Using a reduced dimensionality model to compute the thermodynamic properties of finite polypeptide aggregates

By implementing a simple reduced dimensionality model to describe the interactions in finite systems composed of two seven-amino-acid peptides, the thermodynamic properties of ordered and disordered aggregates were computed. Within this model, the hydrophobicity of each amino acid was varied, and the stability of the systems computed. Accurate averages in the canonical ensemble were obtained using various replica exchange Monte Carlo algorithms. Low and high temperature regions were encountered where the ordered and disordered aggregates were stabilized. It was observed that as the degree of hydrophobicity increased, the stability of the aggregates increased, with a significant energetic stabilization obtained for the ordered aggregates. Upon decreasing the concentration of the solution, the stability of the amorphous aggregates increased when compared to the ordered systems.     

节肢动物群落稳定性分析灰典型相关模型及其应用

稳定性是生态系统最重要的特征之一。根据累加生成可增强两单调增序列线性相关性原理,应用典型相关分析方法,以比值mn/mp(mp为害虫个体数,mn为天敌个体数)为测度群落稳定性的指数,构建群落稳定性分析灰典型相关模型。具体做法是:(1)将各种群的数量序列按害虫各次总数量的递增顺序进行重排,用各种群数量序列的极差去除该序列,将其无量纲化,然后对各序列进行累加生成;(2)以害虫各种群为一组变量,天敌各种群为另一组变量,应用典型相关分析的方法,求出各对典型变量。对达到线性拟合要求的典型变量对,以害虫为自变量,天敌为因变量建立回归方程,并对这些方程中的变量进行累减还原;(3)对这些方程进行线性组合,合并成一个方程,组合系数是使这些害虫典型变量的线性组合与害虫总数量序列的线性相关值达到最大;(4)引进转换系数的概念,建立天敌、害虫总量相互转换模型,该模型称之为灰典型相关模型,通过模型可分析各种群在群落稳定性中的作用。将模型应用于福州金山茶园节肢动物群落的稳定性分析,所得结果与实际基本相符,表明建立的灰典型相关模型是可行的。     

Population Level Inference for Multivariate MEG Analysis

Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. Here we propose a solution based on Canonical Variates Analysis (CVA) model scoring at the subject level and random effects Bayesian model selection at the group level. We apply this approach to beamformer reconstructed MEG data in source space. CVA estimates those multivariate patterns of activation that correlate most highly with the experimental design; the order of a CVA model is then determined by the number of significant canonical vectors. Random effects Bayesian model comparison then provides machinery for inferring the optimal order over the group of subjects. Absence of a multivariate dependence is indicated by the null model being the most likely. This approach can also be applied to CVA models with a fixed number of canonical vectors but supplied with different feature sets. We illustrate the method by identifying feature sets based on variable-dimension MEG power spectra in the primary visual cortex and fusiform gyrus that are maximally discriminative of data epochs before versus after visual stimulation.     

Associations between vegetation patterns and soil texture in the shortgrass steppe

A recent conceptual model of controls on vegetation structure in semiarid regions includes the hypothesis that the balance between the dominance of woody and herbaceous species is partly controlled by soil texture. The model predicts that the dominance of woody plants is associated with coarse textured soils, and that ecotones between woody and herbaceous plant functional types are associated with soil textural changes. We analyzed vegetation and soil data (from US Soil Conservation Service maps) for an area of shortgrass steppe in Northern Weld County, Colorado, in a canonical correlation procedure to test the hypothesis at a regional scale. In support of the model, we found significant correlations between (a) a canonical vegetation variable correlated with C₃ grass biomass and shrub biomass, and a canonical soil variable correlated with sandy topsoils, and (b) a canonical vegetation variable correlated with succulent biomass, and a canonical soil variable correlated with clay soils. Relatively sharp transitions between shrub- and grass-dominated vegetation types occur in a number of areas in the shortgrass steppe of northeastern Colorado and southeastern Wyoming, and we selected four sites to test the above hypothesis at a local scale. We gathered data on vegetation cover and soil texture from transects (50 m long) positioned across the transition zones from grassland to shrubland. We conducted a further canonical correlation analysis of the vegetation and soil data to test for the relationships between vegetation structure and soil texture, and a performed regression analyses on individual site data to describe site-specific relationships between vegetation and soil texture variables. Vegetation structure along the transects, at the level of plant functional types, was similar at all four sites. The transition from grassland to shrubland encompassed a change from a C₄ grass/half-shrub complex to a shrub/C₃ grass/succulent complex. At two of the sites these transitions were associated with a change to coarser-textured soils in the shrubland zone. Within the context of the shortgrass steppe, our overall findings support the predictions of the conceptual at a regional scale, but indicate that soil texture is only one factor that can influence vegetation structure at the local scale.     

Nonparametric Analysis of Ordered Categorical Data in Designs with Longitudinal Observations and Small Sample Sizes

For designs with longitudinal observations of ordered categorical data, a nonparametric model is considered where treatment effects and interactions are defined by means of the marginal distributions. These treatment effects are estimated consistently by ranking methods. The hypotheses in this nonparametric setup are formulated by means of the distribution functions. The asymptotic distribution of the estimators for the nonparametric effects are given under the hypotheses. For small samples, a rather accurate approximation is suggested. A clinical trial with ordered categorical data is used to motivate the ideas and to explain the procedures which are extensions of the Wilcoxon‐Mann‐Whitney test to factorial designs with longitudinal observations. The application of the procedures requires only some trivial regularity assumptions.     

Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity

At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. How the infant’s nervous system supports the acquisition of this ability is unknown. Here we present a computational model that combines a spiking neural network, reinforcement-modulated spike-timing-dependent plasticity, and a human-like vocal tract to simulate the acquisition of canonical babbling. Like human infants, the model’s frequency of canonical babbling gradually increases. The model is rewarded when it produces a sound that is more auditorily salient than sounds it has previously produced. This is consistent with data from human infants indicating that contingent adult responses shape infant behavior and with data from deaf and tracheostomized infants indicating that hearing, including hearing one’s own vocalizations, is critical for canonical babbling development. Reward receipt increases the level of dopamine in the neural network. The neural network contains a reservoir with recurrent connections and two motor neuron groups, one agonist and one antagonist, which control the masseter and orbicularis oris muscles, promoting or inhibiting mouth closure. The model learns to increase the number of salient, syllabic sounds it produces by adjusting the base level of muscle activation and increasing their range of activity. Our results support the possibility that through dopamine-modulated spike-timing-dependent plasticity, the motor cortex learns to harness its natural oscillations in activity in order to produce syllabic sounds. It thus suggests that learning to produce rhythmic mouth movements for speech production may be supported by general cortical learning mechanisms. The model makes several testable predictions and has implications for our understanding not only of how syllabic vocalizations develop in infancy but also for our understanding of how they may have evolved.     

Extinction risk of a meta-population: aggregation approach

Aggregation of variables of a complex mathematical model with realistic structure gives a simplified model which is more suitable than the original one when the amount of data for parameter estimation is limited. Here we explore use of a formula derived for a single unstructured population (canonical model) in predicting the extinction time for a population living in multiple habitats. In particular we focus multiple populations each following logistic growth with demographic and environmental stochasticities, and examine how the mean extinction time depends on the migration and environmental correlation. When migration rate and/or environmental correlation are very large or very small, we may express the mean extinction time exactly using the formula with properly modified parameters. When parameters are of intermediate magnitude, we generate a Monte Carlo time series of the population size for the realistic structured model, estimate the "effective parameters" by fitting the time series to the canonical model, and then calculate the mean extinction time using the formula for a single population. The mean extinction time predicted by the formula was close to those obtained from direct computer simulation of structured models. We conclude that the formula for an unstructured single-population model has good approximation capability and can be applicable in estimating the extinction risk of the structured meta-population model for a limited data set.     

Variational problems for the canonical profiles

A noncontradictory formulation of the variational problem for a canonical profile is proposed that refines the problem posed by B.B. Kadomtsev for a circular plasma cylinder. The results are generalized to a toroidal plasma with an arbitrary cross section. For the problem in toroidal geometry, boundary conditions are proposed with which to single out the Kadomtsev-like solution (the canonical profile) from the solutions to the Euler equation. Canonical profiles for the L-and H-modes are constructed. For a number of interesting examples, it is numerically shown that the second variation of the magnetic energy functional is positive. The canonical profile transport model is outlined, and the relationship between the canonical, numerical, and experimental profiles in tokamaks is briefly discussed.     

Both LRP5 and LRP6 receptors are required to respond to physiological Wnt ligands in mammary epithelial cells and fibroblasts

A canonical Wnt signal maintains adult mammary ductal stem cell activity, and this signal requires the Wnt signaling reception, LRP5. However, previous data from our laboratory have shown that LRP5 and LRP6 are co-expressed in mammary basal cells and that LRP6 is active, leading us to question why LRP6 is insufficient to mediate canonical signaling in the absence of LRP5. Here, we show that at endogenous levels of LRP5 and LRP6 both receptors are required to signal in response to some Wnt ligands both in vitro (in mouse embryonic fibroblasts and mammary epithelial cells) and in vivo (in mammary outgrowths). This subgroup of canonical ligands includes Wnt1, Wnt9b, and Wnt10b; the latter two are expressed in mammary gland. In contrast, the ligand commonly used experimentally, Wnt3a, prefers LRP6 and requires just one receptor regardless of cellular context. When either LRP5 or LRP6 is overexpressed, signaling remains ligand-dependent, but the requirement for both receptors is abrogated (regardless of ligand type). We have documented an LRP5-6 heteromer using immiscible filtration assisted by surface tension (IFAST) immunoprecipitation. Together, our data imply that under physiological conditions some Wnt ligands require both receptors to be present to generate a canonical signal. We have designed a model to explain our results based on the resistance of LRP5-6 heteromers to a selective inhibitor of E1/2-binding Wnt-LRP6 interaction. These data have implications for stem cell biology and for the analysis of the oncogenicity of LRP receptors that are often overexpressed in breast tumors.     

Crystal structures of Cratylia floribunda seed lectin at acidic and basic pHs. Insights into the structural basis of the pH-dependent dimer-tetramer transition

Structural determinants underlaying the pH-dependent dimer-tetramer transition of Diocleinae lectins were investigated from the structures of Cratylia floribunda seed lectin crystallized in conditions where it exist as a dimer (pH 4.6) or as a tetramer (pH 8.5). The acidic (aCFL) and the basic (bCFL) tetramers superimpose with overall r.m.s.d. of 0.53 A, though interdimer contacts are drastically reduced in aCFL, and the r.m.s.d. for the superposition of the 117-120 loops of aCFL vs. the bCFL tetramer is 1.29 A. Our data support the view that His51 plays a role in determining the conformation of the central cavity loops and that interdimer contacts involving ordered loop residues stabilize the canonical, pH-dependent tetramer. In the bCFL tetramer, hydrogen bonds between Asn118 and Thr120 of monomers A and D and residues Ser66, Ser108, Ser110, and Thr49 of the opposite monomer stabilize the canonical, pH-dependent tetrameric lectin structure. In CFL, Asn131 makes intradimer contacts with Asn122 and Ala123. In comparison, His131 in Dioclea grandiflora lectin establishes a network of interdimer interactions bridging the four central loops of the pH-independent tetramer. Our data provide new insights into the participation of specific amino acid residues in the mechanism of the quaternary association of Diocleinae lectins.     

Canonical sensitivities: a useful tool to deal with large perturbations in metabolic network modeling

The dynamic range of metabolic models can be extended to deal with large perturbations by introducing the related concepts of "generalized" kinetic order and "canonical" sensitivities. Generalized kinetic orders are built as a well-defined non linear combination of the canonical sensitivities coefficients, which in turn are obtained by a least-squares regression on central composite factorial design data. In a such way, the whole domain of the operating variables is mapped without need to determine locally neither the first nor the second order model derivatives. The method was validated through numerical simulations, its predictions being compared with those coming from a Michaelis-Menten formalism taken as reference. In parallel, two variants of the Power-law formalism (S-system, least-squares GMA) also were tested. The canonical sensitivities method produced the widest range to predict metabolite concentrations and metabolic fluxes at the steady states. In addition, the variation pattern for the logarithmic gains and for the characteristic eigenvalues have been accurately determined from a unique overall model, being both required to make realistic analysis in metabolic engineering. The achieved information also can be expressed in terms of those typical coefficients derived from the Metabolic Control Analysis (MCA). Even if current first order Power-law or MCA formalisms were used, the canonical sensitivities approach provides a significant advantage, since complete sets of homologous, accurate, locally valid metabolic coefficients can be simultaneously recovered from the array proposed, being representative of the whole range of the operating variables instead of a unique nominal condition as is usual.     

Lateral organization in lipid-cholesterol mixed bilayers

Interactions between lipid and cholesterol molecules in membranes play an important role in the structural and functional properties of cell membranes. Although structural properties of lipid-cholesterol mixtures have been extensively studied, an understanding of the role of cholesterol in the lateral organization of bilayers has been elusive. In this article, we propose a simple yet powerful model, based on self-consistent mean-field theory and molecular dynamics simulations, for lipid bilayers containing cholesterol. Properties predicted by our model are shown to be in excellent agreement with experimental data. Our model predicts that cholesterol induces structural changes in the bilayer through the formation of regions of ordered lipids surrounding each cholesterol molecule. We find that the "smooth" and "rough" sides of cholesterol play crucial roles in formation and distribution of the ordered regions. Our model is predictive in that input parameters are obtained from independent atomistic molecular dynamics simulations. The model and method are general enough to describe other heterogeneous lipid bilayers, including lipid rafts.     

Towards the analysis of vegetation succession

Attention is drawn to canonical analysis as a plausible model for analyzing vegetation succession. An assessment of the opportunities afforded by canonical analysis for this purpose is then made by reference to two applications of the method. The applications deal with characteristics of hydroseral processes and with the dynamic status of an area of lowland tropical rain forest. On the basis of these and other studies the conclusion is drawn that canonical analysis could contribute usefully in efforts to place the study of dynamic ecosystem processes on a more analytic footing.This work was supported by a Natural Sciences and Engineering Research Council award to L. Orlóci. It is a pleasure to acknowledge my indebtedness both to Dr. Orlóci for his support and encouragement and to the Department of Plant Sciences at the University of Western Ontario for hospitality and help. Appreciation is expressed also to Dr. John Ogden, Research School of Pacific Studies, The Australian National University, Canberra for kindly placing his rain forest data at my disposal and for his invaluable help in interpreting the results of analyses of these data.     

Factor Xa active site substrate specificity with substrate phage display and computational molecular modeling

Structural origin of substrate-enzyme recognition remains incompletely understood. In the model enzyme system of serine protease, canonical anti-parallel beta-structure substrate-enzyme complex is the predominant hypothesis for the substrate-enzyme interaction at the atomic level. We used factor Xa (fXa), a key serine protease of the coagulation system, as a model enzyme to test the canonical conformation hypothesis. More than 160 fXa-cleavable substrate phage variants were experimentally selected from three designed substrate phage display libraries. These substrate phage variants were sequenced and their specificities to the model enzyme were quantified with quantitative enzyme-linked immunosorbent assay for substrate phage-enzyme reaction kinetics. At least three substrate-enzyme recognition modes emerged from the experimental data as necessary to account for the sequence-dependent specificity of the model enzyme. Computational molecular models were constructed, with both energetics and pharmacophore criteria, for the substrate-enzyme complexes of several of the representative substrate peptide sequences. In contrast to the canonical conformation hypothesis, the binding modes of the substrates to the model enzyme varied according to the substrate peptide sequence, indicating that an ensemble of binding modes underlay the observed specificity of the model serine protease.     

Separate and distinctive roles for Wnt5a in tongue, lingual tissue and taste papilla development

Although canonical Wnt signaling is known to regulate taste papilla induction and numbers, roles for noncanonical Wnt pathways in tongue and taste papilla development have not been explored. With mutant mice and whole tongue organ cultures we demonstrate that Wnt5a protein and message are within anterior tongue mesenchyme across embryo stages from the initiation of tongue formation, through papilla placode appearance and taste papilla development. The Wnt5a mutant tongue is severely shortened, with an ankyloglossia, and lingual mesenchyme is disorganized. However, fungiform papilla morphology, number and innervation are preserved, as is expression of the papilla marker, Shh. These data demonstrate that the genetic regulation for tongue size and shape can be separated from that directing lingual papilla development. Preserved number of papillae in a shortened tongue results in an increased density of fungiform papillae in the mutant tongues. In tongue organ cultures, exogenous Wnt5a profoundly suppresses papilla formation and simultaneously decreases canonical Wnt signaling as measured by the TOPGAL reporter. These findings suggest that Wnt5a antagonizes canonical Wnt signaling to dictate papilla number and spacing. In all, distinctive roles for Wnt5a in tongue size, fungiform papilla patterning and development are shown and a necessary balance between non-canonical and canonical Wnt paths in regulating tongue growth and fungiform papillae is proposed in a model, through the Ror2 receptor.     

The folding nucleus of the insulin superfamily: a flexible peptide model foreshadows the native state

Oxidative folding of insulin-like growth factor I (IGF-I) and single-chain insulin analogs proceeds via one- and two-disulfide intermediates. A predominant one-disulfide intermediate in each case contains the canonical A20-B19 disulfide bridge (cystines 18-61 in IGF-I and 19-85 in human proinsulin). Here, we describe a disulfide-linked peptide model of this on-pathway intermediate. One peptide fragment (19 amino acids) spans IGF-I residues 7-25 (canonical positions B8-B26 in the insulin superfamily); the other (18 amino acids) spans IGF-I residues 53-70 (positions A12-A21 and D1-D8). Containing only half of the IGF-I sequence, the disulfide-linked polypeptide (designated IGF-p) is not well ordered. Nascent helical elements corresponding to native alpha-helices are nonetheless observed at 4 degrees C. Furthermore, (13)C-edited nuclear Overhauser effects establish transient formation of a native-like partial core; no non-native nuclear Overhauser effects are observed. Together, these observations suggest that early events in the folding of insulin-related polypeptides are nucleated by a native-like molten subdomain containing Cys(A20) and Cys(B19). We propose that nascent interactions within this subdomain orient the A20 and B19 thiolates for disulfide bond formation and stabilize the one-disulfide intermediate once formed. Substitutions in the corresponding region of insulin are associated with inefficient chain combination and impaired biosynthetic expression. The intrinsic conformational propensities of a flexible disulfide-linked peptide thus define a folding nucleus, foreshadowing the structure of the native state.