Characterization of free endogenous C14 and C16 sphingoid bases from Drosophila melanogaster

Sphingolipid metabolites function as signaling molecules in mammalian cells, influencing cell proliferation, migration, and death. Recently, sphingolipid signaling has been implicated in the regulation of developmental processes in Drosophila melanogaster. However, biochemical analysis of endogenous Drosophila sphingoid bases has not been reported. In this study, a rapid HPLC-based method was developed for the analysis of free sphingoid bases endogenous to Drosophila. Four molecular species of endogenous free sphingoid bases were observed in adult flies and identified as C14 and C16 sphingosine (Sph) and C14 and C16 dihydrosphingosine (DHS). The C14 molecular species were the most prevalent, accounting for approximately 94% of the total free sphingoid bases in adult wild-type flies. An Sph kinase (SK) mutant demonstrated significant accumulation of all four sphingoid bases, whereas a serine palmitoyltransferase mutant demonstrated low but detectable levels. When endogenous sphingoid bases were evaluated at different stages of development, the observed ratio of Sph to DHS increased significantly from early embryo to adulthood. Throughout development, this ratio was significantly lower in the SK mutant as compared with the wild-type. This is the first report describing analysis of free C14 and C16 sphingoid bases from Drosophila. The biochemical characterization of these lipids from mutant models of sphingolipid metabolism should greatly facilitate the analysis of the biological significance of these signaling molecules.     

Specification methods for material-handling control algorithms in flexible manufacturing systems

Good methods are needed to specify, test, and debug material-handling control logic. This article surveys a number of representative methods for defining and describing control algorithms for programmable material-handling equipment used in flexible manufacturing systems. The methods are evaluated with regard to their suitability for communication between people and as bases for interfaces to automatic program generators. It is concluded that no single method is entirely satisfactory. Three methods (position diagrams, function block diagrams, and operation networks) have potential to be combined into an effective hybrid approach that minimizes the need for the user to switch between various conceptual models.     

Carbon allocation in fruit trees: from theory to modelling

Carbon allocation within a plant depends on complex rules linking source organs (mainly shoots) and sink organs (mainly roots and fruits). The complexity of these rules comes from both regulations and interactions between various plant processes involving carbon. This paper presents these regulations and interactions, and analyses how agricultural management can influence them. Ecophysiological models of carbon production and allocation are good tools for such analyses. The fundamental bases of these models are first presented, focusing on their underlying processes and concepts. Different approaches are used for modelling carbon economy. They are classified as empirical, teleonomic, driven by source–sink relationships, or based on transport and chemical/biochemical conversion concepts. These four approaches are presented with a particular emphasis on the regulations and interactions between organs and between processes. The role of plant architecture in carbon partitioning is also discussed and the interest of coupling plant architecture models with carbon allocation models is highlighted. As an illustration of carbon allocation models, a model developed for peach trees, describing carbon transfer within the plant, and based on source–sink and Münch transport theory is presented and used for analyzing the link between roots, shoots and reproductive compartments. On this basis, the consequences of fruit load or plant pruning on fruit and vegetative growth can be evaluated.     

Analytical estimation of branchwood volume in sugar maple, linked to branchiness

 An analytical link is proposed between branchwood volume and branchiness. A segmented linear model with one parameter is used to describe the branch basal area density along the tree bole and integrated to find a function describing the cumulative branch basal area. It appears that the bases of insertion of the branches defining the base of the light crown correspond to the maximum branch basal area density along the bole. This function is then used together with an individual branch volume equation to find a model that estimates branchwood volume. This model is calibrated with data gathered in 15 stands dominated by sugar maple (Acer saccharum Marsh.) in southern Quebec. A comparison is made with other models of branchwood volume found in the literature. Received: 22 August 1997 / Accepted: 9 February 1998     

Non-Homogeneous Gibbs Process Models for Forestry — A Case Study

Forestry statistics needs realistic models for non-homogeneously distributed trees in forests. For elder trees, non-homogeneous Poisson or Cox processes are not realistic models. Instead, non-homogeneous Gibbs processes are suggested, which are described by a fixed pair potential describing the short-range interaction of trees and a location dependent intensity function describing long-range variation of tree density. The application of this model is demonstrated for a hickory forest in North Carolina and an artificial forest stand.     

Nomenclature relating to restriction of modified DNA in Escherichia coli.

At least three restriction systems that attack DNA containing naturally modified bases have been found in common Escherichia coli K-12 strains. These systems are McrA, McrBC, and Mrr. A brief summary of the genetic and phenotypic properties so far observed in laboratory strains is set forth, together with a proposed nomenclature for describing these properties.     

Control of mental activities by internal models in the cerebellum

The intricate neuronal circuitry of the cerebellum is thought to encode internal models that reproduce the dynamic properties of body parts. These models are essential for controlling the movement of these body parts: they allow the brain to precisely control the movement without the need for sensory feedback. It is thought that the cerebellum might also encode internal models that reproduce the essential properties of mental representations in the cerebral cortex. This hypothesis suggests a possible mechanism by which intuition and implicit thought might function and explains some of the symptoms that are exhibited by psychiatric patients. This article examines the conceptual bases and experimental evidence for this hypothesis.     

In vitro and in vivo reactions of nucleic acids with reducing sugars

Reducing sugars such as glucose and glucose 6-phosphate have been shown to nonenzymatically react with the amino groups of proteins. The modification of proteins by reducing sugars can alter both physical characteristics and biological functions. Analogous to the reaction observed with proteins, the amino groups of DNA bases are also able to react nonenzymatically with reducing sugars. The modifications of DNA by reducing sugars result in the time- and sugar-concentration-dependent changes in biological properties. In this communication we review data describing in vitro and in vivo models we have used to investigate the biological consequences of the nonenzymatic glycosylation of DNA.     

Rodent models based on endolysosomal genes involved in Parkinson's disease

Genes associated with endolysosomal function have been recently associated with familial Parkinson's disease and described as risk factors for sporadic cases. This indicates that deficits in this pathway predispose to parkinsonism. To better understand the role of these genes in disease development, rodent models have been created by targeting genes playing a role in endolysosomal function, such as LRRK2, DNAJC6, SYNJ1, VPS35, GBA1, ATP13A2 and TMEM175. Here, we review the latest findings describing parkinsonian features in these animal models secondary to endolysosomal dysfunction. Also, we provide suggestions for further development and application of these animal models to better understand the contribution of endolysosomal dysfunction in Parkinson's disease and provide novel models for testing therapeutic approaches.     

A Lyapunov function for piecewise-independent differential equations: stability of the ideal free distribution in two patch environments

In this article we construct Lyapunov functions for models described by piecewise-continuous and independent differential equations. Because these models are described by discontinuous differential equations, the theory of Lyapunov functions for smooth dynamical systems is not applicable. Instead, we use a geometrical approach to construct a Lyapunov function. Then we apply the general approach to analyze population dynamics describing exploitative competition of two species in a two-patch environment. We prove that for any biologically meaningful parameter combination the model has a globally stable equilibrium and we analyze this equilibrium with respect to parameters.      

Carnosine and anserine act as effective transglycating agents in decomposition of aldose-derived Schiff bases

There are numerous publications describing the positive effects of carnosine (beta-alanyl-histidine) and anserine (beta-alanyl-1-N-methyl-histidine) on cell and organ function. Of special interest to us is the fact that these dipeptides act to retard and (in one instance) reverse non-enzymatic glycation. To date, the primary explanation for these anti-glycating effects has been the fact that carnosine and anserine can serve as alternative and competitive glycation targets, thereby protecting proteins from this deleterious process. In this paper, we document another mechanism by which these two peptides can retard or reverse glycation. The process involves decomposition of the very first intermediates of the non-enzymatic glycation cascade (aldosamines a.k.a. Schiff bases) by nucleophilic attack of carnosine and/or anserine on the preformed aldosamine such as glucosyl-lysine. If future research shows this reaction is to be physiologically important, this mechanism could explain some of the beneficial effects of carnosine and anserine as anti-glycating agents.     

Non-local concepts and models in biology

In this paper, we consider local and non-local spatially explicit mathematical models for biological phenomena. We show that, when rate differences between fast and slow local dynamics are great enough, non-local models are adequate simplifications of local models. Non-local models thus avoid describing fast processes in mechanistic detail, instead describing the effects of fast processes on slower ones. As a consequence, non-local models are helpful to biologists because they describe biological systems on scales that are convenient to observation, data collection, and insight. We illustrate these arguments by comparing local and non-local models for the aggregation of hypothetical organisms, and we support theoretical ideas with concrete examples from cell biology and animal behavior.     

Estimation in the progressive illness‐death model: A nonexhaustive review

Multistate models can be successfully used for describing complex event history data, for example, describing stages in the disease progression of a patient. The so‐called “illness‐death” model plays a central role in the theory and practice of these models. Many time‐to‐event datasets from medical studies with multiple end points can be reduced to this generic structure. In these models one important goal is the modeling of transition rates but biomedical researchers are also interested in reporting interpretable results in a simple and summarized manner. These include estimates of predictive probabilities, such as the transition probabilities, occupation probabilities, cumulative incidence functions, and the sojourn time distributions. We will give a review of some of the available methods for estimating such quantities in the progressive illness‐death model conditionally (or not) on covariate measures. For some of these quantities estimators based on subsampling are employed. Subsampling, also referred to as landmarking, leads to small sample sizes and usually to heavily censored data leading to estimators with higher variability. To overcome this issue estimators based on a preliminary estimation (presmoothing) of the probability of censoring may be used. Among these, the presmoothed estimators for the cumulative incidences are new. We also introduce feasible estimation methods for the cumulative incidence function conditionally on covariate measures. The proposed methods are illustrated using real data. A comparative simulation study of several estimation approaches is performed and existing software in the form of R packages is discussed.     

Modelling in molecular biology: describing transcription regulatory networks at different scales

Approaches to describe gene regulation networks can be categorized by increasing detail, as network parts lists, network topology models, network control logic models or dynamic models. We discuss the current state of the art for each of these approaches. We study the relationship between different topology models, and give examples how they can be used to infer functional annotations for genes of unknown function. We introduce a new simple way of describing dynamic models called finite state linear model (FSLM). We discuss the gap between the parts list and topology models on one hand, and network logic and dynamic models, on the other hand. The first two classes of models have reached a genome-wide scale, while for the other model classes high-throughput technologies are yet to make a major impact.     

Some interrelationships among the regression coefficient estimates arising in a class of models appropriate to response-time data.

Interrelationships among three response-time models which incorporate covariate information are explored. The most general of these models is the logistic-exponential in which the log odds of the probability of responding in a fixed interval is assumed to be a linear function of the covariates; this model includes a parameter W for the width of discrete time intervals in which responses occur. As W leads to O this model is equivalent to a continuous time exponential model in which the log hazard is linear in the covariates. As W leads to infininity it is equivalent to a continuous time exponential model in which the hazard itself is a linear function of the covariates. This second model was fitted to the data used in an earlier publication describing the logistic exponential model, and very close agreement of the estimates of the regression coefficients is demonstrated.     

The utility of behavioral models and modules in molecular analyses of social behavior

It is extremely difficult to trace the causal pathway relating gene products or molecular pathways to the expression of behavior. This is especially true for social behavior, which being dependent on interactions and communication between individuals is even further removed from molecular-level events. In this review, we discuss how behavioral models can aid molecular analyses of social behavior. Various models of behavior exist, each of which suggest strategies to dissect complex behavior into simpler behavioral 'modules.' The resulting modules are easier to relate to neural processes and thus suggest hypotheses for neural and molecular function. Here we discuss how three different models of behavior have facilitated understanding the molecular bases of aspects of social behavior. We discuss the response threshold model and two different approaches to modeling motivation, the state space model and models of reinforcement and reward processing. The examples we have chosen illustrate how models can generate testable hypotheses for neural and molecular function and also how molecular analyses probe the validity of a model of behavior. We do not champion one model over another; rather, our examples illustrate how modeling and molecular analyses can be synergistic in exploring the molecular bases of social behavior.