Osteolytic metastases located in the vertebrae reduce strength and enhance the risk of vertebral fractures. This risk can be predicted by means of validated finite element models, but their reproducibility needs to be assessed. For that purpose, experimental data are requested. The aim of this study was to conduct open-access experiments on vertebrae, with artificial defect representing lytic metastasis and using well-defined boundary conditions. Twelve lumbar vertebral bodies (L1) were prepared by removing the cortical endplates and creating defects that represent lytic metastases, by drilling the cancellous bone. Vertebral bodies were scanned using clinical High Resolution peripherical Quantitative Computed Tomography before and after defect creation for 3D reconstruction. The specimens were then tested under compression loading until failure. Surface Digital Image Correlation was used to assess strain fields on the anterior wall of the vertebral body. These data (biomechanics data and the tomographic images needed to build subject-specific models) are shared with the scientific community in order to assess different vertebral models on the same dataset.
Atherosclerotic plaques are accumulations of cholesterol-engorged macrophages in the artery wall. Plaque growth is initiated and sustained by the deposition of low density lipoproteins (LDL) in the artery wall. High density lipoproteins (HDL) counterbalance the effects of LDL by accepting cholesterol from macrophages and removing it from the plaque. In this paper, we develop a free boundary multiphase model to investigate the effects of LDL and HDL on early plaque development. We examine how the rates of LDL and HDL deposition affect cholesterol accumulation in macrophages, and how this impacts cell death rates and emigration. We identify a region of LDL-HDL parameter space where plaque growth stabilises for low LDL and high HDL influxes, due to macrophage emigration and HDL clearance that counterbalances the influx of new cells and cholesterol. We explore how the efferocytic uptake of dead cells and the recruitment of new macrophages affect plaque development for a range of LDL and HDL levels. Finally, we consider how changes in the LDL-HDL profile can change the course of plaque development. We show that changes towards lower LDL and higher HDL can slow plaque growth and even induce regression. We find that these changes have less effect on larger, more established plaques, and that temporary changes will only slow plaque growth in the short term.
Thomas Klotz, Lena Lehmann, Francesco Negro
et al.
Objective: Studying motor units (MUs) is essential for understanding motor control, the detection of neuromuscular disorders and the control of human-machine interfaces. Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals. Due to our body's properties and anatomy, individual motor units can only be separated to a limited extent with surface EMG. Unlike electrical signals, magnetic fields do not interact with human tissues. This physical property and the emerging technology of quantum sensors make magnetomyography (MMG) a highly promising methodology. However, the full potential of MMG to study neuromuscular physiology has not yet been explored. Approach: In this work, we perform in silico trials that combine a biophysical model of EMG and MMG with state-of-the-art algorithms for the decomposition of motor units. This allows the prediction of an upper-bound for the motor unit decomposition accuracy. Main results: It is shown that non-invasive high-density MMG data is superior over comparable high-density surface EMG data for the robust identification of the discharge patterns of individual motor units. Decomposing MMG instead of EMG increased the number of identifiable motor units by 76%. Notably, MMG exhibits a less pronounced bias to detect superficial motor units. Significance: The presented simulations provide insights into methods to study the neuromuscular system non-invasively and in vivo that would not be easily feasible by other means. Hence, this study provides guidance for the development of novel biomedical technologies.
Carles Falcó, Daniel J. Cohen, José A. Carrillo
et al.
Although tissues are usually studied in isolation, this situation rarely occurs in biology, as cells, tissues, and organs, coexist and interact across scales to determine both shape and function. Here, we take a quantitative approach combining data from recent experiments, mathematical modelling, and Bayesian parameter inference, to describe the self-assembly of multiple epithelial sheets by growth and collision. We use two simple and well-studied continuum models, where cells move either randomly or following population pressure gradients. After suitable calibration, both models prove to be practically identifiable, and can reproduce the main features of single tissue expansions. However, our findings reveal that whenever tissue-tissue interactions become relevant, the random motion assumption can lead to unrealistic behaviour. Under this setting, a model accounting for population pressure from different cell populations is more appropriate and shows a better agreement with experimental measurements. Finally, we discuss how tissue shape and pressure affect multi-tissue collisions. Our work thus provides a systematic approach to quantify and predict complex tissue configurations with applications in the design of tissue composites and more generally in tissue engineering.
Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to summarize evidence that oscillations play critical physiological roles. Oscillatory behavior enables systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic beta cells, glycolytic oscillations are in synchrony with calcium and mitochondrial oscillations to drive pulsatile insulin release, which is pivotal for the liver to regulate blood glucose dynamics. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a rethinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed us in the clinic. A more dynamic approach will enable us to view health and disease through a new light and initiate a paradigm shift in treating diseases, including depression and cancer. This modern synthesis also takes a deeper look into the mechanisms that create, sustain and abolish oscillatory processes, which requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory.
Gopikrishnan C. Remesan, Jennifer A Flegg, Helen M Byrne
\emph{In vitro} experiments in which tumour cells are seeded in a gelatinous medium, or hydrogel, show how mechanical interactions between tumour cells and the tissue in which they are embedded, together with local levels of an externally-supplied, diffusible nutrient (e.g., oxygen), affect the tumour's growth dynamics. In this article, we present a mathematical model that describes these \emph{in vitro} experiments. We use the model to understand how tumour growth generates mechanical deformations in the hydrogel and how these deformations in turn influence the tumour's growth. The hydrogel is viewed as a nonlinear hyperelastic material and the tumour is modelled as a two-phase mixture, comprising a viscous tumour cell phase and an isotropic, inviscid interstitial fluid phase. Using a combination of numerical and analytical techniques, we show how the tumour's growth dynamics change as the mechanical properties of the hydrogel vary. When the hydrogel is soft, nutrient availability dominates the dynamics: the tumour evolves to a large equilibrium configuration where the proliferation rate of nutrient-rich cells on the tumour boundary balances the death rate of nutrient-starved cells in the central, necrotic core. As the hydrogel stiffness increases, mechanical resistance to growth increases and the tumour's equilibrium size decreases. Indeed, for small tumours embedded in stiff hydrogels, the inhibitory force experienced by the tumour cells may be so large that the tumour is eliminated. Analysis of the model identifies parameter regimes in which the presence of the hydrogel drives tumour elimination.
Daniele Poli1, Giorgio Mattei, Nadia Ucciferri
et al.
Potential human and environmental hazards resulting from the exposure of living organisms to silver nanoparticles (Ag NPs) have been the subject of intensive discussion in the last decade. Despite the growing use of Ag NPs in biomedical applications, a quantification of the toxic effects as a function of the total silver mass reaching cells (namely, target cell dose) is still needed. To provide a more accurate dose-response analysis, we propose a novel integrated approach combining well-established computational and experimental methodologies. We first used the particokinetic model (ISD3) proposed by Thomas and colleagues (2018) for providing experimental validation of computed Ag NP sedimentation in static-cuvette experiments. After validation, ISD3 was employed to predict the total mass of silver reaching human endothelial cells and hepatocytes cultured in 96 well plates. Cell viability measured after 24h of culture was then related to this target cell dose. Our results show that the dose perceived by the cell monolayer after 24 h of exposure is around 85% lower than the administered nominal media concentration. Therefore, accurate dosimetry considering particle characteristics and experimental conditions (e.g., time, size and shape of wells) should be employed for better interpreting effects induced by the amount of silver reaching cells.
Atanaska Dobreva, Renee Brady, Kamila Larripa
et al.
Uncontrolled, excessive production of pro-inflammatory mediators from immune cells and traumatized tissues can cause systemic inflammatory issues like sepsis, one of the ten leading causes of death in the United States and one of the three leading causes of death in the intensive care unit. Understanding the effects of inflammation on the autonomic control system can improve a patient's chance of recovery after an inflammatory event such as surgery. Though the effects of the autonomic response on the inflammatory system are well defined, there remains a gap in understanding the reverse response. Specifically, the impact of the inflammatory response on the autonomic control system remains unknown. In this study, we investigate hypothesized interactions of the inflammatory system with the thermal and cardiovascular regulatory systems in response to an endotoxin challenge using mathematical modeling. We calibrate the model to data from two independent studies: a) of the inflammatory response in healthy young men and b) a comparative study of the inflammatory response between mice and humans. Simulation analysis is used to explore how the model responds to pathological input and treatment, specifically antibiotics, antipyretics, vasopressors, and combination therapy. Our findings show that multimodal treatment that simultaneously targets both the pathogen and the infection symptoms gives the most favorable recovery outcome.
The pharynx of the nematode Caenorhabditis elegans is a neuromuscular pump that exhibits two typical motions: pumping and peristalsis. While the dynamics of these motions are well characterized, the underlying mechanisms generating most of them are not known. In this paper, we propose comprehensive and detailed mechanisms that can explain the various observed dynamics of the different pharyngeal areas: the dynamics of the pumping muscles - corpus, anterior isthmus, and terminal bulb - and the peristalsis dynamics of the posterior isthmus muscles. While the suggested mechanisms are consistent with all available relevant data, the assumptions on which they are based and the open questions they raise could point at additional interesting research directions on the C. elegans pharynx. We are hoping that appropriate experiments on the nematode will eventually corroborate our results, and improve our understanding of the functioning of the C. elegans pharynx, and possibly of the mammalian digestive system.
Ivo Siekmann, Stefan Bjelosevic, Kerry Landman
et al.
Haemostasis is governed by a highly complex system of interacting proteins. Due to the central role of thrombin, thrombin generation and specifically the thrombin generation curve (TGC) is commonly used as an indicator of haemostatic activity. Functional characteristics of the haemostatic system in neonates and children are significantly different compared with adults; at the same time plasma levels of haemostatic proteins vary considerably with age. However, relating one to the other has been difficult, both due to significant inter-individual differences for individuals of similar age and the complexity of the biochemical reactions underlying haemostasis. Mathematical modelling has been very successful at representing the biochemistry of blood clotting. In this study we address the challenge of large inter-individual variability by parameterising the Hockin-Mann model with data from individual patients, across different age groups from neonates to adults. Calculating TGCs for each patient of a specific age group provides us with insight into the variability of haemostatic activity across that age group. From our model we observe that two commonly used metrics for haemostatic activity are significantly lower in neonates than in older patients. Because both metrics are strongly determined by prothrombin and prothrombin levels are considerably lower in neonates we conclude that decreased haemostatic activity in neonates is due to lower prothrombin availability.
Although mechanical cues are crucial to tissue morphogenesis and development, the tissue mechanical stress field remains poorly characterized. Given traction force timelapse movies, as obtained by traction force microscopy of in vitro cellular sheets, we show that the tissue stress field can be estimated by Kalman filtering. After validation using numerical data, we apply Kalman inversion stress microscopy to experimental data. We combine the inferred stress field with velocity and cell shape measurements to quantify the rheology of epithelial cell monolayers in physiological conditions, found to be close to that of an elastic and active material.
Many neurodegenerative diseases are related to the propagation and accumulation of toxic proteins throughout the brain. The lesions created by aggregates of these toxic proteins further lead to cell death and accelerated tissue atrophy. A striking feature of some of these diseases is their characteristic pattern and evolution, leading to well-codified disease stages visible to neuropathology and associated with various cognitive deficits and pathologies. Here, we simulate the anisotropic propagation and accumulation of toxic proteins in full brain geometry. We show that the same model with different initial seeding zones reproduces the characteristic evolution of different prion-like diseases. We also recover the expected evolution of the total toxic protein load. Finally, we couple our transport model to a mechanical atrophy model to obtain the typical degeneration patterns found in neurodegenerative diseases.
Christian Thiede, Gerhard Ehninger, Kai Simons
et al.
The pathogenesis and progression of many tumors, including hematologic malignancies is highly dependent on enhanced lipogenesis. De novo fatty-acid synthesis permits accelerated proliferation of tumor cells by providing structural components to build the membranes. It may also lead to alterations of physicochemical properties of the formed membranes, which can have an impact on signaling or even increase resistance to drugs in cancer cells. Cancer type-specific lipid profiles would allow understanding the actual effects of lipid changes and therefore could potentially serve as fingerprints for individual tumors and be explored as diagnostic markers. We have used shotgun MS approach to identify lipid patterns in different types of acute myeloid leukemia (AML) patients that either show no karyotype changes or belong to t(8;21) or inv16 types. The observed differences in lipidomes of t(8;21) and inv(16) patients, as compared to AML patients without karyotype changes, concentrate mostly on substantial modulation of ceramides/sphingolipids synthesis. Also significant changes in the physicochemical properties of the membranes, between the t(8;21) and the other patients, were noted that were related to a marked alteration in the saturation levels of lipids. The revealed differences in lipid profiles of various AML types increase our understanding of the affected biochemical pathways and can potentially serve as diagnostic tools.
The dynamic interplay between collective cell movement and the various molecules involved in the accompanying cell signalling mechanisms plays a crucial role in many biological processes including normal tissue development and pathological scenarios such as wound healing and cancer. Information about the various structures embedded within these processes allows a detailed exploration of the binding of molecular species to cell-surface receptors within the evolving cell population. In this paper we establish a general spatio-temporal-structural framework that enables the description of molecular binding to cell membranes coupled with the cell population dynamics. We first provide a general theoretical description for this approach and then illustrate it with two examples arising from cancer invasion.
We propose a multiscale mechanobiological model of bone remodelling to investigate the site-specific evolution of bone volume fraction across the midshaft of a femur. The model includes hormonal regulation and biochemical coupling of bone cell populations, the influence of the microstructure on bone turnover rate, and mechanical adaptation of the tissue. Both microscopic and tissue-scale stress/strain states of the tissue are calculated from macroscopic loads by a combination of beam theory and micromechanical homogenisation. This model is applied to simulate the spatio-temporal evolution of a human midshaft femur scan subjected to two deregulating circumstances: (i) osteoporosis and (ii) mechanical disuse. Both simulated deregulations led to endocortical bone loss, cortical wall thinning and expansion of the medullary cavity, in accordance with experimental findings. Our model suggests that these observations are attributable to a large extent to the influence of the microstructure on bone turnover rate. Mechanical adaptation is found to help preserve intracortical bone matrix near the periosteum. Moreover, it leads to non-uniform cortical wall thickness due to the asymmetry of macroscopic loads introduced by the bending moment. The effect of mechanical adaptation near the endosteum can be greatly affected by whether the mechanical stimulus includes stress concentration effects or not.
The arterial system dynamically loads the heart through changes in arterial compliance. The pressure-volume relation of arteries is known to be nonlinear, but arterial compliance is often modeled as a constant value, due to ease of estimation and interpretation. Incorporating nonlinear arterial compliance affords insight into the continuous variations of arterial compliance in a cardiac cycle and its effects on the heart, as the arterial system is coupled with the left ventricle. We recently proposed a method for estimating nonlinear compliance parameters that yielded good results under various vasoactive states. This study examines the performance of the proposed method by quantifying the uncertainty of the method in the presence of noise and propagating the uncertainty through the system model to analyze its effects on model predictions. Kernel density estimation used within a bootstrap Monte Carlo simulation showed the method to be stable for various vasoactive states.
Tumors are believed to consist of a heterogeneous population of tumor cells originating from rare cancer stem cells (CSCs). However, emerging evidences show that tumor may also originate from non-CSCs. Here, we give evidences supporting that the number of tumorigenic tumor cells is higher than the number of CSCs and tumor can also derive from non-CSCs. First, we applied an idealized mathematical model and theoretically calculated that non-CSCs could initiate tumor if their proliferation potential was adequate. Next, we demonstrated by experimental studies that 17.7%, 38.6% and 5.2% of tumor cells in murine B16 solid melanoma, H22 hepatoma and Lewis lung carcinoma, respectively, were potentially tumorigenic. We propose that the rare CSCs, if exist, are not the only origination of a tumor.
The dynamic patterning of the plant hormone auxin and its efflux facilitator the PIN protein are the key regulator for the spatial and temporal organization of plant development. In particular auxin induces the polar localization of its own efflux facilitator. Due to this positive feedback auxin flow is directed and patterns of auxin and PIN arise. During the earliest stage of vein initiation in leaves auxin accumulates in a single cell in a rim of epidermal cells from which it flows into the ground meristem tissue of the leaf blade. There the localized auxin supply yields the successive polarization of PIN distribution along a strand of cells. We model the auxin and PIN dynamics within cells with a minimal canalization model. Solving the model analytically we uncover an excitable polarization front that triggers a polar distribution of PIN proteins in cells. As polarization fronts may extend to opposing directions from their initiation site we suggest a possible resolution to the puzzling occurrence of bipolar cells, such we offer an explanation for the development of closed, looped veins. Employing non-linear analysis we identify the role of the contributing microscopic processes during polarization. Furthermore, we deduce quantitative predictions on polarization fronts establishing a route to determine the up to now largely unknown kinetic rates of auxin and PIN dynamics.