Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials

Effect of Biosilicate® Addition on Physical-Mechanical and Biological Properties of Dental Glass Ionomer Cements

This study investigated the influence of incorporating Biosilicate^® on the physico-mechanical and biological properties of glass ionomer cement (GIC). This bioactive glass ceramic (23.75% Na₂O, 23.75% CaO, 48.5% SiO₂, and 4% P₂O₅) was incorporated by weight (5%, 10%, or 15%) into commercially available GICs (Maxxion R and Fuji IX GP). Surface characterization was made by SEM (n = 3), EDS (n = 3), and FTIR (n = 1). The setting and working (S/W time) times (n = 3) and compressive strength (CS) were analyzed (n = 10) according to ISO 9917-1:2007. The ion release (n = 6) was determined and quantified by ICP OES and by UV-Vis for Ca, Na, Al, Si, P, and F. To verify cell cytotoxicity, stem cells from the apical papilla (SCAP) were exposed to eluates (n = 3, at a ratio of 1.8 cm²/mL) and analyzed 24 h post-exposure. Antimicrobial activity against Streptococcus mutans (ATCC 25175, NCTC 10449) was analyzed by direct contact for 2 h (n = 5). The data were submitted for normality and lognormality testing. One-way ANOVA and Tukey's test were applied for the working and setting time, compressive strength, and ion release data. Data from cytotoxicity and antimicrobial activity were submitted for Kruskal-Wallis' testing and Dunn's post hoc test (α = 0.05). Among all experimental groups, only those with 5% (wt) of Biosilicate^® showed better surface quality. Only M5% showed a comparable W/S time to the original material (p = 0.7254 and p = 0.5912). CS was maintained for all Maxxion R groups (p > 0.0001) and declined for Fuji IX experimental groups (p < 0.0001). The Na, Si, P, and F ions released were significantly increased for all Maxxion R and Fuji IX groups (p < 0.0001). Cytotoxicity was increased only for Maxxion R with 5% and 10% of Biosilicate^®. A higher inhibition of S. mutans growth was observed for Maxxion R with 5% of Biosilicate^® (less than 100 CFU/mL), followed by Maxxion R with 10% of Biosilicate^® (p = 0.0053) and Maxxion R without the glass ceramic (p = 0.0093). Maxxion R and Fuji IX presented different behaviors regarding Biosilicate^® incorporation. The impacts on physico-mechanical and biological properties were different depending on the GIC, but therapeutic ion release was increased for both materials.

Fundamentals and Applications of Raman-Based Techniques for the Design and Development of Active Biomedical Materials

Raman spectroscopy is an analytical method based on light-matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided.

Potential bioactive coating system for high-performance absorbable magnesium bone implants

Magnesium alloys are considered the most suitable absorbable metals for bone fracture fixation implants. The main challenge in absorbable magnesium alloys is their high corrosion/degradation rate that needs to be controlled. Various coatings have been applied to magnesium alloys to slow down their corrosion rates to match their corrosion rate to the regeneration rate of the bone fracture. In this review, a bioactive coating is proposed to slow down the corrosion rate of magnesium alloys and accelerate the bone fracture healing process. The main aim of the bioactive coatings is to enhance the direct attachment of living tissues and thereby facilitate osteoconduction. Hydroxyapatite, collagen type I, recombinant human bone morphogenetic proteins 2, simvastatin, zoledronate, and strontium are six bioactive agents that show high potential for developing a bioactive coating system for high-performance absorbable magnesium bone implants. In addition to coating, the substrate itself can be made bioactive by alloying magnesium with calcium, zinc, copper, and manganese that were found to promote bone regeneration.

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Bioactive-coated magnesium implant could accelerate bone fracture healing time to match with magnesium degradation.

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Hydroxyapatite, collagen type I, recombinant human bone morphogenetic proteins 2, simvastatin, zoledronate, and strontium are high potential bioactive coating materials.

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The incorporation of Ca, Zn, Cu, Sr, and Mn in Mg base-metal could further enhance bone formation.

Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Conventional approaches to developing biomaterials and implants require intuitive tailoring of manufacturing protocols and biocompatibility assessment. This leads to longer development cycles, and high costs. To meet existing and unmet clinical needs, it is critical to accelerate the production of implantable biomaterials, implants and biomedical devices. Building on the Materials Genome Initiative, we define the concept 'biomaterialomics' as the integration of multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools throughout the entire pipeline of biomaterials development. The Data Science-driven approach is envisioned to bring together on a single platform, the computational tools, databases, experimental methods, machine learning, and advanced manufacturing (e.g., 3D printing) to develop the fourth-generation biomaterials and implants, whose clinical performance will be predicted using 'digital twins'. While analysing the key elements of the concept of 'biomaterialomics', significant emphasis has been put forward to effectively utilize high-throughput biocompatibility data together with multiscale physics-based models, E-platform/online databases of clinical studies, data science approaches, including metadata management, AI/ Machine Learning (ML) algorithms and uncertainty predictions. Such integrated formulation will allow one to adopt cross-disciplinary approaches to establish processing-structure-property (PSP) linkages. A few published studies from the lead author's research group serve as representative examples to illustrate the formulation and relevance of the 'Biomaterialomics' approaches for three emerging research themes, i.e. patient-specific implants, additive manufacturing, and bioelectronic medicine. The increased adaptability of AI/ML tools in biomaterials science along with the training of the next generation researchers in data science are strongly recommended. STATEMENT OF SIGNIFICANCE: This leading opinion review paper emphasizes the need to integrate the concepts and algorithms of the data science with biomaterials science. Also, this paper emphasizes the need to establish a mathematically rigorous cross-disciplinary framework that will allow a systematic quantitative exploration and curation of critical biomaterials knowledge needed to drive objectively the innovation efforts within a suitable uncertainty quantification framework, as embodied in 'biomaterialomics' concept, which integrates multi-omics data and high-dimensional analysis with artificial intelligence (AI) tools, like machine learning. The formulation of this approach has been demonstrated for patient-specific implants, additive manufacturing, and bioelectronic medicine.

Interaction of monodispersed strontium containing bioactive glass nanoparticles with macrophages

The cellular response of murine primary macrophages to monodisperse strontium containing bioactive glass nanoparticles (SrBGNPs), with diameters of 90 ± 10 nm and a composition (mol%) of 88.8 SiO₂-1.8CaO-9.4SrO (9.4% Sr-BGNPs) was investigated for the first time. Macrophage response is critical as applications of bioactive nanoparticles will involve the nanoparticles circulating in the blood stream and macrophages will be the first cells to encounter the particles, as part of inflammatory response mechanisms. Macrophage viability and total DNA measurements were not decreased by particle concentrations of up to 250 μg/mL. The Sr-BGNPs were actively internalised by the macrophages via formation of endosome/lysosome-like vesicles bordered by a membrane inside the cells. The Sr-BGNPs degraded inside the cells, with the Ca and Sr maintained inside the silica network. When RAW264.7 cells were incubated with Sr-BGNPs, the cells were polarised towards the pro-regenerative M2 population rather than the pro-inflammatory M1 population. Sr-BGNPs are potential biocompatible vehicles for therapeutic cation delivery for applications in bone regeneration.

The Clinical Significance and Immunization of MSMO1 in Cervical Squamous Cell Carcinoma Based on Bioinformatics Analysis

Objective: The genetic markers for the detection or treatment of cervical squamous cell carcinoma (CESC) are not yet complete. This study aimed to identify the role of MSMO1 (Alternative name: SC4MOL) in the occurrence and development of CESC. Methods: We evaluated the significance of MSMO1 expression in CESC by using analysis of a public dataset from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Oncomine and GEPIA2 were used to validate MSMO1 as an independent prognostic factor in CESC. Multiple tools were used to analyze the factors and functions associated with MSMO1, such as methylation, miRNA, and co-expressed genes. Furthermore, TIMER and TISIDB were used to study the relationship between MSMO1 expression and immunization in CESC. Results: MSMO1 was highly expressed in tumor specimens and could be used as an independent prognostic factor of CESC (p < 0.05). But Casiopeinas chemotherapeutics and p63 loss could reduce the expression of MSMO1. The level of methylation MSMO1 was significantly increased in tumor tissues but there was an insignificant effect on the prognosis. MSMO1 was also closely related to hsa-miR-23a-3p, hsa-miR-23b-3p, hsa-miR-130b-3p, and gene IDI1. Specifically, the expression level of MSMO1 had a significant negative correlation with the infiltration level of CD4+T cells, Macrophages, Neutrophils, and DCs in CESC. In addition, GSEA identified differential enrichment in systemic lupus erythematosus, vascular smooth muscle contraction, cytokine receptor interaction, focal adhesion, chemokine signaling pathway, and Leishmania infection pathway in KEGG. Conclusion: Our findings provide evidence of the implications of MSMO1 in tumors, suggesting that MSMO1 is a promising prognostic biomarker in CESC.

A biomimetic engineered bone platform for advanced testing of prosthetic implants

Existing methods for testing prosthetic implants suffer from critical limitations, creating an urgent need for new strategies that facilitate research and development of implants with enhanced osseointegration potential. Herein, we describe a novel, biomimetic, human bone platform for advanced testing of implants in vitro, and demonstrate the scientific validity and predictive value of this approach using an assortment of complementary evaluation methods. We anchored titanium (Ti) and stainless steel (SS) implants into biomimetic scaffolds, seeded with human induced mesenchymal stem cells, to recapitulate the osseointegration process in vitro. We show distinct patterns of gene expression, matrix deposition, and mineralization in response to the two materials, with Ti implants ultimately resulting in stronger integration strength, as seen in other preclinical and clinical studies. Interestingly, RNAseq analysis reveals that the TGF-beta and the FGF2 pathways are overexpressed in response to Ti implants, while the Wnt, BMP, and IGF pathways are overexpressed in response to SS implants. High-resolution imaging shows significantly increased tissue mineralization and calcium deposition at the tissue-implant interface in response to Ti implants, contributing to a twofold increase in pullout strength compared to SS implants. Our technology creates unprecedented research opportunities towards the design of implants and biomaterials that can be personalized, and exhibit enhanced osseointegration potential, with reduced need for animal testing.

Role of Artificial Intelligence and Machine Learning in Nanosafety

Robotics and automation provide potentially paradigm shifting improvements in the way materials are synthesized and characterized, generating large, complex data sets that are ideal for modeling and analysis by modern machine learning (ML) methods. Nanomaterials have not yet fully captured the benefits of automation, so lag behind in the application of ML methods of data analysis. Here, some key developments in, and roadblocks to the application of ML methods are reviewed to model and predict potentially adverse biological and environmental effects of nanomaterials. This work focuses on the diverse ways a range of ML algorithms are applied to understand and predict nanomaterials properties, provides examples of the application of traditional ML and deep learning methods to nanosafety, and provides context and future perspectives on developments that are likely to occur, or need to occur in the near future that allow artificial intelligence to make a deeper contribution to nanosafety.

Multiscale Analysis of Metal Oxide Nanoparticles in Tissue: Insights into Biodistribution and Biotransformation

Metal oxide nanoparticles have emerged as exceptionally potent biomedical sensors and actuators due to their unique physicochemical features. Despite fascinating achievements, the current limited understanding of the molecular interplay between nanoparticles and the surrounding tissue remains a major obstacle in the rationalized development of nanomedicines, which is reflected in their poor clinical approval rate. This work reports on the nanoscopic characterization of inorganic nanoparticles in tissue by the example of complex metal oxide nanoparticle hybrids consisting of crystalline cerium oxide and the biodegradable ceramic bioglass. A validated analytical method based on semiquantitative X-ray fluorescence and inductively coupled plasma spectrometry is used to assess nanoparticle biodistribution following intravenous and topical application. Then, a correlative multiscale analytical cascade based on a combination of microscopy and spectroscopy techniques shows that the topically applied hybrid nanoparticles remain at the initial site and are preferentially taken up into macrophages, form apatite on their surface, and lead to increased accumulation of lipids in their surroundings. Taken together, this work displays how modern analytical techniques can be harnessed to gain unprecedented insights into the biodistribution and biotransformation of complex inorganic nanoparticles. Such nanoscopic characterization is imperative for the rationalized engineering of safe and efficacious nanoparticle-based systems.

QSAR without borders

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as quantitative structure-activity relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling but it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas outside of traditional QSAR boundaries including synthesis planning, nanotechnology, materials science, biomaterials, and clinical informatics. As modern research methods generate rapidly increasing amounts of data, the knowledge of robust data-driven modelling methods professed within the QSAR field can become essential for scientists working both within and outside of chemical research. We hope that this contribution highlighting the generalizable components of QSAR modeling will serve to address this challenge.

Degradation and osteogenic induction of a SrHPO4-coated Mg-Nd-Zn-Zr alloy intramedullary nail in a rat femoral shaft fracture model

Magnesium and Mg-based alloys are promising biomaterials for orthopedic implants because of their degradability, osteogenic effects, and biocompatibility. However, the drawbacks of these materials include high hydrogen gas production, unexpected corrosion resistance, and insufficient mechanical strength duration. Surface modification can protect these biomaterials and induce osteogenesis. In this work, a SrHPO₄ coating was developed for our patented biodegradable Mg-Nd-Zn-Zr alloy (abbr. JDBM) through a chemical deposition method. The coating was characterized by in vitro immersion, ion release, and cytotoxicity tests, which showed a slower corrosion behavior and excellent cell viability. RNA sequencing of MC3T3E1 cells treated with SrHPO₄-coated JDBM ion release test extract showed increased Tlr4, followed by the activation of the downstream PI3K/Akt signaling pathway, causing proliferation and growth of pre-osteoblasts. An intramedullary nail (IMN) was implanted in a femoral fracture rat model. Mechanical test, radiological and histological analysis suggested that SrHPO₄-coated JDBM has superior mechanical properties, induces more bone formation, and decreases the degradation rate compared with uncoated JDBM and the administration of TLR4 inhibitor attenuated the new bone formation for fracture healing. SrHPO₄ is a promising coating for JDBM implants, particularly for long-bone fractures.

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.

Supervised Learning and Mass Spectrometry Predicts the in Vivo Fate of Nanomaterials

The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. Here, we developed a workflow to show that the evolution of proteins on nanoparticle surfaces predicts the biological fate of nanoparticles in vivo. This workflow involves extracting nanoparticles at multiple time points from circulation, isolating the proteins off the surface and performing proteomic mass spectrometry. The mass spectrometry protein library served as inputs, while blood clearance and organ accumulation were used as outputs to train a supervised deep neural network that predicts nanoparticle biological fate. In a double-blinded study, we tested the network by predicting nanoparticle spleen and liver accumulation with upward of 94% accuracy. Our neural network discovered that the mechanism of liver and spleen uptake is due to patterns of a multitude of nanoparticle surface adsorbed proteins. There are too many combinations to change these proteins manually using chemical or biological inhibitors to alter clearance. Therefore, we developed a technique that uses the host to act as a bioreactor to prepare nanoparticles with predictable clearance patterns that reduce liver and spleen uptake by 50% and 70%, respectively. These techniques provide opportunities to both predict nanoparticle behavior and also to engineer surface chemistries that are specifically designed by the body.

Osteogenic potential of sol-gel bioactive glasses containing manganese

Bioactive glasses (BGs) are widely used for bone regeneration, and allow the incorporation of different ions with therapeutic properties into the glass network. Amongst the different ions with therapeutic benefits, manganese (Mn) has been shown to influence bone metabolism and activate human osteoblasts integrins, improving cell adhesion, proliferation and spreading. Mn has also been incorporated into bioceramics as a therapeutic ion for improved osteogenesis. Here, up to 4.4 mol% MnO was substituted for CaO in the 58S composition (60 mol% SiO₂, 36 mol% CaO, 4 mol% P₂O₅) and its effects on the glass properties and capability to influence the osteogenic differentiation were evaluated. Mn-containing BGs with amorphous structure, high specific surface area and nanoporosity were obtained. The presence of Mn²⁺ species was confirmed by X-ray photoelectron spectroscopy (XPS). Mn-containing BGs presented no cytotoxic effect on human mesenchymal stem cells (hMSCs) and enabled sustained ion release in culture medium. hMSCs osteogenic differentiation stimulation and influence on the mineralisation process was also confirmed through the alkaline phosphatase (ALP) activity, and expression of osteogenic differentiation markers, such as collagen type I, osteopontin and osteocalcin, which presented higher expression in the presence of Mn-containing samples compared to control. Results show that the release of manganese ions from bioactive glass provoked human mesenchymal stem cell (hMSC) differentiation down a bone pathway, whereas hMSCs exposed to the Mn-free glass did not differentiate. Mn incorporation offers great promise for obtaining glasses with superior properties for bone tissue regeneration.

A comparison of lithium-substituted phosphate and borate bioactive glasses for mineralised tissue repair

OBJECTIVES

Wnt/β-catenin signalling plays important roles in regeneration, particularly in hard tissues such as bone and teeth, and can be regulated by small molecule antagonists of glycogen synthase kinase 3 (GSK3); however, small molecules can be difficult to deliver clinically. Lithium (Li) is also a GSK3 antagonist and can be incorporated into bioactive glasses (BG), which can be used clinically in dental and bone repair applications and tuned to quickly release their constituent ions.

METHODS

Here, we created phosphate (P)- and borate (B)-based BG that also contained Li (LiPBG and LiBBG) and examined their ion release kinetics and the toxicity of their dissolution ions on mouse 17IA4 dental pulp cells.

RESULTS

We found that although LiPBG and LiBBG can both quickly release Li at concentrations known to regulate Wnt/β-catenin signalling, the P and B ions they concomitantly release are highly toxic to cells. Only when relatively low concentrations of LiPBG and LiBBG were placed in cell culture medium were their dissolution products non-toxic. However, at these concentrations, LiPBG and LiBBG's ability to regulate Wnt/β-catenin signalling was limited.

SIGNIFICANCE

These data suggest that identifying a BG composition that can both quickly deliver high concentrations of Li and is non-toxic remains a challenge.

Human mesenchymal stem cells differentiate into an osteogenic lineage in presence of strontium containing bioactive glass nanoparticles

While bioactive glass and ions released during its dissolution are known to stimulate osteoblast cells, the effect bioactive glass has on human stem cells is not clear. Here, we show that spherical monodispersed strontium containing bioactive nanoparticles (Sr-BGNPs) of composition 90.6 mol% SiO₂, 5.0 mol% CaO, 4.4% mol% SrO (4.4%Sr-BGNPs) and 88.8 mol% SiO₂, 1.8 mol% CaO, and 9.4 mol% SrO (9.4%Sr-BGNPs) stimulate bone marrow derived human stem cell (hMSC) differentiation down an osteogenic pathway without osteogenic supplements. The particles were synthesised using a modified Stӧber process and had diameters of 90 ± 10 nm. Previous work on similar particles that did not contain Sr (80 mol% SiO₂, 20 mol% CaO) showed stem cells did not differentiate when exposed to the particles. Here, both compositions of the Sr-BGNPs (up to concentration of 250 μg/mL) stimulated the early-, mid-, and late-stage markers of osteogenic differentiation and accelerated mineralisation in the absence of osteogenic supplements. Sr ions play a key role in osteogenic stem cell differentiation. Sr-BGNP dissolution products did not adversely affect hMSC viability and no significant differences in viability were measured between each particle composition. Confocal and transmission electron microscopy (TEM) demonstrated that monodispersed Sr-BGNPs were internalised and localised within vesicles in the cytoplasm of hMSCs. Degradation of particles inside the cells was observed, whilst maintaining effective cations (Ca and Sr) in their silica network after 24 h in culture. The uptake of Sr-BGNPs by hMSCs was reduced by inhibitors of specific routes of endocytosis, indicating that the Sr-BGNPs uptake by hMSCs was probably via mixed endocytosis mechanisms. Sr-BGNPs have potential as injectable therapeutic devices for bone regeneration or treatment of conditions such as osteoporosis, because of their ability deliver a sustained release of osteogenic inorganic cations, e.g. calcium (Ca) or and strontium (Sr), through particle degradation locally to cells. STATEMENT OF SIGNIFICANCE: Here, we show that 90 nm spherical strontium containing bioactive nanoparticles of stimulate bone marrow derived human stem cell (hMSC) differentiation down an osteogenic pathway without the use of osteogenic supplements. While bioactive glass and its dissolution products are known to promote excellent bone regeneration in vivo and to stimulate osteoblast cells to produce bone matrix in vitro, their effect on human stem cells is not clear. Previously our nanoparticles that contained only SiO₂ and CaO did not provoke human bone marrow or adipose derived stem cell differentiation.

Cellular Response to 3-D Printed Bioactive Silicate and Borosilicate Glass Scaffolds

The repair and regeneration of loaded segmental bone defects is a challenge for both materials and biomedical science communities. Our recent work demonstrated the capability of bioactive glass in supporting bone healing and defect bridging using a rabbit femur segmental defect model without growth factors or bone marrow stromal cells (BMSCs). Here in the current work, a comprehensive in vitro evaluation of bioactive silicate (13-93) and borosilicate (2B6Sr) glass scaffolds was conducted to provide further understanding of their biological performances and to establish a correlation between in vitro and in vivo behaviors. Our in vitro evaluation using a murine MC3T3-E1 cell line confirmed the capability of both scaffolds to support cell attachment, vascular endothelial growth factor (VEGF) formation, and to stimulate mineral deposition and osteoblast marker gene expression. In particular, borosilicate (2B6Sr) glass showed a better capability in supporting the mineralization and gene expression than silicate (13-93) glass, consistent with a faster bone healing ability in vivo. The current in vitro results, combined with our previous in vivo findings, provide a strong basis for the further translational evaluation of bioactive glass scaffolds and for potential preclinical practice. © 2018 Wiley Periodicals, Inc. J. Biomed. Mater. Res. Part B, 2018. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 818-824, 2019.

Multiscale analyses reveal native-like lamellar bone repair and near perfect bone-contact with porous strontium-loaded bioactive glass

The efficient healing of critical-sized bone defects using synthetic biomaterial-based strategies is promising but remains challenging as it requires the development of biomaterials that combine a 3D porous architecture and a robust biological activity. Bioactive glasses (BGs) are attractive candidates as they stimulate a biological response that favors osteogenesis and vascularization, but amorphous 3D porous BGs are difficult to produce because conventional compositions crystallize during processing. Here, we rationally designed a porous, strontium-releasing, bioactive glass-based scaffold (pSrBG) whose composition was tailored to deliver strontium and whose properties were optimized to retain an amorphous phase, induce tissue infiltration and encourage bone formation. The hypothesis was that it would allow the repair of a critical-sized defect in an ovine model with newly-formed bone exhibiting physiological matrix composition and structural architecture. Histological and histomorphometric analyses combined with indentation testing showed pSrBG encouraged near perfect bone-to-material contact and the formation of well-organized lamellar bone. Analysis of bone quality by a combination of Raman spectral imaging, small-angle X-ray scattering, X-ray fluorescence and focused ion beam-scanning electron microscopy demonstrated that the repaired tissue was akin to that of normal, healthy bone, and incorporated small amounts of strontium in the newly formed bone mineral. These data show the potential of pSrBG to induce an efficient repair of critical-sized bone defects and establish the importance of thorough multi-scale characterization in assessing biomaterial outcomes in large animal models.

Quantitative design rules for protein-resistant surface coatings using machine learning

Preventing biological contamination (biofouling) is key to successful development of novel surface and nanoparticle-based technologies in the manufacturing industry and biomedicine. Protein adsorption is a crucial mediator of the interactions at the bio - nano -materials interface but is not well understood. Although general, empirical rules have been developed to guide the design of protein-resistant surface coatings, they are still largely qualitative. Herein we demonstrate that this knowledge gap can be addressed by using machine learning approaches to extract quantitative relationships between the material surface chemistry and the protein adsorption characteristics. We illustrate how robust linear and non-linear models can be constructed to accurately predict the percentage of protein adsorbed onto these surfaces using lysozyme or fibrinogen as prototype common contaminants. Our computational models could recapitulate the adsorption of proteins on functionalised surfaces in a test set with an r2 of 0.82 and standard error of prediction of 13%. Using the same data set that enabled the development of the Whitesides rules, we discovered an extension to the original rules. We describe a workflow that can be applied to large, consistently obtained data sets covering a broad range of surface functional groups and protein types.

The effect of strontium incorporation into sol-gel biomaterials on their protein adsorption and cell interactions

It is known strontium can both inhibit the osteoclast formation and stimulate the osteoblast maturation, so biomaterials containing this element can favour bone structure stabilisation. The addition of Sr to biomaterials could affect their interactions with proteins and cells. Here, a silica-hybrid sol-gel network doped with different amounts of SrCl₂ and applied as coatings on titanium discs was examined. in vitro analysis was performed to determine the potential effect of Sr in the coatings, showing enhanced gene expression of osteogenic markers (alkaline phosphatase and transforming growth factor-β) in MC3T3-E1 incubated with Sr-doped biomaterials. The examination of inflammatory markers (tumour necrosis factor-α and interleukin 10) in RAW 264.7 macrophages revealed an anti-inflammatory potential of these materials. Proteins adsorbed onto the coatings incubated with human serum (3 h at 37 °C) were also analysed; mass spectrometry was used to characterise the proteins adhering to materials with different Sr content. Adding Sr to the coatings increased their affinity to APOE and VTNC proteins (associated with anti-inflammatory and osteogenic functions). Moreover, the proteins involved in coagulation processes, such as prothrombin, were more abundant on the coatings containing Sr than on the base sol-gel surfaces. Correlations between gene expression and proteomic results were also examined.

Strontium-Doped Bioactive Glass Nanoparticles in Osteogenic Commitment

The present work has explored bioactive glass nanoparticles (BGNPs) and developed strontium-doped nanoparticles (BGNPsSr), envisioning orthopedic strategies compatible with vascularization. The nanoparticles were synthesized by the sol-gel method, achieving a diameter of 55 nm for BGNPs and 75 nm for BGNPsSr, and the inclusion of strontium caused no structural alteration. The nanoparticles exhibited high cytocompatibility for human umbilical vein endothelial cells (HUVECs) and SaOS-2. Additionally, the incorporation of strontium emphasized the tubule networking behavior of HUVECs. Our results demonstrate that the nanoparticle dissolution products encouraged the osteogenic differentiation of human adipose stem cells as it favored the expression of key genes and proteins associated with osteogenic lineage. This effect was markedly enhanced for BGNPsSr, which could prompt stem cell osteogenic differentiation without the typical osteogenic inducers. This study not only supports the hypothesis that BGNPs might play a significant role in osteogenic commitment but also highlights that the designed BGNPsSr is a valuable tool for stem cell "tune-up" in bone tissue engineering applications.

Promoting in vivo early angiogenesis with sub-micrometer strontium-contained bioactive microspheres through modulating macrophage phenotypes

Early vascularization capacity of biomaterials plays an essential role in efficient wound healing and tissue regeneration, especially in large tissue tension implanting position such as bone augmentation. Strontium-contained silica-based bioactive materials have shown the role of promoting angiogenesis by stimulating osteoblasts to secrete angiogenesis related cytokines. However, osteoblasts have little effect on early angiogenesis due to the inflammatory reaction of implantation site. Here, for the first time, we found that the monodispersed strontium-contained bioactive glasses microspheres (SrBGM) could significantly promote the early angiogenesis through regulating macrophage phenotypes. After being stimulated with SrBGM in vitro, RAW cells (macrophages) presented a trend towards to M2 phenotype and expressed high level of platelet-derived growth factor-BB (PDGF-BB). Moreover, the RAW conditioned medium of SrBGM significantly enhanced the angiogenic capacity of HUVECs. The in vivo early vascularization studies showed that significant new vessels were observed at the center of SrBGM-based scaffolds after implantation for 1 week in a bone defect model of rats, suggesting their enhanced early vascularization. Due to the efficient vascularization, the in vivo new bone formation was promoted significantly. Our study may provide a novel strategy to promote the early vascularization of biomaterials through modulating the microphage phenotypes, which has wide applications in various tissue regeneration and wound healing.

Widespread changes in transcriptome profile of human mesenchymal stem cells induced by two-dimensional nanosilicates

Two-dimensional nanomaterials, an ultrathin class of materials such as graphene, nanoclays, transition metal dichalcogenides (TMDs), and transition metal oxides (TMOs), have emerged as a new generation of materials due to their unique properties relative to macroscale counterparts. However, little is known about the transcriptome dynamics following exposure to these nanomaterials. Here, we investigate the interactions of 2D nanosilicates, a layered clay, with human mesenchymal stem cells (hMSCs) at the whole-transcriptome level by high-throughput sequencing (RNA-seq). Analysis of cell-nanosilicate interactions by monitoring changes in transcriptome profile uncovered key biophysical and biochemical cellular pathways triggered by nanosilicates. A widespread alteration of genes was observed due to nanosilicate exposure as more than 4,000 genes were differentially expressed. The change in mRNA expression levels revealed clathrin-mediated endocytosis of nanosilicates. Nanosilicate attachment to the cell membrane and subsequent cellular internalization activated stress-responsive pathways such as mitogen-activated protein kinase (MAPK), which subsequently directed hMSC differentiation toward osteogenic and chondrogenic lineages. This study provides transcriptomic insight on the role of surface-mediated cellular signaling triggered by nanomaterials and enables development of nanomaterials-based therapeutics for regenerative medicine. This approach in understanding nanomaterial-cell interactions illustrates how change in transcriptomic profile can predict downstream effects following nanomaterial treatment.

Cobalt-containing bioactive glasses reduce human mesenchymal stem cell chondrogenic differentiation despite HIF-1α stabilisation

Bioactive glasses (BGs) are excellent delivery systems for the sustained release of therapeutic ions and have been extensively studied in the context of bone tissue engineering. More recently, due to their osteogenic properties and expanding application to soft tissue repair, BGs have been proposed as promising materials for use at the osteochondral interface. Since hypoxia plays a critical role during cartilage formation, we sought to investigate the influence of BGs releasing the hypoxia-mimicking agent cobalt (CoBGs) on human mesenchymal stem cell (hMSC) chondrogenesis, as a novel approach that may guide future osteochondral scaffold design. The CoBG dissolution products significantly increased the level of hypoxia-inducible factor-1 alpha in hMSCs in a cobalt dose-dependent manner. Continued exposure to the cobalt-containing BG extracts significantly reduced hMSC proliferation and metabolic activity, as well as chondrogenic differentiation. Overall, this study demonstrates that prolonged exposure to cobalt warrants careful consideration for cartilage repair applications.

Impaired sperm function in infertile men relies on the membrane sterol pattern

Membrane cholesterol removal appears a key step for the gain of fertility potential during sperm maturation. However, the membrane sterol pattern in sperm cells from infertile patients, with impaired sperm parameters, has been poorly investigated. To elucidate a causative link between sperm membrane composition in male fertility, here we have investigated the levels of cholesterol and its oxidized derivatives 7β-hydroxycholesterol and 7-keto-cholesterol in sixteen infertile patients with oligo-asthenozoospermia and 16 normozoospermic (N) fertile subjects. Furthermore, ten of 16 N fertile subjects agreed to receive a defined testicular thermal challenge by adhering to a programme of sauna sessions for 1 month. Semen samples were obtained from each of the participants, and sperm parameters were assessed according to the World Health Organization criteria. Sperm levels of cholesterol, 7β-hydroxycholesterol and 7-keto-cholesterol were quantified by ultra-pressure liquid chromatography mass spectrometry. The results showed that oligo-asthenozoospermia patients had a huge amount of cholesterol content compared with fertile subjects (12.40 ± 6.05 μg/10⁶ cells vs. 0.45 ± 0.28 μg/10⁶ cells, p < 0.001, N and oligo-asthenozoospermia, respectively). Also, oxidized derivatives were significantly higher in oligo-asthenozoospermia patients (7β-hydroxycholesterol: 1.96 ± 1.03 ng/10⁶ cells vs. 0.075 ± 0.05 ng/10⁶ cells, p < 0.001 and 7-keto-cholesterol: 1.11 ± 0.72 ng/10⁶ cells vs. 0.005 ± 0.003 ng/10⁶ cells, p < 0.001). Moreover, sauna exposure, in parallel with a progressive worsening of sperm motility parameters, was associated with a reversible increase in sperm cholesterol after the third and fourth week of treatment, whilst 7β-hydroxycholesterol and 7-keto-cholesterol levels showed an earlier enhancement starting from the second week. Our data show for the first time in humans a strong difference in the cholesterol and its oxidized derivatives of infertile and fertile subjects. These findings suggest a strict biochemical link relating testis function, sperm membrane status and male fertility potential.

In vitro osteogenesis by intracellular uptake of strontium containing bioactive glass nanoparticles

Monodispersed strontium containing bioactive glass nanoparticles (Sr-BGNPs) with two compositions were synthesised, through a modified sol-gel Stöber process, wherein silica nanoparticles (SiO₂-NPs) were formed prior to incorporation of calcium and strontium, with diameters of 90 ± 10 nm. The osteogenic response of a murine preosteoblast cell line, MC3T3-E1, was investigated in vitro for a nanoparticle concentration of 250 µg/mL with compositions of 87 mol% SiO₂, 7 mol% CaO, 6 mol% SrO and 83 mol% SiO₂, 3 mol% CaO, 14 mol% SrO. Dissolution studies in minimum essential media (α-MEM) at pH 7.4 and artificial lysosomal fluid (ALF) at pH 4.5 showed that the particles dissolved and that Sr²⁺ ions were released from Sr-BGNPs in both environments. Both particle compositions and their ionic dissolution products enhanced the alkaline phosphatase (ALP) activity of the cells and calcium deposition. Immunohistochemistry (IHC) staining of Col1a1, osteocalcin (OSC) and osteopontin (OSP) showed that these proteins were expressed in the MC3T3-E1 cells following three weeks of culture. In the basal condition, the late osteogenic differentiation markers, OSC and OSP, were more overtly expressed by cells cultured with Sr-BGNPs with 14 mol% SrO and their ionic release products than in the control condition. Col1a1 expression was only slightly enhanced in the basal condition, but was enhanced further by the osteogenic supplements. These data demonstrate that Sr-BGNPs accelerate mineralisation without osteogenic supplements. Sr-BGNPs were internalised into MC3T3-E1 cells by endocytosis and stimulated osteogenic differentiation of the pre-osteoblast cell line. Sr-BGNPs are likely to be beneficial for bone regeneration and the observed osteogenic effects of these particles can be attributed to their ionic release products.

STATEMENT OF SIGNIFICANCE

We report, for the first time, that monodispersed bioactive glass nanoparticles (∼90 nm) are internalised into preosteoblast cells by endocytosis but by unspecific mechanisms. The bioactive nanoparticles and their dissolution products (without the particles present) stimulated the expression of osteogenic markers from preosteoblast cells without the addition of other osteogenic supplements. Incorporating Sr into the bioactive glass nanoparticle composition, in addition to Ca, increased the total cation content (and therefore dissolution rate) of the nanoparticles, even though nominal total cation addition was constant, without changing size or morphology. Increasing Sr content in the nanoparticles and in their dissolution products enhanced osteogenesis in vitro. The particles therefore have great potential as an injectable therapeutic for bone regeneration, particularly in patients with osteoporosis, for which Sr is known to be therapeutic agent.

Biomaterial Cues Regulate Epigenetic State and Cell Functions-A Systematic Review

Biomaterial cues can act as potent regulators of cell niche and microenvironment. Epigenetic regulation plays an important role in cell functions, including proliferation, differentiation, and reprogramming. It is now well appreciated that biomaterials can alter epigenetic states of cells. In this study, we systematically reviewed the underlying epigenetic mechanisms of how different biomaterial cues, including material chemistry, topography, elasticity, and mechanical stimulus, influence cell functions, such as nuclear deformation, cell proliferation, differentiation, and reprogramming, to summarize the differences and similarities among each biomaterial cues and their mechanisms, and to find common and unique properties of different biomaterial cues. Moreover, this work aims to establish a mechanogenomic map facilitating highly functionalized biomaterial design, and renders new thoughts of epigenetic regulation in controlling cell fates in disease treatment and regenerative medicine.

How Not To Drown in Data: A Guide for Biomaterial Engineers

High-throughput assays that produce hundreds of measurements per sample are powerful tools for quantifying cell-material interactions. With advances in automation and miniaturization in material fabrication, hundreds of biomaterial samples can be rapidly produced, which can then be characterized using these assays. However, the resulting deluge of data can be overwhelming. To the rescue are computational methods that are well suited to these problems. Machine learning techniques provide a vast array of tools to make predictions about cell-material interactions and to find patterns in cellular responses. Computational simulations allow researchers to pose and test hypotheses and perform experiments in silico. This review describes approaches from these two domains that can be brought to bear on the problem of analyzing biomaterial screening data.

Biomimetic molecular design tools that learn, evolve, and adapt

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known "S curve", with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

Competing Roles of Substrate Composition, Microstructure, and Sustained Strontium Release in Directing Osteogenic Differentiation of hMSCs

Strontium releasing bioactive ceramics constitute an important class of biomaterials for osteoporosis treatment. In the present study, we evaluated the synthesis, phase assemblage, and magnetic properties of strontium hexaferrite, SrFe₁₂O₁₉, (SrFe) nanoparticles. On the biocompatibility front, the size- and dose-dependent cytotoxicity of SrFe against human mesenchymal stem cells (hMSCs) were investigated. After establishing their non-toxic nature, we used the strontium hexaferrite nanoparticles (SrFeNPs) in varying amount (x = 0, 10, and 20 wt %) to consolidate bioactive composites with hydroxyapatite (HA) by multi-stage spark plasma sintering (SPS). Rietveld refinement of these spark plasma sintered composites revealed a near complete decomposition of SrFe₁₂O₁₉ to magnetite (Fe₃O₄) along with a marked increase in the unit cell volume of HA, commensurate with strontium-doped HA. The cytocompatibility of SrHA-Fe composites with hMSCs was assessed using qualitative and quantitative morphological analysis along with phenotypic and genotypic expression for stem cell differentiation. A marked decrease in the stemness of hMSCs, indicated by reduced vimentin expression and acquisition of osteogenic phenotype, evinced by alkaline phosphatase (ALP) and collagen deposition was recorded on SrHA-Fe composites in osteoinductive culture. A significant upregulation of osteogenic marker genes (Runx2, ALP and OPN) was detected in case of the SrHA-Fe composites, whereas OCN and Col IA expression were similarly high for baseline HA. However, matrix mineralization was elevated on SrHA-Fe composites in commensurate with the release of Sr²⁺ and Fe²⁺. Summarizing, the current work is the first report of strontium hexaferrite as a non-toxic nanobiomaterial. Also, SrHA-based iron oxide composites can potentially better facilitate bone formation, when compared to pristine HA.

Optimisation of lithium-substituted bioactive glasses to tailor cell response for hard tissue repair

Bioactive glasses (BG) are used clinically because they can both bond to hard tissue and release therapeutic ions that can stimulate nearby cells. Lithium has been shown to regulate the Wnt/β-catenin cell signalling pathway, which plays important roles in the formation and repair of bone and teeth. Lithium-releasing BG, therefore, have the potential to locally regulate hard tissue formation; however, their design must be tailored to induce an appropriate biological response. Here, we optimised the release of lithium from lithium-substituted BG by varying BG composition, particle size and concentration to minimise toxicity and maximise upregulation of the Wnt target gene Axin2 in in vitro cell cultures. Our results show that we can tailor lithium release from BG over a wide therapeutic and non-toxic range. Increasing the concentration of BG in cell culture medium can induce toxicity, likely due to modulations in pH. Nevertheless, at sub-toxic concentrations, lithium released from BG can upregulate the Wnt pathway in 17IA4 cells, similarly to treatment with LiCl. Taken together, these data demonstrate that ion release from lithium-substituted BG can be tailored to maximise biological response. These data may be important in the design of BG that can regulate the Wnt/β-catenin pathway to promote hard tissue repair or regeneration.

Quantitative multi-image analysis for biomedical Raman spectroscopic imaging

Imaging by Raman spectroscopy enables unparalleled label-free insights into cell and tissue composition at the molecular level. With established approaches limited to single image analysis, there are currently no general guidelines or consensus on how to quantify biochemical components across multiple Raman images. Here, we describe a broadly applicable methodology for the combination of multiple Raman images into a single image for analysis. This is achieved by removing image specific background interference, unfolding the series of Raman images into a single dataset, and normalisation of each Raman spectrum to render comparable Raman images. Multivariate image analysis is finally applied to derive the contributing 'pure' biochemical spectra for relative quantification. We present our methodology using four independently measured Raman images of control cells and four images of cells treated with strontium ions from substituted bioactive glass. We show that the relative biochemical distribution per area of the cells can be quantified. In addition, using k-means clustering, we are able to discriminate between the two cell types over multiple Raman images. This study shows a streamlined quantitative multi-image analysis tool for improving cell/tissue characterisation and opens new avenues in biomedical Raman spectroscopic imaging.

Heartbreak hotel: a convergence in cardiac regeneration

In February 2016, The Company of Biologists hosted an intimate gathering of leading international researchers at the forefront of experimental cardiovascular regeneration, with its emphasis on ‘Transdifferentiation and Tissue Plasticity in Cardiovascular Rejuvenation’. As I review here, participants at the workshop revealed how understanding cardiac growth and lineage decisions at their most fundamental level has transformed the strategies in hand that presently energize the prospects for human heart repair.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field.

STATEMENT OF SIGNIFICANCE

In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field.

Material Cues as Potent Regulators of Epigenetics and Stem Cell Function

Biophysical signals act as potent regulators of stem cell function, lineage commitment, and epigenetic status. In recent years, synthetic biomaterials have been used to study a wide range of outside-in signaling events, and it is now well appreciated that material cues modulate the epigenome. Here, we review the role of extracellular signals in guiding stem cell behavior via epigenetic regulation, and we stress the role of physicochemical material properties as an often-overlooked modulator of intracellular signaling. We also highlight promising new research tools for ongoing interrogation of the stem cell-material interface.

Bioactive Glasses: Frontiers and Challenges

Bioactive glasses were discovered in 1969 and provided for the first time an alternative to nearly inert implant materials. Bioglass formed a rapid, strong, and stable bond with host tissues. This article examines the frontiers of research crossed to achieve clinical use of bioactive glasses and glass-ceramics. In the 1980s, it was discovered that bioactive glasses could be used in particulate form to stimulate osteogenesis, which thereby led to the concept of regeneration of tissues. Later, it was discovered that the dissolution ions from the glasses behaved like growth factors, providing signals to the cells. This article summarizes the frontiers of knowledge crossed during four eras of development of bioactive glasses that have led from concept of bioactivity to widespread clinical and commercial use, with emphasis on the first composition, 45S5 Bioglass(®). The four eras are (a) discovery, (b) clinical application, (c) tissue regeneration, and (d) innovation. Questions still to be answered for the fourth era are included to stimulate innovation in the field and exploration of new frontiers that can be the basis for a general theory of bioactive stimulation of regeneration of tissues and application to numerous clinical needs.

Sparse feature selection identifies H2A.Z as a novel, pattern-specific biomarker for asymmetrically self-renewing distributed stem cells

There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs) in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow). Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify such useful and specific DSC biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel "pattern-specific biomarker" for asymmetrically self-renewing cells, with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ.

Multivariate statistical analysis methods in QSAR

The emphasis of this review is particularly on multivariate statistical methods currently used in quantitative structure–activity relationship (QSAR) studies.