene glycol)-diglycidyl ether (PEG-DEG) and ethylene glycol-diglycidyl ether (EG-DGE) monomers were used to incorporate CS bristles into a macromolecule that closely mimics the SLRP biglycan structure in a grafting-to strategy. The kinetics of these reactions was studied along with the specific viscosity and cytocompatibility of resulting CS macromolecules. Structures were found to incorporate two CS chains (similar to biglycan) on average and exhibited cytocompatibility equivalent to or better than CS-only controls.

A Bioinformatics 3D Cellular Morphotyping Strategy for Assessing Biomaterial Scaffold Niches.

Many biomaterial scaffolds have been advanced to provide synthetic cell niches for tissue engineering and drug screening applications; however, current methods for comparing scaffold niches focus on cell functional outcomes or attempt to normalize materials properties between different scaffold formats. We demonstrate a three-dimensional (3D) cellular morphotyping strategy for comparing biomaterial scaffold cell niches between different biomaterial scaffold formats. Primary human bone marrow stromal cells (hBMSCs) were cultured on 8 different biomaterial scaffolds, including fibrous scaffolds, hydrogels, and porous sponges, in 10 treatment groups to compare a variety of biomaterial scaffolds and cell morphologies. A bioinformatics approach was used to determine the 3D cellular morphotype for each treatment group by using 82 shape metrics to analyze approximately 1000 cells. We found that hBMSCs cultured on planar substrates yielded planar cell morphotypes, while those cultured in 3D scaffolds had elongated or equiaxial cellular morphotypes with greater height. Multivariate analysis was effective at distinguishing mean shapes of cells in flat substrates from cells in scaffolds, as was the metric L1-depth (the cell height along its shortest axis after aligning cells with a characteristic ellipsoid). The 3D cellular morphotyping technique enables direct comparison of cellular microenvironments between widely different types of scaffolds and design of scaffolds based on cell structure-function relationships.

Development and characterization of a porous micro-patterned scaffold for vascular tissue engineering applications.

The fabrication of functional small diameter blood vessel analogs has implications in vascular disease treatment. Current 3D models of the medial vessel layer lack micron-scale topographical cues that have shown promise in vitro by recapitulating native vascular smooth muscle cell (VSMC) behavior. A major obstacle to fabricating 3D scaffolds is maintaining adequate nutrient diffusion to cells. We have developed and characterized porous micro-patterned poly-caprolactone (PCL) scaffolds using a novel technique that integrates soft lithography, melt molding and particulate leaching of polylactic-co-glycolic acid (PLGA) micro/nanoparticles. Scanning electron microscopy showed that PLGA-leached scaffolds have circular pores significantly smaller than the size scale of the grooved surface pattern (48 microm grooves; 5 microm deep; 12 microm spacing). Diffusion of media through PLGA-leached scaffolds was six-fold greater than through non-porous scaffolds, indicating successful introduction of through-pores into PCL by the PLGA leaching technique. VSMC alignment on micro-patterned PLGA-leached scaffolds was similar to that on micro-patterned non-porous scaffolds, indicating no loss in cellular organization on PLGA-leached scaffolds. In contrast, cells seeded on micro-patterned sodium bicarbonate-leached scaffolds remained un-aligned. The ability to micro-pattern cells on porous scaffolds may facilitate the transfer of micro-technology from simple 2D substrates to complex 3D architectures, allowing for tight control over cellular organization in fabricated tissues.

Strategies for Achieving Measurement Assurance for Cell Therapy Products.

UNLABELLED: The cell therapy industry has identified the inability to reliably characterize cells as possibly its greatest challenge and has called for standards and reference materials to provide assurance for measurements of cell properties. The challenges in characterization of cell therapy products can be largely addressed with systematic approaches for assessing sources of uncertainty and improving confidence in key measurements. This article presents the many strategies that can be used to ensure measurement confidence and discusses them in terms of how they can be applied to characterization of cell therapy products. SIGNIFICANCE: Application of these strategies to cell measurements will help to establish qualified assays for cell characterization, which may help streamline regulatory approval and enable more efficient development of cell therapy products.

Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.

Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and multi-parametric definitions of cell morphology. To associate cell morphology with cell-material interactions, we developed a shape phenotyping framework based on support vector machines. A feature selection procedure was implemented to select the most significant combination of cell shape metrics to build classifiers with both accuracy and stability to identify and predict microenvironment-driven morphological differences in heterogeneous cell populations. The analysis was conducted at a multi-cell level, where a "supercell" method used average shape measurements of small groups of single cells to account for heterogeneous populations and microenvironment. A subsampling validation algorithm revealed the range of supercell sizes and sample sizes needed for classifier stability and generalization capability. As an example, the responses of human bone marrow stromal cells (hBMSCs) to fibrous vs flat microenvironments were compared on day 1. Our analysis showed that 57 cells (grouped into supercells of size 4) are the minimum needed for phenotyping. The analysis identified that a combination of minor axis length, solidity, and mean negative curvature were the strongest early shape-based indicator of hBMSCs response to fibrous microenvironment.

Vascular tissue engineering: microtextured scaffold templates to control organization of vascular smooth muscle cells and extracellular matrix.

The in vitro construction of tissue-engineered small diameter (<6mm) blood vessels with sufficient strength and mechanical compliance has evaded researchers. We hypothesize that the high spatial organization of the medial layer of vascular smooth muscle cells (VSMCs) and their surrounding matrix provides high burst strength, compliance, and stability. We investigated the effect of microfabricated polydimethylsiloxane (PDMS) scaffolds with various groove widths on VSMC organization. We found that the presence of these grooved topographical cues significantly enhanced VSMC aspect ratio, alignment, and oriented remodeling of the underlying extracellular matrix. This study suggests that topographical patterning of tissue scaffolds can influence cellular and matrix spatial organization and could provide a framework for achieving the required organization and physical properties for blood vessels.

Role of biomolecules on annulus fibrosus micromechanics: effect of enzymatic digestion on elastic and failure properties.

Uniaxial tension was applied to selectively digested single lamellar human cadaveric annulus fibrosus specimens to investigate the role of different biomolecules in annular biomechanics. Single layered and inter-lamellar annulus fibrosus samples were obtained from 10 isolated cadaveric lumbar intervertebral discs in one of four orientations: longitudinal, transverse, radial, and circumferential. Within each orientation the samples were subjected to a selective enzymatic digestion protocol with collagenase, elastase, chondroitinase ABC, or 1× Phosphate Buffered Saline. Uniaxial tensile tests were performed to failure at a strain rate of 0.005s(-1). Failure stress and strain, and elastic moduli were compared among the digested conditions. The collagenase- and elastase-treated groups had the most significant effect on the mechanical properties among the orientation groups, decreasing the failure stress for both interlaminar and intralaminar groups. Collagenase-treated groups showed an increase in the failure strain following enzymatic digestion for the intralaminar groups and one interlaminar testing direction (circumferential). The chondroitinase ABC-treated group only had a significant impact on the single layer orientations, decreasing the failure stress and strain (intralaminar group). The digested properties described provide insights into the laminar mechanical behavior and the role of the molecular components to the annular mechanical behavior. Understanding annular mechanics may prove insightful in diagnosis, prevention and repair of debilitating intervertebral disc disorders and manufacturing of tissue-engineered annulus.

The support of bone marrow stromal cell differentiation by airbrushed nanofiber scaffolds.

Nanofiber scaffolds are effective for tissue engineering since they emulate the fibrous nanostructure of native extracellular matrix (ECM). Although electrospinning has been the most common approach for fabricating nanofiber scaffolds, airbrushing approaches have also been advanced for making nanofibers. For airbrushing, compressed gas is used to blow polymer solution through a small nozzle which shears the polymer solution into fibers. Our goals were 1) to assess the versatility of airbrushing, 2) to compare the properties of airbrushed and electrospun nanofiber scaffolds and 3) to test the ability of airbrushed nanofibers to support stem cell differentiation. The results demonstrated that airbrushing could produce nanofibers from a wide range of polymers and onto a wide range of targets. Airbrushing was safer, 10-fold faster, 100-fold less expensive to set-up and able to deposit nanofibers onto a broader range of targets than electrospinning. Airbrushing yielded nanofibers that formed loosely packed bundles of aligned nanofibers, while electrospinning produced un-aligned, single nanofibers that were tightly packed and highly entangled. Airbrushed nanofiber mats had larger pores, higher porosity and lower modulus than electrospun mats, results that were likely caused by the differences in morphology (nanofiber packing and entanglement). Airbrushed nanofiber scaffolds fabricated from 4 different polymers were each able to support osteogenic differentiation of primary human bone marrow stromal cells (hBMSCs). Finally, the differences in airbrushed versus electrospun nanofiber morphology caused differences in hBMSC shape where cells had a smaller spread area and a smaller volume on airbrushed nanofiber scaffolds. These results highlight the advantages and disadvantages of airbrushing versus electrospinning nanofiber scaffolds and demonstrate that airbrushed nanofiber scaffolds can support stem cell differentiation.

Synthesis and recovery characteristics of branched and grafted PNIPAAm-PEG hydrogels for the development of an injectable load-bearing nucleus pulposus replacement.

A family of injectable poly(N-isopropyl acrylamide) (PNIPAAm) copolymer hydrogels has been fabricated in order to tune mechanical properties to support load-bearing function and dimensional recovery for possible use as load-bearing medical devices, such as a nucleus pulposus replacement for the intervertebral disc. PNIPAAm-polyethylene glycol (PEG) copolymers were synthesized with varying hydrophilic PEG concentrations as grafted or branched structures to enhance dimensional recovery of the materials. Polymerizations were confirmed with attenuated total reflectance-Fourier transform infrared spectroscopy and proton nuclear magnetic resonance spectroscopy studies. Incorporation of PEG was effective in raising water content of pure PNIPAAm hydrogels (29.3% water for pure PNIPAAm vs. 47.7% for PEG branches and 39.5% for PEG grafts). PNIPAAm with 7% grafted as well as 7% branched PEG had significantly reduced compressive modulus compared to that of pure PNIPAAm. Initially recovered compressive strain was significantly increased for 7% PEG branches after pre-testing immersion in PBS for up to 33 days, while 7% PEG grafts decreased this value. Sample height recovery for pure PNIPAAm was limited to 31.6%, while PNIPAAm with 7% branches was increased to 71.3%. When mechanically tested samples were allowed to recover without load over 30 min, each composition was able to significantly recover height, indicating that the time to recovery is slower than the unloading rates typically used in testing. While the incorporation of hydrophilic PEG was expected to alter the mechanical behavior of the hydrogels, only the branched form was able to significantly enhance dimensional recovery.