Perturbation analysis analyzed—mathematical modeling of intact and perturbed gene regulatory circuits for animal development

Gene regulatory networks for animal development are the underlying mechanisms controlling cell fate specification and differentiation. The architecture of gene regulatory circuits determines their information processing properties and their developmental function. It is a major task to derive realistic network models from exceedingly advanced high throughput experimental data. Here we use mathematical modeling to study the dynamics of gene regulatory circuits to advance the ability to infer regulatory connections and logic function from experimental data. This study is guided by experimental methodologies that are commonly used to study gene regulatory networks that control cell fate specification. We study the effect of a perturbation of an input on the level of its downstream genes and compare between the cis-regulatory execution of OR and AND logics. Circuits that initiate gene activation and circuits that lock on the expression of genes are analyzed. The model improves our ability to analyze experimental data and construct from it the network topology. The model also illuminates information processing properties of gene regulatory circuits for animal development.     

Needle insertions modeling: Identifiability and limitations

Soft tissues modeling is a very present preoccupation in different scientific fields, from computer simulation to biomechanics or medical robotics. In this article, we consider the interaction of a needle with living tissues, which is a particularly complex modeling problem since it is characterized by inhomogeneity and nonlinearity properties. We propose a robust method to online estimate forces involved in typical percutaneous interventions. The ability to obtain physically consistent models during in vivo insertions is also discussed.     

An algorithm for a decomposition of weighted digraphs: with applications to life cycle analysis in ecology

In the analysis of organism life cycles in ecology, comparisons of life cycles between species or between different types of life cycles within species are frequently conducted. In matrix population models, partitioning of the elasticity matrix is used to quantify the separate contributions of different life cycles to the population growth rate. Such partition is equivalent to a decomposition of the life cycle graph of the population. A graph theoretic spanning tree method to carry out the decomposition was formalized by Wardle [Ecology 79(7), 2539–2549 (1998)]. However there are difficulties in realizing a suitable decomposition for complex life histories using the spanning-tree method. One of the problems is the occurrence of life cycles that contain contradictory directions that defy biological interpretation. We propose an algorithmic approach for decomposing a directed, weighted graph. The graph is to be decomposed into two parts. The first part is a set of simple cycles that contain no contradictory directions and that consist of edges of equal weight. The second part of the decomposition is a subgraph in which no such simple cycles are obtainable. When applied to life cycle analysis in ecology, the proposed method will guarantee a complete decomposition of the life cycle graph into individual life cycles containing no contradictory directions. Although the research described in this article has been funded in part by the United States Environmental Protection Agency through STAR cooperative agreement R-82940201-0 to the University of Chicago, it has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Molecularly imprinted polymer-assisted sample clean-up of ochratoxin A from red wine: merits and limitations

A new analytical method for the determination of the carcinogenic mycotoxin ochratoxin A (OTA) in red wines has been developed involving a two-dimensional solid-phase extraction (SPE) clean-up protocol on C18-silica and a target-selective molecularly imprinted polymer (MIP). Prior removal of the interfering acidic matrix compounds by C18 solid-phase extraction was crucial for a successful clean-up as direct sample loading onto the MIP led to poor recoveries. The combined solid-phase extraction protocol afforded extracts suitable for sensitive ochratoxin A quantification by HPLC-fluorescence detection. Preliminary validation of the method performance with spiked (0.033-1.0 ng OTA/ml) and commercial red wines provided recoveries >90% and < 10%, with limit of detection (LOD) and limit of quantification (LOQ) of 0.01 and 0.033 ng/ml. However, a similarly favorable performance characteristics was observed in control experiments in which the MIP was replaced by the corresponding non-imprinted polymer (NIP). These findings provide evidence that under the employed experimental conditions specific analyte binding to imprinted binding sites plays a minor role in selective OTA retention. In the framework of this study, other problems inherent to MIP-based solid-phase extraction have been addressed. These include the reproducible preparation of MIP materials with consistent molecular recognition characteristics, the potential for repeated use of MIP, unfavorable polymer swelling in application-relevant solvents, potential sample contamination by template bleeding, and slow analyte binding kinetics.     

Critical review of activated sludge modeling: State of process knowledge,modeling concepts,and limitations

This work critically reviews modeling concepts for standard activated sludge wastewater treatment processes (e.g., hydrolysis, growth and decay of organisms, etc.) for some of the most commonly used models. Based on a short overview on the theoretical biochemistry knowledge this review should help model users to better understand (i) the model concepts used; (ii) the differences between models, and (iii) the limits of the models. The seven analyzed models are: (1) ASM1; (2) ASM2d; (3) ASM3; (4) ASM3 + BioP; (5) ASM2d + TUD; (6) Barker & Dold model; and (7) UCTPHO+. Nine standard processes are distinguished and discussed in the present work: hydrolysis; fermentation; ordinary heterotrophic organisms (OHO) growth; autotrophic nitrifying organisms (ANO) growth; OHO & ANO decay; poly‐hydroxyalkanoates (PHA) storage; polyphosphate (polyP) storage; phosphorus accumulating organisms PAO) growth; and PAO decay. For a structured comparison, a new schematic representation of these processes is proposed. Each process is represented as a reaction with consumed components on the left of the figure and produced components on the right. Standardized icons, based on shapes and color codes, enable the representation of the stoichiometric modeling concepts and kinetics. This representation allows highlighting the conceptual differences of the models, and the level of simplification between the concepts and the theoretical knowledge. The model selection depending on their theoretical limitations and the main research needs to increase the model quality are finally discussed. Biotechnol. Bioeng. 2013; 110: 24–46. © 2012 Wiley Periodicals, Inc.     

Graphical modeling for gene set analysis: A critical appraisal

Current demand for understanding the behavior of groups of related genes, combined with the greater availability of data, has led to an increased focus on statistical methods in gene set analysis. In this paper, we aim to perform a critical appraisal of the methodology based on graphical models developed in Massa et al. ( 2010 ) that uses pathway signaling networks as a starting point to develop statistically sound procedures for gene set analysis. We pay attention to the potential of the methodology with respect to the organizational aspects of dealing with such complex but highly informative starting structures, that is pathways. We focus on three themes: the translation of a biological pathway into a graph suitable for modeling, the role of shrinkage when more genes than samples are obtained, the evaluation of respondence of the statistical models to the biological expectations. To study the impact of shrinkage, two simulation studies will be run. To evaluate the biological expectation we will use data from a network with known behavior that offer the possibility of carrying out a realistic check of respondence of the model to changes in the experimental conditions.     

Analytical and multibody modeling for the power analysis of standing jumps

Two methods for the power analysis of standing jumps are proposed and compared in this article. The first method is based on a simple analytical formulation which requires as input the coordinates of the center of gravity in three specified instants of the jump. The second method is based on a multibody model that simulates the jumps processing the data obtained by a three-dimensional (3D) motion capture system and the dynamometric measurements obtained by the force platforms. The multibody model is developed with OpenSim, an open-source software which provides tools for the kinematic and dynamic analyses of 3D human body models. The study is focused on two of the typical tests used to evaluate the muscular activity of lower limbs, which are the counter movement jump and the standing long jump. The comparison between the results obtained by the two methods confirms that the proposed analytical formulation is correct and represents a simple tool suitable for a preliminary analysis of total mechanical work and the mean power exerted in standing jumps.     

Conformational analysis of the nonapeptide leuprorelin using NMR and molecular modeling

The nonapeptide Leuprorelin, one of the LHRH agonists, was studied by means of 2D nuclear magnetic resonance spectroscopy and molecular modeling. NOESY spectra in aqueous/deuterated methanol solution (50%H₂O/CD₃OD) at low temperature (268 K) revealed short-range nOe connectivities (i, i+1), characteristic of flexibility of the molecule. The H^N–H^N sequential connectivities observed provide evidence that the sequence has the propensity to form a bend involving residues 5 and 6 and the N-terminal segment. The -proton chemical shifts compared to random coil and additional data from the amide proton temperature coefficients support this assumption. One long-range nOe cross peak between H₂ –H^NEth is indicative of proximity between C- and N-termini.     

Conformational analysis of the nonapeptide leuprorelin using NMR and molecular modeling

Summary The nonapeptide Leuprorelin, one of the LHRH agonists, was studied by means of 2D nuclear magnetic resonance spectroscopy and molecular modeling. NOESY spectra in aqueous/deuterated methanol solution (50% H₂O/CD₃OD) at low temperature (268 K) revealed short-range nOe connectivities (i, i+1), characteristic of flexibility of the molecule. The H ^N -H ^N sequential connectivities observed provide evidence that the sequence has the propensity to form a bend involving residues 5 and 6 and the N-terminal segment. The α-proton chemical shifts compared to random coil and additional data from the amide proton temperature coefficients support this assumption. One long-range nOe cross peak between H ₂ ^α -H ^NEth is indicative of proximity between C- and N-termini.     

Reconstructing paleoecology and paleoenvironmental variables using factor analysis and regression: some limitations

We test the success of Principal Components, Factor and Regression Analysis at recovering environmental signals using numerical experiments in which we control species environmental responses, the environmental conditions and the sampling scheme used for calibration. We use two general conditions, one in which sampling of a continental margin for benthic foraminiferal assemblages is done in a standard grid and the driving environmental variables are correlated to one another, and the other where sampling is done so that the environmental variables are uncorrelated. The first condition mimics many studies in the literature. We find that where the controlling environmental variables are correlated, Principal Components/Factor Analysis yield factors that reflect the common variance (correlation) of those variables. Since this common variance is largely a product of the sampling scheme, the factors extracted do not reliably present true species ecologic behavior. This behavior cannot be accurately diagnosed and faulty interpretations may lead to substantial error when using factor coefficients to reconstruct conditions in the past. When the sampling scheme is constructed so that the controlling environmental variables for the calibration data set are uncorrelated the factor patterns will reflect these variables more accurately. Species responses can be more successfully interpreted from the Principal Components/Factor Analysis structure matrices. Additionally, regression analysis can successfully extract the independent environmental signals from the biotic data set. However, matrix closure is a confounding effect in all our numerical results as it distorts species' abundances and spatial distribution in the calibration data set. Our results show clearly that a knowledge of the controlling environmental variables, and the correlations among these variables over a study area, is essential for the successful application of multivariate techniques for paleoenvironmental reconstruction.     

MMM: Integrative ensemble modeling and ensemble analysis

Proteins and their complexes can be heterogeneously disordered. In ensemble modeling of such systems with restraints from several experimental techniques the following problems arise: (a) integration of diverse restraints obtained on different samples under different conditions; (b) estimation of a realistic ensemble width; (c) sufficient sampling of conformational space; (d) representation of the ensemble by an interpretable number of conformers; (e) recognition of weak order with site resolution. Here, I introduce several tools that address these problems, focusing on utilization of distance distribution information for estimating ensemble width. The RigiFlex approach integrates such information with high‐resolution structures of ordered domains and small‐angle scattering data. The EnsembleFit module provides moderately sized ensembles by fitting conformer populations and discarding conformers with low population. EnsembleFit balances the loss in fit quality upon combining restraint subsets from different techniques. Pair correlation analysis for residues and local compaction analysis help in feature detection. The RigiFlex pipeline is tested on data simulated from the structure 70 kDa protein‐RNA complex RsmE/RsmZ. It recovers this structure with ensemble width and difference from ground truth both being on the order of 4.2 Å. EnsembleFit reduces the ensemble of the proliferating‐cell‐nuclear‐antigen‐associated factor p15^PAF from 4,939 to 75 conformers while maintaining good fit quality of restraints. Local compaction analysis for the PaaA2 antitoxin from E. coli O157 revealed correlations between compactness and enhanced residual dipolar couplings in the original NMR restraint set.     

Solute exclusion from cellulose in packed columns: process modeling and analysis

In this investigation, process modeling and analysis were used to explore the behavior of solute exclusion from cellulose in packed columns. The study focused on modeling the effects of dispersion, mass transport, and pore diffusion. Three mathematical models were used to predict the behavior of the columns: an equilibrium model, a mass transfer model, and a combined mass transfer and pore diffusion model. Computer implementations of these models were tested against experimental conditions where cellulose particle size and solution velocity were used to either amplify or minimize dispersion or skewness in the elution curves. For small cellulose particles (200-300 mesh), all three models accurately predicted the shape of the elution curve and the particle porosity. For larger particles (45-60 mesh), the mass transfer model and the combined mass and pore diffusion model best represented the behavior of the column. At high solution velocities (0.63 cm(3) min(-1)) and large particles, only the combined mass transfer and pore diffusion model accurately represent the column behavior. Sensitivity analysis revealed that the mass transfer coefficient had little effect on the elution curves for the range of values (10(-6)-10(-3) cm s(-1)) calculated from the experimental data. The combined mass transfer and pore diffusion model presented in this article can be used to design solute exclusion measurement experiments for the larger cellulose particles found in a commercial cellulose-to-ethanol plant.     

刺旋花种群形态参数的通径分析与亚灌木个体生物量建模

对刺旋花４种形态参数的通径分析表明,冠幅（Ｃ）对种群生物量作用最大,其它依次为分枝数（ＢＮ）、基径（ＢＤ）和高度（Ｈ）．在此基础上,选取ＣＨ和常用变量Ｄ２Ｈ,就７种常规方程对生物量建模的效果进行比较,并同时建立营养器官和单株总生物量的预测方程．结果表明,选取变量ＣＨ较Ｄ２Ｈ合适,线性回归方程较其它方程准确直观,其中单株生物量择优预测方程为Ｙ＝１２．１０＋０．０１０５ＣＨ（Ｒ＝０．９８３,Ｐ＜０．０１）．     

Molecular modeling and statistical analysis in the design of derivatives of human dipeptidyl peptidase IV

Human dipeptidyl peptidase IV (hDDP-IV) has a considerable importance in inactivation of glucagon-like peptide-1, which is related to type 2 diabetes. One approach for the treatment is the development of small hDDP-IV inhibitors. In order to design better inhibitors, we analyzed 5-(aminomethyl)-6-(2,4-dichlrophenyl)-2-(3,5-dimethoxyphenyl)pyrimidin-4-amine and a set of 24 molecules found in the BindingDB web database for model designing. The analysis of their molecular properties allowed the design of a multiple linear regression model for activity prediction. Their docking analysis allowed visualization of the interactions between the pharmacophore regions and hDDP-IV. After both analyses were performed, we proposed a set of nine molecules in order to predict their activity. Four of them displayed promising activity, and thus, had their docking performed, as well as, the pharmacokinetic and toxicological study. Two compounds from the proposed set showed suitable pharmacokinetic and toxicological characteristics, and therefore, they were considered promising for future synthesis and in vitro studies.     

Evaluating health care performance: strengths and limitations of multilevel analysis

An increasing number of health services researchers are using multilevel analysis for evaluating health care performance. This method has the distinct advantage of accounting for within-provider correlation among patients. Alternatively, in a similar manner, estimators based on cluster sampling can also adjust for within-provider correlation. Cluster sampling methods do not require assumptions about error distribution as multilevel analysis does. To our knowledge, no comparison has been made between multilevel analysis and cluster sampling estimators in evaluating health care performance using either a simulated or real dataset. In this paper, we compare the cluster sampling estimators to multilevel estimators in evaluating screening mammography performance using Medicare claims data. We also discuss the strengths and limitations of multilevel analysis in profiling health care providers with small caseloads.     

Quantitative analysis of epithelial morphogenesis in Drosophila oogenesis: New insights based on morphometric analysis and mechanical modeling

The process of epithelial morphogenesis is ubiquitous in animal development, but much remains to be learned about the mechanisms that shape epithelial tissues. The follicle cell (FC) epithelium encapsulating the growing germline of Drosophila is an excellent system to study fundamental elements of epithelial development. During stages 8 to 10 of oogenesis, the FC epithelium transitions between simple geometries-cuboidal, columnar and squamous-and redistributes cell populations in processes described as posterior migration, squamous cell flattening and main body cell columnarization. Here we have carried out a quantitative morphometric analysis of these poorly understood events in order to establish the parameters of and delimit the potential processes that regulate the transitions. Our results compel a striking revision of accepted views of these phenomena, by showing that posterior migration does not involve FC movements, that there is no role for columnar cell apical constriction in FC morphogenesis, and that squamous cell flattening may be a compliant response to germline growth. We utilize mechanical modeling involving finite element computational technologies to demonstrate that time-varying viscoelastic properties and growth are sufficient to account for the bulk of the FC morphogenetic changes.     

Metabolomics assisted metabolic network modeling and network wide analysis of metabolites in microbiology

Metabolomics is the science of qualitatively and quantitatively analyzing low molecular weight metabolites occur in a given biological system. It provides valuable information to elucidate the functional roles and relations of different metabolites in a metabolic pathway. In recent years, a large amount of research on microbial metabolomics has been conducted. It has become a useful tool for achieving highly efficient synthesis of target metabolites. At the same time, many studies have been conducted over the years in order to integrate metabolomics data into metabolic network modeling, which has yielded many exciting results. Additionally, metabolomics also shows great advantages in analyzing the relationship of metabolites network wide. Integrating metabolomics data into metabolic network construction and applying it in network wide analysis of cell metabolism would further improve our ability to control cellular metabolism and optimize the design of cell factories for the overproduction of valuable biochemicals. This review will examine recent progress in the application of metabolomics approaches in metabolic network modeling and network wide analysis of microbial cell metabolism.     

Influence of weak hip abductor muscles on joint contact forces during normal walking: probabilistic modeling analysis

The weakness of hip abductor muscles is related to lower-limb joint osteoarthritis, and joint overloading may increase the risk for disease progression. The relationship between muscle strength, structural joint deterioration and joint loading makes the latter an important parameter in the study of onset and follow-up of the disease. Since the relationship between hip abductor weakness and joint loading still remains an open question, the purpose of this study was to adopt a probabilistic modeling approach to give insights into how the weakness of hip abductor muscles, in the extent to which normal gait could be unaltered, affects ipsilateral joint contact forces. A generic musculoskeletal model was scaled to each healthy subject included in the study, and the maximum force-generating capacity of each hip abductor muscle in the model was perturbed to evaluate how all physiologically possible configurations of hip abductor weakness affected the joint contact forces during walking. In general, the muscular system was able to compensate for abductor weakness. The reduced force-generating capacity of the abductor muscles affected joint contact forces to a mild extent, with 50th percentile mean differences up to 0.5 BW (maximum 1.7 BW). There were greater increases in the peak knee joint loads than in loads at the hip or ankle. Gluteus medius, particularly the anterior compartment, was the abductor muscle with the most influence on hip and knee loads. Further studies should assess if these increases in joint loading may affect initiation and progression of osteoarthritis.