Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

Agriculture is important to New Zealand’s economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer’s decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.     

Using Agent-Based Modelling to Predict the Role of Wild Refugia in the Evolution of Resistance of Sea Lice to Chemotherapeutants

A major challenge for Atlantic salmon farming in the northern hemisphere is infestation by the sea louse parasite Lepeophtheirus salmonis. The most frequent method of controlling these sea louse infestations is through the use of chemical treatments. However, most major salmon farming areas have observed resistance to common chemotherapeutants. In terrestrial environments, many strategies employed to manage the evolution of resistance involve the use of refugia, where a portion of the population is left untreated to maintain susceptibility. While refugia have not been deliberately used in Atlantic salmon farming, wild salmon populations that migrate close to salmon farms may act as natural refugia. In this paper we describe an agent-based model that explores the influence of different sizes of wild salmon populations on resistance evolution in sea lice on a salmon farm. Using the model, we demonstrate that wild salmon populations can act as refugia that limit the evolution of resistance in the sea louse populations. Additionally, we demonstrate that an increase in the size of the population of wild salmon results in an increased effect in slowing the evolution of resistance. We explore the effect of a population fitness cost associated with resistance, finding that in some cases it substantially reduces the speed of evolution to chemical treatments.     

The Role of Pre-Existing Disturbances in the Effect of Marine Reserves on Coastal Ecosystems: A Modelling Approach

We have used an end-to-end ecosystem model to explore responses over 30 years to coastal no-take reserves covering up to 6% of the fifty thousand square kilometres of continental shelf and slope off the coast of New South Wales (Australia). The model is based on the Atlantis framework, which includes a deterministic, spatially resolved three-dimensional biophysical model that tracks nutrient flows through key biological groups, as well as extraction by a range of fisheries. The model results support previous empirical studies in finding clear benefits of reserves to top predators such as sharks and rays throughout the region, while also showing how many of their major prey groups (including commercial species) experienced significant declines. It was found that the net impact of marine reserves was dependent on the pre-existing levels of disturbance (i.e. fishing pressure), and to a lesser extent on the size of the marine reserves. The high fishing scenario resulted in a strongly perturbed system, where the introduction of marine reserves had clear and mostly direct effects on biomass and functional biodiversity. However, under the lower fishing pressure scenario, the introduction of marine reserves caused both direct positive effects, mainly on shark groups, and indirect negative effects through trophic cascades. Our study illustrates the need to carefully align the design and implementation of marine reserves with policy and management objectives. Trade-offs may exist not only between fisheries and conservation objectives, but also among conservation objectives.     

The Role of Fusion in Ant Chromosome Evolution: Insights from Cytogenetic Analysis Using a Molecular Phylogenetic Approach in the Genus Mycetophylax

Among insect taxa, ants exhibit one of the most variable chromosome numbers ranging from n = 1 to n = 60. This high karyotype diversity is suggested to be correlated to ants diversification. The karyotype evolution of ants is usually understood in terms of Robertsonian rearrangements towards an increase in chromosome numbers. The ant genus Mycetophylax is a small monogynous basal Attini ant (Formicidae: Myrmicinae), endemic to sand dunes along the Brazilian coastlines. A recent taxonomic revision validates three species, Mycetophylax morschi, M. conformis and M. simplex. In this paper, we cytogenetically characterized all species that belongs to the genus and analyzed the karyotypic evolution of Mycetophylax in the context of a molecular phylogeny and ancestral character state reconstruction. M. morschi showed a polymorphic number of chromosomes, with colonies showing 2n = 26 and 2n = 30 chromosomes. M. conformis presented a diploid chromosome number of 30 chromosomes, while M. simplex showed 36 chromosomes. The probabilistic models suggest that the ancestral haploid chromosome number of Mycetophylax was 17 (Likelihood framework) or 18 (Bayesian framework). The analysis also suggested that fusions were responsible for the evolutionary reduction in chromosome numbers of M. conformis and M. morschi karyotypes whereas fission may determines the M. simplex karyotype. These results obtained show the importance of fusions in chromosome changes towards a chromosome number reduction in Formicidae and how a phylogenetic background can be used to reconstruct hypotheses about chromosomes evolution.     

A Multiscale Approach to the Migration of Cancer Stem Cells: Mathematical Modelling and Simulations

We propose a multiscale model for the invasion of the extracellular matrix by two types of cancer cells, the differentiated cancer cells and the cancer stem cells. We investigate the epithelial mesenchymal-like transition between them being driven primarily by the epidermal growth factors. We moreover take into account the transdifferentiation program of the cancer stem cells towards the cancer-associated fibroblast cells as well as the fibroblast-driven remodelling of the extracellular matrix. The proposed haptotaxis model combines the macroscopic phenomenon of the invasion of the extracellular matrix by both types of cancer cells with the microscopic dynamics of the epidermal growth factors. We analyse our model in a component-wise manner and compare our findings with the literature. We investigate pathological situations regarding the epidermal growth factors and accordingly propose “mathematical-treatment” scenarios to control the aggressiveness of the tumour.     

Computational Modelling of Cancer Development and Growth: Modelling at Multiple Scales and Multiscale Modelling

In this paper, we present two mathematical models related to different aspects and scales of cancer growth. The first model is a stochastic spatiotemporal model of both a synthetic gene regulatory network (the example of a three-gene repressilator is given) and an actual gene regulatory network, the NF-\(\upkappa \)B pathway. The second model is a force-based individual-based model of the development of a solid avascular tumour with specific application to tumour cords, i.e. a mass of cancer cells growing around a central blood vessel. In each case, we compare our computational simulation results with experimental data. In the final discussion section, we outline how to take the work forward through the development of a multiscale model focussed at the cell level. This would incorporate key intracellular signalling pathways associated with cancer within each cell (e.g. p53–Mdm2, NF-\(\upkappa \)B) and through the use of high-performance computing be capable of simulating up to \(10^9\) cells, i.e. the tissue scale. In this way, mathematical models at multiple scales would be combined to formulate a multiscale computational model.     

Species Invasiveness in Biological Invasions: A Modelling Approach

The study of invasiveness, the traits that enable a species to invade a habitat, and invasibility, the habitat characteristics that determine its susceptibility to the establishment and spread of an invasive species, provide a useful conceptual framework to formulate the biological invasion problem in a modelling context. Another important aspect is the complex interaction emerging among the invader species, the noninvader species already present in the habitat, and the habitat itself. Following a modelling approach to the biological invasion problem, we present a spatially explicit cellular automaton model (Interacting Multiple Cellular Automata (IMCA)). We use field parameters from the invader Gleditsia triacanthos and the native Lithraea ternifolia in montane forests of central Argentina as a case study to compare outputs and performance of different models. We use field parameters from another invader, Ligustrum lucidum, and the native Fagara coco from the same system to run the cellular automaton model. We compare model predictions with invasion values from aerial photographs. We discuss in detail the importance of factors affecting species invasiveness, and give some insights into habitat invasibility and the role of interactions between them. Finally, we discuss the relevance of mathematical modelling for studying and predicting biological invasions. The IMCA model provided a suitable context for integrating invasiveness, invasibility, and the interactions. In the invasion system studied, the presence of an invader's juvenile bank not only accelerated the rate of invasion but was essential to ensure invasion. Using the IMCA model, we were able to determine that not only adult survival but particularly longevity of the native species influenced the spread velocity of the invader, at least when a juvenile bank is present. Other factors determining velocity of invasion detected by the IMCA model were seed dispersal distance and age of reproductive maturity. We derived relationships between species' adult survival, fecundity and longevity of both theoretical and applied relevance for biological invasions. Invasion velocities calculated from the aerial photographs agreed well with predictions of the IMCA model.     

The Role of Adiponectin in Breast Cancer: A Meta-Analysis

Published results suggests that high adiponectin level may decrease the risk of breast cancer. However, available evidence on breast cancer is conflicting. Therefore a meta-analysis was performed to assess the association between blood adiponectin and breast cancer risk. PubMed database, Web of Science, Elsevier Science, Springer Link and bibliographies of retrieved articles were searched for epidemiological studies published up to March 2013. Meta-analysis was performed on the combined effect values (OR) as well as standardized mean difference (SMD) including 17 studies. Fixed or random effect pooled measure was selected on the basis of homogeneity test among studies. The publication bias was assessed by the Egger’s regression asymmetry test and Begg’s rank correlation test with Begg’s funnel plot. Subgroup analyses and sensitivity analysis were also performed. A total of 13 studies involving 3578 breast cancer cases and 4363 controls contributed to the OR analysis. The high adiponectin level did not significantly affect breast cancer risk (OR=0.902, 95% CI=0.773–1.053). After excluding articles that were the key contributors to between-study heterogeneity, the OR of high adiponectin level was associated with decreased breast cancer risk (OR=0.838, 95% CI=0.744–0.943). There was a significantly association between high adiponectin level and postmenopausal breast cancer women (OR=0.752, 95%CI=0.604-0.936); and it was not associated with premenopausal breast cancer women (OR=0.895, 95%CI=0.638-1.256). The result of pooled measure on SMD was that the high adiponectin level was associated with decreased breast cancer risk (SMD= -0.348, 95% CI= -0.533--0.614) after excluding articles which were the key contributors to between-study heterogeneity. Our findings indicate that high adiponectin level might decrease the risk of postmenopausal breast cancer. More randomized clinical trials and observational studies are needed to confirm this association with underlying biological mechanisms in the future.     

The Role of Hippocampal Atrophy in Depression: A Neurocomputational Approach

The role of hippocampal atrophy in the pathogenesis of major depression remains under investigation. Here, we show, within a neural network model, that the incorporation of atrophy reproduces the changes observed in cognitive impairment in depression and could also contribute to the maintenance of the depressed mood. Some other clinical observations, such as treatment resistance and frequent relapses of illness, could also be explained within the framework of the model. We also simulate the action of cognitive therapy and a combined treatment of cognitive therapy and antidepressant drugs. Our findings suggest that, in the presence of hippocampal atrophy, the incorporation of antidepressant drugs would be necessary for the reversal of symptomatology.     

Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.     

Active Nucleosome Displacement: A Theoretical Approach

Three-quarters of eukaryotic DNA are wrapped around protein cylinders forming so-called nucleosomes that block the access to the genetic information. Nucleosomes need therefore to be repositioned, either passively (by thermal fluctuations) or actively (by molecular motors). Here we introduce a theoretical model that allows us to study the interplay between a motor protein that moves along DNA (e.g., an RNA polymerase) and a nucleosome that it encounters on its way. We aim at describing the displacement mechanisms of the nucleosome and the motor protein on a microscopic level to understand better the intricate interplay between the active step of the motor and the nucleosome-repositioning step. Different motor types (Brownian ratchet versus power-stroke mechanism) that perform very similarly under a constant load are shown to have very different nucleosome repositioning capacities.     

A Role of Vesicular Transduction of Intercellular Signals in Cancer Development

Export of biologically active compounds is essential for any living cell. Transport of bioactive molecules through a cellular membrane can be active, or passive, or vesicular. In the past decade, vesicular transduction of intercellular signals has attracted great interest in the scientific community. An extremely important role of the vesicle transduction has been established for almost all processes in a living body. Not only profiles of protein and RNA expression in a cell, but also its secretome change during various pathologies, including cancer development. The enhanced secretion of vesicles by transformed cells is one important factor in creating a special microenvironment that favors tumor progression. At present, a role of exosomes has been demonstrated for such important processes as an epithelial-mesenchymal transition, angiogenesis, metastatic niche formation, chemotherapeutic resistance, and interaction with the immune system. The special biological role of the extracellular vesicles and their basic differences depend on their molecular composition. Therefore, special protein and lipid markers are responsible for a vesicular targeted delivery with information due to the preferable interaction with cells of a definite type. The exosomes of cancer cells can facilitate apoptosis or growth of neighboring malignant cells depending on the exosome composition. These and other special features of the extracellular vesicles make studies of their composition and role especially interesting and attract significant attention from researchers. Despite the rapid progress in this field, there are still many unresolved problems, such as a search for specific markers which allow identification of different types of vesicles or vesicles secreted by distinct cells, as well as screening of vesicular markers of cancers and other diseases that are associated with disorders in a functioning immune system. This review is mainly focused on the role of intercellular vesicular transport of bioorganic molecules in cancer progression. We believe that a successful treatment of oncological diseases is impossible without an understanding of the intercellular communication of both cancer cells between each other and with other systems of an organism and with a concept of an active participation of the cell-secreted vesicles in this process.     

Polarization and Movement of Keratocytes: A Multiscale Modelling Approach

Eukariotic cell motility is a complex phenomenon, in which the cytoskeleton and its major constituent, actin, play an essential role. Actin forms polymers of long, stiff filaments that are cross-linked into an anisotropic network inside a thin sheet-like cellular protrusion, the lamellipod. At the leading edge of this structure, polymerization of actin filaments creates the force that pushes out the membrane and leads to translocation of a motile cell. Dynamics of the actin network account for changes in cell shape, crawling motion and turning of the cell in response to external cues. Regulating the dynamics of the cytoskeleton, and playing a central role in signal transduction in the cell, are Cdc42, Rac and Rho (GTPases of the rho family, collectively known as the small G-proteins) and the actin nucleating complex, Arp2/3.In this paper, we use a multiscale modelling approach in a 2D model of a motile cell. We describe the mutual interactions of the small G-proteins, and their effects on capping and side-branching of actin filaments. We incorporate the pushing exerted by oriented actin filament ends on the cell edge, and a Rho-dependent contraction force. Combining these biochemical and mechanical aspects, we investigate the dynamics of a model epidermal fish keratocyte through in silico experiments. Our model gives insight into how, in response to some cue, a cell can polarize, form a leading edge, and move; concomitantly it explains how a keratocyte cell can maintain its shape and polarity, even after removal of the initial stimulus, and how it can change direction quickly in response to changes in its environment. We show that establishment of polarity stems from interactions of Cdc42, Rac and Rho, while maintenance and robustness of polarity is due to the rapid cytosolic diffusion of the inactive (GDI-bound) forms of the small G-proteins. Our model produces a cell shape that closely resembles the keratocytes and correct speeds for biologically reasonable parameter values. Movies of the simulations can be obtained from http://theory.bio.uu.nl/stan/keratocyte.     

Chromosome Rearrangement Breakpoint Clustering: The Role of Clonal Selection

Chromosome rearrangements may result in fusion genes that encode chimeric proteins. The break-points of many such rearrangements cluster in definite genomic regions. In addition, many breakpoint clusters contain specific genomic elements, such as topoisomerase II consensus sites, nuclear matrix attachment sites, and various nucleotide sequences capable of assuming noncanonical secondary structure. Studies on breakpoint location are reviewed in terms of the available data on chromatin structure. In addition, the relationship between the location of breakpoints and the domain organization of the respective proteins, which has not been dealt with in published studies, is analyzed. The possible mechanisms of chromosome rearrangements are discussed.__________Translated from Molekulyarnaya Biologiya, Vol. 39, No. 3, 2005, pp. 355–363.Original Russian Text Copyright © 2005 by Umanskaya, Bystritskiy, Razin.     

The Role of the Microenvironment in Mammary Gland Development and Cancer

The mammary gland is composed of a diverse array of cell types that form intricate interaction networks essential for its normal development and physiologic function. Abnormalities in these interactions play an important role throughout different stages of tumorigenesis. Branching ducts and alveoli are lined by an inner layer of secretory luminal epithelial cells that produce milk during lactation and are surrounded by contractile myoepithelial cells and basement membrane. The surrounding stroma comprised of extracellular matrix and various cell types including fibroblasts, endothelial cells, and infiltrating leukocytes not only provides a scaffold for the organ, but also regulates mammary epithelial cell function via paracrine, physical, and hormonal interactions. With rare exceptions breast tumors initiate in the epithelial compartment and in their initial phases are confined to the ducts but this barrier brakes down with invasive progression because of a combination of signals emitted by tumor epithelial and various stromal cells. In this article, we overview the importance of cellular interactions and microenvironmental signals in mammary gland development and cancer.The mammary gland is composed of a combination of multiple cell types that together form complex interaction networks required for the proper development and functioning of the organ. The branching milk ducts are formed by an outer myoepithelial cell layer producing the basement membrane (BM) and an inner luminal epithelial cell layer producing milk during lactation. The ducts are surrounded by the microenvironment composed of extracellular matrix (ECM) and various stromal cell types (e.g., endothelial cells, fibroblasts, myofibroblasts, and leukocytes). Large amount of data suggest that cell-cell and cell-microenvironment interactions modify the proliferation, survival, polarity, differentiation, and invasive capacity of mammary epithelial cells. However, the molecular mechanisms underlying these effects are poorly understood. The purification and comprehensive characterization of each cell type comprising normal and neoplastic human breast tissue combined with hypothesis testing in cell culture and animal models are likely to improve our understanding of the role these cells play in the normal functioning of the mammary gland and in breast tumorigenesis. In this article, we overview cellular and microenvironmental interactions that play important roles in the normal functioning of the mammary gland and their abnormalities in breast cancer.     

肿瘤微环境应激因子乳酸在肿瘤发展中的作用

肿瘤微环境应激主要包括:缺氧、胞外酸环境、葡萄糖缺乏等。乳酸堆积也是肿瘤微环境应激中一个重要特征。长期以来,乳酸一直被认为是代谢废物,但随着研究深入,发现乳酸作为癌代谢物与肿瘤增殖、转移、血管生成、免疫逃逸以及放化疗效果等肿瘤生物学功能密切相关,此外乳酸还可促进缺氧诱导因子稳定、作为"替代燃料"供能等进一步促进肿瘤恶性进展。因此,本文就肿瘤微环境中乳酸代谢与调控、乳酸对肿瘤生物学功能的影响等方面作一综述,旨在为针对乳酸这一异常代谢特征的抗肿瘤药物开发及临床治疗提供必要依据。     

外泌体源性miRNAs在肺癌发生发展中的作用

外泌体(exosomes)是细胞分泌的纳米级细胞外囊泡.外泌体通过释放其内的生物活性大分子,比如微小RNA(microRNA,miRNA)到受体细胞,从而介导细胞间交流通讯. MiRNAs作为一类主要在转录后水平负向调控靶mRNAs的非编码RNAs,其在外泌体中含量最为丰富.在肺癌中,miRNAs经肿瘤细胞分泌的外泌体转运释放而发挥重要的作用.本文主要讨论了外泌体源性miRNAs在肺癌发生发展的各个阶段,包括血管生成、细胞增殖、侵袭转移、免疫逃逸、耐药等方面的作用,以及其在作为新型肺癌诊断和预后标志物方面的临床价值.