A nomenclature and data model to describe NMR experiments

Despite ongoing efforts in organising NMR information, there is no consistent and well-described generic standard for naming NMR experiments. The main reason for the absence of a universal naming system is that the information content of the coherence pathways is difficult to describe in full detail. We propose a system that describes the common and generic elements of the coherence pathways produced by pulse sequences. The system itself is formalised by an ‘NMR experiment protocol’ model, which is described in the Universal Modelling Language (UML) as part of the CCPN data model. Furthermore, normalized experiment names can be derived from this proposed model. We hope this article will stimulate discussion to organise the wealth of NMR experiments, and that by bringing this discussion into the public domain we can improve and expand our proposed system to include as much information and as many NMR experiments as possible. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.Joint first authors     

A robust model to describe the differentiation of T-helper cells

There is a wealth of information regarding the differentiation of T-helper cells. Nevertheless, there is no general agreement on the topology and dynamical properties of the molecular network controlling the differentiation of these cells. This paper presents a continuous dynamical system to model the signaling network that controls the differentiation process of T-helper cells. The model is able to represent the differentiation from the precursor Th0 cell to any of the four effectors types (Th1, Th2, Th17, and Treg), as well as the phenotype of single null mutants. We present the first sensitivity analysis of the equations defining the Th model, showing that the qualitative dynamical behavior of the model is very robust against changes in three out of four tested parameters. The robustness of the model is in agreement with our claim that the qualitative behavior of the system is to a large extent independent of the methodological framework used for modeling.     

A suitable model to describe bioremediation of a petroleum-contaminated soil

A critical environmental impact of the petroleum industry is the spillage of oil and related products that causes severe soil contamination. Although biodegradation of petroleum hydrocarbons may be successfully conducted under controlled conditions, the bioremediation of large volumes of contaminated soils still presents some technical challenges, particularly when contamination occurs in soils of high clay content. The main objective of this work is to evaluate the bioremediation of petroleum-contaminated clay-soil by fixed bed experiments. They were conducted in agreement with the full factorial experimental design 2³. The processes employed were shown to be highly effective in decontaminating the soil, achieving removal rates of around 80%. The model chosen to represent the bioremediation process provided satisfactory results. The values calculated by the model were consistent with the experimental results.     

A suitable model to describe bioremediation of a petroleum-contaminated soil

A critical environmental impact of the petroleum industry is the spillage of oil and related products that causes severe soil contamination. Although biodegradation of petroleum hydrocarbons may be successfully conducted under controlled conditions, the bioremediation of large volumes of contaminated soils still presents some technical challenges, particularly when contamination occurs in soils of high clay content. The main objective of this work is to evaluate the bioremediation of petroleum-contaminated clay-soil by fixed bed experiments. They were conducted in agreement with the full factorial experimental design 2³. The processes employed were shown to be highly effective in decontaminating the soil, achieving removal rates of around 80%. The model chosen to represent the bioremediation process provided satisfactory results. The values calculated by the model were consistent with the experimental results.     

A model to describe the performance of the UASB reactor

A dynamic model to describe the performance of the Upflow Anaerobic Sludge Blanket (UASB) reactor was developed. It includes dispersion, advection, and reaction terms, as well as the resistances through which the substrate passes before its biotransformation. The UASB reactor is viewed as several continuous stirred tank reactors connected in series. The good agreement between experimental and simulated results shows that the model is able to predict the performance of the UASB reactor (i.e. substrate concentration, biomass concentration, granule size, and height of the sludge bed).     

A vitalistic model to describe the thermal inactivation ofListeria monocytogenes

Summary Thermal inactivation of microorganisms has traditionally been described as log-linear in nature, that is the reduction in log numbers of survivors decreases in a linear manner with time. This is despite a plethora of data that shows consistent deviations from such kinetics for a wide range of organisms and conditions and that cannot be accounted for by experimental artifacts. Existing thermal death models fail to take such deviations into account and also fail to quantify the effects of heating menstruum on heat sensitivity. The thermal inactivation ofListeria monocytogenes ATCC 19115 has been investigated using a factorially-designed experiment comparing 45 conditions of salt concentration, pH value and temperature. Heating was carried out using a Submerged Coil heating apparatus that minimized experimental artifacts. Low pH values increased, whilst high salt concentrations decreased heat sensitivity. Results showed a significant and consistent deviation from log-linear kinetics, particularly at low temperatures. A number of distributions were tested for suitability to describe the variability of heat sensitivity within the population of heated cells (vitalistic approach). The use of the logistic function and log dose (log time) allowed the development of an accurate unifying predictive model across the whole range of heating conditions. It is proposed that this approach should be tested as a generalized modeling technique for death kinetics of vegetative bacteria.     

蚜虫种群时空分布动态模型

种群空间格局是昆虫种群的重要属性,是为害虫防治提供动态信息的重要前提。关于种群空间格局的时空动态,前人曾建立了富立叶模型和有阻尼自由震荡模型,但忽略了生境资源和空间资源的限制,不能很好地描述昆虫种群在自然界摆布状况的动态行为。因此,在前人研究的基础上,根据蚜虫在自然界的聚集扩散行为逐步建立了描述蚜虫种群聚集扩散规律的变幅、变周期时空分布动态模型,即:y=Ae-nt[sin(w0emtt+φ)+b]+c,并应用该模型对麦长管蚜(Sitobion avenae Fabricius)、麦二叉蚜(Schizaphis graminum Rondani)、禾缢管蚜(Rhopalosiphum padi Linnaeus)和玉米蚜(Rhopalosiphum maidis Fitch)的实验数据进行了拟合。结果表明,麦蚜种群和玉米蚜种群呈现出不同的规律,3种麦蚜均为减幅减周期的变化趋势,玉米蚜则表现为减幅增周期的变化趋势。此外,该模型的拟合效果较好(R20.942,SSE2.6)、生物意义明确,不仅可用于描述蚜虫以及蚜虫以外的其他昆虫和螨类种群的时空动态,还可准确描述不同年龄阶段和不同空间位置上种群的动态,具有普遍适用性。应用该模型考察不同种蚜虫在同一作物上的竞争情况和蚜虫与其天敌的空间分布动态,可为害虫的综合防治奠定基础;对不同小麦抗性品种上同一种蚜虫的聚集扩散行为进行刻画、分析,还可为小麦的抗性育种提供参考依据。     

A linear canal-otolith interaction model to describe the human vestibulo-ocular reflex

A control systems model of the vestibulo-ocular reflex (VOR) originally derived for yaw rotation about an eccentric axis (Crane et al. 1997) was applied to data collected during ambulation and dynamic posturography. The model incorporates a linear summation of an otolith response due to head translation scaled by target distance, adding to a semi-circular canal response that depends only on angular head rotation. The results of the model were compared with human experimental data by supplying head angular velocity as determined by magnetic search coil recording as the input for the canal branch of the model and supplying linear acceleration as determined by flux gate magnetometer measurements of otolith position. The model was fit to data by determining otolith weighting that enabled the model to best fit the data. We fit to the model experimental data from normal subjects who were: standing quietly, walking, running, or making active sinusoidal head movements. We also fit data obtained during dynamic posturography tasks of: standing on a platform sliding in a horizontal plane at 0.2 Hz, standing directly on a platform tilting at 0.1 Hz, and standing on the tilting platform buffered by a 5-cm thick foam rubber cushion. Each task was done with the subject attending a target approximately 500, 100, or 50 cm distant, both in light and darkness. The model accurately predicted the observed VOR response during each test. Greater otolith weighting was required for near targets for nearly all activities, consistent with weights for the otolith component found in previous studies employing imposed rotations. The only exceptions were for vertical axis motion during standing, sliding, and tilting when the platform was buffered with foam rubber. In the horizontal axis, the model always fit near target data better with a higher otolith component. Otolith weights were similar with the target visible and in darkness. The model predicts eye movement during both passive whole-body rotation and free head movement in space implying that the VOR is controlled by a similar mechanism during both situations. Factors such as vision, proprioception, and efference copy that are available during head free motion but not during whole-body rotation are probably not important to gaze stabilization during ambulation and postural stabilizing movement. The linearity of the canal-otolith interaction was tested by re-analysis of the whole body rotation data on which the model is based (Crane et al. 1997). Normalized otolith-mediated gain enhancement was determined for each axis of rotation. This analysis uncovered minor non-linearities in the canal-otolith interaction at frequencies above 1.6 Hz and when the axis of rotation was posterior to the head. Received: 11 March 1998 / Received in revised form: 1 March 1999     

A general bilinear model to describe growth or decline time profiles

Linear models are widely used because of their unrivaled simplicity, but they cannot be applied for data that have a turning-or rate-change-point, even if the data show good linearity sufficiently far from this point. To describe such bilinear-type data, a completely generalized version of a linearized biexponential model (LinBiExp) is proposed here to make possible smooth and fully parametrizable transitions between two linear segments while still maintaining a clear connection with the linear models. Applications and brief conclusions are presented for various time profiles of biological and medical interest including growth profiles, such as those of human stature, agricultural crops and fruits, multicellular tumor spheroids, single fission yeast cells, or even labor productivity, and decline profiles, such as age-effects on cognition in patients who develop dementia and lactation yields in dairy cattle. In all these cases, quantitative model selection criteria such as the Akaike and the Schwartz Bayesian information criteria indicated the superiority of the bilinear model compared to adequate less parametrized alternatives such as linear, parabolic, exponential, or classical growth (e.g., logistic, Gompertz, Weibull, and Richards) models. LinBiExp provides a versatile and useful five-parameter bilinear functional form that is convenient to implement, is suitable for full optimization, and uses intuitive and easily interpretable parameters.     

Dynamic mechanical properties of agarose gels modeled by a fractional derivative model

The complex modulus (E*) and elastic modulus (E') of agarose gels (2% to 4%) are measured with a dynamic mechanical analyzer in frequency sweep shear sandwich mode between 0.1 and 20 Hz. The data showed that E* and E' increase with frequency according to a power law which can be described by a fractional derivative model to characterize the dynamic viscoelasticity of the gel. The functions between the model parameters including storage modulus coefficient (H) and the power law exponent (beta) and the agarose concentration are established. A molecular basis for the application of the fractional derivative model to gel polymers is also discussed. Such an approach can be useful in tissue culture studies employing dynamic pressurization or for validation of magnetic resonance elastography.     

A cellular tensegrity model to analyse the structural viscoelasticity of the cytoskeleton

This study describes the viscoelastic properties of a refined cellular-tensegrity model composed of six rigid bars connected to a continuous network of 24 viscoelastic pre-stretched cables (Voigt bodies) in order to analyse the role of the cytoskeleton spatial rearrangement on the viscoelastic response of living adherent cells. This structural contribution was determined from the relationships between the global viscoelastic properties of the tensegrity model, i.e., normalized viscosity modulus (eta(*)), normalized elasticity modulus (E(*)), and the physical properties of the constitutive elements, i.e., their normalized length (L(*)) and normalized initial internal tension (T(*)). We used a numerical method to simulate the deformation of the structure in response to different types of loading, while varying by several orders of magnitude L(*) and T(*). The numerical results obtained reveal that eta(*) remains almost independent of changes in T(*) (eta(*) proportional, variant T(*+0.1)), whereas E(*) increases with approximately the square root of the internal tension T(*) (from E(*) proportional, variant T(*+0.3) to E(*) proportional, variant T(*+0.7)). Moreover, structural viscosity eta(*) and elasticity E(*) are both inversely proportional to the square of the size of the structure (eta(*) proportional, variant L(*-2) and E(*) proportional, variant L(*-2)). These structural properties appear consistent with cytoskeleton (CSK) mechanical properties measured experimentally by various methods which are specific to the CSK micromanipulation in living adherent cells. Present results suggest, for the first time, that the effect of structural rearrangement of CSK elements on global CSK behavior is characterized by a faster cellular mechanical response relatively to the CSK element response, which thus contributes to the solidification process observed in adherent cells. In extending to the viscoelastic properties the analysis of the mechanical response of the cellular 30-element tensegrity model, the present study contributes to the understanding of recent results on the cellular-dynamic response and allows to reunify the scattered data reported for the viscoelastic properties of living adherent cells.     

A geostatistical model to describe root vitality and ectomycorrhization in Norway spruce

Abstract

The spatial distribution of vital root tips and ectomycorrhizal (ECM) communities in forest soils is characterized by patchiness at a microscale level, mostly related to the distribution patterns of biotic and abiotic factors. A geostatistical model was applied to verify if spatial analyses could be useful in identifying an appropriate sampling method to study root tip vitality, ectomycorrhization and the ECM community. Root samples were collected from two high mountain Norway spruce forests (Trentino province, Italy) following a geometrical design. Laboratory microscopic and geostatistical ordinary kriging analyses were used to map tip vitality and ectomycorrhization degree, ECM richness and distribution grouped in “exploration types” (amount of emanating hyphae or presence and differentiation of rhizomorphs). Spatial gradients of the examined features existed at plant level, associated to the up-downslope direction (root tip vitality and ectomycorrhization, ECM richness) and distance from the stem base (ECM exploration types). The effectiveness of the geostatistical model used demonstrates that a geometrical sampling design, associated to spatial mapping techniques, can be useful in research where the tree, and not the forest, is the subject (mycological and phytopathological studies).     

A stochastic Markov chain model to describe lung cancer growth and metastasis

A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients documenting all primary tumor locations and metastatic sites from this population. The resulting 50 potential metastatic sites are connected by directed edges with distributed weightings, where the site connections and weightings are obtained by calculating the entries of an ensemble of transition matrices so that the steady-state distribution obtained from the long-time limit of the Markov chain dynamical system corresponds to the ensemble metastatic distribution obtained from the autopsy data set. We condition our search for a transition matrix on an initial distribution of metastatic tumors obtained from the data set. Through an iterative numerical search procedure, we adjust the entries of a sequence of approximations until a transition matrix with the correct steady-state is found (up to a numerical threshold). Since this constrained linear optimization problem is underdetermined, we characterize the statistical variance of the ensemble of transition matrices calculated using the means and variances of their singular value distributions as a diagnostic tool. We interpret the ensemble averaged transition probabilities as (approximately) normally distributed random variables. The model allows us to simulate and quantify disease progression pathways and timescales of progression from the lung position to other sites and we highlight several key findings based on the model.     

A spatio-temporal model to describe the spread of Salmonella within a laying flock

Salmonella is one of the major sources of toxi-infection in humans, most often because of consumption of poultry products. The main reason for this association is the presence in hen flocks of silent carriers, i.e. animals harboring Salmonella without expressing any visible symptoms. Many prophylactic means have been developed to reduce the prevalence of Salmonella carrier-state. While none allows a total reduction of the risk, synergy could result in a drastic reduction of it. Evaluating the risk by modeling would be very useful to estimate such gain in food safety. Here, we propose an individual-based model which describes the spatio-temporal spread of Salmonella within a laying flock and takes into account the host response to bacterial infection. The model includes the individual bacterial load and the animals’ ability to reduce it thanks to the immune response, i.e. maximum bacterial dose that the animals may resist without long term carriage and, when carriers, length of bacterial clearance. For model validation, we simulated the Salmonella spread under published experimental conditions. There was a good agreement between simulated and observed published data. This model will thus allow studying the effects, on the spatiotemporal distribution of the bacteria, of both mean and variability of different elements of host response.     

A novel minimal model to describe NEFA kinetics following an intravenous glucose challenge

Dynamics of nonesterified fatty acid (NEFA) metabolism in humans requires quantification if we are to understand the etiology of such diseases as type 1 and 2 diabetes, as well as metabolic syndrome and obesity, or if we are to elucidate the mechanism of action of various interventions. We present a new compartmental model that employs the pattern of plasma glucose concentrations in healthy young adults to predict dynamic changes that occur in plasma NEFA concentrations during either a glucose-only intravenous glucose tolerance test, or an insulin-modified intravenous tolerance test, or a modified protocol during which variable-rate glucose infusions were administered to prevent plasma glucose from declining below 100 mg/dl. The model described all of the major features of NEFA response to an intravenous glucose tolerance test, including an initial latency phase, a phase during which plasma NEFA concentrations plummet to a nadir, and a rebound phase during which plasma NEFA concentrations may rise to a plateau concentration, which may be substantially higher than the initial basal NEFA concentration. This model is consistent with physiological processes and provides seven adjustable parameters that can be used to quantify NEFA production (lipolysis) and utilization (oxidation). When tested on data from the scientific literature, the range in estimated rate of lipolysis was 24-36 micromol.l(-1).min(-1) and for NEFA oxidation rate was 25-54 micromol.l(-1).min(-1). All model parameters were well identified and had coefficients of variation < 15% of their estimated values. It is concluded that this model is suitable to describe NEFA kinetics in human subjects.