Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Orientational distribution functions and order parameters in "de Vries"-type smectics : a simulation study

Simple smectic A liquid crystal phases with different types of prescribed orientational distribution functions have been simulated and compared in order to study the possibility to distinguish between the Maier-Saupe type and cone-like orientational distributions using the popular method of Davidson et al. This method has been used to extract the orientational distribution functions from simulated diffraction patterns, and the results have been compared with actual distribution functions which have been prescribed during simulations. It has been shown that it is indeed possible to distinguish between these two qualitatively different types of orientational distribution already from the shape of the 2D diffraction pattern. Moreover, typical experimental diffraction patterns for ”de Vries”-type smectic liquid crystals appear to be close to the ones which have been simulated using the prescribed Maier-Saupe orientational distribution function

ON ORDERED MINIMAL STRUCTURES

We investigate minimal rst-order structures and consider interpretability and denability of orderings on them. We also prove the minimality of their canonical substructures

Simulating tissue mechanics with Agent Based Models: concepts and perspectives

International audienceIn this paper we present an overview of agent based models that are used to simulate mechanical and physiological phenomena in cells and tissues, and we discuss underlying concepts, limitations and future perspectives of these models. As the interest in cell and tissue mechanics increase, agent based models are becoming more common the modeling community. We overview the physical aspects, complexity, shortcomings and capabilities of the major agent based model categories: lattice-based models (cellular automata, lattice gas cellular automata, cellular Potts models), off-lattice models (center based models, deformable cell models, vertex models), and hybrid discrete-continuum models. In this way, we hope to assist future researchers in choosing a model for the phenomenon they want to model and understand. The article also contains some novel results

Polimorfizm –455G/A genu β-fibrynogenu a ryzyko udaru niedokrwiennego w populacji polskiej

Background and purpose Ischaemic stroke is considered to be multifactorial and interactions between environmental and genetic factors play an important role. Although vascular risk factors are well known, the genetic ones are still undiscovered. In the present study, we assessed the significance of the β-fibrinogen –455G/A gene polymorphism and the risk of ischaemic stroke in a Polish population. Material and methods 426 ischaemic stroke patients classified according to stroke aetiologies (small vessel disease, large vessel disease or cardioembolic stroke) and 234 controls were included in the study. The association of the β-fibrinogen genotypes with ischaemic stroke was tested using logistic regression analysis under dominant, recessive or additive models of inheritance. Results The allele and genotype distributions of the β-fibrinogen –455G/A gene polymorphism did not differ significantly between patients and controls (patients: G – 75%, GG – 56.6%, GA – 36.8%, AA – 6.6%; controls: G – 73.7%, GG – 57.3%, GA – 32.9%, AA – 9.8%; p > 0.05, χ2). In addition, logistic regression analysis adjusted for the known risk factors, i.e. hypertension, ischaemic heart disease, myocardial infarction, hypercholesterolaemia, diabetes mellitus and smoking, did not show a role of the studied polymorphism in ischaemic stroke. Conclusions The β-fibrinogen –455G/A gene polymorphism is not a risk factor for ischaemic stroke in a Polish population.Wstęp i cel pracy Etiologia udaru niedokrwiennego mózgu jest wieloczynnikowa. Istotną rolę odgrywają w niej interakcje pomiędzy czynnikami środowiskowymi i genetycznymi. Naczyniowe czynniki ryzyka udaru mózgu są dość dobrze poznane, natomiast rola czynników genetycznych pozostaje wciąż niejasna. W prezentowanym badaniu oceniano znaczenie polimorfizmu –455G/A genu β-fibrynogenu w kontekście ryzyka wystąpienia udaru niedokrwiennego mózgu w populacji polskiej. Materiał i metody Do badania włączono 426 chorych na udar niedokrwienny mózgu sklasyfikowanych zgodnie z etiologią udaru (choroba małych naczyń, choroba dużych naczyń lub udar sercowozatorowy) oraz 234 osoby z grupy kontrolnej. Związek pomiędzy badanym polimorfizmem a udarem niedokrwiennym mózgu został zbadany przy użyciu regresji logistycznej w dominującym, recesywnym i addytywnym modelu dziedziczenia. Wyniki Nie stwierdzono istotnej różnicy w rozkładzie alleli i genotypów polimorfizmu –455G/A genu β-fibrynogenu pomiędzy pacjentami a osobami z grupy kontrolnej (pacjenci: G – 75%, GG – 56,6%, GA – 36,8%, AA – 6,6%; grupa kontrolna: G – 73,7%, GG – 57,3%, GA – 32,9%, AA – 9,8 %; p > 0,05, test χ2). Ponadto w modelu regresji logistycznej uwzględniającym wpływ znanych czynników ryzyka, takich jak: nadciśnienie tętnicze, choroba niedokrwienna serca, zawał mięśnia sercowego, hipercholesterolemia, cukrzyca i palenie tytoniu, nie wykazano roli badanego polimorfizmu w udarze niedokrwiennym mózgu. Wnioski Polimorfizm –455G/A genu β-fibrynogenu nie jest czynnikiem ryzyka udaru niedokrwiennego mózgu w populacji polskiej

Orientational order parameters of a de Vries–type ferroelectric liquid crystal obtained by polarized Raman spectroscopy and x-ray diffraction

The orientational order parameters 〈P2〉 and 〈P4〉 of the ferroelectric, de Vries–type liquid crystal 9HL have been determined in the SmA* and SmC* phases by means of polarized Raman spectroscopy, and in the SmA* phase using x-ray diffraction. Quantum density functional theory predicts Raman spectra for 9HL that are in good agreement with the observations and indicates that the strong Raman band probed in the experiment corresponds to the uniaxial, coupled vibration of the three phenyl rings along the molecular long axis. The magnitudes of the orientational order parameters obtained in the Raman and x-ray experiments differ dramatically from each other, a discrepancy that is resolved by considering that the two techniques probe the orientational distributions of different molecular axes. We have developed a systematic procedure in which we calculate the angle between these axes and rescale the orientational order parameters obtained from x-ray scattering with results that are then in good agreement with the Raman data. At least in the case of 9HL, the results obtained by both techniques support a “sugar loaf” orientational distribution in the SmA* phase with no qualitative difference to conventional smectics A. The role of individual molecular fragments in promoting de Vries–type behavior is considered

A proof-of-concept pipeline to guide evaluation of tumor tissue perfusion by dynamic contrast-agent imaging: Direct simulation and inverse tracer-kinetic procedures

Dynamic contrast-enhanced (DCE) perfusion imaging has shown great potential to non-invasively assess cancer development and its treatment by their characteristic tissue signatures. Different tracer kinetics models are being applied to estimate tissue and tumor perfusion parameters from DCE perfusion imaging. The goal of this work is to provide an in silico model-based pipeline to evaluate how these DCE imaging parameters may relate to the true tissue parameters. As histology data provides detailed microstructural but not functional parameters, this work can also help to better interpret such data. To this aim in silico vasculatures are constructed and the spread of contrast agent in the tissue is simulated. As a proof of principle we show the evaluation procedure of two tracer kinetic models from in silico contrast-agent perfusion data after a bolus injection. Representative microvascular arterial and venous trees are constructed in silico. Blood flow is computed in the different vessels. Contrast-agent input in the feeding artery, intra-vascular transport, intra-extravascular exchange and diffusion within the interstitial space are modeled. From this spatiotemporal model, intensity maps are computed leading to in silico dynamic perfusion images. Various tumor vascularizations (architecture and function) are studied and show spatiotemporal contrast imaging dynamics characteristic of in vivo tumor morphotypes. The Brix II also called 2CXM, and extended Tofts tracer-kinetics models common in DCE imaging are then applied to recover perfusion parameters that are compared with the ground truth parameters of the in silico spatiotemporal models. The results show that tumor features can be well identified for a certain permeability range. The simulation results in this work indicate that taking into account space explicitly to estimate perfusion parameters may lead to significant improvements in the perfusion interpretation of the current tracer-kinetics models

Variants at APOE influence risk of deep and lobar intracerebral hemorrhage

Objective Prior studies investigating the association between APOE alleles ε2/ε4 and risk of intracerebral hemorrhage (ICH) have been inconsistent and limited to small sample sizes, and did not account for confounding by population stratification or determine which genetic risk model was best applied. Methods We performed a large-scale genetic association study of 2189 ICH cases and 4041 controls from 7 cohorts, which were analyzed using additive models for ε2 and ε4. Results were subsequently meta-analyzed using a random effects model. A proportion of the individuals (322 cases, 357 controls) had available genome-wide data to adjust for population stratification. Results Alleles ε2 and ε4 were associated with lobar ICH at genome-wide significance levels (odds ratio [OR] = 1.82, 95% confidence interval [CI] = 1.50–2.23, p = 6.6 × 10 −10 ; and OR = 2.20, 95%CI = 1.85–2.63, p = 2.4 × 10 −11 , respectively). Restriction of analysis to definite/probable cerebral amyloid angiopathy ICH uncovered a stronger effect. Allele ε4 was also associated with increased risk for deep ICH (OR = 1.21, 95% CI = 1.08–1.36, p = 2.6 × 10 −4 ). Risk prediction evaluation identified the additive model as best for describing the effect of APOE genotypes. Interpretation APOE ε2 and ε4 are independent risk factors for lobar ICH, consistent with their known associations with amyloid biology. In addition, we present preliminary findings on a novel association between APOE ε4 and deep ICH. Finally, we demonstrate that an additive model for these APOE variants is superior to other forms of genetic risk modeling previously applied. ANN NEUROL 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78478/1/22134_ftp.pd

Burden of Risk Alleles for Hypertension Increases Risk of Intracerebral Hemorrhage

Background and Purpose-Genetic variation influences risk of intracerebral hemorrhage (ICH). Hypertension (HTN) is a potent risk factor for ICH and several common genetic variants (single nucleotide polymorphisms [SNPs]) associated with blood pressure levels have been identified. We sought to determine whether the cumulative burden of blood pressure-related SNPs is associated with risk of ICH and pre-ICH diagnosis of HTN. Methods-We conducted a prospective multicenter case-control study in 2272 subjects of European ancestry (1025 cases and 1247 control subjects). Thirty-nine SNPs reported to be associated with blood pressure levels were identified from the National Human Genome Research Institute genomewide association study catalog. Single-SNP association analyses were performed for the outcomes ICH and pre-ICH HTN. Subsequently, weighted and unweighted genetic risk scores were constructed using these SNPs and entered as the independent variable in logistic regression models with ICH and pre-ICH HTN as the dependent variables. Results-No single SNP was associated with either ICH or pre-ICH HTN. The blood pressure-based unweighted genetic risk score was associated with risk of ICH (OR, 1.11; 95% CI, 1.02-1.21; P=0.01) and the subset of ICH in deep regions (OR, 1.18; 95% CI, 1.07-1.30; P=0.001), but not with the subset of lobar ICH. The score was associated with a history of HTN among control subjects (OR, 1.17; 95% CI, 1.04-1.31; P=0.009) and ICH cases (OR, 1.15; 95% CI, 1.01-1.31; P=0.04). Similar results were obtained when using a weighted score. Conclusion-Increasing numbers of high blood pressure-related alleles are associated with increased risk of deep ICH as well as with clinically identified HTN. (Stroke. 2012; 43: 2877-2883.