Genomic expression of mesenchymal stem cells to altered nanoscale topographies.

The understanding of cellular response to the shape of their environment would be of benefit in the development of artificial extracellular environments for potential use in the production of biomimetic surfaces. Specifically, the understanding of how cues from the extracellular environment can be used to understand stem cell differentiation would be of special interest in regenerative medicine.In this paper, the genetic profile of mesenchymal stem cells cultured on two osteogenic nanoscale topographies (pitted surface versus raised islands) are compared with cells treated with dexamethasone, a corticosteroid routinely used to stimulate bone formation in culture from mesenchymal stem cells, using 19k gene microarrays as well as 101 gene arrays specific for osteoblast and endothelial biology.The current studies show that by altering the shape of the matrix a cell response (genomic profile) similar to that achieved with chemical stimulation can be elicited. Here, we show that bone formation can be achieved with efficiency similar to that of dexamethasone with the added benefit that endothelial cell development is not inhibited. We further show that the mechanism of action of the topographies and dexamethasone differs. This could have an implication for tissue engineering in which a simultaneous, targeted, development of a tissue, such as bone, without the suppression of angiogenesis to supply nutrients to the new tissue is required. The results further demonstrate that perhaps the shape of the extracellular matrix is critical to tissue development.     

The effects of vibration loading on adipose stem cell number,viability and differentiation towards bone-forming cells

Mechanical stimulation is an essential factor affecting the metabolism of bone cells and their precursors. We hypothesized that vibration loading would stimulate differentiation of human adipose stem cells (hASCs) towards bone-forming cells and simultaneously inhibit differentiation towards fat tissue. We developed a vibration-loading device that produces 3g peak acceleration at frequencies of 50 and 100 Hz to cells cultured on well plates. hASCs were cultured using either basal medium (BM), osteogenic medium (OM) or adipogenic medium (AM), and subjected to vibration loading for 3 h d^–1 for 1, 7 and 14 day. Osteogenesis, i.e. differentiation of hASCs towards bone-forming cells, was analysed using markers such as alkaline phosphatase (ALP) activity, collagen production and mineralization. Both 50 and 100 Hz vibration frequencies induced significantly increased ALP activity and collagen production of hASCs compared with the static control at 14 day in OM. A similar trend was detected for mineralization, but the increase was not statistically significant. Furthermore, vibration loading inhibited adipocyte differentiation of hASCs. Vibration did not affect cell number or viability. These findings suggest that osteogenic culture conditions amplify the stimulatory effect of vibration loading on differentiation of hASCs towards bone-forming cells.     

Glial progenitor cell recruitment drives aggressive glioma growth: mathematical and experimental modelling

Currently available glioma treatments remain unsuccessful at prolonging disease-free remission. Recent evidence suggests that tumour recruitment of glial progenitor cells by platelet-derived growth factor (PDGF) may play a role in the development and progression of these tumours. Building upon our recent experimental results and previous proliferation–invasion (PI) reaction–diffusion model, in this study, we created a proliferation–invasion–recruitment (PIR) model that includes a mechanism for progenitor cell recruitment, wherein paracrine PDGF signalling stimulates migration and proliferation of progenitors derived from the local brain environment. Parametrizing this mathematical model with data obtained from the PDGF-driven rat glioma model, we explored the consequences of recruitment, using the PIR model to compare the effects of high versus low PDGF secretion rates on tumour growth and invasion dynamics. The mathematical model predicts correlation between high levels of recruitment and both increased radial velocity of expansion on magnetic resonance imaging and less diffusely invasive edges. Thus, the PIR model predicts that PDGF levels correlate with tumour aggressiveness, and results are consistent with both human and experimental data, demonstrating that the effects of progenitor cell recruitment provide a novel mechanism to explain the variability in the rates of proliferation and dispersion observed in human gliomas.     

Impact of plant shoot architecture on leaf cooling: a coupled heat and mass transfer model

Plants display a range of striking architectural adaptations when grown at elevated temperatures. In the model plant Arabidopsis thaliana, these include elongation of petioles, and increased petiole and leaf angles from the soil surface. The potential physiological significance of these architectural changes remains speculative. We address this issue computationally by formulating a mathematical model and performing numerical simulations, testing the hypothesis that elongated and elevated plant configurations may reflect a leaf-cooling strategy. This sets in place a new basic model of plant water use and interaction with the surrounding air, which couples heat and mass transfer within a plant to water vapour diffusion in the air, using a transpiration term that depends on saturation, temperature and vapour concentration. A two-dimensional, multi-petiole shoot geometry is considered, with added leaf-blade shape detail. Our simulations show that increased petiole length and angle generally result in enhanced transpiration rates and reduced leaf temperatures in well-watered conditions. Furthermore, our computations also reveal plant configurations for which elongation may result in decreased transpiration rate owing to decreased leaf liquid saturation. We offer further qualitative and quantitative insights into the role of architectural parameters as key determinants of leaf-cooling capacity.     

Multi-scale modelling of the dynamics of cell colonies: insights into cell-adhesion forces and cancer invasion from in silico simulations

Studying the biophysical interactions between cells is crucial to understanding how normal tissue develops, how it is structured and also when malfunctions occur. Traditional experiments try to infer events at the tissue level after observing the behaviour of and interactions between individual cells. This approach assumes that cells behave in the same biophysical manner in isolated experiments as they do within colonies and tissues. In this paper, we develop a multi-scale multi-compartment mathematical model that accounts for the principal biophysical interactions and adhesion pathways not only at a cell–cell level but also at the level of cell colonies (in contrast to the traditional approach). Our results suggest that adhesion/separation forces between cells may be lower in cell colonies than traditional isolated single-cell experiments infer. As a consequence, isolated single-cell experiments may be insufficient to deduce important biological processes such as single-cell invasion after detachment from a solid tumour. The simulations further show that kinetic rates and cell biophysical characteristics such as pressure-related cell-cycle arrest have a major influence on cell colony patterns and can allow for the development of protrusive cellular structures as seen in invasive cancer cell lines independent of expression levels of pro-invasion molecules.     

Face masking and COVID-19: potential effects of variolation on transmission dynamics

Face masks do not completely prevent transmission of respiratory infections, but masked individuals are likely to inhale fewer infectious particles. If smaller infectious doses tend to yield milder infections, yet ultimately induce similar levels of immunity, then masking could reduce the prevalence of severe disease even if the total number of infections is unaffected. It has been suggested that this effect of masking is analogous to the pre-vaccination practice of variolation for smallpox, whereby susceptible individuals were intentionally infected with small doses of live virus (and often acquired immunity without severe disease). We present a simple epidemiological model in which mask-induced variolation causes milder infections, potentially with lower transmission rate and/or different duration. We derive relationships between the effectiveness of mask-induced variolation and important epidemiological metrics (the basic reproduction number and initial epidemic growth rate, and the peak prevalence, attack rate and equilibrium prevalence of severe infections). We illustrate our results using parameter estimates for the original SARS-CoV-2 wild-type virus, as well as the Alpha, Delta and Omicron variants. Our results suggest that if variolation is a genuine side-effect of masking, then the importance of face masks as a tool for reducing healthcare burdens from COVID-19 may be under-appreciated.     

Experimental characterization and computational modelling of two-dimensional cell spreading for skeletal regeneration.

Limited cell ingrowth is a major problem for tissue engineering and the clinical application of porous biomaterials as bone substitutes. As a first step, migration and proliferation of an interacting cell population can be studied in two-dimensional culture. Mathematical modelling is essential to generalize the results of these experiments and to derive the intrinsic parameters that can be used for predictions. However, a more thorough evaluation of theoretical models is hampered by limited experimental observations. In this study, experiments and image analysis methods were developed to provide a detailed spatial and temporal picture of how cell distributions evolve. These methods were used to quantify the migration and proliferation of skeletal cell types including MG63 and human bone marrow stromal cells (HBMSCs). The high level of detail with which the cell distributions were mapped enabled a precise assessment of the correspondence between experimental results and theoretical model predictions. This analysis revealed that the standard Fisher equation is appropriate for describing the migration behaviour of the HBMSC population, while for the MG63 cells a sharp front model is more appropriate. In combination with experiments, this type of mathematical model will prove useful in predicting cell ingrowth and improving strategies and control of skeletal tissue regeneration.     

Using causal models to distinguish between neurogenesis-dependent and -independent effects on behaviour

There has been a substantial amount of research on the relationship between hippocampal neurogenesis and behaviour over the past 15 years, but the causal role that new neurons have on cognitive and affective behavioural tasks is still far from clear. This is partly due to the difficulty of manipulating levels of neurogenesis without inducing off-target effects, which might also influence behaviour. In addition, the analytical methods typically used do not directly test whether neurogenesis mediates the effect of an intervention on behaviour. Previous studies may have incorrectly attributed changes in behavioural performance to neurogenesis because the role of known (or unknown) neurogenesis-independent mechanisms was not formally taken into consideration during the analysis. Causal models can tease apart complex causal relationships and were used to demonstrate that the effect of exercise on pattern separation is via neurogenesis-independent mechanisms. Many studies in the neurogenesis literature would benefit from the use of statistical methods that can separate neurogenesis-dependent from neurogenesis-independent effects on behaviour.     

Clonal selection and therapy resistance in acute leukaemias: mathematical modelling explains different proliferation patterns at diagnosis and relapse

Recent experimental evidence suggests that acute myeloid leukaemias may originate from multiple clones of malignant cells. Nevertheless, it is not known how the observed clones may differ with respect to cell properties, such as proliferation and self-renewal. There are scarcely any data on how these cell properties change due to chemotherapy and relapse. We propose a new mathematical model to investigate the impact of cell properties on the multi-clonal composition of leukaemias. Model results imply that enhanced self-renewal may be a key mechanism in the clonal selection process. Simulations suggest that fast proliferating and highly self-renewing cells dominate at primary diagnosis, while relapse following therapy-induced remission is triggered mostly by highly self-renewing but slowly proliferating cells. Comparison of simulation results to patient data demonstrates that the proposed model is consistent with clinically observed dynamics based on a clonal selection process.     

Local buckling modelling of isogrid and anisogrid lattice cylindrical shells with triangular cells

The paper deals with a refined analytical model for the local buckling failure modes of composite anisogrid lattice cylindrical shells made of a regular system of triangular cells. Such structures are preliminarily designed with the aid of closed-form solutions specifying the minimum mass and the corresponding optimal design variables under a set of formulated constraint equations. These equations address the main failure mechanisms that can be typically experienced by the structure due to axial compressive loads, namely, the global buckling of the shell, the local buckling of helical ribs, and the material failure of helical ribs. However, the local buckling of helical ribs is normally based on a simplified and qualitative approach. Thus, the scope of the present work is to improve the prediction of this failure mode by means of a rather accurate modelling which accounts for the interaction of intersecting hoop and helical ribs, the influence of the number of hoop sections of the shell, and the effect of the prebuckling tensile force in hoop ribs. The proposed model - that has been verified with the aid of finite-element analysis - lastly suggests the possibility to improve the preliminary design solution with respect to the fully analytical approach.     

An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

It is very important to understand the onset and growth pattern of breast primary tumours as well as their metastatic dissemination. In most cases, it is the metastatic disease that ultimately kills the patient. There is increasing evidence that cancer stem cells are closely linked to the progression of the metastatic tumour. Here, we investigate stem cell seeding to an avascular tumour site using an agent-based stochastic model of breast cancer metastatic seeding. The model includes several important cellular features such as stem cell symmetric and asymmetric division, migration, cellular quiescence, senescence, apoptosis and cell division cycles. It also includes external features such as stem cell seeding frequency and location. Using this model, we find that cell seeding rate and location are important features for tumour growth. We also define conditions in which the tumour growth exhibits decremented and exponential growth patterns. Overall, we find that seeding, senescence and division limit affect not only the number of stem cells, but also their spatial and temporal distribution.     

Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.     

Systems level approach reveals the correlation of endoderm differentiation of mouse embryonic stem cells with specific microstructural cues of fibrin gels

Stem cells receive numerous cues from their associated substrate that help to govern their behaviour. However, identification of influential substrate characteristics poses difficulties because of their complex nature. In this study, we developed an integrated experimental and systems level modelling approach to investigate and identify specific substrate features influencing differentiation of mouse embryonic stem cells (mESCs) on a model fibrous substrate, fibrin. We synthesized a range of fibrin gels by varying fibrinogen and thrombin concentrations, which led to a range of substrate stiffness and microstructure. mESCs were cultured on each of these gels, and characterization of the differentiated cells revealed a strong influence of substrate modulation on gene expression patterning. To identify specific substrate features influencing differentiation, the substrate microstructure was quantified by image analysis and correlated with stem cell gene expression patterns using a statistical model. Significant correlations were observed between differentiation and microstructure features, specifically fibre alignment. Furthermore, this relationship occurred in a lineage-specific manner towards endoderm. This systems level approach allows for identification of specific substrate features from a complex material which are influential to cellular behaviour. Such analysis may be effective in guiding the design of scaffolds with specific properties for tissue engineering applications.     

The business of modelling: some anecdotes on modelling in business and story-telling

There has been a tremendous increase in the use of computer modelling in business appraisal and decision-making over the last ten years or so. This has been driven in part by the adoption of large spreadsheets for modelling every major financial transaction, and also by the widespread availability of cheap computer power on every desk. This paper draws on the author's experiences in industry and management consulting, and argues that much of this computer modelling activity does not follow what might be termed a ‘scientific’ path. Models as actually used in business may be more usefully thought of as contributing to the ‘storytelling’ within an organisation by which it articulates and justifies its business planning.     

Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods

This study develops a new optimisation framework for process inspection planning of a manufacturing system with multiple quality characteristics, in which the proposed framework is based on a mixed-integer mathematical programming (MILP) model. Due to the stochastic nature of production processes and since their production processes are sensitive to manufacturing variations; a proportion of products do not conform the design specifications. A common source of these variations is maladjustment of each operation that leads to a higher number of scraps. Therefore, uncertainty in maladjustment is taken into account in this study. A twofold decision is made on the subject that which quality characteristic needs what kind of inspection, and the time this inspection should be performed. To cope with the introduced uncertainty, two robust optimisation methods are developed based on Taguchi and Monte Carlo methods. Furthermore, a genetic algorithm is applied to the problem to obtain near-optimal solutions. To validate the proposed model and solution approach, several numerical experiments are done on a real industrial case. Finally, the conclusion is provided.     

Spatial stochastic modelling of the Hes1 gene regulatory network: intrinsic noise can explain heterogeneity in embryonic stem cell differentiation

Individual mouse embryonic stem cells have been found to exhibit highly variable differentiation responses under the same environmental conditions. The noisy cyclic expression of Hes1 and its downstream genes are known to be responsible for this, but the mechanism underlying this variability in expression is not well understood. In this paper, we show that the observed experimental data and diverse differentiation responses can be explained by a spatial stochastic model of the Hes1 gene regulatory network. We also propose experiments to control the precise differentiation response using drug treatment.     

Fluorescent silica nanoparticles improve optical imaging of stem cells allowing direct discrimination between live and early-stage apoptotic cells

Highly bright and photostable cyanine dye-doped silica nanoparticles, IRIS Dots, are developed, which can efficiently label human mesenchymal stem cells (hMSCs). The application procedure used to label hMSCs is fast (2 h), the concentration of IRIS Dots for efficient labeling is low (20 μg mL(-1) ), and the labeled cells can be visualized by flow cytometry, confocal microscopy, and transmission electron microscopy. Labeled hMSCs are unaffected in their viability and proliferation, as well as stemness surface marker expression and differentiation capability into osteocytes. Moreover, this is the first report that shows nonfunctionalized IRIS Dots can discriminate between live and early-stage apoptotic stem cells (both mesenchymal and embryonic) through a distinct external cell surface distribution. On the basis of biocompatibility, efficient labeling, and apoptotic discrimination potential, it is suggested that IRIS Dots can serve as a promising stem cell tracking agent.     

矿化柞蚕丝胶膜表面粗糙度的调控及其对骨髓间充质干细胞生长行为的影响

生物材料表面的粗糙度是影响细胞行为的重要因素之一。为了调控丝蛋白生物材料表面的粗糙度,并评价材料表面粗糙度对细胞生长行为的影响,首先,通过湿化学共沉淀法,以柞蚕丝胶(AS)溶液为模板,诱导了羟基磷灰石(HAp)晶体成核,进而调控了AS膜表面的粗糙度。然后,采用SEM、粗糙仪、FTIR及EDX等对HAp/AS复合膜表面形貌、粗糙度及成分进行了表征。最后,通过SEM和CellTiter 96?AQueous单溶液细胞增殖检测试剂盒(MTS)检测了骨髓间充质干细胞(BMSCs)在HAp/AS复合膜表面的形貌及增殖率。结果表明:纯AS膜的表面粗糙度为0.15μm,矿化1、8及24h后,表面粗糙度分别为0.38、0.46和1.20μm;矿化24h后,在HAp/AS复合膜表面可观察到直径为30~80nm的球状复合物,生成的矿化物为HAp;HAp/AS复合膜具有良好的细胞相容性,表面粗糙度为1.20μm的复合膜能够显著促进BMSCs的增殖,粗糙度对BMSCs在HAp/AS复合膜表面的粘附和形貌有着重要的影响。因此,可通过矿化的方法在生物大分子表面诱导HAp晶体的成核与生长,从而调控材料的表面粗糙度,研究材料界面上的细胞行为。     

Effect of nanoparticle behaviour on mud cake buildup for directional and horizontal wells: mathematical modelling and experimental study

The present study examined the effect of nanoparticle size and geometry on filter cake buildup during dynamic filtration using experimental and modeling approaches. A dynamic filtration setup was proposed and designed to test cross-flow circulation against a synthetic core at a constant differential pressure. The proposed mathematical model considers the critical deposition boundary of the porous media for particles along with drag, lift, friction, buoyancy, permeate, and electrostatic forces. The comprehensive model response allowed investigation of the aggregation and shape of nanoparticles at different cross-flow inclinations. The drag and lift force coefficients and moment of inertia of the nanoparticles were determined using cluster structures of nanoparticles identified using dynamic light scattering (DLS) and fractal theory. The deposition and erosion intensity index of all solid particles were experimentally determined and used in the model. Electronic microscope images of the mud cake surface confirmed the proposed cluster structure of the aggregated particles. The mud cake thickness measured by dynamic filtration tests and the nanoparticle-bentonite weight ratio acquired by DLS showed good agreement with the mathematical model results. The proposed approach allows selection of the optimum shape and size of the nano-solid particles as additives to minimize mud cake buildup along the borehole.     

Tissue engineering of replacement skin: the crossroads of biomaterials, wound healing, embryonic development, stem cells and regeneration

Advanced therapies combating acute and chronic skin wounds are likely to be brought about using our knowledge of regenerative medicine coupled with appropriately tissue-engineered skin substitutes. At the present time, there are no models of an artificial skin that completely replicate normal uninjured skin. Natural biopolymers such as collagen and fibronectin have been investigated as potential sources of biomaterial to which cells can attach. The first generation of degradable polymers used in tissue engineering were adapted from other surgical uses and have drawbacks in terms of mechanical and degradation properties. This has led to the development of synthetic degradable gels primarily as a way to deliver cells and/or molecules in situ, the so-called smart matrix technology. Tissue or organ repair is usually accompanied by fibrotic reactions that result in the production of a scar. Certain mammalian tissues, however, have a capacity for complete regeneration without scarring; good examples include embryonic or foetal skin and the ear of the MRL/MpJ mouse. Investigations of these model systems reveal that in order to achieve such complete regeneration, the inflammatory response is altered such that the extent of fibrosis and scarring is diminished. From studies on the limited examples of mammalian regeneration, it may also be possible to exploit such models to further clarify the regenerative process. The challenge is to identify the factors and cytokines expressed during regeneration and incorporate them to create a smart matrix for use in a skin equivalent. Recent advances in the use of DNA microarray and proteomic technology are likely to aid the identification of such molecules. This, coupled with recent advances in non-viral gene delivery and stem cell technologies, may also contribute to novel approaches that would generate a skin replacement whose materials technology was based not only upon intelligent design, but also upon the molecules involved in the process of regeneration.