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Regenerative Medicine Market Analysis Growth Demand, Key Players, Share Size, and Forecast To 2025 – Monroe Scoop

Regenerative Medicine Market: Snapshot

Regenerative medicine is a part of translational research in the fields of molecular biology and tissue engineering. This type of medicine involves replacing and regenerating human cells, organs, and tissues with the help of specific processes. Doing this may involve a partial or complete reengineering of human cells so that they start to function normally.

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Regenerative medicine also involves the attempts to grow tissues and organs in a laboratory environment, wherein they can be put in a body that cannot heal a particular part. Such implants are mainly preferred to be derived from the patients own tissues and cells, particularly stem cells. Looking at the promising nature of stem cells to heal and regenerative various parts of the body, this field is certainly expected to see a bright future. Doing this can help avoid opting for organ donation, thus saving costs. Some healthcare centers might showcase a shortage of organ donations, and this is where tissues regenerated using patients own cells are highly helpful.

There are several source materials from which regeneration can be facilitated. Extracellular matrix materials are commonly used source substances all over the globe. They are mainly used for reconstructive surgery, chronic wound healing, and orthopedic surgeries. In recent times, these materials have also been used in heart surgeries, specifically aimed at repairing damaged portions.

Cells derived from the umbilical cord also have the potential to be used as source material for bringing about regeneration in a patient. A vast research has also been conducted in this context. Treatment of diabetes, organ failure, and other chronic diseases is highly possible by using cord blood cells. Apart from these cells, Whartons jelly and cord lining have also been shortlisted as possible sources for mesenchymal stem cells. Extensive research has conducted to study how these cells can be used to treat lung diseases, lung injury, leukemia, liver diseases, diabetes, and immunity-based disorders, among others.

Global Regenerative Medicine Market: Overview

The global market for regenerative medicine market is expected to grow at a significant pace throughout the forecast period. The rising preference of patients for personalized medicines and the advancements in technology are estimated to accelerate the growth of the global regenerative medicine market in the next few years. As a result, this market is likely to witness a healthy growth and attract a large number of players in the next few years. The development of novel regenerative medicine is estimated to benefit the key players and supplement the markets growth in the near future.

Global Regenerative Medicine Market: Key Trends

The rising prevalence of chronic diseases and the rising focus on cell therapy products are the key factors that are estimated to fuel the growth of the global regenerative medicine market in the next few years. In addition, the increasing funding by government bodies and development of new and innovative products are anticipated to supplement the growth of the overall market in the next few years.

On the flip side, the ethical challenges in the stem cell research are likely to restrict the growth of the global regenerative medicine market throughout the forecast period. In addition, the stringent regulatory rules and regulations are predicted to impact the approvals of new products, thus hampering the growth of the overall market in the near future.

Global Regenerative Medicine Market: Market Potential

The growing demand for organ transplantation across the globe is anticipated to boost the demand for regenerative medicines in the next few years. In addition, the rapid growth in the geriatric population and the significant rise in the global healthcare expenditure is predicted to encourage the growth of the market. The presence of a strong pipeline is likely to contribute towards the markets growth in the near future.

Global Regenerative Medicine Market: Regional Outlook

In the past few years, North America led the global regenerative medicine market and is likely to remain in the topmost position throughout the forecast period. This region is expected to account for a massive share of the global market, owing to the rising prevalence of cancer, cardiac diseases, and autoimmunity. In addition, the rising demand for regenerative medicines from the U.S. and the rising government funding are some of the other key aspects that are likely to fuel the growth of the North America market in the near future.

Furthermore, Asia Pacific is expected to register a substantial growth rate in the next few years. The high growth of this region can be attributed to the availability of funding for research and the development of research centers. In addition, the increasing contribution from India, China, and Japan is likely to supplement the growth of the market in the near future.

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Global Regenerative Medicine Market: Competitive Analysis

The global market for regenerative medicines is extremely fragmented and competitive in nature, thanks to the presence of a large number of players operating in it. In order to gain a competitive edge in the global market, the key players in the market are focusing on technological developments and research and development activities. In addition, the rising number of mergers and acquisitions and collaborations is likely to benefit the prominent players in the market and encourage the overall growth in the next few years.

Some of the key players operating in the regenerative medicine market across the globe areVericel Corporation, Japan Tissue Engineering Co., Ltd., Stryker Corporation, Acelity L.P. Inc. (KCI Licensing), Organogenesis Inc., Medtronic PLC, Cook Biotech Incorporated, Osiris Therapeutics, Inc., Integra Lifesciences Corporation, and Nuvasive, Inc.A large number of players are anticipated to enter the global market throughout the forecast period.

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Regenerative Medicine Market Analysis Growth Demand, Key Players, Share Size, and Forecast To 2025 - Monroe Scoop

Autologous Stem Cell And Non-Stem Cell Based Therapies Market 2020-2025 || Leading Players Fibrocell, Genesis Biopharma, Georgia Health Sciences…

Todays businesses call for the highly focused, comprehensive and detail-oriented information about the market so that they get a clear idea about the market landscape. The Autologous Stem Cell And Non-Stem Cell Based Therapies market research report is generated with a combination of detailed industry insights, and use of latest tools and technology. The study of this market research report covers a market attractiveness analysis, wherein each segment is targeted based on its market size, growth rate, and general attractiveness. The Autologous Stem Cell And Non-Stem Cell Based Therapies market research report plays a key role in developing the strategies for sales, advertising, marketing, and promotion.

TheGlobalAutologous Stem Cell and Non-Stem Cell Based Therapies Marketis expected to reach USD113.04 billion by 2025, from USD 87.59 billion in 2017 growing at a CAGR of 3.7% during the forecast period of 2018 to 2025. The upcoming market report contains data for historic years 2015 & 2016, the base year of calculation is 2017 and the forecast period is 2018 to 2025.

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Some of the major players operating in the global autologous stem cell and non-stem cell based therapies market areAntria (Cro), Bioheart, Brainstorm Cell Therapeutics, Cytori, Dendreon Corporation, Fibrocell, Genesis Biopharma, Georgia Health Sciences University, Neostem, Opexa Therapeutics, Orgenesis, Regenexx, Regeneus, Tengion, Tigenix, Virxsys and many more.

Market Definition:Global Autologous Stem Cell and Non-Stem Cell Based Therapies Market

In autologous stem-cell transplantation persons own undifferentiated cells or stem cells are collected and transplanted back to the person after intensive therapy. These therapies are performed by means of hematopoietic stem cells, in some of the cases cardiac cells are used to fix the damages caused due to heart attacks. The autologous stem cell and non-stem cell based therapies are used in the treatment of various diseases such as neurodegenerative diseases, cardiovascular diseases, cancer and autoimmune diseases, infectious disease.

According to World Health Organization (WHO), cardiovascular disease (CVD) causes more than half of all deaths across the European Region. The disease leads to death or frequently it is caused by AIDS, tuberculosis and malaria combined in Europe. With the prevalence of cancer and diabetes in all age groups globally the need of steam cell based therapies is increasing, according to article published by the US National Library of Medicine National Institutes of Health, it was reported that around 382 million people had diabetes in 2013 and the number is growing at alarming rate which has increased the need to improve treatment and therapies regarding the diseases.

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Market Segmentation:Global Autologous Stem Cell and Non-Stem Cell Based Therapies Market

Competitive Analysis:Global Autologous Stem Cell and Non-Stem Cell Based Therapies Market

The global autologous stem cell and non-stem cell based therapies market is highly fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market. The report includes market shares of autologous stem cell and non-stem cell based therapies market for global, Europe, North America, Asia Pacific and South America.

Major Autologous Stem Cell and Non-Stem Cell Based Therapies Market Drivers and Restraints:

Introduction of novel autologous stem cell based therapies in regenerative medicine

Reduction in transplant associated risks

Prevalence of cancer and diabetes in all age groups

High cost of autologous cellular therapies

Lack of skilled professionals

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Autologous Stem Cell And Non-Stem Cell Based Therapies Market 2020-2025 || Leading Players Fibrocell, Genesis Biopharma, Georgia Health Sciences...

Why Aimmune Therapeutics Shares Fell 23.3% in February – Nasdaq

What happened

Shares of Aimmune Therapeutics (NASDAQ: AIMT) fell 23.3% in February, according to data provided by S&P Global Market Intelligence, as the launch of its new peanut allergy treatment took time to unfold.

Aimmune rose 40% last year as investors anticipated Palforzia, the firsttreatment approved by the Food and Drug Administration for peanut allergy in children. The regulatory agency approved the treatment on Jan. 31, and now investors are waiting to see how the first weeks of sales progress. The process is taking time because of the risk management procedure involved in the launch.

Image source: Getty Images.

Palforzia, an orally administered powder made of peanut protein, works by desensitizing patients to the allergen. In order to lower risk in case a new patient suffers a reaction to the therapy, the FDA has set up the Risk Evaluation and Mitigation Strategy (REMS) program. Physicians and patients must enroll in REMS and follow guidelines before treatment can begin. This process, along with the FDA's standard procedure of examining and releasing the first batches of biologic product, lengthened the timeline from approval to sales. Aimmune said during its recent earnings call that it expects to record the first Palforzia sales this month.

Getting physicians and patients on board in the next few months will be crucial for Aimmune. DBVTechnologies (NASDAQ: DBVT) is close behind, with an FDA decision on its peanut allergy drug expected in August. Aimmune now has the advantage of being first to market, before rivals enter with competing products. Aimmune is also expecting a decision on Palforzia from the Europeanregulatory agency in the fourth quarter, and said a decision in Switzerland could come in mid-2021.

All of these elements represent catalysts for the shares over the next year or so. If Aimmune can assure its position as market leader, the shares of this biotech company will benefit in the long term.

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Why Aimmune Therapeutics Shares Fell 23.3% in February - Nasdaq

Mapping the structure and biological functions within mesenchymal bodies using microfluidics – Science Advances

INTRODUCTION

In recent years, organoids have emerged as powerful tools for basic research, drug screening, and tissue engineering. The organoids formed in vitro show many features of the structural organization and the functional hallmarks of adult or embryonic anatomical structures (1). In addition, the formation of organoids alleviates the need to perform animal studies and provides an attractive platform for robust quantitative studies on the mechanisms regulating organ homeostasis and tissue repair in vivo (1). The formation of organoids usually starts with populations of stem cells. They are therefore expected to be heterogeneous because pluripotent stem cells [induced pluripotent stem cells (pscs) or embryonic stem cells] have been shown to dynamically and stochastically fluctuate from ground to differentiated state (2). In the same vein, LGR5+ intestinal stem cells are reported to contain several distinct populations (3). As such, the formation of organoids involves the inherent capacity of these heterogeneous populations to self-sort and self-pattern to form an organized three-dimensional (3D) architecture (4). However, the rules underlying organoid formation as well as the contribution of intrinsic population heterogeneity to the organoid self-assembly remain poorly understood (5). Consequently, there is a need for novel quantitative approaches at the single-cell level to reliably understand the mechanisms of spatial tissue patterning in 3D organoids, for which microfluidic and quantitative image analysis methods are well suited.

In this work, we use mesenchymal progenitors, alternatively named mesenchymal stromal cells (MSCs), which constitute a self-renewing population with the ability to differentiate into adipocytes, chondrocytes, and osteoblasts (5). Although human MSCs (HMSCs) express high levels of undifferentiation markers (e.g., CD105, CD44, CD73), they constitute a heterogeneous population of cells that exhibit considerable variation in their biophysical properties and epigenetic status, as well as the basal level of expression of genes related to differentiation, immunoregulation, and angiogenesis (6, 7). Nonetheless, their aggregation leads to the formation of highly cohesive 3D spherical structures [which we designate hereafter as mesenchymal bodies (MBs)] with improved biological activities in comparison to 2D cultures (8). However, little is known on how HMSCs self-organize or whether the intrinsic heterogeneity of the population regulates MB formation and individual cell functions in 3D.

The self-aggregation of HMSCs into MBs can recapitulate the early stages of mesenchymal condensation, and it promotes the secretion of paracrine molecules taking part in the process of ossification (9). During mesenchymal condensation in vivo, mesenchymal progenitors self-aggregate and form dense cell-cell contacts that lead to the initiation of bone organogenesis through endochondral (necessitating a chondrogenic intermediate) and intramembranous (direct osteogenic differentiation) ossification (10). In addition, the formation of these 3D MBs in vivo is associated with the secretion of important paracrine molecules such as prostaglandin E2 (PGE2) and vascular endothelial growth factor (VEGF), which participate in the recruitment of endogenous osteoblasts, osteoclasts, and blood vessels, leading to the initiation/restoration of bone homeostasis (11, 12). In these two ossification processes, the induction of nuclear factor B (NF-B) target genes, such as cyclooxygenase-2 (COX-2), and their downstream products (e.g., PGE2 and VEGF) plays a critical role as developmental regulators of ossification and bone healing (13). However, while mesenchymal condensation is critical for bone organogenesis, there is still a limited understanding on how the cellular spatial organization within 3D MBs regulates the individual cells endocrine functions (14).

In the present work, we interrogate the influence of phenotypic heterogeneity within a population of stem cells on the mechanisms of self-assembly and functional patterning within 3D organoids using HMSCs as a model of heterogeneous progenitor cell population. This is performed using a novel microfluidic platform for high-density formation of mensenchymal bodies, combined with the analysis of individual cells by quantitative image analysis. Our study reveals that the progenitor cell population self-assembles in a developmentally hierarchical manner. We also find that the structural arrangement in mensenchymal bodies is linked with the functional patterning in 3D, through a modulation of the activity of regulatory molecular signaling at a local scale. This study demonstrates the interplay between cell size and differentiation status, which mediates cellular spatial rearrangement in 3D, leading to the regionalized activation of unique biological functions while forming aggregates.

HMSCs are known to constitute a heterogeneous population (6, 7). In this study, fetal HMSCs were derived from the Whartons jelly of the umbilical cord (UC). UC-derived HMSCs are considered to be more primitive than HMSCs derived from adult bone marrow because of their higher proliferative capacity, their ability to form colony-forming unitfibroblast, as well as their lower degree of basal commitment (15). To examine the cellular diversity within the population, HMSCs were first characterized by their expression of membrane markers. Most of the HMSC population consistently expresses CD73, CD90, CD105, and CD146, but not CD31 (an endothelial cell marker), CD34 (a hematopoietic cell marker), CD14 (an immune cell marker), or human leukocyte antigenDR (HLA-DR) (a type of major histocompatibility complex II) (Fig. 1, A to F, and fig. S1, A to C). However, a deeper analysis of the flow cytometric data shows that the HMSC population contains cells of heterogeneous size [coefficient of variation (CV) = 33 to 37%] (Fig. 1, G and I), having a broad distribution in the expression of CD146 (Fig. 1F). Of note, the CD146 level of expression was linked to the size of the cells: The highest levels of CD146 were found for the largest cells (Fig. 1, H and J). Similar correlations with cell size were also observed for CD73, CD90, and CD105 (fig. S1, D to F). In addition, upon specific induction, the HMSC population used in this study successfully adopted an adipogenic (Fig. 1K), an osteogenic (Fig. 1L), or a chondrogenic (Fig. 1M) phenotype, demonstrating their mesenchymal progenitor identity.

(A) Percentage of positive cells for CD31, CD73, CD90, CD105, and CD146 (n = 3). Representative histograms of the distribution of the CD31 (B), CD73 (C), CD90 (D), CD105 (E), and CD146 (F) level of expression are shown. (G) Representative histogram of the forward scatter (FSC) distribution. (H) Correlation between cell size [FSC and side scatter (SSC)] and the level of CD146 expression. (I) Representative histogram of the cell projected area distribution. (J) Representative histogram of the size distribution of the CD146dim, CD146int, and CD146bright (ImageSteam analysis). (K) Representative images of hMSCs differentiated toward adipogenic lineage (Oil Red O staining). (L) Representative images of UC-hMSCs differentiated toward osteogenic lineage in (Alizarin Red S staining). (M) Representative images of UC-hMSCs differentiated toward chondrogenic lineage (Alcian Blue staining in 2D and cryosectioned micromass cultures). Scale bars, 50 m. The images were acquired using a binocular. FITC-A, fluorescein isothiocyanateA; APC-A, allophycocyanin-A.

To interrogate contribution of cellular heterogeneity (i.e., in terms of size and levels of CD marker expression) in the self-organization of HMSCs in 3D, MBs were formed at high density on an integrated microfluidic chip. This was done by encapsulating cells into microfluidic droplets at a density of 380 cells per droplet, with a CV of 24% (fig. S2, A and B). The drops were then immobilized in 250 capillary anchors in a culture chamber, as previously described (Fig. 2, A and B) (16). The loading time for the microfluidic device was about 5 min, after which the typical time for complete formation of MBs was about 4 hours (movie S1), as obtained by measuring the time evolution of the projected area (Fig. 2, C and D) and circularity of individual MBs (Fig. 2E and movie S2). The protocol resulted in the formation of a single MB per anchor (fig. S2C) with an average diameter of 158 m (Fig. 2F), when starting with a seeding concentration of 6 106 cells ml1. The diameter of the aggregates can easily be tuned by modulating the concentration of cells in the seeding solution (fig. S2, A and B). In addition, the complete protocol yielded the reproducible formation of a high-density array of fully viable MBs ready for long-term culture (for the images of the individual fluorescent channel, see Fig. 2G and fig. S2D), as described previously (16). Of interest, the CV of the MB diameter distribution was lower than the CV of the individual cell size and of the cell number in droplets (CV MB diameter = 13.3%, CV cell number per drop = 24%, and CV cell size = 35%), which demonstrates that the production of MBs leads to more homogeneous size conditions, compared with the broad heterogeneity in the cell population.

(A) Chip design. Scale bar, 1 cm. (B) Schematized side view of an anchor through the MB formation and culture protocol. (C) Representative time lapse of an MB formation. Scale bar, 100 m. (D and E) Measurement of the time evolution of the projected area (D) and circularity of each aggregate (E). n = 120 MBs. (F) Distribution of the MB diameter normalized by the mean of each chip (n = 10,072 MBs). (G) Top: Representative images of MBs after agarose gelation and oil-to-medium phase change. Bottom: The same MBs are stained with LIVE/DEAD. Scale bar, 100 m. (H) Representative images of MBs formed in the presence of EDTA, an N-cadherin, or a CD146-conjugated blocking antibody (Ab) (the red color shows the position of the CD146 brightest cells, and the dilution of the antibody was 1/100 and remain in the droplet for the whole experiment). Scale bar, 100 m. The images were acquired using a wide-field microscope.

To gain insight into the cellular components required to initiate the self-organization of HMSCs in 3D, the MB formation was disrupted by altering cell-cell interactions. This was first performed by adding EDTA, a chelating agent of the calcium involved in the formation of cadherin junctions, to the droplet contents. Doing so disrupted the MB formation, as shown in Fig. 2H, where the projected area of the cells increased and the circularity decreased in the presence of EDTA compared with the controls, as previously reported (17). The role of N-cadherins among different types of cadherins was further specified by adding a blocking antibody in the droplets before MB formation. This also led to a disruption of the MB formation, demonstrating that N-cadherin homodimeric interactions are mandatory to initiate the process of HMSC aggregation. CD146 [melanoma cell adhesion molecule (M-CAM)] plays important dual roles: as an adhesion molecule (that binds to Laminin 411) (18) and a marker of the commitment of HMSCs (19). We, thus, interrogate its contribution to MB formation. The addition of a CD146-conjugated blocking antibody also disrupted the formation of the MB (Fig. 2H), demonstrating that cell-cell interactions involving CD146 are also required during MB formation, as reported with other cell types (18). Of note, the brightest signal from the CD146-stained cells was located in the core of the cellular aggregates (Fig. 2H), suggesting that HMSCs self-organize relatively to their degree of commitment.

We found that the population of HMSCs constituted of cells of broad size and expressing different levels of undifferentiated markers [i.e., CD90, CD73, CD105, and CD146 are known to be down-regulated upon differentiation; (20)] and that the cells are capable of self-organizing cohesively in 3D. To better understand how the heterogeneous cells organized within the MBs, we measured how the different cell types composing the population self-assembled spatially in 3D by investigating the role of CD146. For this purpose, the CD146dim and CD146bright cells were separated from the whole HMSC population by flow cytometry (Fig. 3, A and B). The cells were then reseeded on a chip for the MB formation after fluorescently labeling the brighter and/or the dimmer CD146 populations. Image analysis revealed that the CD146bright cells were mostly located in the center of the cellular aggregates, while CD146dim cells were found at the boundaries of the MBs (Fig. 3, C to E, figs. S3A and S5A for confocal images, and movie S1). This organization was stable for a 3-day culture (fig. S3B).

(A) Representative dot plot of the hMSC population separation based on the level of CD146: The CD146dim constitutes 20% of the population expressing the highest levels of CD146; the CD146bright constitutes the 20% of the population expressing the lowest levels of CD146. (B) Fluorescence signal distribution in the CD146dim and CD146bright populations after cell sorting. (C) After cell sorting, the CD146bright or the CD146dim was stained with Vybrant Dil (red) or Vybrant DiO (green), remixed together and allowed to form MBs. Representative images of the CD146bright and CD146dim within the MBs. Scale bar, 100 m (n = 185 MBs). (D) The position of the CD146bright and CD146dim was quantified by correlating the fluorescence signal of the different stained cells as a function of their radial position within the MBs, after the staining of individual population with Vybrant Dil (CD146bright) = 500 and CD146dim (MBs; CD146bright = 85). Error bars show the SD. (E) Schematized representation of the structural organization of MBs. (F and G) RT-qPCR analysis of the relative RUNX-2, CEBP/, and SOX-9 expression to glyceraldehyde-3-phosphate dehydrogenase (GADPH) [Ct (cycle threshold) (D) and relative RNA expression (E)] in the CD146bright and CD146dim populations (n = 3). *P < 0.05; **P < 0.01; ***P < 0.001.

As we found that the CD146bright cells were larger than the CD146dim cells, the cells from the HMSC population were also separated on the basis of their relative size (a parameter that also discriminates the CD90, CD105, and CD73bright from the CD90, CD105, and CD73dim cells; fig. S1, D to F). After reseeding on the chip, the MBs were composed of large cells in the core, while the smallest cells were located at the boundaries, as expected from the previous experiments (fig. S3A). Moreover, we found that the speed of self-assembly of each population is not related to the rearrangement of CD146dim and CD146bright cells in 3D, because the mixing of dissociated cells or the fusion of aggregates made each population give rise to the same structural organization (21). It is well established that CD146bright defines the most undifferentiated HMSCs (20). The heterogeneity in level of commitment between the two subpopulations was therefore checked by reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis to quantify differences in the expression of differentiation markers. The analysis showed that the CD146dim cells expressed higher levels of osteogenic differentiation markers (i.e., RUNX-2) than the CD146bright cells (Fig. 3, F and G).

The level of RUNX-2 expression was also quantified at the protein level using immunocytochemistry and image analysis of the MBs on the microfluidic device by developing a layer-by-layer description of the MBs. This mapping was constructed by estimating the boundaries of each cell in the image from a Voronoi diagram, built around the positions of the cell nuclei stained with 4,6-diamidino-2-phenylindole (DAPI) (Fig. 4A) (22). These estimates were then used to associate the fluorescence signal from each cell with one of the concentric layers (Fig. 4B). Such a mapping provides better resolution for discriminating the spatial heterogeneity of protein expression than simply assigning a fluorescence signal to a defined radial coordinate (fig. S4). Moreover, the reliability of the measurements by quantitative image analysis was confirmed by performing several control experiments. In particular, we verified (i) the specificity of the fluorescence labeling, (ii) the absence of limitation for antibody diffusion, and (iii) the absence of the light path alteration in the 3D structure (fig. S5 and Materials and Methods). Consistent with the qPCR data, we found that HMSCs located at the boundaries of the MBs expressed higher levels of the protein RUNX-2 than the cells located in the core (see Fig. 4, C and D, and fig. S7 for individual experiments).

(A and B) The detection of nuclei within MBs enables the construction of a Voronoi diagram (A) that allows the identification of concentric cell layers (B) within the MBs. (C and D) Representative image (C) and quantitative analysis (D) (error bars represent the SD) of RUNX-2 staining within the cell layers of the MB (Nchips = 3 and nMBs = 458). N.S., nonsignificant. (E to H) Quantitative analysis (E) and representative images (F to H) of N-cadherin staining after methanol/acetone (F) (Nchips = 3 and nMBs = 405), after PFA/Triton X-100 fixation and permeabilization (G) (Nchips = 3 and nMBs = 649), and F-actin staining with phalloidin (H) (Nchips = 3 and nMBs = 421). Scale bars, 20 m. The images were acquired using a wide-field microscope. ***P < 0.001. (I) Schematized representation of the structural organization of MBs.

Thus, as CD146 defines the most undifferentiated and clonogenic cells as well as regulates the trilineage differentiation potential of HMSCs, the results indicate that HMSCs self-organize within MBs based on their initial commitment. The most undifferentiated and largest cells are found in the core (r/R < 0.8), while more differentiated cells positioned in the outer layers of the MBs (r/R > 0.8) (Fig. 4, C to E). In addition, these data reveal that HMSCs are conditioned a priori to occupy a specific location within the MBs.

The commitment of HMSCs is known to regulate their level of CD146 expression and the type of cell-cell adhesion molecules (23), which plays a fundamental role in the structural cohesion of the MBs (Fig. 2H). For this reason, we interrogated the organization of cell-cell junctions after the MB formation through measurements of the N-cadherin and F-actin fluorescence signal distribution. Two different protocols were used to discriminate several forms of N-cadherin interactions. First, paraformaldehyde (PFA) fixation and Triton X-100 permeabilization were used, because they were reported to retain in place only the detergent-insoluble forms of N-cadherin. Alternatively, ice-cold methanol/acetone fixation and permeabilization enabled the detection of all forms of N-cadherins (26). The results show a higher density of total N-cadherins in the core of the MBs (Fig. 4, E and F), while a higher density of F-actin was found in the cell layers located near the edge of the MBs (Fig. 4, E and H). The pattern of F-actin distribution was not related to the agarose gel surrounding the MBs (fig. S5B). These results are consistent with the theories of cell sorting in spheroids that postulate that more adhesive cells (i.e., expressing more N-cadherin or CD146) should be located in the core, while more contractile cells (i.e., containing denser F-actin) are located at the edge of the MBs (24). Moreover, our observations are in accordance with recent results demonstrating that HMSCs establishing higher N-cadherin interactions show reduced osteogenic commitment than HMSCs making fewer N-cadherin contacts, potentially through the modulation of Yap/Taz signaling and cell contractility (23).

In contrast, the most triton-insoluble forms of N-cadherins were located at the boundaries of the HMSC aggregates (Fig. 4, E and G), at the same position as the cells containing the denser F-actin. These results demonstrate that different types of cellular interactions were formed between the core and the edges of the MBs, which correlated with the degree of cell commitment that apparently stabilize the adherens junctions (Fig. 4I) (25).

We found above that the degree of commitment was linked with the pattern of HMSC self-organization in MBs (i.e., formation of adherens junctions), which may also regulate their paracrine functions (26). We therefore interrogated the functional consequences of the cellular organization in MBs by investigating the distribution of VEGF- and PGE2-producing cells.

The specific production of COX-2, VEGF, and two other molecules regulating bone homeostasis such as tumor necrosis factorinducible gene 6 (TSG-6) (27) and stanniocalcin 1 (STC-1) (28) was evaluated by RT-qPCR analysis. An increased transcription (20- to 60-fold) of these molecules was measured in 3D in comparison to the monolayer culture (Fig. 5, A and B). Consistent with this observation, while a very limited level of secreted PGE2 and VEGF was measured by enzyme-linked immunosorbent assay (ELISA) in 2D culture, they were significantly increased (by about 15-fold) upon the aggregation of HMSCs in 3D (Fig. 5C). In addition, to interrogate the specific role of COX-2 [the only inducible enzyme catalyzing the conversion of arachidonic acid into prostanoids; (29)] in PGE2 and VEGF production, indomethacin (a pan-COX inhibitor) was added to the culture medium. Indomethacin abrogated the production of PGE2, and it significantly decreased VEGF secretion (Fig. 5C), which suggests an intricate link between COX-2 expression and the secretion of these two molecules (30, 31).

(A and B) RT-qPCR analysis of the relative TSG-6, COX-2, STC-1, and VEGF expression to GADPH (Ct) (A) and relative RNA expression (B) in the 3D and 2D populations (n3D = 3 and n2D = 3). (C) Quantification by ELISA of the PGE-2 and VEGF secreted by hMSCs cultivated in 2D, as MBs or as MBs treated with indomethacin (nchips = 3 and n2D = 3). (D and E) Representative image (D) and quantitative analysis (E) of COX-2 (Nchips = 13 and nMBs = 2936) and (F) VEGF-A (Nchips = 3 and nMBs = 413) staining within the cell layers of the MBs (error bars represent the SD). Scale bars, 50 m. The images were acquired using a wide-field microscope *P < 0.05; ***P < 0.001; a and b: P < 0.05. (G) Schematized representation of the structural organization of MBs.

To further interrogate the link between the COX-2 and the VEGF-producing cells, their location was analyzed by quantitative image analysis at a layer-by-layer resolution. These measurements showed significantly higher levels of COX-2 in the first two layers, compared with the successive layers of the MBs (Fig. 5, D and E), with a continuous decrease of about 40% of the COX-2 signal between the edge and the core. This pattern of COX-2 distribution was not affected by the MB diameter (fig. S7B). Similar observations were made with VEGF (Fig. 5, D and F), demonstrating that cells at the boundaries of the MBs expressed both COX-2 and VEGF (Fig. 5G). Taken with the measurements of Fig. 5C, these results imply that COX-2 acts as an upstream regulator of PGE2 and VEGF secretion. Conversely, oxygen deprivation was unlikely to occur within the center of the MBs because no hypoxic area was detected through the whole MBs (fig. S5). Consequently, it is unlikely that hypoxia-inducible factor1 (HIF-1) signaling mediates the increase in VEGF expression at the boundaries of the MBs. Note that finding the link between these three molecules requires the 3D format, because the molecules are not detected in 2D. Here, the combination of population-scale measurements (Fig. 5C) and cell layer analysis (Fig. 5, E and F) provides strong evidence for this pathway.

Because variations of COX-2 and adherens junction distribution are colocalized within the MBs (Figs. 4, E to G, and 5, D and E), the results point to a link between the quality of cell-cell interactions and the spatial distribution of the COX-2high cells in 3D. The mechanisms leading to the spatial patterning of COX-2 expression in the MBs were therefore explored using inhibitors of the signaling pathways related to anti-inflammatory molecule production and of the molecular pathways regulating the structural organization (table S3): (i) 4-N-[2-(4-phenoxyphenyl)ethyl]quinazoline-4,6-diamine (QNZ) that inhibits NF-B, a critical transcription factor regulating the level of COX-2 expression (32); (ii) N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT) that inhibits the canonical Notch pathway, modulating cell-cell interactions and several differentiation pathways; (iii) Y-27632 (Y27) that inhibits ROCK involved in the bundling of F-actin (i.e., formation of stress fibers) to assess the role of actomyosin organization; and (iv) cytochalasin D (CytoD) that inhibits the polymerization of actin monomers.

While the addition of DAPT had virtually no effect on the ability of the cells to form MBs, Y27 led to MBs with more rounded cells, and both QNZ and CytoD strongly interfered with the MB formation process (Fig. 6, A to C). The results indicate that NF-B activation and the promotion of actin polymerization are critical signaling steps initiating the process of MB formation by HMSCs.

(A) Representative images of MBs formed 1 day after the droplet loading. Scale bar, 100 m. Inhibitors are added to the culture medium before the MB formation. (B and C) Quantitative analysis of the aggregates projected area (B) and shape index (C) in the presence of the different inhibitors. Red lines represent the mean value for each condition. (D and E) Representative images (D) (contrast is adjusted individually for a better visualization of the pattern; scale bar, 100 m; the images were acquired using a wide-field microscope) and quantitative analysis (E) of the COX-2 fluorescence signal intensity normalized by the control value with the different inhibitors. For these longer culturing times, QNZ and CytoD are only added during the phase change to allow the MB formation. Small dots represent one MB. Large dots represent the average normalized COX-2 fluorescence signal per chip. Each color corresponds to a specific chip. *P < 0.05. (F) Estimation of inhibitor effect in the cell layers with the COX-2 signal normalized by the control value. Control: Nchips = 11 and nMBs = 2,204; QNZ: Nchips = 6 and nMBs = 1215; DAPT: Nchips = 3 and nMBs = 658; Y27: Nchips = 4 and nMBs = 709; CytoD: Nchips = 3 and nMBs = 459. *P < 0.05; **P < 0.01; ***P < 0.001. (G) Proposed mechanisms regulating the MB formation and the patterning of their biological functions. (i) Regulation of the formation of MBs. (ii and iii) Spatial patterning of hMSC biological properties within MBs.

To assess the role of NF-B and actin polymerization in the pattern and the level of COX-2 expression in the MBs, QNZ and CytoD were added 1 day after the cell seeding, once the MBs were completely formed. In contrast, Y27 and DAPT were included in the initial droplets and maintained in the culture medium for the whole culture period. Typical images showing the COX-2 signal in these different conditions are shown in Fig. 6D (see also fig. S7 for quantification of the individual experiments). Of note, none of the inhibitors had an effect on Casp3 activation, indicating that they do not induce apoptosis at the concentration used in this study (fig. S8). The levels of COX-2 expression in MBs, after 3 days in culture, were significantly reduced with QNZ, also decreasing after the addition of CytoD (Fig. 6E). By contrast, Y27 and DAPT had no effect on the levels of COX-2 expression. As a consequence, the results demonstrate that a sustained NF-B activity after the MB formation is required to promote COX-2 expression. Moreover, the induction of actin polymerization in MBs constitutes a mandatory step to initiate COX-2 production.

To get a deeper understanding on the local regulation of these signaling pathways, we analyzed at the single-cell resolution the distribution of COX-2 within the MBs. The spatial mapping revealed that the COX-2 fluorescence intensity was mostly attenuated at the edge of the MBs treated with CytoD and QNZ, while more limited change in the pattern of its expression was observed in the presence of Y27 and even less so with DAPT (Fig. 6F). Consequently, the results revealed a strong link between cell phenotype, the capability to form functional adherens junctions, and the local regulation of NF-B and actin polymerization leading to the increased expression of PGE2 and VEGF that are mediated by COX-2 in 3D (Fig. 6G). Together, the results indicate that in 3D cell aggregates, the spatial organization has some implications on the specific activation of signaling pathways, resulting in local functional heterogeneity.

Understanding the mechanisms of the formation and the spatial tissue patterning within organoids requires a characterization at single-cell level in 3D. In this study, we used a novel microfluidic and epifluorescence imaging technology to obtain a precise quantitative mapping of the structure, the position, and the link with individual cell functions within MBs. The image analysis provided quantitative data that were resolved on the scale of the individual cells, yielding measurements on 700,000 cells in situ within over 10,000 MBs.

While the microfluidic technology developed here is very efficient for high-density size-controlled MB formation, the method is prone to some limitations. Chief among them, the cultivation in nanoliter-scale drops may subject the cells to nutrient deprivation and by-product accumulation under static culture conditions. This limits the duration of the culture to a few days, depending on the cell type and droplet size. To overcome this limitation, it is possible to continuously perfuse the chip with fresh culture medium after performing the oil-aqueous phase exchange, as we demonstrated previously (16). Alternatively, it is also possible to maintain the cells in liquid droplets (without using a hydrogel) by resupplying culture medium through the fusion of additional drops at later times. This operation requires, however, a new design of the anchors and additional microfluidic steps (21).

The second major drawback of the method emerges from the large distance between the MBs and the microscope objective, which requires the use of very large working distance objectives. This compounds the difficulty of applying different confocal techniques by limiting the fluorescence intensity of the images, which, in turn, reduces the throughput when 3D image stacks are required. Although we have shown above that wide-field imaging can be used to obtain spatial mappings of spheroid structure and cell functions, true single-cell measurements will need to overcome the limitations on imaging in the future.

A Voronoi segmentation was used to categorize the cells into concentric layers, starting from the edge of the MBs and ending with the cells in the central region (22), which allowed us to measure variations in the structural organization and in the protein expressions on a layer-by-layer basis within the 3D cultures. The MBs were found to organize into a core region of undifferentiated cells, surrounded by a shell of committed cells. This hierarchical organization results from the spatial segregation of an initially heterogeneous population, as is generally the case for populations of pluripotent and somatic stem cells (2, 3, 33). The process of aggregation of HMSCs obtained within a few hours takes place through different stages (Fig. 6G): The first steps of the aggregation of MBs are mediated by N-cadherin interactions. In parallel, NF-B signaling is activated, promoting cell survival by preventing anoikis of suspended cells (34, 35). At later stages, the formation of polymerized F-actin and, to a lesser extent, stress fibers mediates the MB compaction, mainly at the edge of the MBs where the cellular commitment helps the stabilization of adherens junctions. The formation of adherens junctions facilitates the cohesion of the 3D structure, probably through the enhanced - and -catenin availability in the CD146dim/RUNX-2+ cells (36, 37, 38), which are recruited in the CCC complexes of the adherens junctions to promote the stable coupling of the F-actin to the N-cadherin (39), which become more insoluble to Triton X-100 than unbounded N-cadherins.

A functional phenotype that correlates with this hierarchical segregation is an increase in endocrine activity of the cells located at the boundaries of the MBs. COX-2 expression is increased in the outer layers of the MBs, which also contain more functional adherens junctions as well as a sustained NF-B activity in this region. The promoter of COX-2 contains RUNX-2 and NF-B cis-acting elements (40). While RUNX-2 is required for COX-2 expression in mesenchymal cells, its level of expression does not regulate the levels of COX-2 (40). The increased COX-2 expression is, in turn, due to the unbundled form of F-actin (i.e., a more relaxed form of actin, in comparison to the dense stress fibers observed in 2D) near the edge of the MBs, which was reported to sustain NF-B activity (41) and to down-regulate COX-2 transcriptional repressors (42). Therefore, NF-B has a high activity in the outer layers of the MB, where it locally promotes COX-2 expression.

These results show that the 3D culture format may provide some insights to understand the mesenchymal cell behavior in vivo, because we found that the expression of key bone regulatory molecules is spatially regulated as a function of the structural organization of the MBs. The 3D structure obtained here recalls some of the conditions found at the initial steps of intramembranous ossification that occurs after mesenchymal condensation (i.e., no chondrogenic intermediate was found in the MBs). In the developing calvaria, the most undifferentiated mesenchymal cells (e.g., Sca-1+/RUNX-2 cells) are located in the intrasutural mesenchyme, which is surrounded by an osteogenic front containing more committed cells (e.g., Sca-1/RUNX-2+ cells) (43, 44). Similarly, we observed that undifferentiated HMSCs (i.e., CD146bright/RUNX-2 HMSCs) were surrounded by osteogenically committed cells (i.e., CD146dim/RUNX-2+ HMSCs), which also coexpressed pro-osteogenic molecules, namely, COX-2 and its downstream targets, PGE2 and VEGF. While the link between COX-2 and PGE2 is well established, there is also evidence that COX-2 can induce the production of VEGF in different cell types, e.g., colon cancer cells (45), prostate cancer cells (46), sarcoma (47), pancreatic cancer cells (48), retinal Mller cells (49), gastric fibroblasts (50), skin or lung fibroblasts (51). In these cases, the mechanism for VEGF production through COX-2 induction is thought to be linked to PGE-2, either in an autocrine/paracrine manner (52) or in an intracrine manner (53).

Beyond HMSCs, spatial organization related to the level of differentiation and cell size has been documented in growing embryoids and organoids, with more committed cells being positioned in the outer layers (54, 55, 56). Our results show that a similar hierarchical structure can also be obtained through the aggregation of a mixed population of adult progenitors. This suggests that cell sorting, based on the size and commitment, plays a dominant role in organizing stem cell aggregates. This data-driven approach of combining high-throughput 3D culture and multiscale cytometry (16) on complex biological models can be applied further for getting a better understanding of the equilibria that determine the structure and the function of cells within multicellular tumor spheroids, embryoid bodies, or organoids.

HMSCs derived from the Whartons jelly of the UC (HMSCs) [American Type Culture Collection (ATCC) PCS-500-010, LGC, Molsheim, France] were obtained at passage 2. Four different lots of HMSCs were used in this study (lot nos. 60971574, 63739206, 63516504, and 63739206). While the lots were not selected a priori, we found consistent results for COX-2 and CD146 distribution within MBs. HMSCs from the different lots were certified for being CD29, CD44, CD73, CD90, CD105, and CD166 positive (more than 98% of the population is positive for these markers) and CD14, CD31, CD34, and CD45 negative (less than 0.6% of the population is positive for these markers) and to differentiate into adipocytes, chondrocytes, and osteocytes (ATCC, certificates of analysis). HMSCs were maintained in T175 cm2 flasks (Corning, France) and cultivated in a standard CO2 incubator (Binder, Tuttlingen, Germany). The culture medium was composed of modified Eagles medium (-MEM) (Gibco, Life Technologies, Saint Aubin, France) supplemented with 10% (v/v) fetal bovine serum (FBS) (Gibco) and 1% (v/v) penicilin-streptomycin (Gibco). The cells were seeded at 5 103 cells/cm2, subcultivated every week, and the medium was refreshed every 2 days. HMSCs at passage 2 were first expanded until passage 4 [for about five to six population doublings (PDs)], then cryopreserved in 90% (v/v) FBS/10% (v/v) dimethyl sulfoxide (DMSO), and stored in a liquid nitrogen tank. The experiments were carried out with HMSCs at passages 4 to 11 (about 24 to 35 PDs, after passage 2).

HMSCs were harvested by scrapping or trypsinization from T175 cm2 flasks. Then, the cells were incubated in staining buffer [2% FBS in phosphate-buffered saline (PBS)], stained with a mouse anti-human CD146Alexa Fluor 647 (clone P1-H12, BD Biosciences), a mouse anti-human CD31Alexa Fluor 488 (BD Biosciences, San Jose, CA) antibody, a mouse anti-human CD105Alexa Fluor 647 (BD Biosciences, San Jose, CA), a mouse anti-human CD90fluorescein isothiocyanate (FITC) and a mouse anti-human CD73allophycocyanin (APC) (Miltenyi Biotec, Germany), a CD14-APC (Miltenyi Biotec), a CD34-FITC (BioLegend), and an HLA-DRAPC (BD Biosciences).

The percentages of CD73-, CD90-, CD105-, CD146-, CD31-, CD34-, and HLA-DRpositive cells were analyzed using a FACS LSRFortessa (BD Biosciences, San Jose, CA) or an ImageStream (Amnis) flow cytometer. To validate the specificity of the antibody staining, the distributions of fluorescently labeled cells were compared to cells stained with isotype controls: mouse immunoglobulin G1 (IgG1), k-PE-Cy5 (clone MOPC-21, BD Biosciences), and mouse IgG2a K isotype control FITC (BD Biosciences, San Jose, CA). Alternatively, HMSCs were sorted on the basis of their level of expression of CD146 or their size [forward scatter (FSC) and side scatter (SSC)] using a FACSAria III (BD Biosciences, San Jose, CA).

To induce adipogenic differentiation, UC-HMSCs were seeded at 1 104 cells/cm2 in culture medium. The day after, the culture medium was switched to StemPro Adipogenesis Differentiation medium (Life Technologies) supplemented with 10 M rosiglitazone (Sigma-Aldrich) for 2 weeks. To visualize the differentiated adipocytes, the cells were stained with Oil Red O (Sigma-Aldrich). As a control, UC-HMSCs were maintained in culture medium for 2 weeks and stained with Oil Red O, as above.

To induce osteogenic differentiation, UC-HMSCs were seeded at 5 103 cells/cm2 in culture medium. The day after, the culture medium was switched to StemPro Osteogenesis Differentiation medium (Life Technologies) supplemented with 2-nm bone morphogenetic protein 2 (BMP-2) (Sigma-Aldrich) for 2 weeks. To visualize the differentiated osteoblasts, the cells were stained with Alizarin Red S (Sigma-Aldrich). As a control, UC-HMSCs were maintained in culture medium for 2 weeks and stained with Alizarin Red S, as above.

To induce chondrogenic differentiation, UC-HMSCs were seeded at 1 106 cells/ml in a 15-ml conical tube to promote micromass culture. The medium consisted of StemPro Chondrogenic Differentiation medium (Life Technologies). After 3 weeks in culture, the pellets were fixed and cryosectioned and then stained for Alcian Blue 8GX (Sigma-Aldrich). As a control, UC-HMSCs were maintained in 2D using culture medium for 3 weeks and stained with Alcian Blue, as above.

The color images were acquired using a binocular (SMZ18, Nikon) equipped with a camera (D7500, Nikon).

Standard dry-film soft lithography was used for the flow-focusing device (top of the chip) fabrication, while a specific method for the fabrication of the anchors (bottom of the chip) was developed. For the first part, up to five layers of dry-film photoresist consisting of 50-m Eternal Laminar E8020, 33-m Eternal Laminar E8013 (Eternal Materials, Taiwan), and 15-m Alpho NIT215 (Nichigo-Morton, Japan) negative films were successively laminated using an office laminator (PEAK pro PS320) at a temperature of 100C until the desired channel height, either 135, 150, 165, or 200 m, was reached. The photoresist film was then exposed to ultraviolet (Lightningcure, Hamamatsu, Japan) through a photomask of the junction, the channels, and the culture chamber boundaries. The masters were revealed after washing in a 1% (w/w) K2CO3 solution (Sigma-Aldrich). For the anchor fabrication, the molds were designed with RhinoCAM software (MecSoft Corporation, LA) and were fabricated by micromilling a brass plate (CNCMini-Mill/GX, Minitech Machinery, Norcross). The topography of the molds and masters was measured using an optical profilometer (Veeco Wyco NT1100, Veeco, Mannheim, Germany).

For the fabrication of the top of the chip, poly(dimethylsiloxane) [PDMS; SYLGARD 184, Dow Corning, 1:10 (w/w) ratio of curing agent to bulk material] was poured over the master and cured for 2 hours at 70C. For the fabrication of the bottom of the chip, the molds for the anchors were covered with PDMS. Then, a glass slide was immersed into uncured PDMS, above the anchors. The mold was lastly heated on a hot plate at 180C for 15 min. The top and the bottom of the chip were sealed after plasma treatment (Harrick, Ithaca). The chips were filled three times with Novec Surface Modifier (3M, Paris, France), a fluoropolymer coating agent, for 30 min at 110C on a hot plate.

HMSCs were harvested with TrypLE at 60 to 70% confluence, and a solution containing 6 105 cells in 70 l of medium was mixed with 30 l of a 3% (w/v) liquid low-melting agarose solution (i.e., stored at 37C) (Sigma-Aldrich, Saint Quentin Fallavier, France) diluted in culture medium containing gentamicin (50 g/ml; Sigma-Aldrich) (1:3, v/v), resulting in a 100-l solution of 6 106 cells/ml in 0.9% (w/v) agarose.

HMSCs and agarose were loaded into a 100-l glass syringe (SGE, Analytical Science, France), while Fluorinert FC-40 oil (3M, Paris, France) containing 1% (w/w) PEG-di-Krytox surfactant (RAN Biotechnologies, Beverly, USA) was loaded into a 1- and 2.5-ml glass syringes (SGE, Analytical Science). Droplets of cell-liquid agarose were generated in the FC-40 containing PEG-di-Krytox, at the flow-focusing junction, by controlling the flow rates using syringe pumps (neMESYS Low-Pressure Syringe Pump, Cetoni GmbH, Korbussen, Germany) (table S1). After complete loading, the chips were immersed in PBS, and the cells were allowed to settle down and to organize as MBs overnight in the CO2 incubator. Then, the agarose was gelled at 4C for 30 min, after which the PEG-di-Krytox was extensively washed in flushing pure FC-40 in the culture chamber. After washing, cell culture medium was injected to replace the FC-40. All flow rates are indicated in table S1. Further operations were allowed by gelling the agarose in the droplets, such that the resulting beads were retained mechanically in the traps rather than by capillary forces (Fig. 2G). This step allowed the exchange of the oil surrounding the droplets by an aqueous solution, for example, to bring fresh medium for long-term culture, chemical stimuli, or the different solutions required for cell staining.

For the live imaging of the MB formation, the chips were immersed in PBS and then were incubated for 24 hours in a microscope incubator equipped with temperature, CO2, and hygrometry controllers (Okolab, Pozzuoli, Italy). The cells were imaged every 20 min.

2D cultures or MBs were washed in PBS and incubated with a 5 M NucView 488 caspase-3 substrate (Interchim, Montluon, France) diluted in PBS. After washing with PBS, HMSCs were fixed with a 4% (w/v) PFA (Alpha Aesar, Heysham, UK) for 30 min and permeabilized with 0.2 to 0.5% (v/v) Triton X-100 (Sigma-Aldrich) for 5 min. The samples were blocked with 5% (v/v) FBS in PBS for 30 min and incubated with a rabbit polyclonal antiCOX-2 primary antibody (ab15191, Abcam, Cambridge, UK) diluted at 1:100 in 1% (v/v) FBS for 4 hours. After washing with PBS, the samples were incubated with an Alexa Fluor 594conjugated goat polyclonal anti-rabbit IgG secondary antibody (A-11012, Life Technologies, Saint Aubin, France) diluted at 1:100 in 1% (v/v) FBS for 90 min. Last, the cells were counterstained with 0.2 M DAPI for 5 min (Sigma-Aldrich) and then washed with PBS.

The same protocol was used for the staining of VEGF-Aexpressing cells using a rabbit anti-human VEGF-A monoclonal antibody (ab52917, Abcam, Cambridge, UK), which was revealed using the same secondary antibody as above. RUNX-2positive cells were similarly stained using a mouse anti-human RUNX-2 monoclonal antibody (ab76956, Abcam, Cambridge, UK), which was revealed using an Alexa Fluor 488 goat anti-mouse IgG2a secondary antibody (A-21131, Life Technologies, Saint Aubin, France), both diluted at 1:100 in 1% (v/v) FBS.

To measure potential induction of hypoxia within the core of the MBs, the cells were stained with Image-iT Red Hypoxia Reagent (Invitrogen) for 3 hours and then imaged using a fluorescence microscope. As a positive control, the chips containing the MBs were immersed into PBS, incubated overnight in an incubator set at 37C under 3% O2/5% CO2, and lastly imaged as above.

To interrogate the contribution of signaling related to anti-inflammatory molecule production (COX-2 and NF-B) or molecular pathways regulated by the cell structural organization (Notch, ROCK, and F-actin), several small molecules inducing their inhibition were added to the culture medium (table S1). For all the conditions, the final concentration of DMSO was below 0.1% (v/v) in the culture medium.

The cell viability was assessed using LIVE/DEAD staining kit (Molecular Probes, Life Technologies). The MBs were incubated for 30 min in PBS containing 1 M calcein AM and 2 M ethidium homodimer-1, in flushing 100 l of the solution. The samples were then washed with PBS and imaged under a motorized fluorescence microscope (Nikon, France).

For the detection of the functional forms of N-cadherins (i.e., the N-cadherins closely linked to the actin network, which are PFA insoluble), the MBs were fixed with a 4% (w/v) PFA (Alpha Aesar, Heysham, UK) for 30 min and permeabilized with 0.2 to 0.5% (v/v) Triton X-100 (Sigma-Aldrich) for 5 min. Alternatively, the aggregates were incubated for 5 min with 100% cold methanol followed by 1 min with cold acetone, for the detection of total N-cadherins (i.e., the PFA-soluble and PFA-insoluble forms).

Then, the samples were blocked with 5% (v/v) FBS in PBS for 30 min and incubated with a rabbit polyclonal antiN-cadherin primary antibody (ab18203, Abcam, Cambridge, UK) diluted at 1:100 in 1% (v/v) FBS for 4 hours. After washing with PBS, the samples were incubated with an Alexa Fluor 594conjugated goat polyclonal anti-rabbit IgG secondary antibody (A-11012, Life Technologies, Saint Aubin, France) diluted at 1:100 in 1% (v/v) FBS for 90 min. Last, the cells were counterstained with 0.2 M DAPI for 5 min (Sigma-Aldrich) and then washed with PBS.

For the quantification of the polymerized form of actin (F-actin), the MBs were first fixed with a 4% (w/v) PFA (Alpha Aesar, Heysham, UK) for 30 min and permeabilized with 0.2 to 0.5% (v/v) Triton X-100 (Sigma-Aldrich) for 5 min. The samples were then blocked with a 5% (v/v) FBS solution and incubated for 90 min in a 1:100 phalloidinAlexa Fluor 594 (Life Technologies) diluted in a 1% (v/v) FBS solution. The cells were then counterstained with 0.2 M DAPI for 5 min (Sigma-Aldrich) and then washed with PBS.

To ensure the specificity of the antibody to COX-2 and N-cadherin, control UC-HMSCs were permeabilized, fixed, and incubated only with the secondary antibody (Alexa Fluor 594conjugated goat polyclonal anti-rabbit IgG), as above. The absence of fluorescence signal indicated the specific staining for intracellular COX-2 and N-cadherin.

Next, to validate that the distribution of the fluorescence intensity was not related to any antibody diffusion limitation, the MBs were fixed and permeabilized, as above. For this assay, the MBs were not subjected to any blocking buffer. The cells were incubated for 90 min with the Alexa Fluor 594conjugated goat polyclonal anti-rabbit IgG secondary antibody (A-11012, Life Technologies, Saint Aubin, France) diluted at 1:100 in 1% (v/v) FBS. Then, the cells were counterstained for DAPI, as above. Last, the MBs were collected from the chip, deposed on a glass slide, and imaged.

For the analysis of COX-2 expression by flow cytometry, the total MBs were recovered from the chip. The MBs were then trypsinized and triturated to obtain single-cell suspension. UC-HMSCs were stained for COX-2, as above. The percentage of COX-2positive cells was quantified on 5 103 dissociated UC-HMSCs using a Guava easyCyte Flow Cytometer (Merck Millipore, Guyancourt, France). The results were compared to the fluorescence intensity distribution obtained by image analysis.

To interrogate the influence of the MB opacity in the COX-2 and N-cadherin fluorescence signals, the samples were treated by the Clear(T2) method after immunostaining (57). Briefly, the MBs were incubated for 10 min in 25% (v/v) formamide/10% (w/v) polyethylene glycol (PEG) (Sigma-Aldrich), then for 5 min in 50% (v/v) formamide/20% (w/v) PEG, and lastly for 60 min in 50% (v/v) formamide/20% (w/v) PEG, before their imaging. The fluorescence signal distribution was compared with the noncleared samples.

The MBs were collected from the chip and then fixed using PFA, as above. The MBs were incubated overnight in a 30% sucrose solution at 4C. Then, the sucrose solution was exchanged to O.C.T. medium (optimal cutting temperature; Tissue-Tek) in inclusion molds, which were slowly cooled down using dry ice in ethanol. The molds were then placed at 80C. On the day of the experiments, the O.C.T. blocks were cut at 7 m using a cryostat (CM3050 S, Leica). The cryosections were placed on glass slides (SuperFrost Plus Adhesion, Thermo Fisher Scientific), dried at 37C, and rehydrated using PBS. The cryosections were permeabilized and stained for COX-2, as above. The slides were lastly mounted in mounting medium containing DAPI (Fluoromount-G, Invitrogen).

All the images used for the quantitative analysis were taken using a motorized wide-field microscope (Ti, Eclipse, Nikon), equipped with a CMOS (complementary metal-oxide semiconductor) camera (ORCA-Flash4.0, Hamamatsu) and a fluorescence light-emitting diode source (Spectra X, Lumencor). The images were taken with a 10 objective with a 4-mm working distance (extra-long working distance) and a 0.45 numerical aperture (NA) (Plan Apo , Nikon).

For control experiments, images were taken using a motorized (Ti2, Nikon) confocal spinning disc microscope equipped with lasers (W1, Yokogawa) and the same camera and objective as above. Alternatively, the samples were imaged with a multiphoton microscope (TCS SP8 NLO, MP, Leica). The objective was an HCX PL APO CS 10, 0.40 NA, working distance of 2.2 mm (Leica).

All immunostained samples were counterstained with DAPI, and most of the images (i.e., for N-cadherin, COX-2, VEGF-A, and F-actin) were taken using red light excitation that is known to penetrate deeper into the 3D objects than dyes emitting at lower weight length (e.g., DAPI, FITC). For wide-field microscopy, the focal plane was defined as the area containing the maximal number of DAPI-stained nuclei covering the focal area, while z stacks were taken for the whole in-focus planes containing DAPI-stained nuclei using spinning discs and two-photon confocal microscopy.

Wide-field imaging is sensitive for the emission of fluorescence from inside and outside the focal plane (i.e., from the out-of-focus upper and bottom planes of the spheroids) (58). Consistently, more DAPI signal from nuclei is emitted from the core than in the edges of MBs using epifluorescence microscopy (fig. S5I). We confirmed that our interpretation of the signal distribution from epifluorescence images was consistent with confocal and two-photon microscopy by comparing with images taken from the median z plane and the maximal z projection (fig. S5, N to P).

Consequently, the results unambiguously demonstrate that even if there are more cells in the z plane of the middle area of the MBs, the contribution of the out-of-focus signal from N-cadherin, COX-2, VEGF-A, and F-actin staining in this area of the MBs is minimal using wide-field imaging. Because of the higher throughput of wide-field microscopy, this method was chosen to quantitatively analyze the distribution of these immunolabeled proteins within MBs.

The culture supernatants of six-well plates were collected, while the total medium content of the chip was recovered by flushing the culture chamber with pure oil. A PGE2 human ELISA kit (ab133055, Abcam, Cambridge, UK) was used for the quantification of PGE2 concentration in the culture supernatant, following the manufacturers instructions. Briefly, a polynomial standard curve of PGE2 concentration derived from the serial dilution of a PGE2 standard solution was generated (r2 > 0.9). The absorbance was measured using a plate reader (Chameleon, Hidex, Finland).

A VEGF-A human ELISA kit (Ab119566, Abcam, Cambridge, UK) was used for the quantification of VEGF-A concentration in the culture supernatant of 2D cultures or from the chips. A linear standard curve of VEGF-A concentration derived from the serial dilution of a VEGF-A standard solution was generated (r2 > 0.9). The absorbance was measured using a plate reader (Chameleon, Hidex, Finland).

The total MBs of a 3-day culture period were harvested from the chips, as described above. Alternatively, cells cultured on regular six-well plates were recovered using trypsin after the same cultivation time; CD146dim and CD146bright isolated cells were immediately treated for RNA extraction after sorting. The total RNA of 1 104 cells were extracted and converted to complementary DNA (cDNA) using SuperScript III CellsDirect cDNA Synthesis System (18080200, Invitrogen, Life Technologies), following the manufacturers instructions. After cell lysis, a comparable quality of the extracted RNA was observed using a bleach agarose gel, and similar RNA purity was obtained by measurement of the optical density at 260 and 280 nm using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Wilmington, DE) between total RNA preparations from 2D and on-chip cultures.

The cDNA was amplified using a GoTaq qPCR Master Mix (Promega, Charbonnieres, France) or a FastStart Universal SYBR Green Master Mix (containing Rox) (Roche) and primers (Life Technologies, Saint Aubin, France or Eurofins Scientific, France) at the specified melting temperature (Tm) (table S2) using a MiniOpticon (Bio-Rad) or a QuantStudio 3 (Thermo Fisher Scientific) thermocycler. As a negative control, water and total RNA served as template for PCR. To validate the specificity of the PCR, the amplicons were analyzed by dissociation curve and subsequent loading on a 2.5% (w/v) agarose gel and migration at 100 V for 40 min. The PCR products were revealed by ethidium bromide (Sigma-Aldrich) staining, and the gels were imaged using a transilluminator. The analysis of the samples not subjected to reverse transcription (RT) indicated negligible genomic DNA contamination (i.e., <0.1%), while no amplification signal was observed for the water template (no template control). The amount of TSG-6, COX-2, STC-1, VEGF-A, RUNX-2, CEBP-, and SOX-9 transcripts was normalized to the endogenous reference [glyceraldehyde-3-phosphate dehydrogenase (GADPH)], and the relative expression to a calibrator (2D cultures) was given by 2Ct calculation. At least five biological replicates of 2D and on-chip cultures were analyzed by at least duplicate measurements. The standard curves for GADPH, TSG-6, COX-2, and STC-1 were performed using a five serial dilution of the cDNA templates and indicated almost 100% PCR efficiency.

The image analysis allowed us to perform a multiscale analysis (16) of the MBs. For each chip, single images of the anchors were acquired automatically with the motorized stage of the microscope. The analysis was conducted on a montage of the detected anchors using a custom MATLAB code (r2016a, MathWorks, Natick, MA). Two distinct routines were used: one with bright-field detection and one for the fluorescence experiments.

For the bright field-detection described previously (16), the cells were detected in each anchor as pixels with high values of the intensity gradient. This allowed for each cell aggregate to compute morphological parameters such as the projected area A and the shape index SI that quantifies the circularity of an objectSI=4APwhere P is the perimeter. Shape index values range from 0 to 1, with 1 being assigned for perfect disk.

The MB detection with fluorescence staining (DAPI/Casp3/COX-2, DAPI/phalloidin, DAPI/N-cadherin, or LIVE/DEAD) was performed as described previously (16). First, morphological data were extracted at the MB level, such as the equivalent diameter of the MBs or the shape index. Also, the mean fluorescence signal of each MB was defined as the subtraction of the local background from the mean raw intensity.

At the cellular level, two different methods were used, both relying on the detection of the nuclei centers with the DAPI fluorescence signal. On the one hand, each cell location could be assigned to a normalized distance from the MB center (r/R) to correlate a nuclear fluorescence signal with a position in the MB, as previously described (16). On the other hand, the cell shapes inside the MBs were approximated by constructing Voronoi diagrams on the detected nuclei centers. Basically, the edges of the Voronoi cells are formed by the perpendicular bisectors of the segments between the neighboring cell centers. These Voronoi cells were used to quantify the cellular cytoplasmic signal (COX-2, F-actin and N-cadherin, VEGF and RUNX-2). In detail, to account for the variability of the cytoplasmic signal across the entire cell (nucleus included), the fluorescence signal of a single cell was defined as the mean signal of the 10% highest pixels of the corresponding Voronoi cell.

Image processing was also used to get quantitative data on 2D cultures, as previously described (16). Last, different normalization procedures were chosen in this paper. When an effect was quantified compared with a control condition, the test values were divided by the mean control value, and the significance was tested against 1. For some other data, the values were simply normalized by the corresponding mean at the chip level to discard the interchip variation from the analysis.

*P < 0.05; **P < 0.01; ***P < 0.001; NS, nonsignificant. Details of each statistical test and P values can be found in table S4.

Acknowledgments: C. Frot is gratefully acknowledged for the help with the microfabrication, and F. Soares da Silva is gratefully acknowledged for the help in flow cytometry. The group of Biomaterials and Microfluidics (BMCF) of the Center for Innovation and Technological Research as well as the Center for Translational Science (CRT)Cytometry and Biomarkers Unit of Technology and Service (CB UTechS is also acknowledged for the access to the microfabrication and flow cytometry platform at the Institut Pasteur). Funding: The research leading to these results received funding from the European Research Council (ERC) grant agreement 278248 Multicell. Author contributions: S.S., C.N.B., and A.C. conceived the experiments. S.S. performed the experiments. R.F.-X.T. wrote the image processing code and performed the image analysis. R.F.-X.T., S.S., G.A., and A.B. performed the image and data analyses. S.S., C.N.B., and A.C. discussed the results and wrote the manuscript. All authors discussed the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

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Mapping the structure and biological functions within mesenchymal bodies using microfluidics - Science Advances

Can You Naturally Rejuvenate Skin Cells? Yes Here Are 5 Proven Ways – mindbodygreen.com

Sure, this is the most extreme of the recommendations here, but if you are serious about helping your skin cells function at their peak, platelet-rich plasma injections are the most sophisticated (and natural) integrative treatment available. You might hear facial injections and immediately think of filler or botox, but these injections are entirely naturalbecause it comes from your own blood.

A vial of your own blood is drawn, put in a machine called a centrifuge, which separates the platelets from the rest of the blood cells (white and red). Platelets, which contain growth-factors, are in charge of recovery and inflammation in the body. When an area of the body is damaged (i.e.: premature aging from oxidative stress or environmental aggressors, like pollution), that area needs more repair cells, but sometimes it's hard for the body to get those cells to said location. So that's why you inject (or use acupuncture or via microneedling) a concentrated amount, so the platelets can hyper focus on damaged and aging skin cells. The result is skin that is better able to heal itselfresulting it smoother lines, more even texture, and improved tone.

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Can You Naturally Rejuvenate Skin Cells? Yes Here Are 5 Proven Ways - mindbodygreen.com

SpaceX set to launch Falcon 9 rocket and Dragon capsule from Cape Canaveral this week – Florida Today

FLORIDA TODAY's Rob Landers brings you some of today's top stories on the News in 90 Seconds. Florida Today

Get ready to rumble Friday night. And that's not just because it's Friday and it's time to party.

SpaceX is poised to launch its Falcon 9 rocket and cargo Dragon capsule from Cape Canaveral Air Force Station Launch Complex 40 no earlier than 11:50 p.m. Friday.

From there it will head on a three-day journey to the International Space Station where Dragon will deliver science experiments, cargo and supplies to the crew onboard.

This will mark the aerospace company's 20th flight under NASA's Commercial Resupply Services contract as well as the last time SpaceX uses its Dragon 1 capsule before retiring it to make way to its newer, more advanced spacecraft: Dragon 2.

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The newer spacecraft is not only equipped to carry supplies to and from the space station, but it is also certified to refly up to five times (Dragon 1 for instance, was only certified for three re-flights) and can also carry humans, which could happen as soon as May for NASA's Commercial Crew Program.

"Some of the accomplishments of SpaceX under the CRS One program includesthe first U.S. Commercial provider toberth the ISS ... With that we're looking forward to SpaceX continuing on the CRS Two contract with SpaceX-21," said Jennifer Buchli, deputy chief scientist for NASA's International Space Station Program Science Office during a media teleconference.

SpaceX launched a Falcon 9 rocket with cargo for the International Space Station on Thursday, Dec. 5, 2019. Cape Canaveral hosted the liftoff. Florida Today

For this mission, Dragon 1 will deliver several science experiments including:

ACE-T-Ellipsoids: Researchers from the New Jersey Institute of Technology will examine colloids small particles suspended within a fluid in microgravity to not only understand fluid physics more but to advance space-based additive manufacturing, an area of great interest to NASA and other agencies in the U.S.

MVP Cell-03: Emory University School of Medicine will study whether microgravity increases the production of heart cells from specific stem cells, called "human-induced pluripotent stem cells." Those specific cells have the potential to be used toreplenish cells that are damaged or lost due to cardiac diseases.

Flow Chemistry in Microgravity: Researchers from Boston University will study the effects of microgravity on chemical reactions as a step toward on-demand production of chemicals and materials in space.

Droplet Formation Study: Delta Faucet Company will study water droplet formation and water flow in microgravity to gain a better understanding on how to improve its showerhead technology in an effort to create better performance while also conserving water and energy.

Dragon will also deliver the European external payload hosting facility called Bartolomeo that will be an enhancement to the space station's European Columbus Module.

Contact Jaramillo at321-242-3668or antoniaj@floridatoday.com. Follow her onTwitterat@AntoniaJ_11.

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10 things to know about stem cell therapy – Outlook India

10 things to know about stem cell therapy

New Delhi, March 3 (IANSlife) The usage of stem cells to cure or treat a disease or repair the injured tissue is defined as stem cell therapy. The best example of the stem cell treatment is seen in patients suffering from restoring the vision of the damaged eyes, grafting of the skin in severe burnt conditions. Stem cell treatments for brain or neural diseases like Parkinson''s and Alzheimer''s disease, multiple sclerosis, preventing heart strokes, curing diabetes, kidney disorders, autism, and spinal cord injuries are progressively making their way. Vipul Jain, CEO of Advancells and also a Serial entrepreneur, explains in detail the treatment, its uses, cost and effectiveness.

Q: What are stem cells?

Undifferentiated cells that are able to differentiate and transform into any type of cells of the body when and where needed. They have an enormous potential to repair, heal and regenerate. Stem cells come from blood, bone marrow, umbilical cord blood and adipose tissue.

Types of stem cell therapy

Autologous stem cell therapy: Patient receives stem cells from his/her own body

Allogeneic stem cell therapy: Patient receives the stem cells donated by another individual

Autologous stem cell therapy is better than allogeneic stem cell therapy as chances of mismatching are not there and they pose the minimum risk of immune rejection. Also, no side effects or adverse effects are seen as a person''s own blood cells are used. They start the healing process immediately in a natural way.

What is stem cell therapy?

The usage of stem cells to cure or treat a disease or repair the injured tissue is defined as stem cell therapy. Stem cells can be obtained from the bone marrow, adipose tissues etc. Due to their tremendous potential to prevent and to treat various health conditions and to repair the injured tissues global research investigation is continuously being done as to explore the maximum advantage of these cell lines.

The best example of the stem cell treatment is seen in patients suffering from restoring the vision of the damaged eyes, grafting of the skin in severe burnt conditions. Stem cell treatments for brain or neural diseases like Parkinson''s and Alzheimer''s disease, multiple sclerosis, preventing heart strokes, curing diabetes, kidney disorders, autism, and spinal cord injuries are progressively making their way.

What are the sources of stem cell?

Depending upon the disease, different stem cell source can be used in a specific condition. The procedure may involve the extraction of stem cells from adipose tissue-derived stem cells with the combination of PRP (Platelet-rich plasma) or can be obtained from bone marrow that can differentiate into progenitor cells that differentiate into various other tissues which can help in the therapy.

Procedure of stem cell therapy

The stem cells are isolated from the bone marrow or adipose tissues followed by their processing and enrichment under sterile conditions. These activated stem cells are placed back into the patient''s body at the target site for repairing the damaged tissue. It is necessary that the stem cells are injected in the specific area of injury as only then the desired results will be achieved.

Adipose stem cells are preferred over bone marrow stem cells as they are easy to isolate and contain a higher number of stem cells.

Stem cells injection

The stem cells injections are gaining much interest because it is devoid of the painful procedure, takes less time in comparison to a surgery, there are no host and recipient rejections as stem cells are harvested from the patient''s body itself and a targeted delivery system is available.

The stem cells obtained are processed in a sophisticated stem cell lab and after activation are inserted back into the host with the help of intravenous, intramuscular, intra-arterial, intradermal and intrathecal injections as per the requirement of the treatment process.

What is the use of anesthetics and why? Usually, local anesthetics are used during a stem cell procedure to numb the area but sometimes general anesthesia is also given while extracting the stem cells from bone marrow. But it is necessary to find out what anesthetic your doctor uses during orthopedic stem cell treatments.

A number of anesthetics have been found to kill the stem cells thus; the treatment''s end result will greatly depend on the use of anesthetics. Some anesthetics very well sync with the stem cell and hence, aid in the treatment.

How good are the processing techniques in the onsite labs?

Stem cells are to be extracted and processed in a clean room, under aseptic conditions maintaining a controlled environment. The doctor should explain the entire process and the number of viable stem cells infused into the patient during the process. Also, the precision of the injections to provide good quality of stem cells at the site of injury will help in better and faster recovery of the patient''s damaged area.

Duration and cost of the therapy

Cost of the treatment and its duration varies from one patient to another. The disease which needs to be cured, the severity, age factor, health condition, etc, define the duration of the therapy. One may respond during the treatment phase itself while the other may show results after a few sessions or weeks. Depending upon the disease diagnosed, the stem cells extracted, duration of the therapy, other adjuvants used in the process, the cost of the stem cell therapy can vary.

Follow-up visits

It is essential that after the stem cell therapy the patient should visit the stem cell doctor for recuperation therapies. The primary goals of such therapy is the prevention of secondary complications, analysis of recovery of motor, sensory and all the bodily functioning, psychological support/counseling for depression, mood swings or anxiety etc. and reintegration into the community.

There can be different sets of precautions which need to be followed at various steps for the recovery of the damaged tissues. The treatment and post treatment conditions may vary from person to person depending upon the disease and the severity.

Success rate of stem cell therapy

Stem cell therapy has shown results in treating serious ailments like leukemia, grafting tissues, autism, orthopedic conditions and skin problems etc. Stem Cell Therapy has been successfully used in the treatment of around 80 serious disorders.

Survival rates among patients who received stem cell treatment are significantly high, whether the cell donors are related or unrelated to them. With the ongoing research around the world, scientists are exploring new possibilities in which a number of life threatening diseases can be prevented and cured hence, the stem cells have proved to be promising in the near future as many aspects are yet to be revealed.

--IANS

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Disclaimer :- This story has not been edited by Outlook staff and is auto-generated from news agency feeds. Source: IANS

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10 things to know about stem cell therapy - Outlook India

Global Research Antibodies Market Expected to Grow with a CAGR of 6.2% During the Forecast Period, 2020-2027 – ResearchAndMarkets.com – Yahoo Finance

The "Research Antibodies Market Size, Share & Trends Analysis Report by Type (Monoclonal, Polyclonal), by End Use, by Product, by Technology, by Source, by Application (Oncology, Stem Cells), and Segment Forecasts, 2020 - 2027" report has been added to ResearchAndMarkets.com's offering.

The global research antibodies market size is expected to reach USD 5.6 billion by 2027, exhibiting a CAGR of 6.2% over the forecast period according to this report.

Major market drivers include rise in R&D initiatives undertaken by biopharmaceutical and biotechnology companies and government bodies, growing interest in the study of neurobiology and stem cell, availability of technologically advanced products, and strategic collaborations among various market players and academic research organizations.

Designer antibodies are also anticipated to attract the attention of various academic organizations for their use in the R&D of novel products. For instance, in April 2019, scientists from ALS Canada Research Program developed a set of antibodies that can help in the detection of misfolded TDP-43 in various lab experiments that utilize post-mortem brain tissues. Rising usage of research antibodies for the development of novel diagnostic therapies is thus anticipated to fuel market growth in the near future.

Increase in the usage of research antibodies to develop treatment options for various diseases is also expected to boost market growth during the forecast period. For instance, in June 2019, the Institute of Life Sciences (ILS, India) developed antibodies against chikungunya viral infection. These antibody structures were developed to aid in the understanding of various aspects of virus pathogenesis, entailing further research on antiviral therapies. Growing government funds and initiatives for R&D is anticipated to fuel the Asia Pacific market during the forecast period. According to the 2018-2019 Australian Budget, approximately USD 94 million was estimated for four years for new industry collaborations, research as well as new biomedical and medical programs.

Additionally, rise in funds invested by pharmaceutical and biotechnology companies to enhance the study of proteomics and genomics is expected to drive the market. For instance, in 2017, Biognosys Inc. raised USD 5 million in funds to increase, advance, and develop next-generation proteomics products and workflow for high throughput and high content protein analysis. Rise in the number of major market players investing in advanced technologies and collaborating with other market players is also anticipated to positively impact market potential in the near future. For instance, Abcellera uses technologically advanced techniques to test antibodies from single B cells, map and screen natural immune responses, and to discover novel antibody therapies. The company has also partnered with Sanofi, Pfizer, Teva, Merck, and GSK to discover and develop new antibody-based therapies.

North America dominated the research antibodies market in owing to increasing focus on R&D in the fields of biomedicine, stem cell, and cancer. Rising prevalence of chronic diseases such as cardiovascular and blood diseases is also expected to fuel market growth.

Further key findings from the report suggest:

Key Topics Covered:

Chapter 1 Methodology and Scope

1.1 Market segmentation & scope

1.2 Market definition

1.3 Information procurement

1.4 Information analysis

1.5 Market formulation & data visualization

1.6 Data validation & publishing

Chapter 2 Executive Summary

2.1 Market Outlook

2.2 Segment Outlook

2.3 Competitive Insights

Chapter 3 Research Antibodies Market Variables, Trends & Scope

3.1 Market Lineage Outlook

3.2 Penetration And Growth Prospect Mapping

3.3 Regulatory Framework

3.4 Market Dynamics

3.5 Research Antibodies Market Analysis Tools

Chapter 4 Research Antibodies Market - Competitive Analysis

4.1 Recent Developments & Impact Analysis, By Key Market Participants

4.2 Company Categorization

4.3 Public Companies

4.4 Private Companies

Chapter 5 Research Antibodies Market: Product Estimates And Trend Analysis

5.1 Definition & Scope

5.2 Product Market Share Analysis, 2019 & 2027

5.3 Segment Dashboard

5.4 Global Research Antibodies Market, By Product, 2016 To 2027

Story continues

5.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

5.6 Primary Antibodies

5.7 Secondary Antibodies

Chapter 6 Research Antibodies Market: Type Estimates And Trend Analysis

6.1 Definition & Scope

6.2 Type Market Share Analysis, 2019 & 2027

6.3 Segment Dashboard

6.4 Global Research Antibodies Market, By Type, 2016 To 2027

6.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

6.6 Monoclonal Antibodies

6.7 Polyclonal Antibodies

Chapter 7 Research Antibodies Market: Technology Estimates And Trend Analysis

7.1 Definition & Scope

7.2 Technology Market Share Analysis, 2019 & 2027

7.3 Segment Dashboard

7.4 Global Research Antibodies Market, By Technology, 2016 To 2027

7.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

7.6 Immunochemistry

7.7 Immunofluorescence

7.8 Western Blotting

7.9 Flow Cytometry

7.10 Immunoprecipitation

7.11 Elisa

7.12 Other Technologies

Chapter 8 Research Antibodies Market: Application Estimates And Trend Analysis

8.1 Definition & Scope

8.2 Application Market Share Analysis, 2019 & 2027

8.3 Segment Dashboard

8.4 Global Research Antibodies Market, By Application, 2016 To 2027

8.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

8.6 Infectious Diseases

8.7 Immunology

8.8 Oncology

8.9 Stem Cells

8.10 Neurobiology

8.11 Other Applications

Chapter 9 Research Antibodies Market: Source Estimates And Trend Analysis

9.1 Definition & Scope

9.2 Source Market Share Analysis, 2019 & 2027

9.3 Segment Dashboard

9.4 Global Research Antibodies Market, By Source, 2016 To 2027

9.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

9.6 Mouse Antibodies

9.7 Rabbit Antibodies

9.8 Goat Antibodies

9.9 Other Sources

Chapter 10 Research Antibodies Market: End Use Estimates And Trend Analysis

10.1 Definition & Scope

10.2 End Use Market Share Analysis, 2019 & 2027

10.3 Segment Dashboard

10.4 Global Research Antibodies Market, By End Use, 2016 To 2027

10.5 Market Size & Forecasts And Trend Analyses, 2016 To 2027

10.6 Academic & Research Institutes

10.7 Contract Research Organizations

10.8 Pharmaceutical & Biotechnology Companies

Chapter 11 Research Antibodies Market: Regional Estimates & Trend Analysis

11.1 Regional Market Snapshot

11.2 Market Share Analysis By Country, 2019

11.3 SWOT Analysis, By Factor

11.4 Market Size & Forecasts, And Trend Analysis, 2019 To 2026

11.4.1 North America

11.4.2 Europe

11.4.3 Asia Pacific

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Global Research Antibodies Market Expected to Grow with a CAGR of 6.2% During the Forecast Period, 2020-2027 - ResearchAndMarkets.com - Yahoo Finance

aTyr Pharma Announces Poster Presentation at the American Association for Cancer Research (AACR) Annual Meeting – BioSpace

SAN DIEGO, March 03, 2020 (GLOBE NEWSWIRE) -- aTyr Pharma Inc., (Nasdaq: LIFE), a biotherapeutics company engaged in the discovery and development of innovative medicines based on novel immunological pathways, today announced that the company will present an abstract in a poster session at the upcoming AACR Annual Meeting, which is being held April 24 29, 2020 at the San Diego Convention Center.

Details of the presentation are as follows:Title:Domain-specific antibodies to Neuropilin-2 implicate VEGF-C and not Semaphorin 3F in breast cancer stem cell functionSession Date and Time:Monday, Apr 27, 2020 9:00 AM - 12:30 PMAbstract Control Number:7308Session Category:Experimental and Molecular TherapeuticsSession Title:Identification of Molecular Targets 1Location: San Diego Convention Center, Exhibit Halls A-F, Poster Section 25Poster Board Number:14Permanent Abstract Number: 1785

About ATYR1923

aTyr is developing ATYR1923 as a potential therapeutic for patients with interstitial lung diseases. ATYR1923, a fusion protein comprised of the immuno-modulatory domain of histidyl tRNA synthetase fused to the FC region of a human antibody, is a selective modulator of neuropilin-2 that downregulates the innate and adaptive immune response in inflammatory disease states. aTyr is currently enrolling a proof-of-concept Phase 1b/2a trial evaluating ATYR1923 in patients with pulmonary sarcoidosis. This Phase 1b/2a study is a multi-ascending dose, placebo-controlled, first-in-patient study of ATYR1923 that has been designed to evaluate the safety, tolerability, steroid sparing effect, immunogenicity and pharmacokinetics profile of multiple doses of ATYR1923.

About aTyr

aTyr is a biotherapeutics company engaged in the discovery and development of innovative medicines based on novel immunological pathways. aTyrs research and development efforts are concentrated on a newly discovered area of biology, the extracellular functionality and signaling pathways of tRNA synthetases. aTyr has built a global intellectual property estate directed to a potential pipeline of protein compositions derived from 20 tRNA synthetase genes and their extracellular targets. aTyrs primary focus is ATYR1923, a clinical-stage product candidate which binds to the neuropilin-2 receptor and is designed to down-regulate immune engagement in interstitial lung diseases. For more information, please visit http://www.atyrpharma.com.

Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the Private Litigation Reform Act. Forward-looking statements are usually identified by the use of words such as anticipates, believes, estimates, expects, intends, may, plans, projects, seeks, should, will, and variations of such words or similar expressions. We intend these forward-looking statements to be covered by such safe harbor provisions for forward-looking statements and are making this statement for purposes of complying with those safe harbor provisions. These forward-looking statements, include statements regarding the potential therapeutic benefits and applications of our product candidates; our ability to successfully advance our product candidates, undertake certain development activities (such as the initiation of clinical trials, clinical trial enrollment, the conduct of clinical trials and the announcement of top-line results) and accomplish certain development goals, and the timing of such events; and the scope and strength of our intellectual property portfolio. These forward-looking statements also reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects, as reflected in or suggested by these forward-looking statements, are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. All forward-looking statements are based on estimates and assumptions by our management that, although we believe to be reasonable, are inherently uncertain. Furthermore, actual results may differ materially from those described in these forward-looking statements and will be affected by a variety of risks and factors that are beyond our control including, without limitation, risks associated with the discovery, development and regulation of our product candidates, the risk that we may cease or delay preclinical or clinical development activities for any of our existing or future product candidates for a variety of reasons (including difficulties or delays in patient enrollment in planned clinical trials), the possibility of unexpected expenses or other demands on our cash resources, and the risk that we may not be able to raise the additional funding required for our business and product development plans, as well as those risks set forth in our most recent Annual Report on Form 10-K, Quarterly Reports on Form 10-Q and in our other SEC filings. Except as required by law, we assume no obligation to update publicly any forward-looking statements, whether as a result of new information, future events or otherwise.

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aTyr Pharma Announces Poster Presentation at the American Association for Cancer Research (AACR) Annual Meeting - BioSpace

The Global Cell Viability Assays MARKET is expected to grow by USD 1.40 bn during 2020-2024, progressing at a CAGR of 8% during the forecast period -…

Global Cell Viability Assays Market 2020-2024 The analyst has been monitoring the global cell viability assays market and it is poised to grow by USD 1. 40 bn during 2020-2024, progressing at a CAGR of 8% during the forecast period.

New York, March 02, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Cell Viability Assays Market 2020-2024" - https://www.reportlinker.com/p05868124/?utm_source=GNW Our reports on global cell viability assays market provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors. The report offers an up-to-date analysis regarding the current global market scenario, latest trends and drivers, and the overall market environment. The market is driven by growing emphasis on timely diagnosis of diseases.In addition, growing focus on stem cell research is anticipated to boost the growth of the global cell viability assays market as well.

Market Segmentation The global cell viability assays market is segmented as below: Product: o Consumables

o Instruments

Geographic Segmentation: o North America

o APAC

o Europe

o South America

o MEA

Key Trends for global cell viability assays market growth This study identifies growing focus on stem cell research as the prime reasons driving the global cell viability assays market growth during the next few years.

Prominent vendors in global cell viability assays market We provide a detailed analysis of around 25 vendors operating in the global cell viability assays market, including some of the vendors such as Agilent Technologies Inc., Becton, Dickinson and Co., Bio-Rad Laboratories Inc., Biotium Inc., Danaher Corp., General Electric Co., Merck KGaA, PerkinElmer Inc., Promega Corp. and Thermo Fisher Scientific Inc. . The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to an analysis of the key vendors.Read the full report: https://www.reportlinker.com/p05868124/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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The Global Cell Viability Assays MARKET is expected to grow by USD 1.40 bn during 2020-2024, progressing at a CAGR of 8% during the forecast period -...