Accelerating the development of vaccine microarray patches for epidemic response and equitable immunization coverage requires investment in microarray patch manufacturing facilities.

INTRODUCTION: There is a need for investment in manufacturing for vaccine microarray patches (vMAPs) to accelerate vMAP development and access. vMAPs could transform vaccines deployment and reach to everyone, everywhere. AREAS COVERED: We outline vMAPs' potential benefits for epidemic preparedness and for outreach in low- and lower-middle-income countries (LMICs), share lessons learned from pandemic response, and highlight that investment in manufacturing-at-risk could accelerate vMAP development. EXPERT OPINION: Pilot manufacturing capabilities are needed to produce clinical trial material and enable emergency response. Funding vMAP manufacturing scale-up in parallel to clinical proof-of-concept studies could accelerate vMAP approval and availability. Incentives could mitigate the risks of establishing multi-vMAP manufacturing facilities early.

Synthetic Health Data Can Augment Community Research Efforts to Better Inform the Public During Emerging Pandemics.

The COVID-19 pandemic had disproportionate effects on the Veteran population due to the increased prevalence of medical and environmental risk factors. Synthetic electronic health record (EHR) data can help meet the acute need for Veteran population-specific predictive modeling efforts by avoiding the strict barriers to access, currently present within Veteran Health Administration (VHA) datasets. The U.S. Food and Drug Administration (FDA) and the VHA launched the precisionFDA COVID-19 Risk Factor Modeling Challenge to develop COVID-19 diagnostic and prognostic models; identify Veteran population-specific risk factors; and test the usefulness of synthetic data as a substitute for real data. The use of synthetic data boosted challenge participation by providing a dataset that was accessible to all competitors. Models trained on synthetic data showed similar but systematically inflated model performance metrics to those trained on real data. The important risk factors identified in the synthetic data largely overlapped with those identified from the real data, and both sets of risk factors were validated in the literature. Tradeoffs exist between synthetic data generation approaches based on whether a real EHR dataset is required as input. Synthetic data generated directly from real EHR input will more closely align with the characteristics of the relevant cohort. This work shows that synthetic EHR data will have practical value to the Veterans' health research community for the foreseeable future.

Sepsis Among Medicare Beneficiaries: 4. Precoronavirus Disease 2019 Update January 2012-February 2020.

OBJECTIVES: To provide updated information on the burdens of sepsis during acute inpatient admissions for Medicare beneficiaries. DESIGN: Analysis of paid Medicare claims via the Centers for Medicare and Medicaid Services DataLink Project. SETTING: All U.S. acute-care hospitals, excluding federally operated hospitals (Veterans Administration and Defense Health Agency). PATIENTS: All Medicare beneficiaries, January 2012-February 2020, with an explicit sepsis diagnostic code assigned during an inpatient admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The count of Medicare Part A/B (fee-for-service) plus Medicare Advantage inpatient sepsis admissions rose from 981,027 (CY2012) to 1,700,433 (CY 2019). The proportion of total admissions with sepsis in the Medicare Advantage population rose from 21.43% to 35.39%, reflecting the increasing beneficiary proportion enrolled in Medicare Advantage. In CY2019, 6-month mortality rates in Medicare fee-for-service beneficiaries for sepsis continued to decline, but remained high: 59.9% for septic shock, 35.5% for severe sepsis, 30.8% for sepsis attributed to a specific organism, and 26.5% for unspecified sepsis. Total fee-for-service-only inpatient hospital costs rose from $17.79B (CY2012) to $22.98B (CY2019). We estimated that the aggregate cost of sepsis hospital care for the entire U.S. population was at least $57.47B in 2019. Inclusion of 14 months' (January 2019-February 2020) newer data exposed new trends: the cost per patient, number of admissions, and fraction of patients with sepsis labeled as present on admission inflected around November 2015, coincident with the change to International Classification of Diseases, 10th Edition, and introduction of the Severe Sepsis and Septic Shock Management Bundle (SEP-1) metric. CONCLUSIONS: Sepsis among Medicare beneficiaries precoronavirus disease 2019 imposed immense burdens upon patients, their families, and the taxpayers.

Enhanced GLT-1 mediated glutamate uptake and migration of primary astrocytes directed by fibronectin-coated electrospun poly-L-lactic acid fibers.

Bioengineered fiber substrates are increasingly studied as a means to promote regeneration and remodeling in the injured central nervous system (CNS). Previous reports largely focused on the ability of oriented scaffolds to bridge injured regions and direct outgrowth of axonal projections. In the present work, we explored the effects of electrospun microfibers on the migration and physiological properties of brain astroglial cells. Primary rat astrocytes were cultured on either fibronectin-coated poly-L-lactic acid (PLLA) films, fibronectin-coated randomly oriented PLLA electrospun fibers, or fibronectin-coated aligned PLLA electrospun fibers. Aligned PLLA fibers strongly altered astrocytic morphology, orienting cell processes, actin microfilaments, and microtubules along the length of the fibers. On aligned fibers, astrocytes also significantly increased their migration rates in the direction of fiber orientation. We further investigated if fiber topography modifies astrocytic neuroprotective properties, namely glutamate and glutamine transport and metabolism. This was done by quantifying changes in mRNA expression (qRT-PCR) and protein levels (Western blotting) for a battery of relevant biomolecules. Interestingly, we found that cells grown on random and/or aligned fibers increased the expression levels of two glutamate transporters, GLAST and GLT-1, and an important metabolic enzyme, glutamine synthetase, as compared to the fibronectin-coated films. Functional assays revealed increases in glutamate transport rates due to GLT-1 mediated uptake, which was largely determined by the dihydrokainate-sensitive GLT-1. Overall, this study suggests that aligned PLLA fibers can promote directed astrocytic migration, and, of most importance, our in vitro results indicate for the first time that electrospun PLLA fibers can positively modify neuroprotective properties of glial cells by increasing rates of glutamate uptake.

p53 as Batman: using a movie plot to understand control of the cell cycle.

This Teaching Resource provides and describes a two-part classroom exercise to help students understand control of the cell cycle, with a focus on the transcription factor p53, the E3 ubiquitin ligase Mdm2, the Mdm2 inhibitor ARF, the kinases ATM and ATR, the kinase Chk2, and the cell cycle inhibitor p21(Cip1). Students use characters and scenes from the movie The Dark Knight to represent elements of the cell cycle control machinery, then they apply these characters and scenes to translate a primary research article on p53 function into a new movie scene in the "Batman universe." This exercise is appropriate for college-level courses in cell biology and cancer biology and requires students to have a background in introductory cell biology. Explicit learning outcomes and associated assessment methods are provided, as well as slides, student assignments, the primary research article, and an instructor's guide for the exercise.

Novel image analysis approach quantifies morphological characteristics of 3D breast culture acini with varying metastatic potentials.

Prognosis of breast cancer is primarily predicted by the histological grading of the tumor, where pathologists manually evaluate microscopic characteristics of the tissue. This labor intensive process suffers from intra- and inter-observer variations; thus, computer-aided systems that accomplish this assessment automatically are in high demand. We address this by developing an image analysis framework for the automated grading of breast cancer in in vitro three-dimensional breast epithelial acini through the characterization of acinar structure morphology. A set of statistically significant features for the characterization of acini morphology are exploited for the automated grading of six (MCF10 series) cell line cultures mimicking three grades of breast cancer along the metastatic cascade. In addition to capturing both expected and visually differentiable changes, we quantify subtle differences that pose a challenge to assess through microscopic inspection. Our method achieves 89.0% accuracy in grading the acinar structures as nonmalignant, noninvasive carcinoma, and invasive carcinoma grades. We further demonstrate that the proposed methodology can be successfully applied for the grading of in vivo tissue samples albeit with additional constraints. These results indicate that the proposed features can be used to describe the relationship between the acini morphology and cellular function along the metastatic cascade.

Coupled analysis of in vitro and histology tissue samples to quantify structure-function relationship.

The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. However, at the tissue level of biological complexity we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological tissues at the cellular and subcellular level, we cannot assemble it in a way that explains the correspondingly complex biological functions these structures perform. To help close this information gap we define here several quantitative temperospatial features that link tissue structure to its corresponding biological function. Both histological images of human tissue samples and fluorescence images of three-dimensional cultures of human cells are used to compare the accuracy of in vitro culture models with their corresponding human tissues. To the best of our knowledge, there is no prior work on a quantitative comparison of histology and in vitro samples. Features are calculated from graph theoretical representations of tissue structures and the data are analyzed in the form of matrices and higher-order tensors using matrix and tensor factorization methods, with a goal of differentiating between cancerous and healthy states of brain, breast, and bone tissues. We also show that our techniques can differentiate between the structural organization of native tissues and their corresponding in vitro engineered cell culture models.

Phenylboronic acid is a more potent inhibitor than boric acid of key signaling networks involved in cancer cell migration.

Previous studies from our lab have shown that both boric (BA) and phenylboronic- acid (PBA) inhibit the migration of prostate cancer cell lines, as well as non-tumorigenic prostate cells. Our results indicate that PBA is more potent than BA in targeting metastatic and proliferative properties of cancer cells. Here we focus on the impact of BA and PBA on Rho family of GTP-binding proteins and their downstream targets. Treatment with 1mM PBA and BA decreases activities of RhoA, Rac1, and Cdc42 in DU-145 metastatic prostate cancer cells, but not in normal RWPE-1 prostate cells. Furthermore, ROCKII activity and phosphorylation of myosin light chain kinase decrease as a result of either PBA or BA treatment in DU-145 cells, suggesting these compounds target actomyosin-based contractility.

Quantitative metric profiles capture three-dimensional temporospatial architecture to discriminate cellular functional states.

BACKGROUND: Computational analysis of tissue structure reveals sub-visual differences in tissue functional states by extracting quantitative signature features that establish a diagnostic profile. Incomplete and/or inaccurate profiles contribute to misdiagnosis. METHODS: In order to create more complete tissue structure profiles, we adapted our cell-graph method for extracting quantitative features from histopathology images to now capture temporospatial traits of three-dimensional collagen hydrogel cell cultures. Cell-graphs were proposed to characterize the spatial organization between the cells in tissues by exploiting graph theory wherein the nuclei of the cells constitute the nodes and the approximate adjacency of cells are represented with edges. We chose 11 different cell types representing non-tumorigenic, pre-cancerous, and malignant states from multiple tissue origins. RESULTS: We built cell-graphs from the cellular hydrogel images and computed a large set of features describing the structural characteristics captured by the graphs over time. Using three-mode tensor analysis, we identified the five most significant features (metrics) that capture the compactness, clustering, and spatial uniformity of the 3D architectural changes for each cell type throughout the time course. Importantly, four of these metrics are also the discriminative features for our histopathology data from our previous studies. CONCLUSIONS: Together, these descriptive metrics provide rigorous quantitative representations of image information that other image analysis methods do not. Examining the changes in these five metrics allowed us to easily discriminate between all 11 cell types, whereas differences from visual examination of the images are not as apparent. These results demonstrate that application of the cell-graph technique to 3D image data yields discriminative metrics that have the potential to improve the accuracy of image-based tissue profiles, and thus improve the detection and diagnosis of disease.

Quantification of three-dimensional cell-mediated collagen remodeling using graph theory.

BACKGROUND: Cell cooperation is a critical event during tissue development. We present the first precise metrics to quantify the interaction between mesenchymal stem cells (MSCs) and extra cellular matrix (ECM). In particular, we describe cooperative collagen alignment process with respect to the spatio-temporal organization and function of mesenchymal stem cells in three dimensions. METHODOLOGY/PRINCIPAL FINDINGS: We defined two precise metrics: Collagen Alignment Index and Cell Dissatisfaction Level, for quantitatively tracking type I collagen and fibrillogenesis remodeling by mesenchymal stem cells over time. Computation of these metrics was based on graph theory and vector calculus. The cells and their three dimensional type I collagen microenvironment were modeled by three dimensional cell-graphs and collagen fiber organization was calculated from gradient vectors. With the enhancement of mesenchymal stem cell differentiation, acceleration through different phases was quantitatively demonstrated. The phases were clustered in a statistically significant manner based on collagen organization, with late phases of remodeling by untreated cells clustering strongly with early phases of remodeling by differentiating cells. The experiments were repeated three times to conclude that the metrics could successfully identify critical phases of collagen remodeling that were dependent upon cooperativity within the cell population. CONCLUSIONS/SIGNIFICANCE: Definition of early metrics that are able to predict long-term functionality by linking engineered tissue structure to function is an important step toward optimizing biomaterials for the purposes of regenerative medicine.

The natural and engineered 3D microenvironment as a regulatory cue during stem cell fate determination.

The concept of using stem cells as self-renewing sources of healthy cells in regenerative medicine has existed for decades, but most applications have yet to achieve clinical success. A main reason for the lack of successful stem cell therapies is the difficulty in fully recreating the maintenance and control of the native stem cell niche. Improving the performance of transplanted stem cells therefore requires a better understanding of the cellular mechanisms guiding stem cell behavior in both native and engineered three-dimensional (3D) microenvironments. Most techniques, however, for uncovering mechanisms controlling cell behavior in vitro have been developed using 2D cell cultures and are of limited use in 3D environments such as engineered tissue constructs. Deciphering the mechanisms controlling stem cell fate in native and engineered 3D environments, therefore, requires rigorous quantitative techniques that permit mechanistic, hypothesis-driven studies of cell-microenvironment interactions. Here, we review the current understanding of 2D and 3D stem cell control mechanisms and propose an approach to uncovering the mechanisms that govern stem cell behavior in 3D.

Inhibition of ERK promotes collagen gel compaction and fibrillogenesis to amplify the osteogenesis of human mesenchymal stem cells in three-dimensional collagen I culture.

Tissue morphogenesis remains one of the least understood problems in cell and developmental biology. There is a disconnect between the mechanisms that apply to two-dimensional (2D) cultures and those seen in vivo. Three-dimensional (3D) culture presents a complex stimulus triggering cellular responses that are only partially understood. We compared 2D and 3D cultures of human mesenchymal stem cells in the presence of mitogen-activated protein kinase kinase (MEK) inhibitor, PD98059, to determine the role of extracellular signal-related kinase (ERK) in collagen-induced differentiation. 3D collagen I culture enhanced and accelerated the osteogenic differentiation of human mesenchymal stem cells (hMSC). Contrary to 2D results, the addition of PD98059 induced a significant amplification of osteogenic gene expression and matrix mineralization in 3D cultures. The inhibition of ERK altered cell-mediated compaction, proliferation, and resulted in the development of distinct tissue microstructure. Therefore, we suggest that the ability to reorganize collagen in 3D is an important step in ERK-mediated osteogenic differentiation. This work aims to propose a correlation between osteogenic differentiation and hMSC-directed collagen I remodeling. We present a potential mechanistic link (ERK) through which the three dimensionality of an engineered tissue acts to differentially induce and maintain cellular phenotype during tissue development.

ECM-Aware Cell-Graph Mining for Bone Tissue Modeling and Classification.

Pathological examination of a biopsy is the most reliable and widely used technique to diagnose bone cancer. However, it suffers from both inter- and intra- observer subjectivity. Techniques for automated tissue modeling and classification can reduce this subjectivity and increases the accuracy of bone cancer diagnosis. This paper presents a graph theoretical method, called extracellular matrix (ECM)-aware cell-graph mining, that combines the ECM formation with the distribution of cells in hematoxylin and eosin (H&E) stained histopathological images of bone tissues samples. This method can identify different types of cells that coexist in the same tissue as a result of its functional state. Thus, it models the structure-function relationships more precisely and classifies bone tissue samples accurately for cancer diagnosis. The tissue images are segmented, using the eigenvalues of the Hessian matrix, to compute spatial coordinates of cell nuclei as the nodes of corresponding cell-graph. Upon segmentation a color code is assigned to each node based on the composition of its surrounding ECM. An edge is hypothesized (and established) between a pair of nodes if the corresponding cell membranes are in physical contact and if they share the same color. Hence, multiple colored-cell-graphs coexist in a tissue each modeling a different cell-type organization. Both topological and spectral features of ECM-aware cell-graphs are computed to quantify the structural properties of tissue samples and classify their different functional states as healthy, fractured, or cancerous using support vector machines. Classification accuracy comparison to related work shows that ECM-aware cell-graph approach yields 90.0% whereas Delaunay triangulation and simple cell-graph approach achieves 75.0% and 81.1% accuracy, respectively.

Multiway modeling and analysis in stem cell systems biology.

BACKGROUND: Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. RESULTS: We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link x gene ontology category x osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs x osteogenic stimulus x replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate. CONCLUSION: Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.

Osteogenic differentiation of mesenchymal stem cells in defined protein beads.

There is a need to develop improved methods for directing and maintaining the differentiation of human mesenchymal stem cells (hMSC) for regenerative medicine. Here, we present a method for embedding cells in defined protein microenvironments for the directed osteogenic differentiation of hMSC. Composite matrices of collagen I and agarose were produced by emulsification and simultaneous polymerization in the presence of hMSC to produce 30-150 mum diameter hydrogel "beads." The proliferation, morphology, osteogenic gene expression, and calcium deposition of hMSC in bead environments were compared to other two- and three-dimensional culture environments over 14-21 days in culture. Cells embedded within 40% collagen beads exhibited equivalent proliferation rates to those in gel disks, but showed upregulation of bone sialoprotein and increased calcium deposition over 2D controls. Osteocalcin gene expression was not changed in 3D beads and disks, while collagen type I gene expression was downregulated relative to cells in 2D culture. The hydrogel bead format allows controlled cell differentiation and is a cell delivery vehicle that may also enhance vascular invasion and host incorporation. Our results indicate that the application of such beads can be used to promote the osteogenic phenotype in hMSC, which is an important step toward using them in bone repair applications.

Dissection of the osteogenic effects of laminin-332 utilizing specific LG domains: LG3 induces osteogenic differentiation, but not mineralization.

The overall mechanisms governing the role of laminins during osteogenic differentiation of human mesenchymal stem cells (hMSC) are poorly understood. We previously reported that laminin-332 induces an osteogenic phenotype in hMSC and does so through a focal adhesion kinase (FAK) and extracellular signal-related kinase (ERK) dependent pathway. We hypothesized that this is a result of integrin-ECM binding, and that it occurs via the known alpha3 LG3 integrin binding domain of laminin-332. To test this hypothesis we cultured hMSC on several different globular domains of laminin-332. hMSC adhered best to the LG3 domain, and this adhesion maximally activated FAK and ERK within 120 min. Prolonged culturing (8 or 16 days) of hMSC on LG3 led to activation of the osteogenic transcription factor Runx2 and expression of key osteogenic markers (osterix, bone sialoprotein 2, osteocalcin, alkaline phosphatase, extracellular calcium) in hMSC. LG3 domain binding did not increase matrix mineralization, demonstrating that the LG3 domain alone is not sufficient to induce complete osteogenic differentiation in vitro. We conclude that the LG3 domain mediates attachment of hMSC to laminin-332 and that this adhesion recapitulates most, but not all, of the osteogenic differentiation associated with laminin-5 binding to hMSC.

Phosphorylation of focal adhesion kinase promotes extravasation of breast cancer cells.

Inhibition of focal adhesion kinase (FAK) delays transendothelial migration of breast cancer cells. Here we investigate whether phosphorylation of specific tyrosine residues of FAK (397, 861, and 925) known to control aspects of cell migration on extracellular matrix (ECM), are also involved in transendothelial migration. AU-565 and MDA-MB-231 cells expressing Phe397 FAK show delayed or decreased transendothelial migration, demonstrating the involvement of the FAK autophosphorylation site. Only MDA-MB-231 cells expressing Phe861 FAK exhibit delayed transendothelial migration. Neither MDA-MB-231 nor AU-565 cells expressing Phe925 FAK show a change in transendothelial migration compared to untreated cancer cells. These findings suggest that modified signaling mechanisms regulate cancer cell migration through an endothelial monolayer versus those involved in cell migration on or through ECM.

Phenylboronic acid selectively inhibits human prostate and breast cancer cell migration and decreases viability.

We compared the in vitro effect of boric acid (BA) versus phenylboronic acid (PBA) on the migration of prostate and breast cancer cell lines and non-tumorigenic cells from the same tissues. Treatment at 24 hours with BA (< or =500 microM) did not inhibit chemotaxis on fibronectin in any cell line. However, treatment over the same time course with concentrations of PBA as low as 1 muM significantly inhibited cancer cell migration without effecting non-tumorigenic cell lines. The compounds did not affect cell adhesion or viability at 24 hours but did alter morphology; both decreased cancer cell viability at eight days. These results suggest that PBA is more potent than BA in targeting the metastatic and proliferative properties of cancer cells.

Proteomics reveals multiple routes to the osteogenic phenotype in mesenchymal stem cells.

BACKGROUND: Recently, we demonstrated that human mesenchymal stem cells (hMSC) stimulated with dexamethazone undergo gene focusing during osteogenic differentiation (Stem Cells Dev 14(6): 1608-20, 2005). Here, we examine the protein expression profiles of three additional populations of hMSC stimulated to undergo osteogenic differentiation via either contact with pro-osteogenic extracellular matrix (ECM) proteins (collagen I, vitronectin, or laminin-5) or osteogenic media supplements (OS media). Specifically, we annotate these four protein expression profiles, as well as profiles from naïve hMSC and differentiated human osteoblasts (hOST), with known gene ontologies and analyze them as a tensor with modes for the expressed proteins, gene ontologies, and stimulants. RESULTS: Direct component analysis in the gene ontology space identifies three components that account for 90% of the variance between hMSC, osteoblasts, and the four stimulated hMSC populations. The directed component maps the differentiation stages of the stimulated stem cell populations along the differentiation axis created by the difference in the expression profiles of hMSC and hOST. Surprisingly, hMSC treated with ECM proteins lie closer to osteoblasts than do hMSC treated with OS media. Additionally, the second component demonstrates that proteomic profiles of collagen I- and vitronectin-stimulated hMSC are distinct from those of OS-stimulated cells. A three-mode tensor analysis reveals additional focus proteins critical for characterizing the phenotypic variations between naïve hMSC, partially differentiated hMSC, and hOST. CONCLUSION: The differences between the proteomic profiles of OS-stimulated hMSC and ECM-hMSC characterize different transitional phenotypes en route to becoming osteoblasts. This conclusion is arrived at via a three-mode tensor analysis validated using hMSC plated on laminin-5.