Time-lapse microscopy and classification of 2D human mesenchymal stem cells based on cell shape picks up myogenic from osteogenic and adipogenic differentiation

Volumetric imaging of human mesenchymal stem cells (hMSCs) for non-destructive quantification of 3D cell culture growth

The adoption of cell-based therapies into the clinic will require tremendous large-scale expansion to satisfy future demand, and bioreactor-microcarrier cultures are best suited to meet this challenge. The use of spherical microcarriers, however, precludes in-process visualization and monitoring of cell number, morphology, and culture health. The development of novel expansion methods also motivates the advancement of analytical methods used to characterize these microcarrier cultures. A robust optical imaging and image-analysis assay to non-destructively quantify cell number and cell volume was developed. This method preserves 3D cell morphology and does not require membrane lysing, cellular detachment, or exogenous labeling. Complex cellular networks formed in microcarrier aggregates were imaged and analyzed in toto. Direct cell enumeration of large aggregates was performed in toto for the first time. This assay was successfully applied to monitor cellular growth of mesenchymal stem cells attached to spherical hydrogel microcarriers over time. Elastic scattering and fluorescence lightsheet microscopy were used to quantify cell volume and cell number at varying spatial scales. The presented study motivates the development of on-line optical imaging and image analysis systems for robust, automated, and non-destructive monitoring of bioreactor-microcarrier cell cultures.

Comparison of the Characteristics of Breast Milk-derived Stem Cells with the Stem Cells Derived from the Other Sources: A Comparative Review

Breast milk (BrM) not only supplies nutrition, but it also contains a diverse population of cells. It has been estimated that up to 6% of the cells in human milk possess the characteristics of mesenchymal stem cells (MSC). Available data also indicate that these cells are multipotent and capable of self-renewal and differentiation with other cells. In this review, we have compared different characteristics, such as CD markers, differentiation capacity, and morphology of stem cells, derived from human breast milk (hBr-MSC) with human bone marrow (hBMSC), Wharton's jelly (WJMSC), and human adipose tissue (hADMSC). Through the literature review, it was revealed that human breast milk-derived stem cells specifically express a group of cell surface markers, including CD14, CD31, CD45, and CD86. Importantly, a group of markers, CD13, CD29, CD44, CD105, CD106, CD146, and CD166, were identified, which were common in the four sources of stem cells. WJMSC, hBMSC, hADMSC, and hBr-MSC are potently able to differentiate into the mesoderm, ectoderm, and endoderm cell lineages. The ability of hBr-MSCs todifferentiate into the neural stem cells, neurons, adipocyte, hepatocyte, chondrocyte, osteocyte, and cardiomyocytes has made these cells a promising source of stem cells in regenerative medicine, while isolation of stem cells from the commonly used sources, such as bone marrow, requires invasive procedures. Although autologous breast milk-derived stem cells are an accessible source for women who are in the lactation period, breast milk can be considered as a source of stem cells with high differentiation potential without any ethical concern.

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging

Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to reproduce, largely due to the inherently significant heterogeneity in MSCs, which has not been well investigated. To quantify cell heterogeneity, a standard approach is to measure marker expression on the protein level via immunochemistry assays. Performing such measurements non-invasively and at scale has remained challenging as conventional methods such as flow cytometry and immunofluorescence microscopy typically require cell fixation and laborious sample preparation. Here, we developed an artificial intelligence (AI)-based method that converts transmitted light microscopy images of MSCs into quantitative measurements of protein expression levels. By training a U-Net+ conditional generative adversarial network (cGAN) model that accurately (mean [Formula: see text] = 0.77) predicts expression of 8 MSC-specific markers, we showed that expression of surface markers provides a heterogeneity characterization that is complementary to conventional cell-level morphological analyses. Using this label-free imaging method, we also observed a multi-marker temporal-spatial fluctuation of protein distributions in live MSCs. These demonstrations suggest that our AI-based microscopy can be utilized to perform quantitative, non-invasive, single-cell, and multi-marker characterizations of heterogeneous live MSC culture. Our method provides a foundational step toward the instant integrative assessment of MSC properties, which is critical for high-throughput screening and quality control in cellular therapies.

The shape-effect of calcium phosphate nanoparticle based films on their osteogenic properties

Calcium phosphates (CaPs) in the form of hydroxyapatite (HA) have been extensively studied in the context of bone regeneration due to their chemical similarity to natural bone mineral. While HA is known to promote osteogenic differentiation, the structural properties of the ceramic have been shown to affect the extent of this effect; several studies have suggested that nanostructured HA can improve the bioactivity. However, the role shape plays in the osteogenic potential is more elusive. Here we studied the effect of HA nanoparticle shape on the ability to induce osteogenesis in human mesenchymal stromal cells (hMSCs) by developing nanoparticle films using needle-, rice- and spherical-shaped HA. We showed that the HA films made from all three shapes of nanoparticles induced increased levels of osteogenic markers (i.e. runt-related transcription factor 2 (RUNX2), bone morphogenetic protein 2 (BMP2), alkaline phosphatase (ALP), osteopontin (OPN), osteocalcin (OCN) on protein and gene level in comparison to hMSCs cultured on cover glass slides. Furthermore, their expression levels and profiles differed significantly as a function of nanoparticle shape. We also showed that nanoparticle films were more efficient in inducing osteogenic gene expression in hMSCs compared to adding nanoparticles to hMSCs in culture media. Finally, we demonstrated that hMSC morphology upon adhesion to the HA nanoparticle films is dependent on nanoparticle shape, with hMSCs exhibiting a more spread morphology on needle-shaped nanoparticle films compared to hMSCs seeded on rice- and spherical-shaped nanoparticle films. Our data suggests that HA nanoparticle films are efficient in inducing hMSC osteogenesis in basic cell culture conditions and that nanoparticle shape plays a vital role in cell adhesion and morphology and extent of induction of osteogenic differentiation.

Automated mesenchymal stem cell segmentation and machine learning-based phenotype classification using morphometric and textural analysis

Purpose: Mesenchymal stem cells (MSCs) have demonstrated clinically relevant therapeutic effects for treatment of trauma and chronic diseases. The proliferative potential, immunomodulatory characteristics, and multipotentiality of MSCs in monolayer culture is reflected by their morphological phenotype. Standard techniques to evaluate culture viability are subjective, destructive, or time-consuming. We present an image analysis approach to objectively determine morphological phenotype of MSCs for prediction of culture efficacy. Approach: The algorithm was trained using phase-contrast micrographs acquired during the early and mid-logarithmic stages of MSC expansion. Cell regions are localized using edge detection, thresholding, and morphological operations, followed by cell marker identification using H-minima transform within each region to differentiate individual cells from cell clusters. Clusters are segmented using marker-controlled watershed to obtain single cells. Morphometric and textural features are extracted to classify cells based on phenotype using machine learning. Results: Algorithm performance was validated using an independent test dataset of 186 MSCs in 36 culture images. Results show 88% sensitivity and 86% precision for overall cell detection and a mean Sorensen-Dice coefficient of 0.849 ± 0.106 for segmentation per image. The algorithm exhibited an area under the curve of 0.816 (CI 95 = 0.769 to 0.886) and 0.787 (CI 95 = 0.716 to 0.851) for classifying MSCs according to their phenotype at early and mid-logarithmic expansion, respectively. Conclusions: The proposed method shows potential to segment and classify low and moderately dense MSCs based on phenotype with high accuracy and robustness. It enables quantifiable and consistent morphology-based quality assessment for various culture protocols to facilitate cytotherapy development.

Antioxidant Strategy to Prevent Simulated Microgravity-Induced Effects on Bone Osteoblasts

The effects induced by microgravity on human body functions have been widely described, in particular those on skeletal muscle and bone tissues. This study aims to implement information on the possible countermeasures necessary to neutralize the oxidative imbalance induced by microgravity on osteoblastic cells. Using the model of murine MC3T3-E1 osteoblast cells, cellular morphology, proliferation, and metabolism were investigated during exposure to simulated microgravity on a random positioning machine in the absence or presence of an antioxidant—the 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox). Our results confirm that simulated microgravity-induced morphological and metabolic alterations characterized by increased levels of reactive oxygen species and a slowdown of the proliferative rate. Interestingly, the use of Trolox inhibited the simulated microgravity-induced effects. Indeed, the antioxidant-neutralizing oxidants preserved cell cytoskeletal architecture and restored cell proliferation rate and metabolism. The use of appropriate antioxidant countermeasures could prevent the modifications and damage induced by microgravity on osteoblastic cells and consequently on bone homeostasis.

Automated collective motion analysis validates human keratinocyte stem cell cultures

Identification and quality assurance of stem cells cultured in heterogeneous cell populations are indispensable for successful stem cell therapy. Here we present an image-processing pipeline for automated identification and quality assessment of human keratinocyte stem cells. When cultivated under appropriate conditions, human epidermal keratinocyte stem cells give rise to colonies and exhibit higher locomotive capacity as well as significant proliferative potential. Image processing and kernel density estimation were used to automatically extract the area of keratinocyte colonies from phase-contrast images of cultures containing feeder cells. The DeepFlow algorithm was then used to calculate locomotion speed of the colony area by analyzing serial images. This image-processing pipeline successfully identified keratinocyte stem cell colonies by measuring cell locomotion speed, and also assessed the effect of oligotrophic culture conditions and chemical inhibitors on keratinocyte behavior. Therefore, this study provides automated procedures for image-based quality control of stem cell cultures and high-throughput screening of small molecules targeting stem cells.

Time-lapse image analysis for whole colony growth curves and daily distribution of the cell number per colony during the expansion of mesenchymal stem cells

Mesenchymal stem cells from the synovium (synovial MSCs) are attractive for cartilage and meniscus regeneration therapy. We developed a software program that can distinguish individual colonies and automatically count the cell number per colony using time-lapse images. In this study, we investigated the usefulness of the software and analyzed colony formation in cultured synovial MSCs. Time-lapse image data were obtained for 14-day-expanded human synovial MSCs. The cell number per colony (for 145 colonies) was automatically counted from phase-contrast and nuclear-stained images. Colony growth curves from day 1 to day 14 (for 140 colonies) were classified using cluster analysis. Correlation analysis of the distribution of the cell number per colony at 14 days versus that number at 1–14 days revealed a correlation at 7 and 14 days. We obtained accurate cell number counts from phase-contrast images. Individual colony growth curves were classified into three main groups and subgroups. Our image analysis software has the potential to improve the evaluation of cell proliferation and to facilitate successful clinical applications using MSCs.

Diversity of dermal fibroblasts as major determinant of variability in cell reprogramming

Induced pluripotent stem cells (iPSCs) are adult somatic cells genetically reprogrammed to an embryonic stem cell-like state. Notwithstanding their autologous origin and their potential to differentiate towards cells of all three germ layers, iPSC reprogramming is still affected by low efficiency. As dermal fibroblast is the most used human cell for reprogramming, we hypothesize that the variability in reprogramming is, at least partially, because of the skin fibroblasts used. Human dermal fibroblasts harvested from five different anatomical sites (neck, breast, arm, abdomen and thigh) were cultured and their morphology, proliferation, apoptotic rate, ability to migrate, expression of mesenchymal or epithelial markers, differentiation potential and production of growth factors were evaluated in vitro. Additionally, gene expression analysis was performed by real-time PCR including genes typically expressed by mesenchymal cells. Finally, fibroblasts isolated from different anatomic sites were reprogrammed to iPSCs by integration-free method. Intriguingly, while the morphology of fibroblasts derived from different anatomic sites differed only slightly, other features, known to affect cell reprogramming, varied greatly and in accordance with anatomic site of origin. Accordingly, difference also emerged in fibroblasts readiness to respond to reprogramming and ability to form colonies. Therefore, as fibroblasts derived from different anatomic sites preserve positional memory, it is of great importance to accurately evaluate and select dermal fibroblast population prior to induce reprogramming.

A new method of SC image processing for confluence estimation

Stem cells images are a strong instrument in the estimation of confluency during their culturing for therapeutic processes. Various laboratory conditions, such as lighting, cell container support and image acquisition equipment, effect on the image quality, subsequently on the estimation efficiency. This paper describes an efficient image processing method for cell pattern recognition and morphological analysis of images that were affected by uneven background. The proposed algorithm for enhancing the image is based on coupling a novel image denoising method through BM3D filter with an adaptive thresholding technique for improving the uneven background. This algorithm works well to provide a faster, easier, and more reliable method than manual measurement for the confluency assessment of stem cell cultures. The present scheme proves to be valid for the prediction of the confluency and growth of stem cells at early stages for tissue engineering in reparatory clinical surgery. The method used in this paper is capable of processing the image of the cells, which have already contained various defects due to either personnel mishandling or microscope limitations. Therefore, it provides proper information even out of the worst original images available.

SIRT3 Enhances Mesenchymal Stem Cell Longevity and Differentiation

Mesenchymal stem cells (MSCs) are multipotent cells that are currently being investigated in a wide variety of clinical trials for their anti-inflammatory and immunomodulatory properties as well as their osteogenic and chondrogenic capabilities. However, there are considerable interdonor variability and heterogeneity of MSC populations, making it challenging to compare different products. Furthermore, proliferation, differentiation, and immunomodulation of MSCs decrease with aging and ex vivo expansion. The sirtuins have emerged as a class of protein deacylases involved in aging, oxidative stress, and metabolism. Sirtuin 3 (SIRT3) is the major mitochondrial deacetylase involved in reducing oxidative stress while preserving oxidative metabolism, and its levels have been shown to decrease with age. This study investigated the role of SIRT3 in MSC differentiation and aging. As MSCs were expanded ex vivo, SIRT3 levels decreased. In addition, SIRT3 depletion reduced MSC differentiation into adipocytes and osteoblasts. Furthermore, overexpression of SIRT3 in later-passage MSCs reduced aging-related senescence, reduced oxidative stress, and enhanced their ability to differentiate. These data suggest that overexpressing SIRT3 might represent a strategy to increase the quality and quantity of MSCs utilized for clinical applications.

Quantitative evaluation of single cell spread on collagen matrices

Cells change their morphology as a response to environmental cues. The quantitative evaluation of single cell spread on extracellular matrices, such as type I collagen, is a key tool in cancer research. Inherent to the manual scoring of cellular spread is inter-observer but also intra-observer variation. To overcome these problems, we have developed the Morphology Analysis Software (MAS). MAS scores phase-contrast images of cells on native type I collagen gels and identifies whether a cell has a spread or round morphology using a combination of four unique parameters: the presence of a cellular extension, the cell area, the cell eccentricity and cell circularity. The MAS software scores are equivalent to the average score of five independent observers but MAS is faster, more objective and standardized. A functional screening assay using six cytokines identified TGFα as a stimulator of HCT8/E11 and SK-BR-3 single cell spreading on top of type I collagen gels. This change in morphology correlates with increased migration potential as evidenced by xCELLigence migration assays and are counteracted by EGFR signaling pathway inhibitors. This underscores the use of morphology classification on a population of unlabeled cells as read-out of an important cancer cell property and the potential for the MAS software in drug screening strategies.

Potency Biomarker Signature Genes from Multiparametric Osteogenesis Assays: Will cGMP Human Bone Marrow Mesenchymal Stromal Cells Make Bone?

In skeletal regeneration approaches using human bone marrow derived mesenchymal stromal cells (hBM-MSC), functional evaluation before implantation has traditionally used biomarkers identified using fetal bovine serum-based osteogenic induction media and time courses of at least two weeks. However, emerging pre-clinical evidence indicates donor-dependent discrepancies between these ex vivo measurements and the ability to form bone, calling for improved tests. Therefore, we adopted a multiparametric approach aiming to generate an osteogenic potency assay with improved correlation. hBM-MSC populations from six donors, each expanded under clinical-grade (cGMP) conditions, showed heterogeneity for ex vivo growth response, mineralization and bone-forming ability in a murine xenograft assay. A subset of literature-based biomarker genes was reproducibly upregulated to a significant extent across all populations as cells responded to two different osteogenic induction media. These 12 biomarkers were also measurable in a one-week assay, befitting clinical cell expansion time frames and cGMP growth conditions. They were selected for further challenge using a combinatorial approach aimed at determining ex vivo and in vivo consistency. We identified five globally relevant osteogenic signature genes, notably TGF-ß1 pathway interactors; ALPL, COL1A2, DCN, ELN and RUNX2. Used in agglomerative cluster analysis, they correctly grouped the bone-forming cell populations as distinct. Although donor #6 cells were correlation slope outliers, they contrastingly formed bone without showing ex vivo mineralization. Mathematical expression level normalization of the most discrepantly upregulated signature gene COL1A2, sufficed to cluster donor #6 with the bone-forming classification. Moreover, attenuating factors causing genuine COL1A2 gene down-regulation, restored ex vivo mineralization. This suggested that the signature gene had an osteogenically influential role; nonetheless no single biomarker was fully deterministic whereas all five signature genes together led to accurate cluster analysis. We show proof of principle for an osteogenic potency assay providing early characterization of primary cGMP-hBM-MSC cultures according to their donor-specific bone-forming potential.

Separation of Mesenchymal Stem Cells Through a Strategic Centrifugation Protocol

Despite great promise surrounding mesenchymal stem cells (MSCs), their implementation for tissue engineering strategies remains in the development phases. Many of the concerns regarding the clinical use of MSCs originate from population heterogeneity, during both isolation and differentiation. In this study, we utilize our previously developed centrifugation cell adhesion protocol for the separation of MSCs. Our findings reveal that MSCs can be isolated from whole bone marrow using a 200 g (700 pN) centrifugal force after 24 h of culture on polystyrene with cell surface marker expression equivalent to positive controls. During differentiation, a centrifugation protocol with identical force parameters could be applied 14 days into chondrogenic differentiation to isolate differentiated chondrocytes, which exhibited increased expression of chondrogenic markers compared to controls. In summary, the use of our developed centrifugation cell adhesion protocol has proven to be an effective means to separate MSC populations, decreasing the heterogeneity of subsequent cell therapy products.

Cell motion predicts human epidermal stemness

Keratinocyte stem cell colonies can be identified by analyzing cell motion, an emergent stem cell property.

Image-based identification of cultured stem cells and noninvasive evaluation of their proliferative capacity advance cell therapy and stem cell research. Here we demonstrate that human keratinocyte stem cells can be identified in situ by analyzing cell motion during their cultivation. Modeling experiments suggested that the clonal type of cultured human clonogenic keratinocytes can be efficiently determined by analysis of early cell movement. Image analysis experiments demonstrated that keratinocyte stem cells indeed display a unique rotational movement that can be identified as early as the two-cell stage colony. We also demonstrate that α6 integrin is required for both rotational and collective cell motion. Our experiments provide, for the first time, strong evidence that cell motion and epidermal stemness are linked. We conclude that early identification of human keratinocyte stem cells by image analysis of cell movement is a valid parameter for quality control of cultured keratinocytes for transplantation.

Mesenchymal stem cells and collagen patches for anterior cruciate ligament repair

AIM: To investigate collagen patches seeded with mesenchymal stem cells (MSCs) and/or tenocytes (TCs) with regards to their suitability for anterior cruciate ligament (ACL) repair.

METHODS: Dynamic intraligamentary stabilization utilizes a dynamic screw system to keep ACL remnants in place and promote biological healing, supplemented by collagen patches. How these scaffolds interact with cells and what type of benefit they provide has not yet been investigated in detail. Primary ACL-derived TCs and human bone marrow derived MSCs were seeded onto two different types of 3D collagen scaffolds, Chondro-Gide^® (CG) and Novocart^® (NC). Cells were seeded onto the scaffolds and cultured for 7 d either as a pure populations or as “premix” containing a 1:1 ratio of TCs to MSCs. Additionally, as controls, cells were seeded in monolayers and in co-cultures on both sides of porous high-density membrane inserts (0.4 μm). We analyzed the patches by real time polymerase chain reaction, glycosaminoglycan (GAG), DNA and hydroxy-proline (HYP) content. To determine cell spreading and adherence in the scaffolds microscopic imaging techniques, i.e., confocal laser scanning microscopy (cLSM) and scanning electron microscopy (SEM), were applied.

RESULTS: CLSM and SEM imaging analysis confirmed cell adherence onto scaffolds. The metabolic cell activity revealed that patches promote adherence and proliferation of cells. The most dramatic increase in absolute metabolic cell activity was measured for CG samples seeded with tenocytes or a 1:1 cell premix. Analysis of DNA content and cLSM imaging also indicated MSCs were not proliferating as nicely as tenocytes on CG. The HYP to GAG ratio significantly changed for the premix group, resulting from a slightly lower GAG content, demonstrating that the cells are modifying the underlying matrix. Real-time quantitative polymerase chain reaction data indicated that MSCs showed a trend of differentiation towards a more tenogenic-like phenotype after 7 d.

CONCLUSION: CG and NC are both cyto-compatible with primary MSCs and TCs; TCs seemed to perform better on these collagen patches than MSCs.

In vitro cell motility as a potential mesenchymal stem cell marker for multipotency

Mesenchymal stem cells (MSCs) are expected to have a fundamental role in future cell-based therapies because of their high proliferative ability, multilineage potential, and immunomodulatory properties. Autologous transplantations have the "elephant in the room" problem of wide donor variability, reflected by variability in MSC quality and characteristics, leading to uncertain outcomes in the use of these cells. We propose life imaging as a tool to characterize populations of human MSCs. Bone marrow MSCs from various donors and in vitro passages were evaluated for their in vitro motility, and the distances were correlated to the adipogenic, chondrogenic, and osteogenic differentiation potentials and the levels of senescence and cell size. Using life-image measuring of track lengths of 70 cells per population for a period of 24 hours, we observed that slow-moving cells had the higher proportion of senescent cells compared with fast ones. Larger cells moved less than smaller ones, and spindle-shaped cells had an average speed. Both fast cells and slow cells were characterized by a low differentiation potential, and average-moving cells were more effective in undergoing all three lineage differentiations. Furthermore, heterogeneity in single cell motility within a population correlated with the average-moving cells, and fast- and slow-moving cells tended toward homogeneity (i.e., a monotonous moving pattern). In conclusion, in vitro cell motility might be a useful tool to quickly characterize and distinguish the MSC population's differentiation potential before additional use.

Label-free morphology-based prediction of multiple differentiation potentials of human mesenchymal stem cells for early evaluation of intact cells

Precise quantification of cellular potential of stem cells, such as human bone marrow-derived mesenchymal stem cells (hBMSCs), is important for achieving stable and effective outcomes in clinical stem cell therapy. Here, we report a method for image-based prediction of the multiple differentiation potentials of hBMSCs. This method has four major advantages: (1) the cells used for potential prediction are fully intact, and therefore directly usable for clinical applications; (2) predictions of potentials are generated before differentiation cultures are initiated; (3) prediction of multiple potentials can be provided simultaneously for each sample; and (4) predictions of potentials yield quantitative values that correlate strongly with the experimental data. Our results show that the collapse of hBMSC differentiation potentials, triggered by in vitro expansion, can be quantitatively predicted far in advance by predicting multiple potentials, multi-lineage differentiation potentials (osteogenic, adipogenic, and chondrogenic) and population doubling potential using morphological features apparent during the first 4 days of expansion culture. In order to understand how such morphological features can be effective for advance predictions, we measured gene-expression profiles of the same early undifferentiated cells. Both senescence-related genes (p16 and p21) and cytoskeleton-related genes (PTK2, CD146, and CD49) already correlated to the decrease of potentials at this stage. To objectively compare the performance of morphology and gene expression for such early prediction, we tested a range of models using various combinations of features. Such comparison of predictive performances revealed that morphological features performed better overall than gene-expression profiles, balancing the predictive accuracy with the effort required for model construction. This benchmark list of various prediction models not only identifies the best morphological feature conversion method for objective potential prediction, but should also allow clinicians to choose the most practical morphology-based prediction method for their own purposes.

Characterization of time-course morphological features for efficient prediction of osteogenic potential in human mesenchymal stem cells

Human bone marrow mesenchymal stem cells (hBMSCs) represents one of the most frequently applied cell sources for clinical bone regeneration. To achieve the greatest therapeutic effect, it is crucial to evaluate the osteogenic differentiation potential of the stem cells during their culture before the implantation. However, the practical evaluation of stem cell osteogenicity has been limited to invasive biological marker analysis that only enables assaying a single end-point. To innovate around invasive quality assessments in clinical cell therapy, we previously explored and demonstrated the positive predictive value of using time-course images taken during differentiation culture for hBMSC bone differentiation potential. This initial method establishes proof of concept for a morphology-based cell evaluation approach, but reveals a practical limitation when considering the need to handle large amounts of image data. In this report, we aimed to scale-down our proposed method into a more practical, efficient modeling scheme that can be more broadly implemented by physicians on the frontiers of clinical cell therapy. We investigated which morphological features are critical during the osteogenic differentiation period to assure the performance of prediction models with reduced burden on image acquisition. To our knowledge, this is the first detailed characterization that describes both the critical observation period and the critical number of time-points needed for morphological features to adequately model osteogenic potential. Our results revealed three important observations: (i) the morphological features from the first 3 days of differentiation are sufficiently informative to predict bone differentiation potential, both activities of alkaline phosphatase and calcium deposition, after 3 weeks of continuous culture; (ii) intervals of 48 h are sufficient for measuring critical morphological features; and (iii) morphological features are most accurately predictive when early morphological features from the first 3 days of differentiation are combined with later features (after 10 days of differentiation). Biotechnol. Bioeng. 2014;111: 1430–1439.

Photonic crystal enhanced microscopy for imaging of live cell adhesion

A form of microscopy that utilizes a photonic crystal biosensor surface as a substrate for cell attachment enables label-free, quantitative, submicron resolution, time-resolved imaging of cell-surface interactions without cytotoxic staining agents or temporally-unstable fluorophores. Other forms of microscopy do not provide this direct measurement of live cell-surface attachment localization and strength that includes unique, dynamic morphological signatures critical to the investigation of important biological phenomena such as stem cell differentiation, chemotaxis, apoptosis, and metastasis. Here, we introduce Photonic Crystal Enhanced Microscopy (PCEM), and apply it to the study of murine dental stem cells to image the evolution of cell attachment and morphology during chemotaxis and drug-induced apoptosis. PCEM provides rich, dynamic information about the evolution of cell-surface attachment profiles over biologically relevant time-scales. Critically, this method retains the ability to monitor cell behavior with spatial resolution sufficient for observing both attachment footprints of filopodial extensions and intracellular attachment strength gradients.