XFVM modelling of fracture aperture induced by shear and tensile opening.

In reservoir simulation, it is important to understand the mechanical behaviour of fractured rocks and the effect of shear and tensile displacements of fractures on their aperture. Tensile opening directly enhances the fracture aperture, whereas shear of a preexisting rough-walled fracture creates aperture changes dependent on the local stress state. Since fracture dilatation increases reservoir permeability, both processes must be included in a realistic and consistent manner into the mechanical reservoir simulation model. Here, we use the extended finite volume method (XFVM) to conduct flow and geomechanics simulations. In XFVM, fractures are embedded in a poroelastic matrix and are modelled with discontinuous basis functions. On each fracture segment the tractions and compressive forces are calculated, and one extra degree of freedom is added for both the shear and tensile displacement. In this particular XFVM implementation we assume that linear elasticity and steady state fluid pressure adequately constrain the effective stress. In this paper, shear dilation is not calculated a posteriori, but it enters the equations such that aperture changes directly affect the stress state. This is accomplished by adding shear dilation to the displacement gradients and therefore ascertains a consistent representation in the stress-strain relations and force balances. We illustrate and discuss the influence of this extra term in two simple test cases and in a realistic layer-restricted two-dimensional fracture network subjected to plausible in situ stress and pore pressure conditions.

The role of leptomeningeal collaterals in redistributing blood flow during stroke.

Leptomeningeal collaterals (LMCs) connect the main cerebral arteries and provide alternative pathways for blood flow during ischaemic stroke. This is beneficial for reducing infarct size and reperfusion success after treatment. However, a better understanding of how LMCs affect blood flow distribution is indispensable to improve therapeutic strategies. Here, we present a novel in silico approach that incorporates case-specific in vivo data into a computational model to simulate blood flow in large semi-realistic microvascular networks from two different mouse strains, characterised by having many and almost no LMCs between middle and anterior cerebral artery (MCA, ACA) territories. This framework is unique because our simulations are directly aligned with in vivo data. Moreover, it allows us to analyse perfusion characteristics quantitatively across all vessel types and for networks with no, few and many LMCs. We show that the occlusion of the MCA directly caused a redistribution of blood that was characterised by increased flow in LMCs. Interestingly, the improved perfusion of MCA-sided microvessels after dilating LMCs came at the cost of a reduced blood supply in other brain areas. This effect was enhanced in regions close to the watershed line and when the number of LMCs was increased. Additional dilations of surface and penetrating arteries after stroke improved perfusion across the entire vasculature and partially recovered flow in the obstructed region, especially in networks with many LMCs, which further underlines the role of LMCs during stroke.

Results from Canton Grisons of Switzerland suggest repetitive testing reduces SARS-CoV-2 incidence (February-March 2021).

In February 2021, in response to emergence of more transmissible SARS-CoV-2 virus variants, the Canton Grisons launched a unique RNA mass testing program targeting the labour force in local businesses. Employees were offered weekly tests free of charge and on a voluntary basis. If tested positive, they were required to self-isolate for ten days and their contacts were subjected to daily testing at work. Thereby, the quarantine of contact persons could be waved.Here, we evaluate the effects of the testing program on the tested cohorts. We examined 121,364 test results from 27,514 participants during February-March 2021. By distinguishing different cohorts of employees, we observe a noticeable decrease in the test positivity rate and a statistically significant reduction in the associated incidence rate over the considered period. The reduction in the latter ranges between 18 and 50%. The variability is partly explained by different exposures to exogenous infection sources (e.g., contacts with visiting tourists or cross-border commuters). Our analysis provides the first empirical evidence that applying repetitive mass testing to a real population over an extended period of time can prevent spread of COVID-19 pandemic. However, to overcome logistic, uptake, and adherence challenges it is important that the program is carefully designed and that disease incursion from the population outside of the program is considered and controlled.

Embedded Computational Heart Model for External Ventricular Assist Device Investigations.

PURPOSE: External cardiac assist devices are based on a promising and simple concept for treating heart failure, but they are surprisingly difficult to design. Thus, a structured approach combining experiments with computer-based optimization is essential. The latter provides the motivation for the work presented in this paper. METHODS: We present a computational modeling framework for realistic representation of the heart's tissue structure, electrophysiology and actuation. The passive heart tissue is described by a nonlinear anisotropic material law, considering fiber and sheetlet directions. For muscle contraction, an orthotropic active-strain model is employed, initiated by a periodically propagating electrical potential. The model allows for boundary conditions at the epicardium accounting for external assist devices, and it is coupled to a circulation network providing appropriate pressure boundary conditions inside the ventricles. RESULTS: Simulated results from an unsupported healthy and a pathological heart model are presented and reproduce accurate deformations compared to phenomenological measurements. Moreover, cardiac output and ventricular pressure signals are in good agreement too. By investigating the impact of applying an exemplary external actuation to the pathological heart model, it shows that cardiac patches can restore a healthy blood flow. CONCLUSION: We demonstrate that the devised computational modeling framework is capable of predicting characteristic trends (e.g. apex shortening, wall thickening and apex twisting) of a healthy heart, and that it can be used to study pathological hearts and external activation thereof.

Smart investment of virus RNA testing resources to enhance Covid-19 mitigation.

A variety of mitigation strategies have been employed against the Covid-19 pandemic. Social distancing is still one of the main methods to reduce spread, but it entails a high toll on personal freedom and economic life. Alternative mitigation strategies that do not come with the same problems but are effective at preventing disease spread are therefore needed. Repetitive mass-testing using PCR assays for viral RNA has been suggested, but as a stand-alone strategy this would be prohibitively resource intensive. Here, we suggest a strategy that aims at targeting the limited resources available for viral RNA testing to subgroups that are more likely than the average population to yield a positive test result. Importantly, these pre-selected subgroups include symptom-free people. By testing everyone in these subgroups, in addition to symptomatic cases, large fractions of pre- and asymptomatic people can be identified, which is only possible by testing-based mitigation. We call this strategy smart testing (ST). In principle, pre-selected subgroups can be found in different ways, but for the purpose of this study we analyze a pre-selection procedure based on cheap and fast virus antigen tests. We quantify the potential reduction of the epidemic reproduction number by such a two-stage ST strategy. In addition to a scenario where such a strategy is available to the whole population, we analyze local applications, e.g. in a country, company, or school, where the tested subgroups are also in exchange with the untested population. Our results suggest that a two-stage ST strategy can be effective to curb pandemic spread, at costs that are clearly outweighed by the economic benefit. It is technically and logistically feasible to employ such a strategy, and our model predicts that it is even effective when applied only within local groups. We therefore recommend adding two-stage ST to the portfolio of available mitigation strategies, which allow easing social distancing measures without compromising public health.

Dynamic modelling to identify mitigation strategies for the COVID-19 pandemic.

Relevant pandemic-spread scenario simulations can provide guiding principles for containment and mitigation policies. We devised a compartmental model to predict the effectiveness of different mitigation strategies with a main focus on mass testing. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries, and the number of COVID-19-inflicted deaths. We assumed that COVID-19 survivors are immune (e.g., mutations are not considered) and that the virus is primarily passed on by asymptomatic and pre-symptomatic individuals. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. The model parameters have been chosen in a plausible range based on information found in the literature, but it is easily adaptable, i.e., these values can be replaced by updated information any time. We compared infection rates, the total number of people getting infected and the number of deaths in different scenarios. Social distancing or mass testing can contain or drastically reduce the infections and the predicted number of deaths when compared with a situation without mitigation. We found that mass testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. It is of high practical relevance that a relationship between testing frequency and the effective reproduction number of the virus can be provided. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economic costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the COVID-19 pandemic. Moreover, we quantify the theoretical limit of contact tracing and by how much the effect of testing is enhanced, if applied to sub-populations with increased exposure risk or prevalence.

The severity of microstrokes depends on local vascular topology and baseline perfusion.

Cortical microinfarcts are linked to pathologies like cerebral amyloid angiopathy and dementia. Despite their relevance for disease progression, microinfarcts often remain undetected and the smallest scale of blood flow disturbance has not yet been identified. We employed blood flow simulations in realistic microvascular networks from the mouse cortex to quantify the impact of single-capillary occlusions. Our simulations reveal that the severity of a microstroke is strongly affected by the local vascular topology and the baseline flow rate in the occluded capillary. The largest changes in perfusion are observed in capillaries with two inflows and two outflows. This specific topological configuration only occurs with a frequency of 8%. The majority of capillaries have one inflow and one outflow and is likely designed to efficiently supply oxygen and nutrients. Taken together, microstrokes bear potential to induce a cascade of local disturbances in the surrounding tissue, which might accumulate and impair energy supply locally.

A blockage in one of the tiny blood vessels or capillaries of the brain causes a 'microstroke'. Microstrokes do not cause the same level of damage as a major stroke, which is caused by a blockage in a larger blood vessel that completely cuts off oxygen to a part of the brain for a period. But microstrokes do increase the risk of developing conditions like dementia ­ including Alzheimer's disease ­ later in life. People with these neurodegenerative conditions have fewer capillaries in their brains. The capillaries make up a mesh-like network of millions of vessels that supply most of the energy and oxygen to the brain. Repeated microstrokes may contribute to progressive loss of capillaries over time. Reduced numbers of capillaries may increase memory loss and other brain difficulties. To better understand how microstrokes affect blood flow in the brain, Schmid et al. created a computer model to simulate blood flow in capillaries in the mouse brain. Then, they modeled what happens to the blood flow when one capillary is blocked. The experiments showed that the configuration of the blocked capillary determines how much blood flow in neighboring capillaries changes. Blockages in capillaries with two vessels feeding in and two vessels feeding out caused the greatest blood flow disturbances. But these 2-in-2-out vessels only make up about 8% of all brain capillaries. Blockages in capillaries with different configurations with respect to feeding vessels had less effect. The experiments suggest that most microstrokes have limited effects on blood flow on the scale of the entire brain because of redundancies in the capillary network in the brain. However, the ability of the capillary network to adapt and reroute blood flow in response to small blockages may decrease with aging. Over time, ministrokes in a single capillary may set off a chain reaction of disturbed blood flow and more blockages. This may decrease energy and oxygen supplies explaining age- and disease-related brain decline. Better understanding the effects of microstrokes on blood flow may help scientists develop new ways to prevent such declines.

Predicting Vessel Diameter Changes to Up-Regulate Biphasic Blood Flow During Activation in Realistic Microvascular Networks.

A dense network of blood vessels distributes blood to different regions of the brain. To meet the temporarily and spatially varying energy demand resulting from changes in neuronal activity, the vasculature is able to locally up-regulate the blood supply. However, to which extent diameter changes of different vessel types contribute to the up-regulation, as well as the spatial and temporal characteristics of their changes, are currently unknown. Here, we present a new simulation method, which solves an inverse problem to calculate diameter changes of individual blood vessels needed to achieve predefined blood flow distributions in microvascular networks. This allows us to systematically compare the impact of different vessel types in various regulation scenarios. Moreover, the method offers the advantage that it handles the stochastic nature of blood flow originating from tracking the movement of individual red blood cells. Since the inverse problem is formulated for time-averaged pressures and flow rates, a deterministic approach for calculating the diameter changes is used, which allows us to apply the method for large realistic microvascular networks with high-dimensional parameter spaces. Our results obtained in both artificial and realistic microvascular networks reveal that diameter changes at the level of capillaries enable a very localized regulation of blood flow. In scenarios where only larger vessels, i.e., arterioles, are allowed to adapt, the flow increase cannot be confined to a specific activated region and flow changes spread into neighboring regions. Furthermore, relatively small dilations and constrictions of all vessel types can lead to substantial changes of capillary blood flow distributions. This suggests that small scale regulation is necessary to obtain a localized increase in blood flow.

On the mechanical power output required for human running - Insight from an analytical model.

In this paper the dynamics of human running on flat terrain and the required mechanical power output with its dependency on various parameters is investigated. Knowing the required mechanical power output is of relevance due to its relationship with the metabolic power. For example, a better understanding of the dependencies of required mechanical power output on weight, running and wind speed, step frequency, ground contact time etc. is very valuable for the assessment, analysis and optimization of running performance. Therefore, a mathematical model based on very few assumptions is devised. The purpose of the proposed model is to relate running speed and required mechanical power output as an algebraic function of the runner's mass, height, step rate, ground contact time and wind speed. This is relevant in order to better understand the mechanical energy cost of locomotion, and how much it depends on which parameters. The first of the main energy dissipation mechanisms is due to vertical oscillation, i.e., during each step some of the potential energy difference gets transformed into heat. The second mechanism is due to the anterior ground reaction force during the first part of stance and the third is due to aerodynamic drag. With the approximations of constant running speed and a sinusoidal vertical ground reaction force profile one obtains closed algebraic expressions for the center of mass trajectory and the required mechanical power output. Comparisons of model predictions and reported performance data suggest that approximately a quarter of the ground impact energy is stored during the first part of ground contact and then released during the remaining stance phase. Further, one can conclude from the model that less mechanical power output is required when running with higher step rates and a higher center of mass. Non intuitive is the result that a shorter ground contact time is beneficial for fast runs, while the opposite holds for slow runs. An important advantage of the devised model compared to others is that it leads to closed algebraic expressions for the center of mass trajectory and mechanical power output, which are functions of measurable quantities, i.e., of step rate, ground contact time, running speed, runner's mass, center of mass height, aerodynamic drag at some given speed, wind speed and heart rate. Moreover, the model relies on very few assumptions, which have been verified, and the only tuning parameter is the ratio of recovered elastic energy.

Red blood cells stabilize flow in brain microvascular networks.

Capillaries are the prime location for oxygen and nutrient exchange in all tissues. Despite their fundamental role, our knowledge of perfusion and flow regulation in cortical capillary beds is still limited. Here, we use in vivo measurements and blood flow simulations in anatomically accurate microvascular network to investigate the impact of red blood cells (RBCs) on microvascular flow. Based on these in vivo and in silico experiments, we show that the impact of RBCs leads to a bias toward equating the values of the outflow velocities at divergent capillary bifurcations, for which we coin the term "well-balanced bifurcations". Our simulation results further reveal that hematocrit heterogeneity is directly caused by the RBC dynamics, i.e. by their unequal partitioning at bifurcations and their effect on vessel resistance. These results provide the first in vivo evidence of the impact of RBC dynamics on the flow field in the cortical microvasculature. By structural and functional analyses of our blood flow simulations we show that capillary diameter changes locally alter flow and RBC distribution. A dilation of 10% along a vessel length of 100 µm increases the flow on average by 21% in the dilated vessel downstream a well-balanced bifurcation. The number of RBCs rises on average by 27%. Importantly, RBC up-regulation proves to be more effective the more balanced the outflow velocities at the upstream bifurcation are. Taken together, we conclude that diameter changes at capillary level bear potential to locally change the flow field and the RBC distribution. Moreover, our results suggest that the balancing of outflow velocities contributes to the robustness of perfusion. Based on our in silico results, we anticipate that the bi-phasic nature of blood and small-scale regulations are essential for a well-adjusted oxygen and energy substrate supply.

Vascular density and distribution in neocortex.

An amazingly wide range of complex behavior emerges from the cerebral cortex. Much of the information processing that leads to these behaviors is performed in neocortical circuits that span throughout the six layers of the cortex. Maintaining this circuit activity requires substantial quantities of oxygen and energy substrates, which are delivered by the complex yet well-organized and tightly-regulated vascular system. In this review, we provide a detailed characterization of the most relevant anatomical and functional features of the cortical vasculature. This includes a compilation of the available data on laminar variation of vascular density and the topological aspects of the microvascular system. We also review the spatio-temporal dynamics of cortical blood flow regulation and oxygenation, many aspects of which remain poorly understood. Finally, we discuss some of the important implications of vascular density, distribution, oxygenation and blood flow regulation for (laminar) fMRI.

The Relation Between Capillary Transit Times and Hemoglobin Saturation Heterogeneity. Part 2: Capillary Networks.

Brain metabolism is highly dependent on continuous oxygen supply. Cortical microvascular networks exhibit heterogeneous blood flow, leading to non-uniform tissue oxygenation and capillary hemoglobin saturation. We recently proposed capillary outflow saturation heterogeneity (COSH) to represent effects of heterogeneity on oxygen supply to tissue regions most vulnerable to hypoxia, and showed that diffusive oxygen exchange among red blood cells within capillaries and among capillaries (diffusive interaction) significantly reduces COSH in simplified geometrical configurations. Here, numerical simulations of oxygen transport in capillary network geometries derived from mouse somatosensory cortex are presented. Diffusive interaction was found to reduce COSH by 41 to 62% compared to simulations where diffusive interaction was excluded. Hemoglobin saturation drop across the microvascular network is strongly correlated with red blood cell transit time, but the coefficient of variation of saturation drop is approximately one third lower. Unexpectedly, the radius of the tissue cylinder supplied by a capillary correlates weakly with the anatomical tissue cylinder radius, but strongly with hemoglobin saturation. Thus, diffusive interaction contributes greatly to the microcirculation's ability to achieve tissue oxygenation, despite heterogeneous capillary transit time and hematocrit distribution. These findings provide insight into the effects of cerebral small vessel disease on tissue oxygenation and brain function.

The Relation Between Capillary Transit Times and Hemoglobin Saturation Heterogeneity. Part 1: Theoretical Models.

Capillary dysfunction impairs oxygen supply to parenchymal cells and often occurs in Alzheimer's disease, diabetes and aging. Disturbed capillary flow patterns have been shown to limit the efficacy of oxygen extraction and can be quantified using capillary transit time heterogeneity (CTH). However, the transit time of red blood cells (RBCs) through the microvasculature is not a direct measure of their capacity for oxygen delivery. Here we examine the relation between CTH and capillary outflow saturation heterogeneity (COSH), which is the heterogeneity of blood oxygen content at the venous end of capillaries. Models for the evolution of hemoglobin saturation heterogeneity (HSH) in capillary networks were developed and validated using a computational model with moving RBCs. Two representative situations were selected: a Krogh cylinder geometry with heterogeneous hemoglobin saturation (HS) at the inflow, and a parallel array of four capillaries. The heterogeneity of HS after converging capillary bifurcations was found to exponentially decrease with a time scale of 0.15-0.21 s due to diffusive interaction between RBCs. Similarly, the HS difference between parallel capillaries also drops exponentially with a time scale of 0.12-0.19 s. These decay times are substantially smaller than measured RBC transit times and only weakly depend on the distance between microvessels. This work shows that diffusive interaction strongly reduces COSH on a small spatial scale. Therefore, we conclude that CTH influences COSH yet does not determine it. The second part of this study will focus on simulations in microvascular networks from the rodent cerebral cortex. Actual estimates of COSH and CTH will then be given.

Depth-dependent flow and pressure characteristics in cortical microvascular networks.

A better knowledge of the flow and pressure distribution in realistic microvascular networks is needed for improving our understanding of neurovascular coupling mechanisms and the related measurement techniques. Here, numerical simulations with discrete tracking of red blood cells (RBCs) are performed in three realistic microvascular networks from the mouse cerebral cortex. Our analysis is based on trajectories of individual RBCs and focuses on layer-specific flow phenomena until a cortical depth of 1 mm. The individual RBC trajectories reveal that in the capillary bed RBCs preferentially move in plane. Hence, the capillary flow field shows laminar patterns and a layer-specific analysis is valid. We demonstrate that for RBCs entering the capillary bed close to the cortical surface (< 400 µm) the largest pressure drop takes place in the capillaries (37%), while for deeper regions arterioles are responsible for 61% of the total pressure drop. Further flow characteristics, such as capillary transit time or RBC velocity, also vary significantly over cortical depth. Comparison of purely topological characteristics with flow-based ones shows that a combined interpretation of topology and flow is indispensable. Our results provide evidence that it is crucial to consider layer-specific differences for all investigations related to the flow and pressure distribution in the cortical vasculature. These findings support the hypothesis that for an efficient oxygen up-regulation at least two regulation mechanisms must be playing hand in hand, namely cerebral blood flow increase and microvascular flow homogenization. However, the contribution of both regulation mechanisms to oxygen up-regulation likely varies over depth.

The relative influence of hematocrit and red blood cell velocity on oxygen transport from capillaries to tissue.

OBJECTIVE: Oxygen transport to parenchymal cells occurs mainly at the microvascular level and depends on convective RBC flux, which is proportional in an individual capillary to the product of capillary hematocrit and RBC velocity. This study investigates the relative influence of these two factors on tissue PO2 . METHODS: A simple analytical model is used to quantify the respective influences of hematocrit, RBC velocity, and RBC flow on tissue oxygenation around capillaries. Predicted tissue PO2 levels are compared with a detailed computational model. RESULTS: Hematocrit is shown to have a larger influence on tissue PO2 than RBC velocity. The effect of RBC velocity increases with distance from the arterioles. Good agreement between analytical and numerical results is obtained, and the discrepancies are explained. Significant dependence of MTCs on RBC velocity at low hematocrit is demonstrated. CONCLUSIONS: For a given RBC flux in a capillary, the PO2 in the surrounding tissue increases with increasing hematocrit, as a consequence of decreasing IVR to diffusive oxygen transport from RBCs to tissue. These results contribute to understanding the effects of blood flow changes on oxygen transport, such as those that occur in functional hyperemia in the brain.

The impact of capillary dilation on the distribution of red blood cells in artificial networks.

Recent studies suggest that pericytes around capillaries are contractile and able to alter the diameter of capillaries. To investigate the effects of capillary dilation on network dynamics, we performed simulations in artificial capillary networks of different sizes and complexities. The unequal partition of hematocrit at diverging bifurcations was modeled by assuming that each red blood cell (RBC) enters the branch with the faster instantaneous flow. Network simulations with and without RBCs were performed to investigate the effect of local dilations. The results showed that the increase in flow rate due to capillary dilation was less when the effects of RBCs are included. For bifurcations with sufficient RBCs in the parent vessel and nearly equal flows in the branches, the flow rate in the dilated branch did not increase. Instead, a self-regulation of flow was observed due to accumulation of RBCs in the dilated capillary. A parametric study was performed to examine the dependence on initial capillary diameter, dilation factor, and tube hematocrit. Furthermore, the conditions needed for an efficient self-regulation mechanism are discussed. The results support the hypothesis that RBCs play a significant role for the fluid dynamics in capillary networks and that it is crucial to consider the blood flow rate and the distribution of RBCs to understand the supply of oxygen in the vasculature. Furthermore, our results suggest that capillary dilation/constriction offers the potential of being an efficient mechanism to alter the distribution of RBCs locally and hence could be important for the local regulation of oxygen delivery.

A dynamic model of oxygen transport from capillaries to tissue with moving red blood cells.

Most oxygen required to support the energy needs of vertebrate tissues is delivered by diffusion from microvessels. The presence of red blood cells (RBCs) makes blood flow in the microcirculation highly heterogeneous. Additionally, flow regulation mechanisms dynamically respond to changes in tissue energy demand. These spatiotemporal variations directly affect the supply of oxygen to parenchymal cells. Due to various limiting assumptions, current models of oxygen transport cannot fully capture the consequences of complex hemodynamic effects on tissue oxygenation and are often not suitable for studying unsteady phenomena. With our new approach based on moving RBCs, the impact of blood flow heterogeneity on oxygen partial pressure (Po2) in the tissue can be quantified. Oxygen transport was simulated using parachute-shaped solid RBCs flowing through a capillary. With the use of a conical tissue domain with radii 19 and 13 µm, respectively, our computations indicate that Po2 at the RBC membrane exceeds Po2 between RBCs by 30 mmHg on average and that the mean plasma Po2 decreases by 9 mmHg over 50 µm. These results reproduce well recent intravascular Po2 measurements in the rodent brain. We also demonstrate that instantaneous variations of capillary hematocrit cause associated fluctuations of tissue Po2. Furthermore, our results suggest that homogeneous tissue oxygenation requires capillary networks to be denser on venular side than on arteriolar side. Our new model for oxygen transport will make it possible to quantify in detail the effects of blood flow heterogeneity on tissue oxygenation in realistic capillary networks.

Empirical model for target depth estimation used in the time-domain subsurface imaging.

Monte Carlo simulations were performed in order to obtain reflectance measurements from phantoms typically used in biomedical optics when either unpolarized or circularly polarized incident light is used. Phantoms contain spherical targets of different diameters, placed at different depths, with higher absorption than the surrounding medium, which are detected using a coaxial setup of laser and detector. The considered turbid media have highly anisotropic scattering phase functions, so detected light for the considered times of flight is not diffuse, but rather in the multiple-scattering regime. Therefore, the target reconstruction methods typically used in diffuse optical imaging cannot be employed. However, spatially resolved reflectance measurements in the time domain allow use of a novel reconstruction method based on the approximation of average photon trajectories, which are functions of the separation distance from the point of incidence and of the time of flight. With the approximated average photon trajectories, one can estimate the depth of the target.

Near surface swimming of Salmonella Typhimurium explains target-site selection and cooperative invasion.

Targeting of permissive entry sites is crucial for bacterial infection. The targeting mechanisms are incompletely understood. We have analyzed target-site selection by S. Typhimurium. This enteropathogenic bacterium employs adhesins (e.g. fim) and the type III secretion system 1 (TTSS-1) for host cell binding, the triggering of ruffles and invasion. Typically, S. Typhimurium invasion is focused on a subset of cells and multiple bacteria invade via the same ruffle. It has remained unclear how this is achieved. We have studied target-site selection in tissue culture by time lapse microscopy, movement pattern analysis and modeling. Flagellar motility (but not chemotaxis) was required for reaching the host cell surface in vitro. Subsequently, physical forces trapped the pathogen for ∼1.5-3 s in "near surface swimming". This increased the local pathogen density and facilitated "scanning" of the host surface topology. We observed transient TTSS-1 and fim-independent "stopping" and irreversible TTSS-1-mediated docking, in particular at sites of prominent topology, i.e. the base of rounded-up cells and membrane ruffles. Our data indicate that target site selection and the cooperative infection of membrane ruffles are attributable to near surface swimming. This mechanism might be of general importance for understanding infection by flagellated bacteria.

A coupled discrete/continuum model for describing cancer-therapeutic transport in the lung.

We propose a computational simulation framework for describing cancer-therapeutic transport in the lung. A discrete vascular graph model (VGM) is coupled to a double-continuum model (DCM) to determine the amount of administered therapeutic agent that will reach the cancer cells. An alveolar cell carcinoma is considered. The processes in the bigger blood vessels (arteries, arterioles, venules and veins) are described by the VGM. The processes in the alveolar capillaries and the surrounding tissue are represented by a continuum approach for porous media. The system of equations of the coupled discrete/continuum model contains terms that account for degradation processes of the therapeutic agent, the reduction of the number of drug molecules by the lymphatic system and the interaction of the drug with the tissue cells. The functionality of the coupled discrete/continuum model is demonstrated in example simulations using simplified pulmonary vascular networks, which are designed to show-off the capabilities of the model rather than being physiologically accurate.