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The simulation and modelling of tree growth is a complex subject with a long history and an important area of research in both computer graphics and botany. For more than 50 years, new approaches to this topic have been presented frequently, including several aspects to increase realism. To further improve these achievements, we present a compact and robust functional‐structural plant model (FSPM) that is consistent with botanical rules. While we show several extensions to typical approaches, we focus mainly on the distribution of light as a resource in three‐dimensional space. We therefore present four different light distribution models based on ray tracing, space colonization, voxel‐based approaches and bounding volumes. By simulating individual light sources, we were able to create a more specified scene setup for plant simulation than it has been presented in the past. By taking into account such a more accurate distribution of light in the environment, this technique is capable of modelling realistic and diverse tree models. [ABSTRACT FROM AUTHOR]

Background: Hyperthermia treatment quality is usually evaluated by thermal (dose) parameters, though hyperthermic radiosensitization effects are also influenced by the time interval between the two modalities. This work applies biological modelling for clinical treatment evaluation of cervical cancer patients treated with radiotherapy plus hyperthermia by calculating the equivalent radiation dose (EQDRT, i.e., the dose needed for the same effect with radiation alone). Subsequent analyses evaluate the impact of logistics. Methods: Biological treatment evaluation was performed for 58 patients treated with 23–28 fractions of 1.8–2 Gy plus 4–5 weekly hyperthermia sessions. Measured temperatures (T50) and recorded time intervals between the radiotherapy and hyperthermia sessions were used to calculate the EQDRT using an extended linear quadratic (LQ) model with hyperthermic LQ parameters based on extensive experimental data. Next, the impact of a 30-min time interval (optimized logistics) as well as a 4‑h time interval (suboptimal logistics) was evaluated. Results: Median average measured T50 and recorded time intervals were 41.2 °C (range 39.7–42.5 °C) and 79 min (range 34–125 min), respectively, resulting in a median total dose enhancement (D50) of 5.5 Gy (interquartile range [IQR] 4.0–6.6 Gy). For 30-min time intervals, the enhancement would increase by ~30% to 7.1 Gy (IQR 5.5–8.1 Gy; p < 0.001). In case of 4‑h time intervals, an ~ 40% decrease in dose enhancement could be expected: 3.2 Gy (IQR 2.3–3.8 Gy; p < 0.001). Normal tissue enhancement was negligible (< 0.3 Gy), even for short time intervals. Conclusion: Biological treatment evaluation is a useful addition to standard thermal (dose) evaluation of hyperthermia treatments. Optimizing logistics to shorten time intervals seems worthwhile to improve treatment efficacy. [ABSTRACT FROM AUTHOR]

Introduction: The reduction of drag is a crucial concern within the shipping industry as it directly influences energy consumption. This study addresses this issue by proposing a novel approach inspired by the unique ridge structure found on killer whale skin. The objective is to develop a non-smooth surface drag reduction method that can effectively decrease drag and improve energy efficiency for ships.Methods: The study introduces a technique involving the creation of transverse bionic groove surfaces modeled after the killer whale skin’s ridge structure. These grooves are aligned perpendicular to the flow direction and are intended to modify the behavior of turbulent boundary layer flows that form around the ship’s hull. Numerical simulations are employed using the Shear Stress Transport k-ω model to analyze the effects of the proposed groove surface across a wide range of flow conditions. The research investigates the impact of various parameters, such as the width-to-depth ratio (λ/A), groove depth, and inlet velocity, on the drag reduction performance of the bionic groove surface.Results: The study reveals several key findings. Optimal shape parameters for the bionic groove surface are determined, enabling the most effective drag reduction. The numerical simulations demonstrate that the proposed groove surface yields notable drag reduction benefits within the velocity range of 2∼12 m/s. Specifically, the friction drag reduction ratio is measured at 26.91%, and the total drag reduction ratio at 9.63%. These reductions signify a substantial decrease in the forces opposing the ship’s movement through water, leading to enhanced energy efficiency.Discussion: Comparative analysis is conducted between the performance of the bionic groove surface and that of a smooth surface. This investigation involves the examination of velocity gradient, streamwise mean velocity, and turbulent intensity. The results indicate that the bionic groove structure effectively mitigates viscous stress and Reynolds stress, which in turn reduces friction drag. This reduction in drag is attributed to the alteration in flow behavior induced by the non-smooth surface.Conclusion: The study proposes a novel approach for drag reduction in the shipping industry by emulating the ridge structure of killer whale skin. The transverse bionic groove surface, aligned perpendicular to flow direction, demonstrates promising drag reduction outcomes across diverse flow conditions. Through systematic numerical simulations and analysis of key parameters, the research provides insights into the drag reduction mechanism and identifies optimal design parameters for the groove surface. The potential for significant energy savings and improved fuel efficiency in maritime transportation underscores the practical significance of this research.

Post‐operative bone growth and long‐term bone adaptation around the orthopaedic implants are simulated using the mechanoregulation based tissue‐differentiation and adaptive bone remodelling algorithms, respectively. The primary objective of these algorithms was to assess biomechanical feasibility and reliability of orthopaedic implants. This article aims to offer a comprehensive review of the developments in mathematical models of tissue‐differentiation and bone adaptation and their applications in studies involving design optimization of orthopaedic implants over three decades. Despite the different mechanoregulatory models developed, existing literature confirm that none of the models can be highly regarded or completely disregarded over each other. Not much development in mathematical formulations has been observed from the current state of knowledge due to the lack of in vivo studies involving clinically relevant animal models, which further retarded the development of such models to use in translational research at a fast pace. Future investigations involving artificial intelligence (AI), soft‐computing techniques and combined tissue‐differentiation and bone‐adaptation studies involving animal subjects for model verification are needed to formulate more sophisticated mathematical models to enhance the accuracy of pre‐clinical testing of orthopaedic implants. [ABSTRACT FROM AUTHOR]

Background and purpose: Photons and protons have fundamentally different properties, i.e. protons have a reduced dose bath but a higher relative biological effectiveness. Photon-based normal tissue complication probability (NTCP) models may therefore not immediately be applicable to proton therapy (PT). The aim was to derive parameters of the Lyman-Kutcher-Burman (LKB) NTCP model using prospectively recorded late morbidity data from PT, focusing on rectal morbidity and prostate cancer. Materials and methods: Prospectively collected data were available for 1151 prostate cancer patients treated with passive scattering PT and prescribed target doses of 78–82 Gy (RBE = 1.1) in 2 Gy fractions. Morbidity data (CTCAE v3.0) consisted of two alternative late grade 2 rectal bleeding endpoints: Medical Grade2A (GR2A) and procedural Grade2B (GR2B), as well as late grade 3 + urinary morbidity. GR2A + 2B were observed in 156/1047 patients (15%), GR2B in 45/1047 patients (4%), and urinary grade 3 + in 51/1151 patients (4%). LKB NTCP model parameters (D50, m, and n) were derived by maximum likelihood estimation. Results: For the rectum/rectal wall the volume parameter n was low (0.07–0.14) for both GR2A + 2B and GR2B, as was the m parameter (range: 0.16–0.20). For the bladder/bladder wall both parameters were high (n-range: 0.20–0.36; m-range: 0.32–0.36). D50 parameters were higher for GR2B of the rectum/rectal wall (95.9–98.0 Gy) and bladder/bladder wall (118.1–119.9 Gy), but lower for GR2A2B (71.7–73.6 Gy). Conclusion: PT specific LKB NTCP model parameters were derived from a population of more than 1000 patients. The D50 parameter differed for all structures and endpoints and deviated from typical photon-based LKB model values.

Integrated modelling of biological systems is becoming a necessity for constructing models containing the major biochemical processes of such systems in order to obtain a holistic understanding of their dynamics and to elucidate emergent behaviours. Hybrid modelling methods are crucial to achieve integrated modelling of biological systems. This paper reviews currently popular hybrid modelling methods, developed for systems biology, mainly revealing why they are proposed, how they are formed from single modelling formalisms and how to simulate them. By doing this, we identify future research requirements regarding hybrid approaches for further promoting integrated modelling of biological systems. [ABSTRACT FROM AUTHOR]

To achieve the best treatment of mitral valve disease in a patient, surgeons aim to optimally combine complementary surgical techniques. Image‐based in silico simulation as well as visualization of the mitral valve dynamics can support the visual analysis of the patient‐specific valvular dynamics and enable an exploration of different therapy options. The usage in a time‐constrained clinical environment requires a mitral valve model that is cost‐effective, easy to set up, parameterize and evaluate. Working towards this goal, we develop a simplified model of the mitral valve and analyse its applicability for the sketched use‐case. We propose a novel approach to simulate the mitral valve with position‐based dynamics. The resulting mitral valve model can be deformed to simulate the closing and opening, and incorporate changes caused by virtual interventions in the simulation. Ten mitral valves were reconstructed from transesophageal echocardiogram sequences of patients with normal and abnormal physiology for evaluation. Simulation results showed good agreements with expert annotations of the original image data and reproduced valve closure in all cases. In four of five pathological cases, abnormal closing behaviour was correctly reproduced. In future research, we aim to improve the parameterization of the model in terms of biomechanical correctness and perform a more extensive validation. [ABSTRACT FROM AUTHOR]

Objective. Oxygen depletion is generally believed to play an important role in the FLASH effect-a differential reduction of the radiosensitivity of healthy tissues, relative to that of the tumour under ultra-high dose-rate (UHDR) irradiation conditions. In proton therapy (PT) with pencil-beam scanning (PBS), the deposition of dose, and, hence, the degree of (radiolytic) oxygen depletion varies both spatially and temporally. Therefore, the resulting oxygen concentration and the healthy-tissue sparing effect through radiation-induced hypoxia varies both spatially and temporally as well. Approach. We propose and numerically solve a physical oxygen diffusion model to study these effects and their dependence on tissue parameters and the scan pattern in pencil-beam delivery. Since current clinical FLASH PT (FLASH-PT) is based on 250 MeV shoot-through (transmission) beams, for which dose and dose rate (DR) hardly vary with depth compared to the variation transverse to the beam axis, we focus on the two-dimensional case. We numerically integrate the model to obtain the oxygen concentration in each voxel as a function of time and extract voxel-based and spatially and temporarily integrated metrics for oxygen (FLASH) enhanced dose. Furthermore, we evaluate the impact on oxygen enhancement of standard pencil-beam delivery patterns and patterns that were optimised on dose-rate. Our model can contribute to the identification of tissue properties and pencil-beam delivery parameters that are critical for FLASH-PT and it may be used for the optimisation of FLASH-PT treatment plans and their delivery. Main results. (i) the diffusive properties of oxygen are critical for the steady state concentration and therefore the FLASH effect, even more so in two dimensions when compared to one dimension. (ii) The FLASH effect through oxygen depletion depends primarily on dose and less on other parameters. (iii) At a fixed fraction dose there is a slight dependence on DR. (iv) Scan patterns optimised on DR slightly increase the oxygen induced FLASH effect. Significance. To our best knowledge, this is the first study assessing the impact of scan-pattern optimization (SPO) in FLASH-PT with PBS on a biological FLASH model. While the observed impact of SPO is relatively small, a larger effect is expected for larger target volumes. A better understanding of the FLASH effect and the role of oxygen (depletion) therein is essential for the further development of FLASH-PT with PBS, and SPO., (Creative Commons Attribution license.)

• Proton specific multivariate NTCP models were developed for the rectum and bladder. • Anticoagulant use and age were the most prominent predictors. • V75Gy of the rectal wall and bladder was also a common predictor. • Spatial predictors of rectal bleeding were found in the lower part of the rectum. Normal tissue complication probability (NTCP) models applied for model-based patient selection to proton therapy (PT) have usually been derived using dose/volume histogram (DVH) parameters from photon-based radiotherapy. This study aimed to derive PT-specific multivariate NTCP models that also accounted for the spatial dose distribution (rectum only) as well as non-dose/volume related factors. The study included rectum and bladder DVHs, 2D rectal dose maps and relevant patient/treatment characteristics from 1151 prostate cancer cases treated with PT. Prospectively scored Grade 2 late rectal bleeding (CTCAE v3.0, also procedural interventions separately) (n = 156 (15%)) and Grade 3+ GU morbidity (n = 51 (4%)) were entered into a multivariate logistic regression analysis. Model evaluation included assessment of the area under the receiver operating characteristic curve (AUC). Anticoagulant use was a dominant predictor, chosen in four of the six rectum models and in the bladder model. Age was a dominant predictor in all procedural only rectum models while prostate volume, bladder D5% and V75Gy were predictors in the bladder model. The selection frequency of the dose/volume predictors varied widely, where the percentage of the anterior rectum surface receiving >=75 Gy was the most robust. AUC values ranged from 0.58 to 0.70 across all models, with no clear difference between the DVH- and spatial-based models for the rectum. Anticoagulant use and age were the most prominent predictors in the NTCP models. V75Gy of the rectal wall and the bladder was a predictor in the DVH-based models of the rectum and bladder respectively. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study an age-structured model which has strong biological background about mosquito plasticity. Firstly, we prove the existence of solutions and the comparison principle for a generalized system. Then, we prove the existence of the optimal control for the best harvesting. Finally, we establish necessary optimality conditions. [ABSTRACT FROM AUTHOR]

Purpose: In this study, we propose a novel laparoscopy-based renal denervation (RDN) system for treating patients with resistant hypertension. In this feasibility study, we investigated whether our proposed surgical instrument can ablate renal nerves from outside of the renal artery safely and effectively and can overcome the depth-related limitations of the previous catheter-based system with less damage to the arterial walls. Method: We designed a looped bipolar electrosurgical instrument to be used with laparoscopy-based RDN system. The tip of instrument wraps around the renal artery and delivers the radio-frequency (RF) energy. We evaluated the thermal distribution via simulation study on a numerical model designed using histological data and validated the results by the in vitro study. Finally, to show the effectiveness of this system, we compared the performance of our system with that of catheter-based RDN system through simulations. Results: Simulation results were within the 95% confidence intervals of the in vitro experimental results. The validated results demonstrated that the proposed laparoscopy-based RDN system produces an effective thermal distribution for the removal of renal sympathetic nerves without damaging the arterial wall and addresses the depth limitation of catheter-based RDN system. Conclusions: We developed a novel laparoscope-based electrosurgical RDN method for hypertension treatment. The feasibility of our system was confirmed through a simulation study as well as in vitro experiments. Our proposed method could be an effective treatment for resistant hypertension as well as central nervous system diseases. [ABSTRACT FROM AUTHOR]

Purpose:Biological modelling of thermoradiotherapy may further improve patient selection and treatment plan optimisation, but requires a model that describes the biological effect as a function of variables that affect treatment outcome (e.g. temperature, radiation dose). This study aimed to establish such a model and its parameters. Additionally, a clinical example was presented to illustrate the application. Methods:Cell survival assays were performed at various combinations of radiation dose (0–8 Gy), temperature (37–42 °C), time interval (0–4 h) and treatment sequence (radiotherapy before/after hyperthermia) for two cervical cancer cell lines (SiHa and HeLa). An extended linear-quadratic model was fitted to the data using maximum likelihood estimation. As an example application, a thermoradiotherapy plan (23 × 2 Gy + weekly hyperthermia) was compared with a radiotherapy-only plan (23 × 2 Gy) for a cervical cancer patient. The equivalent uniform radiation dose (EUD) in the tumour, including confidence intervals, was estimated using the SiHa parameters. Additionally, the difference in tumour control probability (TCP) was estimated. Results:Our model described the dependency of cell survival on dose, temperature and time interval well for both SiHa and HeLa data (R2=0.90 andR2=0.91, respectively), making it suitable for biological modelling. In the patient example, the thermoradiotherapy plan showed an increase in EUD of 9.8 Gy that was robust (95% CI: 7.7–14.3 Gy) against propagation of the uncertainty in radiobiological parameters. This corresponded to a 20% (95% CI: 15–29%) increase in TCP. Conclusions:This study presents a model that describes the cell survival as a function of radiation dose, temperature and time interval, which is essential for biological modelling of thermoradiotherapy treatments. [ABSTRACT FROM PUBLISHER]

How to think about salmon in the Deatnu River in northern Norway? Sámi local ecological experts and biological modellers respond to this question in quite different ways. Local people are embedded in complex and situated webs of relations which include people, salmon, different kinds of fishing, forms of salmon unknown to biology, the state of the river and its flow, and the activities of tourists. For the biologists salmon are known as populations, spawning escapements, stock-specific spawning targets and production potentials. The biologists argue that salmon populations are in decline, and seek fishing restrictions. Since they are close to state regulatory authorities their recommendations lead to policies which reduce fishing and seriously erode Sámi practices and ways of living. This article explores this difference and the controversies to which it leads by situating these historically in the long-term extension of colonial state power and the subordination of Sámi people. Then this difference is explored in terms of care. Arguably both scientists and local ecological experts care for salmon, but how they care and what they care for are also very different. So the biologists divide nature from culture as they care for salmon populations. Despite the fact that they are required to relate to traditional ecological knowledge, in practice population biology does not care for local people in ways recognisable to Sámi. In contrast, Sámi modes of caring simultaneously respond to salmon, to the river and to Sámi economic and cultural practices, but not to population projections. The study uses the STS focus on practice and Helen Verran’s attention to ‘going on well together in difference’ to explore how this power-saturated intersection between these two realities might be rendered more productive. It is argued that scientific ways of thinking need to be ‘softened’ while Sámi ways of knowing might be ‘hardened’ and made more transportable. [ABSTRACT FROM AUTHOR]

Detecting and analysing protein cavities provides significant information about active sites for biological processes (e.g. protein-protein or protein-ligand binding) in molecular graphics and modelling. Using the three-dimensional (3D) structure of a given protein (i.e. atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution-based, energy-based and geometry-based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere-, grid- and tessellation-based methods, but also surface-based, hybrid geometric, consensus and time-varying methods. Finally, we detail those techniques that have been customized for GPU (graphics processing unit) computing. [ABSTRACT FROM AUTHOR]

A new systems model of psoriasis is presented and analysed from the perspective of control theory. Cytokines are treated as actuators to the plant model that govern the cell population under the reasonable assumption that cytokine dynamics are faster than the cell population dynamics. The analysis of various equilibria is undertaken based on singular perturbation theory. Finite-time stability and stabilisation have been studied in various engineering applications where the principal paradigm uses non-Lipschitz functions of the states. A comprehensive study of the finite-time stability properties of the proposed psoriasis dynamics is carried out. It is demonstrated that the dynamics are finite-time convergent to certain equilibrium points rather than asymptotically or exponentially convergent. This feature of finite-time convergence motivates the development of a modified version of the Michaelis-Menten function, frequently used in biology. This framework is used to model cytokines as fast finite-time actuators. [ABSTRACT FROM AUTHOR]

Purpose:Currently, clinical decisions regarding thermoradiotherapy treatments are based on clinical experience. Quantification of the radiosensitising effect of hyperthermia allows comparison of different treatment strategies, and can support clinical decision-making regarding the optimal treatment. The software presented here enables biological evaluation of thermoradiotherapy plans through calculation of equivalent 3D dose distributions. Methods:Our in-house developed software (X-Term) uses an extended version of the linear-quadratic model to calculate equivalent radiation dose, i.e. the radiation dose yielding the same effect as the thermoradiotherapy treatment. Separate sets of model parameters can be assigned to each delineated structure, allowing tissue specific modelling of hyperthermic radiosensitisation. After calculation, the equivalent radiation dose can be evaluated according to conventional radiotherapy planning criteria. The procedure is illustrated using two realistic examples. First, for a previously irradiated patient, normal tissue dose for a radiotherapy and thermoradiotherapy plan (with equal predicted tumour control) is compared. Second, tumour control probability (TCP) is assessed for two (otherwise identical) thermoradiotherapy schedules with different time intervals between radiotherapy and hyperthermia. Results:The examples demonstrate that our software can be used for individualised treatment decisions (first example) and treatment optimisation (second example) in thermoradiotherapy. In the first example, clinically acceptable doses to the bowel were exceeded for the conventional plan, and a substantial reduction of this excess was predicted for the thermoradiotherapy plan. In the second example, the thermoradiotherapy schedule with long time interval was shown to result in a substantially lower TCP. Conclusions:Using biological modelling, our software can facilitate the evaluation of thermoradiotherapy plans and support individualised treatment decisions. [ABSTRACT FROM PUBLISHER]

Introduction: The reduction of drag is a crucial concern within the shipping industry as it directly influences energy consumption. This study addresses this issue by proposing a novel approach inspired by the unique ridge structure found on killer whale skin. The objective is to develop a non-smooth surface drag reduction method that can effectively decrease drag and improve energy efficiency for ships. Methods: The study introduces a technique involving the creation of transverse bionic groove surfaces modeled after the killer whale skin's ridge structure. These grooves are aligned perpendicular to the flow direction and are intended to modify the behavior of turbulent boundary layer flows that form around the ship's hull. Numerical simulations are employed using the Shear Stress Transport k-ω model to analyze the effects of the proposed groove surface across a wide range of flow conditions. The research investigates the impact of various parameters, such as the width-to-depth ratio (λ/A), groove depth, and inlet velocity, on the drag reduction performance of the bionic groove surface. Results: The study reveals several key findings. Optimal shape parameters for the bionic groove surface are determined, enabling the most effective drag reduction. The numerical simulations demonstrate that the proposed groove surface yields notable drag reduction benefits within the velocity range of 2∼12 m/s. Specifically, the friction drag reduction ratio is measured at 26.91%, and the total drag reduction ratio at 9.63%. These reductions signify a substantial decrease in the forces opposing the ship's movement through water, leading to enhanced energy efficiency. Discussion: Comparative analysis is conducted between the performance of the bionic groove surface and that of a smooth surface. This investigation involves the examination of velocity gradient, streamwise mean velocity, and turbulent intensity. The results indicate that the bionic groove structure effectively mitigates viscous stress and Reynolds stress, which in turn reduces friction drag. This reduction in drag is attributed to the alteration in flow behavior induced by the non-smooth surface. Conclusion: The study proposes a novel approach for drag reduction in the shipping industry by emulating the ridge structure of killer whale skin. The transverse bionic groove surface, aligned perpendicular to flow direction, demonstrates promising drag reduction outcomes across diverse flow conditions. Through systematic numerical simulations and analysis of key parameters, the research provides insights into the drag reduction mechanism and identifies optimal design parameters for the groove surface. The potential for significant energy savings and improved fuel efficiency in maritime transportation underscores the practical significance of this research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zheng, Liang, Li, Liu and Tang.)

Studying the gene regulatory networks (GRNs) that govern how cells change into specific cell types with unique roles throughout development is an active area of experimental research. The fate specification process can be viewed as a biological program prescribing the system dynamics, governed by a network of genetic interactions. To investigate the possibility that GRNs are not fixed but rather change their topology, for example as cells progress through commitment, we introduce the concept of Switching Gene Regulatory Networks (SGRNs) to enable the modelling and analysis of network reconfiguration. We define the synthesis problem of constructing SGRNs that are guaranteed to satisfy a set of constraints representing experimental observations of cell behaviour. We propose a solution to this problem that employs methods based upon Satisfiability Modulo Theories (SMT) solvers, and evaluate the feasibility and scalability of our approach by considering a set of synthetic benchmarks exhibiting possible biological behaviour of cell development. We outline how our approach is applied to a more realistic biological system, by considering a simplified network involved in the processes of neuron maturation and fate specification in the mammalian cortex. [ABSTRACT FROM AUTHOR]

Purpose Radiotherapy plan evaluation is currently performed by assessing physical parameters, which has many limitations. Biological modelling can potentially allow plan evaluation that is more reflective of clinical outcomes, however further research is required into this field before it can be used clinically. Methods A simple program, RADBIOMOD, has been developed using Visual Basic for Applications (VBA) for Microsoft Excel that incorporates multiple different biological models for radiotherapy plan evaluation, including modified Poisson tumour control probability (TCP), modified Zaider–Minerbo TCP, Lyman–Kutcher–Burman normal tissue complication probability (NTCP), equivalent uniform dose (EUD), EUD-based TCP, EUD-based NTCP, and uncomplicated tumour control probability (UTCP). RADBIOMOD was compared to existing biological modelling calculators for 15 sample cases. Results Comparing RADBIOMOD to the existing biological modelling calculators, all models tested had mean absolute errors and root mean square errors less than 1%. Conclusions RADBIOMOD produces results that are non-significantly different from existing biological modelling calculators for the models tested. It is hoped that this freely available, user-friendly program will aid future research into biological modelling. [ABSTRACT FROM AUTHOR]

A modified version of the Gierer-Meinhardt reaction-diffusion system (without source terms) is used in a model for hair follicle spacing in mice, proposed by Sick, Reinker, Timmer and Schlake. Global existence of solutions of this model system is shown by computing uniform bounds. Analysis of conditions for emergence of spatially heterogeneous solutions is performed using a limiting form of the original reaction-diffusion system. The conditions for pattern formation given in are improved by including those subregions in the parameter space where far-from-equilibrium heterogeneous solutions occur. [ABSTRACT FROM AUTHOR]

Choosing balls that best approximate a 3D object is a non-trivial problem. To answer it, we first address the inner approximation problem, which consists of approximating an object [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the stochastic, continuous and instantaneous (hybrid) modelling of systems defined in Bio-PEPA, a quantitative process algebra for biological modelling. This is achieved by mapping a Bio-PEPA model to a model in stochastic HYPE, a process algebra that models these three behaviour types in a compositional and structured manner. The novel mapping between process algebras provides another method of analysis for Bio-PEPA models and presents the modeller with a well-structured stochastic HYPE model which can itself be easily modified and is only a small constant larger in size than the Bio-PEPA model. The structure of the stochastic HYPE model generated has desirable properties and also gives a general framework for modelling biochemical systems where the advantages of both stochastic and deterministic simulation are required. Thresholds are introduced for each reaction, and when all values are above these thresholds, the reaction is treated deterministically. However, if a relevant value is below a threshold, the reaction is treated stochastically (as are the changes in species quantities as a result of that reaction). It is proved that in the purely deterministic case and in the purely stochastic case, the stochastic HYPE model has the same behaviour as the Bio-PEPA model when considered purely deterministically and purely stochastically, respectively. Furthermore, addition of instantaneous events in the style of Bio-PEPA with events is illustrated, and a proposal for mapping Bio-PEPA with delays (Bio-PEPAd) to stochastic HYPE is presented. [Copyright &y& Elsevier]

Abstract: This paper investigates Bio-PEPA, the stochastic process algebra for biological modelling developed by Ciocchetta and Hillston. It focuses on Bio-PEPA with levels where molecular counts are grouped or concentrations are discretised into a finite number of levels. Basic properties of well-defined Bio-PEPA systems are established after which equivalences used for the stochastic process algebra PEPA are considered for Bio-PEPA, and are shown to be identical for well-defined Bio-PEPA systems. Two new semantic equivalences parameterised by functions, called -bisimilarity and weak -bisimilarity are introduced. Different functions lead to different equivalences for Bio-PEPA. Congruence is shown for both forms of -bisimilarity under certain reasonable conditions on the function and the use of these equivalences are demonstrated with a biologically-motivated example where two similar species are treated as a single species, and modelling of alternative pathways in the MAPK kinase signalling cascade. [Copyright &y& Elsevier]

Abstract: This article discusses how a cognitive modelling approach for criminal behaviour can be related to a biological modelling approach. The discussion is illustrated by a case study for the behaviour of three types of violent criminals as known from literature within the area of Criminology. A cognitive model is discussed that can show each of the behaviours of these types of criminals, depending on the characteristics set and inputs in terms of stimuli from the environment. Based on literature in Criminology about motivations and opportunities and their underlying biological factors, it is shown by a formal interpretation mapping how the model can be related to a biological grounding. This formal mapping covers ontology elements for states and dynamic properties for processes, and thus shows how the cognitive model can be biologically grounded. [Copyright &y& Elsevier]

We present a model of competition between an artificially induced tumor and the adaptive immune system based on the use of an autonomous system of ordinary differential equations (ODE). The aim of this work is to reproduce experimental results which find two possible outcomes depending on the initial quantities of the tumor and the adaptive immune cells. The ODE system is positively invariant and its solutions are bounded. The linear stability analysis of the fixed points of the model yields two groups of solutions depending on the initial conditions. In the first one, the immune system wins against the tumor cells, so the cancer disappears (elimination). In the second one, the cancer keeps on growing (escape). These results are coherent with experimental results which show these two possibilities, so the model reproduces the macroscopic behavior of the experiments. From the model some conclusions on the underlying competitive behavior can be derived. [ABSTRACT FROM AUTHOR]

Multi-valued networks (MVNs) provide a simple yet expressive qualitative state based modelling approach for biological systems. In this paper we develop an abstraction theory for asynchronous MVNs that allows the state space of a model to be reduced while preserving key properties. The abstraction theory therefore provides a mechanism for coping with the state space explosion problem and supports the analysis and comparison of MVNs. We take as our starting point the abstraction theory for synchronous MVNs which uses the under-approximation approach of trace set inclusion. We show this definition of asynchronous abstraction allows the sound inference of analysis properties and preserves other interesting model properties. One problem that arises in the asynchronous case is that the trace set of an MVN can be infinite making a simple trace set inclusion check infeasible. To address this we develop a decision procedure for checking asynchronous abstractions based on using the finite state graph of an asynchronous MVN to reason about its trace semantics and formally show that this decision procedure is correct. We illustrate the abstraction techniques developed by considering two detailed case studies in which asynchronous abstractions are identified and validated for existing asynchronous MVN models taken from the literature. [ABSTRACT FROM AUTHOR]

Abstract: Bio-PEPA is a process algebra for modelling biological systems. An important aspect of Bio-PEPA is the ability it provides to discretise concentrations resulting in a smaller, more manageable state space. The discretisation is based on a step size which determines the size of each discrete level and also the number of levels. This paper considers the relationship between two discretisations of the same Bio-PEPA model that differ only in the step size and hence the number of levels, by using the idea of equivalence from concurrency and process algebra. We present a novel behavioural semantic equivalence, compression bisimilarity, and investigate when this equates two discretisations of the same model and the circumstances in which this equivalence is a congruence with respect to the synchronisation operator. [Copyright &y& Elsevier]

Abstract: Within the AMEDEUS European project, a work package is dedicated to biological modelling of Membrane Bioreactors (MBR) processes as well as the impact of a pre-treatment by primary sedimentation on sludge production, sludge characteristics and permeate quality. The supposed interest of this pre-treatment is to decrease sludge production and to improve oxygen transfer by decreasing sludge concentration. Two MBR pilots were operated side by side under the same operating conditions, one fed by screened (1mm screen) raw municipal wastewater and the other by primary settled raw municipal wastewater. This side by side operation allows a true comparison of the performances and model calibration. In average, screened water was observed to contain 30% more solids than settled water. In this study, the sludge age was fixed at 40days and then modified to 15days to calibrate the model on a broad range of operating conditions in order to validate and identify the biological activated sludge model (ASM) limits. With a sludge retention time (SRT) of 15days, sludge production is less important in the pilot fed by settled water because of better bio-accessibility behaviour of settled water. In comparison with ASM1 default parameter values, calibrated parameters are quite different concerning nitrification and denitrification because of an improvement of oxygen transfer induced by lower floc size distribution (K OA =0.25–0.3g O2/m3, K OH =0.1g O2/m3). With a SRT of 40days, model calibration is not validated and the pilot fed with screened water has a sludge production reduction that is less important than the one of the pilot fed by settled water where accumulation of inert organic matter is observed. [Copyright &y& Elsevier]

Abstract: We present an efficient algorithm for individual-based, stochastic simulation of biological populations in continuous time. A simple method for its implementation is given and it is compared to Gillespie''s commonly used Direct Method. These two methods are proven to be exactly equivalent and, using a basic evolutionary model, it is demonstrated that the new algorithm can run thousands of times faster. Furthermore, while computational cost per event increases linearly with population size under the Direct Method, this cost is independent of population size under the new algorithm. We argue that this gain in efficiency opens up the possibility to explore a new class of models in population biology. [Copyright &y& Elsevier]

Abstract: Systems biology aims to develop mathematical models of biological systems by integrating experimental and theoretical techniques. During the last decade, many systems biological approaches that base on genome-wide data have been developed to unravel the complexity of gene regulation. This review deals with the reconstruction of gene regulatory networks (GRNs) from experimental data through computational methods. Standard GRN inference methods primarily use gene expression data derived from microarrays. However, the incorporation of additional information from heterogeneous data sources, e.g. genome sequence and protein–DNA interaction data, clearly supports the network inference process. This review focuses on promising modelling approaches that use such diverse types of molecular biological information. In particular, approaches are discussed that enable the modelling of the dynamics of gene regulatory systems. The review provides an overview of common modelling schemes and learning algorithms and outlines current challenges in GRN modelling. [Copyright &y& Elsevier]

Abstract: A simplified model of a marine mussel is proposed. We model the digestive system as a cellular analogue, physically partitioned into a lysosome and endosome, with the flow of particulate carbon to represent energy. The parameters in the rate equations that govern the interactions between compartments are assumed to be a simple linear form but are consistent with experiment and observation. The model is tested first by using continuous feeding and then by using a periodic feeding representative of tidal input. The responses in both cases produce interesting results compatible with observations of the biology of the animal. We define a “health function” which indicates whether or not the animal survives. It is found that survival is critically dependent on lysosomal efficiency. [Copyright &y& Elsevier]

Abstract: This paper presents an application of Bond Graphs in physiological modelling. In this work, a Bond Graph model is utilised as boundary condition for a detailed model of an idealized mitral valve. Applications of this type fit within the framework described by the “Virtual Physiological Human” initiative. This supports the integration of physical, mechanical and biochemical models encompassing a range of different length and time scales to obtain predictive models of the human body. Because 3D detailed modelling and simulation is computationally intensive, a 3D computational model of a whole biological system is, by today’s standards, impossible to achieve. Due to their unique multi-physics nature of internal coherence, Bond Graphs are particularly suited to biological applications and can be coupled to 3D models and lumped parameter models. A specific application in cardiovascular modelling is demonstrated by focusing on a specific example; a 3D model of the mitral valve coupled to a lumped parameter model of the left ventricle. [Copyright &y& Elsevier]

We present a formal model inspired by the epigenetic process of gene annotation via histone modification. In particular, we study the generative capacity of a system in which annotations on a set of strings control which substrings are ultimately produced by the system and in which only the annotations, and not the strings themselves, may be rewritten. On a biological level this represents a first attempt to better understand the computational limits of this form of epigenetic regulation. We introduce two different derivation modes for our formal system and show that these systems are actually quite weak. The weaker of the derivation modes is directly capable only of generating a subset of the regular languages while the more powerful derivation mode is also only capable of generating all regular languages modulo a begin- and an end-marker. [ABSTRACT FROM AUTHOR]

Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. In this paper we illustrate its applicability to a complex biological system: the FGF (Fibroblast Growth Factor) signalling pathway. We give a detailed description of how this case study can be modelled in the probabilistic model checker PRISM, discussing some of the issues that arise in doing so, and show how we can thus examine a rich selection of quantitative properties of this model. We present experimental results for the case study under several different scenarios and provide a detailed analysis, illustrating how this approach can be used to yield a better understanding of the dynamics of the pathway. Finally, we outline a number of exact and approximate techniques to enable the verification of larger and more complex pathways and apply several of them to the FGF case study. [Copyright &y& Elsevier]