Structural modelling of the cardiovascular system

Computational modelling of the cardiovascular system offers much promise, but represents a truly interdisciplinary challenge, requiring knowledge of physiology, mechanics of materials, fluid dynamics and biochemistry. This paper aims to provide a summary of the recent advances in cardiovascular structural modelling, including the numerical methods, main constitutive models and modelling procedures developed to represent cardiovascular structures and pathologies across a broad range of length and timescales; serving as an accessible point of reference to newcomers to the field. The class of so-called hyperelastic materials provides the theoretical foundation for the modelling of how these materials deform under load, and so an overview of these models is provided; comparing classical to application-specific phenomenological models. The physiology is split into components and pathologies of the cardiovascular system and linked back to constitutive modelling developments, identifying current state of the art in modelling procedures from both clinical and engineering sources. Models which have originally been derived for one application and scale are shown to be used for an increasing range and for similar applications. The trend for such approaches is discussed in the context of increasing availability of high performance computing resources, where in some cases computer hardware can impact the choice of modelling approach used.     

Kinetic modelling of plant metabolic pathways

This paper provides a review of kinetic modelling of plant metabolic pathways as a tool for analysing their control and regulation. An overview of different modelling strategies is presented, starting with those approaches that only require a knowledge of the network stoichiometry; these are referred to as structural. Flux-balance analysis, metabolic flux analysis using isotope labelling, and elementary mode analysis are briefly mentioned as three representative examples. The main focus of this paper, however, is a discussion of kinetic modelling, which requires, in addition to the stoichiometry, a knowledge of the kinetic properties of the constituent pathway enzymes. The different types of kinetic modelling analysis, namely time-course simulation, steady-state analysis, and metabolic control analysis, are explained in some detail. An overview is presented of strategies for obtaining model parameters, as well as software tools available for simulation of such models. The kinetic modelling approach is exemplified with discussion of three models from the general plant physiology literature. With the aid of kinetic modelling it is possible to perform a control analysis of a plant metabolic system, to identify potential targets for biotechnological manipulation, as well as to ascertain the regulatory importance of different enzymes (including isoforms of the same enzyme) in a pathway. Finally, a framework is presented for extending metabolic models to the whole-plant scale by linking biochemical reactions with diffusion and advective flow through the phloem. Future challenges include explicit modelling of subcellular compartments, as well as the integration of kinetic models on the different levels of the cellular and organizational hierarchy.     

Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics

Functional genomics has been driven greatly by emerging experimental technologies. Its development as a scientific discipline will be enhanced by systems biology, which generates novel, quantitative hypotheses via modelling. However, in order to better assist crop improvement, the impact of developing functional genomics needs to be assessed at the crop level, given a projected diminishing effect of genetic alteration on phenotypes from the molecule to crop levels. This review illustrates a recently proposed research field, crop systems biology, which is located at the crossroads of crop physiology and functional genomics, and intends to promote communications between the two. Past experiences with modelling whole-crop physiology indicate that the layered structure of biological systems should be taken into account. Moreover, modelling not only plays a role in data synthesis and quantitative prediction, but certainly also in heuristics and system design. These roles of modelling can be applied to crop systems biology to enhance its contribution to our understanding of complex crop phenotypes and subsequently to crop improvement. The success of crop systems biology needs commitments from scientists along the entire knowledge chain of plant biology, from molecule or gene to crop and agro-ecosystem.     

Mathematical modelling in physiology

The article illustrates the method of mathematical modelling in physiology as a unique tool to study physiological processes. A number of demonstrated examples appear as a result of long-term experience in mathematical modelling of electrical and mechanical phenomena in the heart muscle. These examples are presented here to show that the modelling provides insight into mechanisms underlying these phenomena and is capable to predict new ones that were previously unknown. While potentialities of the mathematical modelling are analyzed with regard to the myocardium, they are quite universal to deal with any physiological processes.     

Hierarchical modelling of acclimatory processes

The term acclimation has been used with several connotations in the field of acclimatory physiology. An attempt has been made, in this paper, to define precisely the term “acclimation” for effective modelling of acclimatory processes. Acclimation is defined with respect to a specific variable, as cumulative experience gained by the organism when subjected to a step change in the environment. Experimental observations on a large number of variables in animals exposed to sustained stress, show that after initial deviation from the basal value (defined as “growth”), the variables tend to return to basal levels (defined as “decay”). This forms the basis for modelling biological responses in terms of their growth and decay.Hierarchical systems theory as presented by Mesarovic, Macko & Takahara (1970) facilitates modelling of complex and partially characterized systems. This theory, in conjunction with “growth-decay” analysis of biological variables, is used to model temperature regulating system in animals exposed to cold. This approach appears to be applicable at all levels of biological organization. Regulation of hormonal activity which forms a part of the temperature regulating system, and the relationship of the latter with the “energy” system of the animal of which it forms a part, are also effectively modelled by this approach. It is believed that this systematic approach would eliminate much of the current circular thinking in the area of acclimatory physiology.     

Software for systems biology: from tools to integrated platforms

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.     

In situ to in silico and back: elucidating the physiology and ecology of Geobacter spp. using genome-scale modelling

There is a wide diversity of unexplored metabolism encoded in the genomes of microorganisms that have an important environmental role. Genome-scale metabolic modelling enables the individual reactions that are encoded in annotated genomes to be organized into a coherent whole, which can then be used to predict metabolic fluxes that will optimize cell function under a range of conditions. In this Review, we summarize a series of studies in which genome-scale metabolic modelling of Geobacter spp. has resulted in an in-depth understanding of their central metabolism and ecology. A similar iterative modelling and experimental approach could accelerate elucidation of the physiology and ecology of other microorganisms inhabiting a diversity of environments, and could guide optimization of the practical applications of these species.     

Genome sequence completed of Alcanivorax borkumensis, a hydrocarbon-degrading bacterium that plays a global role in oil removal from marine systems

In this paper, we provide background to the genome sequencing project of Alcanivorax borkumensis, which is a marine bacterium that uses exclusively petroleum oil hydrocarbons as sources of carbon and energy (therefore designated "hydrocarbonoclastic"). It is found in low numbers in all oceans of the world and in high numbers in oil-contaminated waters. Its ubiquity and unusual physiology suggest it is globally important in the removal of hydrocarbons from polluted marine systems. A functional genomics analysis of Alcanivorax borkumensis strain SK2 was recently initiated, and its genome sequence has just been completed. Annotation of the genome, metabolome modelling, and functional genomics, will soon reveal important insights into the genomic basis of the properties and physiology of this fascinating and globally important bacterium.     

Integrating knowledge representation and quantitative modelling in physiology

A wealth of potentially shareable resources, such as data and models, is being generated through the study of physiology by computational means. Although in principle the resources generated are reusable, in practice, few can currently be shared. A key reason for this disparity stems from the lack of consistent cataloguing and annotation of these resources in a standardised manner. Here, we outline our vision for applying community-based modelling standards in support of an automated integration of models across physiological systems and scales. Two key initiatives, the Physiome Project and the European contribution - the Virtual Phsysiological Human Project, have emerged to support this multiscale model integration, and we focus on the role played by two key components of these frameworks, model encoding and semantic metadata annotation. We present examples of biomedical modelling scenarios (the endocrine effect of atrial natriuretic peptide, and the implications of alcohol and glucose toxicity) to illustrate the role that encoding standards and knowledge representation approaches, such as ontologies, could play in the management, searching and visualisation of physiology models, and thus in providing a rational basis for healthcare decisions and contributing towards realising the goal of of personalized medicine.     

High-resolution analysis of tomato leaf elongation: the application of novel time-series analysis techniques

This paper demonstrates the use of a novel suite of data-based, recursive modelling techniques for the investigation of biological and other time-series data, including high resolution leaf elongation. The Data-Based Mechanistic (DBM) modelling methodology rejects the common practice of empirical curve fitting for a more objective approach where the model structure is not assumed a priori, but instead is identified directly from the data series in a stochastic form. Further, this novel approach takes advantage of the latest techniques in optimal recursive estimation of non-stationary and non-linear time-series. Here, the utility and ease of use of these techniques is demonstrated in the examination of two time-series of leaf elongation in an expanding leaf of tomato (Lycopersicon esculentum L. cv. Ailsa Craig) growing in a root pressure vessel (RPV). Using this analysis, the component signals of the elongation series are extracted and considered in relation to physiological processes. It is hoped that this paper will encourage the wider use of these new techniques, as well as the associated Data-Based Mechanistic (DBM) modelling strategy, in analytical plant physiology.     

Integrating process engineering and microbiology tools to advance activated sludge wastewater treatment research and development

Wastewater treatment is a huge industryworldwide. Despite the massive capital andoperating costs, only a relatively small amountof R&D investment is made. This might havebeen related to the limited demands in terms ofeffluent quality in the past, but today'senvironmental awareness requires much strictereffluent standards to be achieved. This inturn should give sufficient incentives,together with the possible large cost savings,to increase the R&D activities in this field. There are certainly significant knowledge gapsto be filled and substantial benefits could begained from this.A range of knowledge gaps are identified inthis paper, extending from the role ofintermediates in nutrient removal overparameter estimation in modelling andsimulation to understanding the microbialmetabolic pathways at a genetic and enzymaticlevel. These gaps are opportunities andchallenges for all researchers andprofessionals in this field. Addressing themwill help substantially in the continuingdevelopment of wastewater treatmenttechnologies.The complexity of biological wastewatertreatment processes requires a broad range oftools and expertise to address the knowledgegaps. Novel process analysis tools arecritically important to investigate biologicaltreatment processes in future. They will comefrom different expertise areas and will need tobe used in close integration to gain maximalbenefits from the efforts. These tools willlikely include respirometry, novel chemicalanalyses, microsensors, gene-basedidentification, microbial physiology techniquesand integrated modelling and simulation. Examples of the application of such techniquesare provided to demonstrate the way thesetechniques may be used in future. In the nextfew years, there is likely an exciting andhighly interactive period of research anddevelopment for the wastewater industry.     

“植物抗性生理”一章的教学方法探讨

植物抗性生理主要研究植物在各种不良环境条件下的生理特征。为了提高＂植物抗性生理学＂一章的教学效果,从学生实际出发,在6个方面阐述了本章的教学方法和手段。     

Inter-model consistency and complementarity: learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology

Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.     

Broad‐scale ecological implications of ectothermy and endothermy in changing environments

Aim Physiology is emerging as a basis for understanding the distribution and diversity of organisms, and ultimately for predicting their responses to climate change. Here we review how the difference in physiology of terrestrial vertebrate ectotherms (amphibians and reptiles) and endotherms (birds and mammals) is expected to influence broad‐scale ecological patterns. Location Global terrestrial ecosystems. Methods We use data from the literature and modelling to analyse geographic gradients in energy use and thermal limits. We then compare broad‐scale ecological patterns for both groups with expectations stemming from these geographic gradients. Results The differences in thermal physiology between ectotherms and endotherms result in geographically disparate macrophysiological constraints. Field metabolic rate (FMR) is stable or decreases slightly with temperature for endotherms, while it generally increases for ectotherms, leading to opposing latitudinal gradients of expected FMR. Potential activity time is a greater constraint on the distributions of ectotherms than endotherms, particularly at high latitudes. Differences in the primary correlates of abundance and species richness for two representative taxonomic groups are consistent with the consequences of these basic physiological differences. Ectotherm richness is better predicted by temperature, whereas endotherm richness is more strongly associated with primary productivity. Finally, in contrast to endotherms, ectotherm richness is not strongly related to abundance. Main conclusions Differences in thermal physiology affect how organisms interact with and are constrained by their environment, and may ultimately explain differences in the geographic pattern of biodiversity for endotherms and ectotherms. Linking the fields of physiological and broad‐scale ecology should yield a more mechanistic understanding of how biodiversity will respond to environmental change.     

UTCI-Fiala multi-node model of human heat transfer and temperature regulation

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.     

Toward a synthetic understanding of the role of phenology in ecology and evolution

Phenology affects nearly all aspects of ecology and evolution. Virtually all biological phenomena—from individual physiology to interspecific relationships to global nutrient fluxes—have annual cycles and are influenced by the timing of abiotic events. Recent years have seen a surge of interest in this topic, as an increasing number of studies document phenological responses to climate change. Much recent research has addressed the genetic controls on phenology, modelling techniques and ecosystem-level and evolutionary consequences of phenological change. To date, however, these efforts have tended to proceed independently. Here, we bring together some of these disparate lines of inquiry to clarify vocabulary, facilitate comparisons among habitat types and promote the integration of ideas and methodologies across different disciplines and scales. We discuss the relationship between phenology and life history, the distinction between organismal- and population-level perspectives on phenology and the influence of phenology on evolutionary processes, communities and ecosystems. Future work should focus on linking ecological and physiological aspects of phenology, understanding the demographic effects of phenological change and explicitly accounting for seasonality and phenology in forecasts of ecological and evolutionary responses to climate change.     

Using functional–structural plant models to study, understand and integrate plant development and ecophysiology

Functional–structural plant models (FSPMs) explore and integrate relationships between a plant’s structure and processes that underlie its growth and development. In recent years, the range of topics being addressed by scientists interested in functional–structural plant modelling has expanded greatly. FSPM techniques are now being used to dynamically simulate growth and development occurring at the microscopic scale involving cell division in plant meristems to the macroscopic scales of whole plants and plant communities. The plant types studied also cover a broad spectrum from algae to trees. FSPM is highly interdisciplinary and involves scientists with backgrounds in plant physiology, plant anatomy, plant morphology, mathematics, computer science, cellular biology, ecology and agronomy. This special issue of Annals of Botany features selected papers that provide examples of comprehensive functional–structural models, models of key processes such as partitioning of resources, software for modelling plants and plant environments, data acquisition and processing techniques and applications of functional–structural plant models for agronomic purposes.