Homogenization of Large-Scale Movement Models in Ecology

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10–100 m) habitat variability on large scale (10–100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models.     

Testing Models: A Key Aspect to Promote Teaching Activities Related to Models and Modelling in Biology Lessons?

This study investigated biology teachers’ (N = 148) understanding of models and modelling (MoMo), their model-related teaching activities and relations between the two. A framework which distinguishes five aspects of MoMo in science (nature of models, multiple models, purpose of models, testing models and changing models) served as a theoretical background. Teachers’ understanding of MoMo was assessed using constructed-response items which were analysed qualitatively based on a coding scheme. The biology teachers mainly expressed a limited understanding of models as copies or idealised depictions used to show or to explain something. Model-related teaching activities were assessed through rating-scale items. The findings propose that models are primarily generated in biology lessons to show or to explain something but are rarely contrasted with other models, evaluated and modified. Significant correlations between teachers’ understanding of the aspect testing models and their intensity of model-related teaching activities were found. This suggests that the aspect testing models is a key aspect of promoting teaching activities related to MoMo in biology lessons. The findings are discussed with respect to relevant literature about MoMo in science education and educational implications are provided.     

Invasion Success and Community Resistance in Single and Multiple Species Invasion Models: Do the Models Support the Conclusions?

Elton's concept of community-level resistance to invasion has derived significant theoretical support from community assembly models in which species invade (colonize) singly at low densities. Several theoretical models have provided support to this concept and are frequently cited as providing evidence that invasion resistance occurs in nature. The underlying assumptions of these models however, are derived from island or island-like systems in which species invade infrequently at low abundances. We suggest that these island-like models cannot be generalized to systems in which species arrive in greater frequencies and densities. To investigate the effects of altering the basic assumptions of these original models, we utilized assembly algorithms similar to those used in previous studies, but allowed either two species to invade per time step or single species invasions at relatively high inoculation densities. In these models, invasion resistance only occurred when the invasion process was restricted to single species invading at low densities (as in previous models). When two species were allowed to invade per time step, invasion resistant states did not occur in any of 20 simulated communities, even after 10,000 invasion events. Relaxation of the assumption of invasion at low density also resulted in a lack of invasion resistance. These results may explain why the strict concept of complete invasion resistance appears only to operate in island and island-like systems.     

Animal Models and Experimental Medicine被PubMed Central收录

Animal Models and Experimental Medicine (简称AMEM,《动物模型与实验医学(英文)》)主管单位是中国科学技术协会,由中国实验动物学会、中国医学科学院医学实验动物研究所共同主办,与国际著名出版集团Wiley合作出版。AMEM获"中国科技期刊国际影响力提升计划"D类项目支持,于2018年3月创刊,季刊,主编为中国实验动物学会理事长、中国医学科学院医学实验动物研究所所长秦川教授。     

Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.     

5′-C-Tosyloxyalkylnucleosides. Models for Oligonucleotide Coupling with Nucleophiles

Abstract

5′-C-substituted nucleosides with an hydroxyalkyl chain are synthesized. The stereochemistry of the new stereogenic center is defined. After introduction of a tosyl group, dimer models are prepared to evaluate the conjugation with amines used as nucleophiles.     

Deriving Macroscopic Myocardial Conductivities by Homogenization of Microscopic Models

We derive the values for the intracellular and extracellular conductivities needed for bidomain simulations of cardiac electrophysiology using homogenization of partial differential equations. In our model, cardiac myocytes are rectangular prisms and gap junctions appear in a distributed manner as flux boundary conditions for Laplace’s equation. Using directly measurable microproperties such as cellular dimensions and end-to-end and side-to-side gap junction coupling strengths, we inexpensively obtain effective conductivities close to those given by simulations with a detailed cyto-architecture (Stinstra et al. in Ann. Biomed. Eng. 33:1743–1751, 2005). This model provides a convenient framework for studying the effect on conductivities of aligned vs. brick-like arrangements of cells and the effect of different distributions of gap junctions along the myocyte membranes.     

Animal Models and Experimental Medicine被国际数据库DOAJ收录

正2018年7月26日,Animal Models and Experimental Medicine——AMEM正式被国际著名开放存取期刊目录数据库DOAJ(Directory of Open Access Journals)收录,这意味着AMEM的期刊质量以及开放获取的出版政策得到了认可。AMEM被DOAJ数据库收录,标志着AMEM向国际化又迈出了重要的一步,不仅可以扩     

Spatial Models of Prebiotic Evolution: Soup Before Pizza?

The problem of information integration andresistance to the invasion of parasitic mutants in prebiotic replicator systemsis a notorious issue of research on the origin of life.Almost all theoretical studies published so far havedemonstrated that some kind of spatial structure is indispensable forthe persistence and/or the parasite resistance of any feasible replicator system.Based on a detailed critical survey of spatial models on prebiotic informationintegration, we suggest a possible scenario for replicator system evolution leadingto the emergence of the first protocells capable of independent life.We show that even the spatial versions of the hypercycle model are vulnerable toselfish parasites in heterogeneous habitats. Contrary, the metabolic system remainspersistent and coexistent with its parasites both on heterogeneous surfaces andin chaotically mixing flowing media. Persistent metabolic parasites can beconverted to metabolic cooperators, or they can gradually obtain replicase activity.Our simulations show that, once replicase activity emerged, a gradual and simultaneousevolutionary improvement of replicase functionality (speed and fidelity) andtemplate efficiency is possible only on a surface that constrains the mobility ofmacromolecule replicators. Based on the results of the models reviewed, we suggestthat open chaotic flows (`soup') and surface dynamics (`pizza') both played keyroles in the sequence of evolutionary events ultimately concluding in theappearance of the first living cell on Earth.     

(Too Many) Mathematical Models of Circadian Clocks (?)

Many mathematical models derived from the principles obtained from empirical observations in chronobiology have been proposed and explored. They cover several organisms and phenomena, and utilize quite different formal approaches. These models can be divided into the ones that intend to describe pacemaker core function, such the Goodwin-oscillator family, non-genetic approaches or purely mathematical (i.e., without clear biochemical correlations) models, and the ones that represent events depending on pacemaker activity, i.e., photoperiodic phenomena. We aim to illustrate the diversity of mathematical and methodological approaches to describe circadian systems and related matters.     

Animal Models and Experimental Medicine启动工作会议隆重召开

正盛夏七月,骄阳似火。在各界人士的鼎力支持和协助下,《中国实验动物学报》编辑部荣获中国科技期刊国际影响力提升计划D类项目资助后,创办期刊Animal Models and Experimental Medicine(AMEM)。7月11日,由AMEM主编、中国实验动物学会理事长秦川教授策划,由编辑部李继平主任执行的AMEM启动工作会议在北京京瑞温泉国际酒店第四会议室隆重召开。来自全国各地的近二十位实验动物相关领域专家学     

Are Quasi-Steady-State Approximated Models Suitable for Quantifying Intrinsic Noise Accurately?

Large gene regulatory networks (GRN) are often modeled with quasi-steady-state approximation (QSSA) to reduce the huge computational time required for intrinsic noise quantification using Gillespie stochastic simulation algorithm (SSA). However, the question still remains whether the stochastic QSSA model measures the intrinsic noise as accurately as the SSA performed for a detailed mechanistic model or not? To address this issue, we have constructed mechanistic and QSSA models for few frequently observed GRNs exhibiting switching behavior and performed stochastic simulations with them. Our results strongly suggest that the performance of a stochastic QSSA model in comparison to SSA performed for a mechanistic model critically relies on the absolute values of the mRNA and protein half-lives involved in the corresponding GRN. The extent of accuracy level achieved by the stochastic QSSA model calculations will depend on the level of bursting frequency generated due to the absolute value of the half-life of either mRNA or protein or for both the species. For the GRNs considered, the stochastic QSSA quantifies the intrinsic noise at the protein level with greater accuracy and for larger combinations of half-life values of mRNA and protein, whereas in case of mRNA the satisfactory accuracy level can only be reached for limited combinations of absolute values of half-lives. Further, we have clearly demonstrated that the abundance levels of mRNA and protein hardly matter for such comparison between QSSA and mechanistic models. Based on our findings, we conclude that QSSA model can be a good choice for evaluating intrinsic noise for other GRNs as well, provided we make a rational choice based on experimental half-life values available in literature.     

Assessing Coverage of Protein Interaction Data Using Capture–Recapture Models

Protein interaction networks comprise thousands of individual binary links between distinct proteins. Whilst these data have attracted considerable attention and been the focus of many different studies, the networks, their structure, function, and how they change over time are still not fully known. More importantly, there is still considerable uncertainty regarding their size, and the quality of the available data continues to be questioned. Here, we employ statistical models of the experimental sampling process, in particular capture–recapture methods, in order to assess the false discovery rate and size of protein interaction networks. We uses these methods to gauge the ability of different experimental systems to find the true binary interactome. Our model allows us to obtain estimates for the size and false-discovery rate from simple considerations regarding the number of repeatedly interactions, and provides suggestions as to how we can exploit this information in order to reduce the effects of noise in such data. In particular our approach does not require a reference dataset. We estimate that approximately more than half of the true physical interactome has now been sampled in yeast.     

Learning Biomarker Models for Progression Estimation of Alzheimer’s Disease

Being able to estimate a patient’s progress in the course of Alzheimer’s disease and predicting future progression based on a number of observed biomarker values is of great interest for patients, clinicians and researchers alike. In this work, an approach for disease progress estimation is presented. Based on a set of subjects that convert to a more severe disease stage during the study, models that describe typical trajectories of biomarker values in the course of disease are learned using quantile regression. A novel probabilistic method is then derived to estimate the current disease progress as well as the rate of progression of an individual by fitting acquired biomarkers to the models. A particular strength of the method is its ability to naturally handle missing data. This means, it is applicable even if individual biomarker measurements are missing for a subject without requiring a retraining of the model. The functionality of the presented method is demonstrated using synthetic and—employing cognitive scores and image-based biomarkers—real data from the ADNI study. Further, three possible applications for progress estimation are demonstrated to underline the versatility of the approach: classification, construction of a spatio-temporal disease progression atlas and prediction of future disease progression.     

Do Food Web Models Reproduce the Structure of Mutualistic Networks?

Background

Simple models inspired by processes shaping consumer-resource interactions have helped to establish the primary processes underlying the organization of food webs, networks of trophic interactions among species. Because other ecological interactions such as mutualisms between plants and their pollinators and seed dispersers are inherently based in consumer-resource relationships we hypothesize that processes shaping food webs should organize mutualistic relationships as well.

Methodology/Principal Findings

We used a likelihood-based model selection approach to compare the performance of food web models and that of a model designed for mutualisms, in reproducing the structure of networks depicting mutualistic relationships. Our results show that these food web models are able to reproduce the structure of most of the mutualistic networks and even the simplest among the food web models, the cascade model, often reproduce overall structural properties of real mutualistic networks.

Conclusions/Significance

Based on our results we hypothesize that processes leading to feeding hierarchy, which is a characteristic shared by all food web models, might be a fundamental aspect in the assembly of mutualisms. These findings suggest that similar underlying ecological processes might be important in organizing different types of interactions.