Beyond Eyeballing: Fitting Models to Experimental Data

Abstract

As we learn more about the biology of the Toll-like receptors (TLRs), a wide range of molecules that can activate this fascinating family of pattern recognition receptors emerges. In addition to conserved pathogenic components, endogenous danger signals created upon tissue damage are also sensed by TLRs. Detection of these types of stimuli results in TLR mediated inflammation that is vital to fight pathogenic invasion and drive tissue repair. Aberrant activation of TLRs by pathogenic and endogenous ligands has also been linked with the pathogenesis of an increasing number of infectious and autoimmune diseases, respectively. Most recently, allergen activation of TLRs has also been described, creating a third broad class of TLR stimulus that has helped to shed light on the pathogenesis of allergic disease. To date, microbial activation of TLRs remains best characterized. Each member of the TLR family senses a specific subset of pathogenic ligands, pathogen associated molecular patterns (PAMPS), and a wealth of structural and biochemical data continues to reveal the molecular mechanisms of TLR activation by PAMPs, and to demonstrate how receptor specificity is achieved. In contrast, the mechanisms by which endogenous molecules and allergens activate TLRs remain much more mysterious. Here, we provide an overview of our current knowledge of how very diverse stimuli activate the same TLRs and the structural basis of these modes of immunity.     

Climate-Based Models for Pulsed Resources Improve Predictability of Consumer Population Dynamics: Outbreaks of House Mice in Forest Ecosystems

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer–resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year’s advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer–resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.     

Moth Outbreaks Reduce Decomposition in Subarctic Forest Soils

Ecosystems - Tree mortality from insect infestations can significantly reduce carbon storage in forest soils. In subarctic birch forests (Betula pubescens), ecosystem C cycling is largely affected...     

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.     

Evaluation of Habitat Suitability Models for Forest Passerines Using Demographic Data

ABSTRACT Habitat suitability is often used as a surrogate for demographic responses (i.e., abundance, survival, fecundity, or population viability) in the application of habitat suitability index (HSI) models. Whether habitat suitability actually relates to demographics, however, has rarely been evaluated. We validated HSI models of breeding habitat suitability for wood thrush (Hylocichla mustelina) and yellow-breasted chat (Icteria virens) in Missouri, USA. First, we evaluated HSI models as a predictor of 3 demographic responses: within-site territory density, site-level territory density, and nest success. We demonstrated a link between HSI values and all 3 types of demographic responses for the yellow-breasted chat and site-level territory density for the wood thrush. Second, we evaluated support for models containing HSI values, models containing measured habitat features (e.g., tree age, tree species, ecological land type), and models containing management treatments (e.g., even-aged and uneven-aged forest regeneration treatments) for each demographic response using model selection. Models containing HSI values received more support, in general, than models containing only habitat features or management treatments for all 3 types of wildlife response. The assumption that changes in habitat suitability represent wildlife demographic response to vegetation change is supported by our models. However, differences in species ecology may contribute to the degree to which HSI values are related to specific demographic responses. We recommend validation of HSI models with the particular demographic data of interest (i.e., density, productivity) to increase confidence in the model used for conservation planning.     

Linkage Disequilibrium in Humans: Models and Data

In this review, we describe recent empirical and theoretical work on the extent of linkage disequilibrium (LD) in the human genome, comparing the predictions of simple population-genetic models to available data. Several studies report significant LD over distances longer than those predicted by standard models, whereas some data from short, intergenic regions show less LD than would be expected. The apparent discrepancies between theory and data present a challenge-both to modelers and to human geneticists-to identify which important features are missing from our understanding of the biological processes that give rise to LD. Salient features may include demographic complications such as recent admixture, as well as genetic factors such as local variation in recombination rates, gene conversion, and the potential segregation of inversions. We also outline some implications that the emerging patterns of LD have for association-mapping strategies. In particular, we discuss what marker densities might be necessary for genomewide association scans.     

Organ-Specific Metastases in Melanoma: Experimental Animal Models

Metastases from certain primary tumors frequently exhibit specific organ preference. Animal models have been developed to induce in a reproducible fashion the formation of organ-specific metastases by malignant melanoma cells. Some of these models rely on the use of immunodeficient mice, which can support the growth of murine as well as human malignant melanomas. Moreover, immunodeficient mice, because of their diminished ability to mount an effective immune response, allow the expression of malignant properties (e.g., preferential colonization of certain organs), which are intrinsic to transplanted melanoma cells. This review discusses the relevant factors (and limitations) of some of the animal models used to study the in vivo properties of melanoma cells.     

Evaluation and Calibration of In Silico Models of Thrombin Generation Using Experimental Data from Healthy and Haemophilic Subjects

The coagulation cascade comprises numerous chemical reactions between many proteins, that finally lead to the formation of a clot to stop bleeding. Many numerical models have attempted to translate understanding of this cascade into mathematical equations that simulate the chain reactions. However, their predictions have not been validated against clinical data stemming from patients. In this paper, we propose an extensive validation of five available models, by comparing in healthy and haemophilic subjects, thrombin generation measured in vitro to thrombin generation predicted by the models in silico. In order to render the models more predictive, we calibrated the models to have an acceptable agreement between the experimental and estimated data. Optimization processes based on genetic algorithms were developed to search for those calibrated kinetic parameters. Our results show that the thrombin generation kinetics are so complex that they cannot be predicted by a unique set of kinetic parameters for all patients: the calibration of only three parameters in a subject-specific way allows reaching good model estimations for different experimental conditions realized on the same patient.     

Socio-Ecological Webs and Sites of Sociality:Levins' Strategy of Model Building Revisited

This essay extends Levins' 1966 analysis of modelbuilding in ecology and evolutionary biology. Amodel, as the product of modeling, might bevalued according to its correspondence to reality. Yet Levins' emphasis on provisionality and changeredirects attention to the processes ofmodeling, through which scientists select and generatetheir problems, define their categories, collect theirdata, compare competing models, and present theirfindings. I identify several points where decisionsare required that are not determined by nature. Thisinvites examination of the social considerationsmodelers are reacting to at the sites of sociality.Modelers must weave socio-ecological webs so thatthe models can be seen to represent their subjectmatter at the same time as the modelers secure thesupport of colleagues, collaborators and institutions,and enjoin others to act upon their conclusions. Notonly do theory justification and theory generationmerge, but the joint project becomes simultaneouslyphilosophical and sociological.     

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation''s citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.     

Intuitive Logic Revisited: New Data and a Bayesian Mixed Model Meta-Analysis

Recent research on syllogistic reasoning suggests that the logical status (valid vs. invalid) of even difficult syllogisms can be intuitively detected via differences in conceptual fluency between logically valid and invalid syllogisms when participants are asked to rate how much they like a conclusion following from a syllogism (Morsanyi & Handley, 2012). These claims of an intuitive logic are at odds with most theories on syllogistic reasoning which posit that detecting the logical status of difficult syllogisms requires effortful and deliberate cognitive processes. We present new data replicating the effects reported by Morsanyi and Handley, but show that this effect is eliminated when controlling for a possible confound in terms of conclusion content. Additionally, we reanalyze three studies () without this confound with a Bayesian mixed model meta-analysis (i.e., controlling for participant and item effects) which provides evidence for the null-hypothesis and against Morsanyi and Handley''s claim.     

Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75° S, 48.37° W) in the eastern Amazon, and then compared with forest stand data at Tapajos National Forest (3.08° S, 54.94° W) in the central Amazon. The average remotely sensed crown width (mean ± SE) was 12.7 ± 0.1 m (range: 2.0–34.0 m) and frequency of trees was 76.6 trees/ha at Cauaxi. At Tapajos, remotely sensed crown width was 13.1 ± 0.1 m (range: 2.0–38.0 m) and frequency of trees was 76.4 trees/ha. At both Cauaxi and Tapajos, the remotely sensed average crown widths were within 3 percent of the crown widths derived from field measurements, although crown distributions showed significant differences between field-measured and automated methods. We used the remote sensing algorithm to estimate crown dimensions and forest structural properties in 51 forest stands (1 km²) throughout the Brazilian Amazon. The estimated crown widths, tree diameters (dbh), and stem frequencies differed widely among sites, while estimated biomass was similar among most sites. Sources of observed errors included an inability to detect understory crowns and to separate adjacent, intermingled crowns. Nonetheless, our technique can serve to provide information about structural characteristics of large areas of unsurveyed forest throughout Amazonia.     

Phospholipase A2 in Experimental Allergic Bronchitis: A Lesson from Mouse and Rat Models

Background

Phospholipases A₂ (PLA₂) hydrolyzes phospholipids, initiating the production of inflammatory lipid mediators. We have previously shown that in rats, sPLA₂ and cPLA₂ play opposing roles in the pathophysiology of ovalbumin (OVA)-induced experimental allergic bronchitis (OVA-EAB), an asthma model: Upon disease induction sPLA₂ expression and production of the broncho-constricting CysLTs are elevated, whereas cPLA₂ expression and the broncho-dilating PGE₂ production are suppressed. These were reversed upon disease amelioration by treatment with an sPLA₂ inhibitor. However, studies in mice reported the involvement of both sPLA₂ and cPLA₂ in EAB induction.

Objectives

To examine the relevance of mouse and rat models to understanding asthma pathophysiology.

Methods

OVA-EAB was induced in mice using the same methodology applied in rats. Disease and biochemical markers in mice were compared with those in rats.

Results

As in rats, EAB in mice was associated with increased mRNA of sPLA₂, specifically sPLA₂gX, in the lungs, and production of the broncho-constricting eicosanoids CysLTs, PGD₂ and TBX₂ in bronchoalveolar lavage (BAL). In contrast, EAB in mice was associated also with elevated cPLA₂ mRNA and PGE₂ production. Yet, treatment with an sPLA₂ inhibitor ameliorated the EAB concomitantly with reverting the expression of both cPLA₂ and sPLA₂, and eicosanoid production.

Conclusions

In both mice and rats sPLA₂ is pivotal in OVA-induced EAB. Yet, amelioration of asthma markers in mouse models, and human tissues, was observed also upon cPLA₂ inhibition. It is plausible that airway conditions, involving multiple cell types and organs, require the combined action of more than one, essential, PLA₂s.     

Using Publicly Available Forest Inventory Data in Climate-Based Models of Tree Species Distribution: Examining Effects of True Versus Altered Location Coordinates

Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J. osteosperma) and two piñons (Pinus edulis, P. monophylla), were analyzed. The presence–absence models based on current climatic variables were generated over a series of species-specific modeling extents using Random Forests and applied to forecast climatic conditions. The distributions of predictor variables sampled with public coordinates were compared to those sampled with true coordinates using t tests with a Bonferroni adjustment for multiple comparisons. Public- and true-based models were compared using metrics of classification accuracy. The modeled current and forecast distributions were compared in terms of their overall areal agreement and their geographic mean centroids. Comparison of the underlying distributions of predictor variables sampled with true versus public coordinates did not indicate a significant difference for any species at any extent. Both the public- and true-based models had comparable classification accuracies across extent for each species, with the exception of one species, J. occidentalis. True-based models produced geographic distributions with smaller areas under current and future scenarios. The greatest areal difference occurred in the species with the lowest modeled accuracies (J. occidentalis), and had a forecast distribution which diverged severely. The other species had forecast distributions with similar magnitudes of modeled distribution shifts.     

Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models

Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene–gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design.     

Additive Manufacturing of Anatomical Models from Computed Tomography Scan Data

The purpose of the study presented here was to investigate the manufacturability of human anatomical models from Computed Tomography (CT) scan data via a 3D desktop printer which uses fused deposition modelling (FDM) technology. First, Digital Imaging and Communications in Medicine (DICOM) CT scan data were converted to 3D Standard Triangle Language (STL) format by using InVaselius digital imaging program. Once this STL file is obtained, a 3D physical version of the anatomical model can be fabricated by a desktop 3D FDM printer. As a case study, a patient’s skull CT scan data was considered, and a tangible version of the skull was manufactured by a 3D FDM desktop printer. During the 3D printing process, the skull was built using acrylonitrile-butadiene-styrene (ABS) co-polymer plastic. The printed model showed that the 3D FDM printing technology is able to fabricate anatomical models with high accuracy. As a result, the skull model can be used for preoperative surgical planning, medical training activities, implant design and simulation to show the potential of the FDM technology in medical field. It will also improve communication between medical stuff and patients. Current result indicates that a 3D desktop printer which uses FDM technology can be used to obtain accurate anatomical models.