Robustness of differentiation cascades with symmetric stem cell division

Stem cells (SCs) perform the task of maintaining tissue homeostasis by both self-renewal and differentiation. While it has been argued that SCs divide asymmetrically, there is also evidence that SCs undergo symmetric division. Symmetric SC division has been speculated to be key for expanding cell numbers in development and regeneration after injury. However, it might lead to uncontrolled growth and malignancies such as cancer. In order to explore the role of symmetric SC division, we propose a mathematical model of the effect of symmetric SC division on the robustness of a population regulated by a serial differentiation cascade and we show that this may lead to extinction of such population. We examine how the extinction likelihood depends on defining characteristics of the population such as the number of intermediate cell compartments. We show that longer differentiation cascades are more prone to extinction than systems with less intermediate compartments. Furthermore, we have analysed the possibility of mixed symmetric and asymmetric cell division against invasions by mutant invaders in order to find optimal architecture. Our results show that more robust populations are those with unfrequent symmetric behaviour.     

A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues

Cancers are rarely caused by single mutations, but often develop as a result of the combined effects of multiple mutations. For most cells, the number of possible cell divisions is limited because of various biological constraints, such as progressive telomere shortening, cell senescence cascades or a hierarchically organized tissue structure. Thus, the risk of accumulating cells carrying multiple mutations is low. Nonetheless, many diseases are based on the accumulation of such multiple mutations. We model a general, hierarchically organized tissue by a multi-compartment approach, allowing any number of mutations within a cell. We derive closed solutions for the deterministic clonal dynamics and the reproductive capacity of single clones. Our results hold for the average dynamics in a hierarchical tissue characterized by an arbitrary combination of proliferation parameters. We show that hierarchically organized tissues strongly suppress cells carrying multiple mutations and derive closed solutions for the expected size and diversity of clonal populations founded by a single mutant within the hierarchy. We discuss the example of childhood acute lymphoblastic leukaemia in detail and find good agreement between our predicted results and recently observed clonal diversities in patients. This result can contribute to the explanation of very diverse mutation profiles observed by whole genome sequencing of many different cancers.     

Constrained optimization of divisional load in hierarchically organized tissues during homeostasis

It has been hypothesized that the structure of tissues and the hierarchy of differentiation from stem cell to terminally differentiated cell play a significant role in reducing the incidence of cancer in that tissue. One specific mechanism by which this risk can be reduced is by minimizing the number of divisions—and hence the mutational risk—that cells accumulate as they divide to maintain tissue homeostasis. Here, we investigate a mathematical model of cell division in a hierarchical tissue, calculating and minimizing the divisional load while constraining parameters such that homeostasis is maintained. We show that the minimal divisional load is achieved by binary division trees with progenitor cells incapable of self-renewal. Contrary to the protection hypothesis, we find that an increased stem cell turnover can lead to lower divisional load. Furthermore, we find that the optimal tissue structure depends on the time horizon of the duration of homeostasis, with faster stem cell division favoured in short-lived organisms and more progenitor compartments favoured in longer-lived organisms.     

Biophysical Phenotyping and Modulation of ALDH+ Inflammatory Breast Cancer Stem‐Like Cells

Cancer stem‐like cells (CSCs) have been shown to initiate tumorigenesis and cancer metastasis in many cancer types. Although identification of CSCs through specific marker expression helps define the CSC compartment, it does not directly provide information on how or why this cancer cell subpopulation is more metastatic or tumorigenic. In this study, the functional and biophysical characteristics of aggressive and lethal inflammatory breast cancer (IBC) CSCs at the single‐cell level are comprehensively profiled using multiple microengineered tools. Distinct functional (cell migration, growth, adhesion, invasion and self‐renewal) and biophysical (cell deformability, adhesion strength and contractility) properties of ALDH+ SUM149 IBC CSCs are found as compared to their ALDH? non‐CSC counterpart, providing biophysical insights into why CSCs has an enhanced propensity to metastasize. It is further shown that the cellular biophysical phenotype can predict and determine IBC cells' tumorigenic ability. SUM149 and SUM159 IBC cells selected and modulated through biophysical attributes—adhesion and stiffness—show characteristics of CSCs in vitro and enhance tumorigenicity in in vivo murine models of primary tumor growth. Overall, the multiparametric cellular biophysical phenotyping and modulation of IBC CSCs yields a new understanding of IBC's metastatic properties and how they might develop and be targeted for therapeutic interventions.     

Cell-type based semantic segmentation of histopathological images using deep convolutional neural networks

Histopathological whole-slide image (WSI) analysis is still one of the most important ways to identify regions of cancer risk. For cancer in which early diagnosis is vital, pathologists are at the center of the decision-making process. Thanks to the widespread use of digital pathology and the development of artificial intelligence methods, automatic histopathological image analysis methods help pathologists in their decision-making process. In this process, rather than producing labels for whole-slide image patches, semantic segmentation is very useful, which facilitates the pathologists’ interpretation. In this study, automatic semantic segmentation based on cell type is proposed for the first time in the literature using novel deep convolutional networks structure (DCNN). We presents semantic information on four classes, including white areas in the whole-slide image, tissue without cells, tissue with normal cells and tissue with cancerous cells. This visual information presented to the pathologist is an easy-to-understand picture of the status of the cells and their implications for the spread of cancerous cells. A new DCNN architecture is created, inspired by the residual network and deconvolution network architecture. Our network is trained end-to-end manner with histopathological image patches for cell structures to be more discriminative. The proposed method not only produces more successful results than other state-of-art semantic segmentation algorithms with 9.2% training error and 88.89% F-score for test, but also has the most important advantage in that it has the ability to generate automatic information about the cancer and also provides information that pathologists can quickly interpret.     

Anisotropic Materials for Skeletal‐Muscle‐Tissue Engineering

Repair of damaged skeletal‐muscle tissue is limited by the regenerative capacity of the native tissue. Current clinical approaches are not optimal for the treatment of large volumetric skeletal‐muscle loss. As an alternative, tissue engineering represents a promising approach for the functional restoration of damaged muscle tissue. A typical tissue‐engineering process involves the design and fabrication of a scaffold that closely mimics the native skeletal‐muscle extracellular matrix (ECM), allowing organization of cells into a physiologically relevant 3D architecture. In particular, anisotropic materials that mimic the morphology of the native skeletal‐muscle ECM, can be fabricated using various biocompatible materials to guide cell alignment, elongation, proliferation, and differentiation into myotubes. Here, an overview of fundamental concepts associated with muscle‐tissue engineering and the current status of muscle‐tissue‐engineering approaches is provided. Recent advances in the development of anisotropic scaffolds with micro‐ or nanoscale features are reviewed, and how scaffold topographical, mechanical, and biochemical cues correlate to observed cellular function and phenotype development is examined. Finally, some recent developments in both the design and utility of anisotropic materials in skeletal‐muscle‐tissue engineering are highlighted, along with their potential impact on future research and clinical applications.     

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.     

The Fibrillar Matrix: Novel Avenues for Breast Cancer Detection and Treatment

Breast cancer is marked by large increases in the protein fibers around tumor cells. These fibers increase the mechanical stiffness of the tissue, which has long been used for tumor diagnosis by manual palpation. Recent research in bioengineering has led to the development of novel biomaterials that model the mechanical and architectural properties of the tumor microenvironment and can be used to understand how these cues regulate the growth and spread of breast cancer. Herein, we provide an overview of how the mechanical properties of breast tumor tissues differ from those of normal breast tissue and non-cancerous lesions. We also describe how biomaterial models make it possible to understand how the stiffness and viscosity of the extracellular environment regulate cell migration and breast cancer metastasis. We highlight the need for biomaterial models that allow independent analysis of the individual and different mechanical properties of the tumor microenvironment and that use cells derived from different regions within tumors. These models will guide the development of novel mechano-based therapies against breast cancer metastasis.     

Integrated workforce capacity and inventory management under labour supply uncertainty

In a manufacturing environment with volatile demand, inventory management can be coupled with dynamic capacity adjustments for handling the fluctuations more effectively. In this study, we consider the problem of integrated capacity and inventory management under non-stationary stochastic demand and capacity uncertainty. The capacity planning problem is investigated from the workforce planning perspective where the capacity can be temporarily increased by utilising contingent workers from an external labour supply agency. The contingent capacity received from the agency is subject to an uncertainty, but the supply of a certain number of workers can be guaranteed through contracts. There may also be uncertainty in the availability of the permanent and contracted workers due to factors such as absenteeism and fatigue. We formulate a dynamic programming model to make the optimal capacity decisions at a tactical level (permanent workforce size and contracted number of workers) as well as the operational level (number of workers to be requested from the external labour supply agency in each period), integrated with the optimal operational decision of how much to produce in each period. We analyse the characteristics of the optimal policies and we conduct an extensive numerical analysis that helps us provide several managerial insights.     

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.     

Nanosized fibers' effect on adult human articular chondrocytes behavior

Tissue engineering with chondrogenic cell based therapies is an expanding field with the intention of treating cartilage defects. It has been suggested that scaffolds used in cartilage tissue engineering influence cellular behavior and thus the long-term clinical outcome. The objective of this study was to assess whether chondrocyte attachment, proliferation and post-expansion re-differentiation could be influenced by the size of the fibers presented to the cells in a scaffold. Polylactic acid (PLA) scaffolds with different fiber morphologies were produced, i.e. microfiber (MS) scaffolds as well as nanofiber-coated microfiber scaffold (NMS). Adult human articular chondrocytes were cultured in the scaffolds in vitro up to 28 days, and the resulting constructs were assessed histologically, immunohistochemically, and biochemically. Attachment of cells and serum proteins to the scaffolds was affected by the architecture. The results point toward nano-patterning onto the microfibers influencing proliferation of the chondrocytes, and the overall 3D environment having a greater influence on the re-differentiation. In the efforts of finding the optimal scaffold for cartilage tissue engineering, studies as the current contribute to the knowledge of how to affect and control chondrocytes behavior.     

3D Bioprinting: from Benches to Translational Applications

Over the last decades, the fabrication of 3D tissues has become commonplace in tissue engineering and regenerative medicine. However, conventional 3D biofabrication techniques such as scaffolding, microengineering, and fiber and cell sheet engineering are limited in their capacity to fabricate complex tissue constructs with the required precision and controllability that is needed to replicate biologically relevant tissues. To this end, 3D bioprinting offers great versatility to fabricate biomimetic, volumetric tissues that are structurally and functionally relevant. It enables precise control of the composition, spatial distribution, and architecture of resulting constructs facilitating the recapitulation of the delicate shapes and structures of targeted organs and tissues. This Review systematically covers the history of bioprinting and the most recent advances in instrumentation and methods. It then focuses on the requirements for bioinks and cells to achieve optimal fabrication of biomimetic constructs. Next, emerging evolutions and future directions of bioprinting are discussed, such as freeform, high‐resolution, multimaterial, and 4D bioprinting. Finally, the translational potential of bioprinting and bioprinted tissues of various categories are presented and the Review is concluded by exemplifying commercially available bioprinting platforms.     

Mathematical modelling of adult hippocampal neurogenesis: effects of altered stem cell dynamics on cell counts and bromodeoxyuridine-labelled cells

In the adult hippocampus, neurogenesis—the process of generating mature granule cells from adult neural stem cells—occurs throughout the entire lifetime. In order to investigate the involved regulatory mechanisms, knockout (KO) experiments, which modify the dynamic behaviour of this process, were conducted in the past. Evaluating these KOs is a non-trivial task owing to the complicated nature of the hippocampal neurogenic niche. In this study, we model neurogenesis as a multicompartmental system of ordinary differential equations based on experimental data. To analyse the results of KO experiments, we investigate how changes of cell properties, reflected by model parameters, influence the dynamics of cell counts and of the experimentally observed counts of cells labelled by the cell division marker bromodeoxyuridine (BrdU). We find that changing cell proliferation rates or the fraction of self-renewal, reflecting the balance between symmetric and asymmetric cell divisions, may result in multiple time phases in the response of the system, such as an initial increase in cell counts followed by a decrease. Furthermore, these phases may be qualitatively different in cells at different differentiation stages and even between mitotically labelled cells and all cells existing in the system.     

Next generation adoptive immunotherapy--human T cells as carriers of therapeutic nanoparticles

An important step in adoptive immunotherapy in general and specifically with respect to cancer treatment is the initiation of an inflammatory T cell response at the tumor site. Here we suggest a new concept for a controlled inflammatory response in which the intrinsic cytotoxic properties of T cells are upgraded with the properties of nanoparticles transfected into the T cells during the ex vivo expansion process. We report in vitro upgrading of human T cells using PEGylated boron carbide nanoparticles functionalised with a translocation peptide aimed at Boron Neutron Capture Therapy (BNCT). A key finding is that the metabolism of such upgraded human T cells were not affected by a payload of 0.13 pg boron per cell and that the nanoparticles were retained in the cell population after several cell divisions. This is vital for transporting nanoparticles by T cells to the tumor site.     

An Extension to the Class of Easy Economic Lot Scheduling Problems

We extend known conditions under which a rotation schedule is optimal in the Economic Lot Scheduling Problem by using a tighter lower bound that explicitly considers machine capacity. We also show how these results can be used when backorders are allowed.     

Mechano-biology as an optimization principle for biological tissue engineering

Rapid prototyping and direct fabrication has provided researchers and scientist with a wealth of opportunities to fabricate synthetic tissue replacements, so called scaffolds. The goal is to fill critical size defects with such materials and allow the body to slowly degrade them and build de-novo biological tissue on its place. However, for this process to take place the structural organization levels of these synthetic tissue replacements need to follow design criteria that promote cell attachment, cell proliferation, and maintain the cell's differentiated function. The scaffold's architecture defines the ultimate shape of the newly grown tissue. Furthermore, since most scaffolds are needed for tissue repair in load-bearing applications, the mechano-biological component affects tissue growth long after biochemical factors (e.g., growth hormones) or pre-seeded cells are lasting. This article describes current efforts in identifying mechano-biological principle that are believed to guide tissue formation based on biomechanical loading.     

Spatial moment dynamics for collective cell movement incorporating a neighbour-dependent directional bias

The ability of cells to undergo collective movement plays a fundamental role in tissue repair, development and cancer. Interactions occurring at the level of individual cells may lead to the development of spatial structure which will affect the dynamics of migrating cells at a population level. Models that try to predict population-level behaviour often take a mean-field approach, which assumes that individuals interact with one another in proportion to their average density and ignores the presence of any small-scale spatial structure. In this work, we develop a lattice-free individual-based model (IBM) that uses random walk theory to model the stochastic interactions occurring at the scale of individual migrating cells. We incorporate a mechanism for local directional bias such that an individual''s direction of movement is dependent on the degree of cell crowding in its neighbourhood. As an alternative to the mean-field approach, we also employ spatial moment theory to develop a population-level model which accounts for spatial structure and predicts how these individual-level interactions propagate to the scale of the whole population. The IBM is used to derive an equation for dynamics of the second spatial moment (the average density of pairs of cells) which incorporates the neighbour-dependent directional bias, and we solve this numerically for a spatially homogeneous case.     

Effect of different modes of viral spread on the dynamics of multiply infected cells in human immunodeficiency virus infection

Infection of individual cells with more than one HIV particle is an important feature of HIV replication, which may contribute to HIV pathogenesis via the occurrence of recombination, viral complementation and other outcomes that influence HIV replication and evolutionary dynamics. A previous mathematical model of co-infection has shown that the number of cells infected with i viruses correlates with the ith power of the singly infected cell population, and this has partly been observed in experiments. This model, however, assumed that virus spread from cell to cell occurs only via free virus particles, and that viruses and cells mix perfectly. Here, we introduce a cellular automaton model that takes into account different modes of virus spread among cells, including cell to cell transmission via the virological synapse, and spatially constrained virus spread. In these scenarios, it is found that the number of multiply infected cells correlates linearly with the number of singly infected cells, meaning that co-infection plays a greater role at lower virus loads. The model further indicates that current experimental systems that are used to study co-infection dynamics fail to reflect the true dynamics of multiply infected cells under these specific assumptions, and that new experimental techniques need to be designed to distinguish between the different assumptions.     

Succession of hide–seek and pursuit–evasion at heterogeneous locations

Many interactions between searching agents and their elusive targets are composed of a succession of steps, whether in the context of immune systems, predation or counterterrorism. In the simplest case, a two-step process starts with a search-and-hide phase, also called a hide-and-seek phase, followed by a round of pursuit–escape. Our aim is to link these two processes, usually analysed separately and with different models, in a single game theory context. We define a matrix game in which a searcher looks at a fixed number of discrete locations only once each searching for a hider, which can escape with varying probabilities according to its location. The value of the game is the overall probability of capture after k looks. The optimal search and hide strategies are described. If a searcher looks only once into any of the locations, an optimal hider chooses it''s hiding place so as to make all locations equally attractive. This optimal strategy remains true as long as the number of looks is below an easily calculated threshold; however, above this threshold, the optimal position for the hider is where it has the highest probability of escaping once spotted.     

Evaluating cell proliferation based on internal pore size and 3D scaffold architecture fabricated using solid freeform fabrication technology

The scaffold, as a medical component to regenerate tissues or organs in humans, plays an important role in tissue engineering. Recently, solid freeform fabrication (SFF) technology using computer-assisted methods was applied to address the problems of conventional fabrication methods in which the internal/outer architectures cannot be controlled. In this report, we propose suitable scaffolds for bone tissue regeneration considering the internal pore size and scaffold architecture. Poly(propylene fumarate) was used as the biodegradable photopolymer, and scaffolds were fabricated using microstereolithography (MSTL). We observed the relationship between the internal pores and architecture, and the proliferation of pre-osteoblast cells. To demonstrate the superiority of MSTL, we fabricated conventional and SFF scaffolds, and measured the cell proliferation rates for each. The results showed that cell proliferation on the MSTL scaffold was clearly superior and indicated that MSTL would be a good replacement for current conventional methods.