A human liver microphysiology platform for investigating physiology,drug safety,and disease models

This paper describes the development and characterization of a microphysiology platform for drug safety and efficacy in liver models of disease that includes a human, 3D, microfluidic, four-cell, sequentially layered, self-assembly liver model (SQL-SAL); fluorescent protein biosensors for mechanistic readouts; as well as a microphysiology system database (MPS-Db) to manage, analyze, and model data. The goal of our approach is to create the simplest design in terms of cells, matrix materials, and microfluidic device parameters that will support a physiologically relevant liver model that is robust and reproducible for at least 28 days for stand-alone liver studies and microfluidic integration with other organs-on-chips. The current SQL-SAL uses primary human hepatocytes along with human endothelial (EA.hy926), immune (U937) and stellate (LX-2) cells in physiological ratios and is viable for at least 28 days under continuous flow. Approximately, 20% of primary hepatocytes and/or stellate cells contain fluorescent protein biosensors (called sentinel cells) to measure apoptosis, reactive oxygen species (ROS) and/or cell location by high content analysis (HCA). In addition, drugs, drug metabolites, albumin, urea and lactate dehydrogenase (LDH) are monitored in the efflux media. Exposure to 180 μM troglitazone or 210 μM nimesulide produced acute toxicity within 2–4 days, whereas 28 μM troglitazone produced a gradual and much delayed toxic response over 21 days, concordant with known mechanisms of toxicity, while 600 µM caffeine had no effect. Immune-mediated toxicity was demonstrated with trovafloxacin with lipopolysaccharide (LPS), but not levofloxacin with LPS. The SQL-SAL exhibited early fibrotic activation in response to 30 nM methotrexate, indicated by increased stellate cell migration, expression of alpha-smooth muscle actin and collagen, type 1, alpha 2. Data collected from the in vitro model can be integrated into a database with access to related chemical, bioactivity, preclinical and clinical information uploaded from external databases for constructing predictive models.     

A probabilistic framework for microarray data analysis: Fundamental probability models and statistical inference

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.     

A statistical human rib cage geometry model accounting for variations by age,sex, stature and body mass index

In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject?s ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks.     

Some statistical properties of differencing schemes for baseline correction of sedimentation velocity data

For the detailed analysis of sedimentation velocity data, the consideration of radial-dependent baseline offsets is indispensable. Two main approaches are data differencing (“delta-c” approach) and explicit inclusion of baseline parameters in the model (“direct boundary model” of the raw data). The current work aims to clarify the relationships between the two approaches. To this end, a simple model problem is examined. We show that the explicit consideration of the baseline in the model is equivalent to a differencing scheme where the average value is subtracted from all data points. Pairwise differencing in the delta-c approach always results in higher parameter uncertainty. For equidistant time points, the increase is smallest when the reference points are taken at intervals of 1/3 or 2/3 of the total number of time points. If the difference data are misinterpreted to be statistically independent samples, errors in the calculation of the parameter uncertainties can occur. Contrary to claims in the literature, we observe that there is no distinction in the approaches regarding their “model dependence”; both approaches arise from the integral or differential form of the same model, and both approaches can and should provide explicit estimates of the baseline values in the original data space for optimal discrimination between macromolecular sedimentation models.     

Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models

Estimating the risk of osteoporotic fractures is an important diagnostic step that needs to be taken before medicinal treatment. Densitometry-based criteria are normally used in clinical practice for this purpose. However, densitometry-based techniques could not explain all low-energy fractures. As patient-specific finite element (FE) models allow for consideration of other parameters (e.g. load conditions) that are known to be associated with fracture, they are considered promising candidates for more accurate fracture risk estimation. Nevertheless, they are often time consuming, expensive, and complex to build and may need the type of expertise that is not normally available in clinical settings. In this study, we report the development of an automated platform for estimating proximal femur fracture loads using patient-specific 2D FE models generated using dual-energy x-ray absorptiometry (DXA) scans. First, a statistical shape and appearance model (SSAM) is built using DXA scans of patients screened for osteoporosis following a low energy fracture. SSAM is then used together with Active Appearance Models (AAM) for automated segmentation of the proximal femur from new unseen DXA scans. The mean point-to-curve error of the automated procedure, i.e. 1.2–1.4 mm, is shown to be only slightly larger than the intra-observer variability of manual segmentation, i.e. 1.0 mm. Moreover, the developed platform automatically meshes the segmented shape, assigns density-based mechanical properties, assigns loads and boundary conditions, submits the 2D FE model for solution, and performs post-processing of the 2D FE simulation data to determine fracture loads. The fracture loads predicted using the manually generated and automatically generated 2D FE models are shown to be very close with a mean difference of around 8.8%. Repeated measures ANOVA showed no significant differences between the fracture loads calculated using FE models manually generated by three independent observers and those calculated using the automatically generated FE models (p>0.05).     

New statistical tools for analyzing the structure of animal groups

The statistical characterization of the spatial structure of large animal groups has been very limited so far, mainly due to a lack of empirical data, especially in three dimensions (3D). Here we focus on the case of large flocks of starlings (Sturnus vulgaris) in the field. We reconstruct the 3D positions of individual birds within flocks of up to few thousands of elements. In this respect our data constitute a unique set. We perform a statistical analysis of flocks' structure by using two quantities that are new to the field of collective animal behaviour, namely the conditional density and the pair correlation function. These tools were originally developed in the context of condensed matter theory. We explain what is the meaning of these two quantities, how to measure them in a reliable way, and why they are useful in assessing the density fluctuations and the statistical correlations across the group. We show that the border-to-centre density gradient displayed by starling flocks gives rise to an anomalous behaviour of the conditional density. We also find that the pair correlation function has a structure incompatible with a crystalline arrangement of birds. In fact, our results suggest that flocks are somewhat intermediate between the liquid and the gas phase of physical systems.     

On the solution of mathematical models of herd immunity in human helminth infections

The general solution of the mathematical model of herd immunity to human helminth infections recently proposed by Anderson and May [3] is obtained. The numerical solution of a more accurate biological model is indistinguishable from the corresponding exact solution of a more tractable mathematical model. Computer simulations of some particular cases of this model support the notion that both ecological and immunological factors determine the observed convex patterns of age-prevalence and age-intensity curves of human helminth infections.This work was made thanks to the advise and support of Dr. Robert M. May while the author was Postdoctoral Fellow at Princeton University     

A unification of models for meta-analysis of diagnostic accuracy studies

Studies of diagnostic accuracy require more sophisticated methods for their meta-analysis than studies of therapeutic interventions. A number of different, and apparently divergent, methods for meta-analysis of diagnostic studies have been proposed, including two alternative approaches that are statistically rigorous and allow for between-study variability: the hierarchical summary receiver operating characteristic (ROC) model (Rutter and Gatsonis, 2001) and bivariate random-effects meta-analysis (van Houwelingen and others, 1993), (van Houwelingen and others, 2002), (Reitsma and others, 2005). We show that these two models are very closely related, and define the circumstances in which they are identical. We discuss the different forms of summary model output suggested by the two approaches, including summary ROC curves, summary points, confidence regions, and prediction regions.     

Testing goodness of fit for stochastic models of carcinogenesis.

This paper considers the utility of statistical goodness of fit testing in the context of mechanistic models of carcinogenesis. Two stochastic models of carcinogenesis were tested with several sets of experimental and epidemiological data using a formal goodness of fit test specially designed to accommodate censored observations: these were the two-stage model allowing for clonal expansion of initiated cells and its simpler version with gamma distributed promotion time. The results of this application, supplemented by visual examination of local likelihood kernel estimates of the hazard function and the corresponding model-based estimates, show that mechanistic models of carcinogenesis provide a good fit to the data in the majority of cases under study.     

Phosphoglucose isomerase variability of Cerastoderma glaucum as a model for testing the influence of environmental conditions and dispersal patterns through quantitative ecology approaches

Extreme conditions of coastal lagoons could directly modify the genetic patterns of species. The aim of this work was to investigate the influence of environmental conditions and small scale dispersal patterns on the phosphoglucose isomerase (PGI*) genetic variability of Cerastoderma glaucum from the Mar Menor coastal lagoon. For this purpose, 284 cockles were collected around the perimeter of the lagoon. Vertical polyacrylamide gel electrophoresis was used to scan for PGI* polymorphisms, giving a total of seven alleles. The spatial genetic distribution of the PGI* variability, which seems to be marked by the main circulation in the lagoon, discriminates four hydrological basins. In the central basin, a gradient of allelic composition reflects the circulation forced by the dominant winds and the main channel communicated to the open sea. This result is well supported by the salinity GAM model that defines this gradient.The other three basins are defined by the distribution of fine sand in a more complex model that tries to explain the isolation of the three sites localized inside these basins. The southern, western and northern basins show the lowest degree of interconnection and are considered the most confined areas of the Mar Menor lagoon. This situation agrees with the confinement theory for benthic assemblages in the lagoon. The greater degree of differentiation seen in the Isla del Ciervo population is probably due to recent human intervention on the nearby Marchamalo channel, which has been drained in recent years thus altering the influence of the Mediterranean Sea on the southern basin.     

A multiple reaction monitoring method for absolute quantification of the human liver alcohol dehydrogenase ADH1C1 isoenzyme

Although significant progress has been made in protein quantification using mass spectrometry during recent years, absolute protein quantification in complex biological systems remains a challenging task in proteomics. The use of stable isotope-labeled standard peptide is the most commonly used strategy for absolute quantification, but it might not be suitable in all instances. Here we report an alternative strategy that employs a stable isotope-labeled intact protein as an internal standard to absolutely quantify the alcohol dehydrogenase (ADH) expression level in a human liver sample. In combination with a new targeted proteomics approach employing the method of multiple reaction monitoring (MRM), we precisely and quantitatively measured the absolute protein expression level of an ADH isoenzyme, ADH1C1, in human liver. Isotope-labeled protein standards are predicted to be particularly useful for measurement of highly homologous isoenzymes such as ADHs where multiple signature peptides can be examined by MRM in a single experiment.     

鞭角华扁叶蜂虫卵数模型研究

该研究在野外获得了鞭角华扁叶蜂虫卵数与生境因子海拔、胸径、树高、海拔、冠幅坡向的数据;内业利用Matlab7软件分别建立了鞭角华扁叶蜂虫卵数的全变量模型、逐步回归模型和主成分模型,三模型的复相关系数R~2分别为0.9204,0.91841和0.9289,均方误差RMSE分别为322.4069,331.7300和310.9550,从两个系数看,得出一致结论以主成分法拟合最佳.逐步回归模型只采用了两个因子即树高和冠幅,主成分法采用了前三个主成分量,其信息量达93.6359%,可代表原特征变量的大部分信息.     

Heterogeneity of muscle activation in relation to force direction: A multi-channel surface electromyography study on the triceps surae muscle

Several skeletal muscles can be divided into sub-modules, called neuromuscular compartments (NMCs), which are thought to be controlled independently and to have distinct biomechanical functions. We looked for distinct muscle activation patterns in the triceps surae muscle (TS) using surface electromyography (EMG) during voluntary contraction. Nine subjects performed isometric and isotonic plantar flexions combined with forces along pre-defined directions. Besides the forces under the ball of the foot, multi-channel surface EMG was measured with electrodes homogeneously distributed over the entire TS. Using principal component analysis, common (global) components were omitted from the EMG signals, thereby estimating muscle activity sufficiently accurate to track fine fluctuations of force during an isotonic contraction (r = 0.80 ± 0.09). A subsequent cluster analysis showed a topographical organization of co-activated parts of the muscle that was different between subjects. Low and negative correlations between the EMG activity within clusters were found, indicating a substantial heterogeneity of TS activation. The correlations between cluster time series and forces at the foot in specific directions differed substantially between clusters, showing that the differentially activated parts of the TS had specific biomechanical functions.     

Comparison of electrophysiological models for human ventricular cells and tissues

In this paper we briefly review currently published models for human ventricular cells and tissues. We discuss the Priebe–Beuckelmann (PB) model and the reduced version of this model constructed by Bernus et al. (redPB), the Ten Tusscher–Noble–Noble–Panfilov (TNNP) model and the Iyer–Mazhari–Winslow (IMW) model. We compare several characteristics of these models such as: sources of experimental data the models are based on, action potential morphology, action potential duration (APD) and conduction velocity (CV) restitution and computational efficiency. Finally, we discuss the application of a subset of these models—the redPB and the TNNP model—to study simulated spiral wave dynamics in 2D tissue sheets and in the human ventricles. We discuss the suitability of the different models for particular research questions and their limitations.     

超声在评价大鼠酒精性脂肪肝模型中的应用

目的利用超声技术来评价大鼠酒精性脂肪肝动物模型。方法选取40只SD大鼠随机分为两组（n=20只）。模型组按每周测定的体重早晚各1次乙醇灌胃（10 g/kg）,第1周浓度为40%,第2、3周分别为45%和50%,第4周为55%灌胃直至12周;对照组给予等体积的生理盐水灌胃。造模于第4、8和12周时对两组大鼠进行超声监测,并从两组中各随机抽取3只大鼠进行肝脏病理学分析,与超声监测结果进行对比分析。结果超声与病理检查结果均提示酒精性脂肪肝造模成功,超声可以监测模型组大鼠肝脏脂肪病变从轻到重的渐变过程以及对照组大鼠无脂肪病变过程。这与肝组织的病理学诊断结果具有一致性。结论超声检测技术可以较好地进行活体评价大鼠酒精性脂肪肝动物模型。     

一种评价脑循环动力学综合功能的新方法

目的通过对与脑循环功能相关的12个血液动力学参数进行分析,得出能够反映脑循环总体功能的一个综合指标。方法采用病例对照方法,获得120例脑血管疾病患者和130例正常者对照的流行病学资料,年龄在20岁至70岁。综合应用主成分分析、logistic回归分析等方法得到四种综合指标计算模型,并将这四种模型在临床上通过ROC曲线进行初步检验评价。结果在对原始计算数据250例人群的检验中,四个综合指标的ROC曲线下面积分别为0．905、0．901、0．942、0．911。在临床上对另外的年龄为20岁至70岁的775例人群的检验中,四个综合指标的ROC曲线下面积分别为0．943、0．940、0．969和0．945;在对年龄为50岁至60岁的144例人群的检验中,四个综合指标的ROC曲线下面积分别为0．866、0．862、0．935和0．847。讨论对12个参数进行主成分回归后选取前三个主成分进行logistic回归分析后得到的评价模型作为反应脑循环总体功能的综合指标具有较佳的评价能力与更好的稳定性。