太湖区域环境中基于PBPK模型的DDTs和HCHs混合健康风险

针对太湖区域环境中DDTs和HCHs混合暴露的健康危害,基于对居民DDTs及HCHs不同途径暴露量的分析,通过建立DDTs及HCHs的PBPK模型,分析其在人体内的累积分布过程,并应用内效应综合危害指数评价其混合暴露的健康风险。结果表明,居民健康风险度分别为0.147～2.499（男性）和0.138～2.223（女性）,超过可接受风险的概率分别为24.6%（男性）和16.5%（女性）。相较于传统的混合健康风险评价方法（HI法）,基于PBPK模型的内效应综合危害指数法（HI_tissue-dose）更能反映混合健康风险的发展趋势。     

Combining cell culture analogue reactor designs and PBPK models to probe mechanisms of naphthalene toxicity

An alternative method of evaluating the toxicology of a chemical is to use cultured mammalian cells in a novel cell culture analogue reactor (CCA) together with a corresponding physiologically based pharmacokinetic model (PBPK). The PBPK is a mathematical model that divides the body into compartments representing organs, integrating the kinetic, thermodynamic, and anatomical parameters of the animal. The bioreactor is a physical replica of the PBPK; where the PBPK specifies an organ or tissue compartment, the bioreactor contains compartments with a corresponding cell type. The device is a continuous, dynamic system composed of multiple cell types that interact through a common circulating cell culture medium. The bioreactor and the model are coupled to evaluate the plausibility of the molecular mechanism that is input into the model. This concept is tested with naphthalene as a model of PAH (polycyclic aromatic hydrocarbons) toxicants. Two physically different CCA reactors were tested with naphthalene, and different results were observed. In the prototype system using cells attached to glass dilution bottles, naphthalene dosing resulted in generation of a circulating metabolite from the "liver" compartment (based on H4IIE cells from a rat hepatoma) that caused cell death in the "lung" compartment (L2 cells from a rat lung), as well as depletion of glutathione in the L2 cells. An improved CCA using packed bed reactors of microcarrier cultured cells did not show differences between naphthalene-dosed and nondosed controls. To explain the different responses of the two CCA designs, PBPKs of the two reactors were tested with variations in physical and kinetic parameters, and toxic mechanism. When the toxic metabolite of naphthalene was naphthoquinone rather than naphthalene epoxide as initially assumed, the PBPK results were consistent with the results of the two CCA designs. This result indicates that the mechanism of naphthalene toxicity in the CCAs may be mediated through naphthoquinone formation. The CCA-PBPK concept is demonstrated to be applicable to the study of toxic mechanisms. In particular, use of this approach suggests that in vitro naphthalene toxicity is mediated through the naphthoquinone metabolite.     

Role of endothelins in animal models of hypertension: focus on cardiovascular protection

Investigation of the regulation of vascular function by endothelium-derived factors has been a prominent topic of research in the field of hypertension during the last decade. Of the different endothelial factors, endothelins, which play an important role in vasodilatation-vasoconstriction balance, have been the subject of great interest and an impressive number of publications. This peptide, a very potent vasoconstrictor, triggers as well events involved in growth, proliferation, matrix production and local inflammation. In parallel, its role in hypertension has evolved from a simple vasoconstrictor to a central local regulator of vascular homeostasis contributing not only to the elevation of blood pressure, but also to the complications of hypertension. This review summarizes research on endothelins and its receptor antagonists in experimental hypertension, with special emphasis on vascular remodeling and target-organ protection.     

Cartilage-specific autoimmunity in animal models and clinical aspects in patients - focus on relapsing polychondritis

Relapsing polychondritis is an autoimmune disease in which an inappropriate immune response destroys cartilage. Cartilage of the ears, larynx and nose rather than spine and joint cartilage is affected by a chronic relapsing and erosive inflammation. Several animal models for relapsing polychondritis have been published in which immunization with various cartilage proteins induces a variety of chondritis symptoms that mimic those seen in patients. In this review we describe the collagens, matrilin-1 and cartilage oligomeric matrix protein as potential autoantigens able to trigger the tissue-specific immune response seen both in patients and in animal models for relapsing polychondritis and related autoimmune diseases.     

Structure-based kinetic models of modular signaling protein function: focus on Shp2

We present here a computational, rule-based model to study the function of the SH2 domain-containing protein tyrosine phosphatase, Shp2, in intracellular signal transduction. The two SH2 domains of Shp2 differentially regulate the enzymatic activity by a well-characterized mechanism, but they also affect the targeting of Shp2 to signaling receptors in cells. Our kinetic model integrates these potentially competing effects by considering the intra- and intermolecular interactions of the Shp2 SH2 domains and catalytic site as well as the effect of Shp2 phosphorylation. Even for the isolated Shp2/receptor system, which may seem simple by certain standards, we find that the network of possible binding and phosphorylation states is composed of over 1000 members. To our knowledge, this is the first kinetic model to fully consider the modular, multifunctional structure of a signaling protein, and the computational approach should be generally applicable to other complex intermolecular interactions.     

Synaptic microcircuit dysfunction in genetic models of neurodevelopmental disorders: focus on Mecp2 and Met

Recent findings in the genetics of neurodevelopmental syndromes have ushered in an exciting era of discovery in which substrates of neurologic dysfunction are being identified at the synaptic and microcircuit levels in mouse models of these disorders. We review recent progress in this area, focusing on two examples of mouse models of autism spectrum disorders (ASDs): Mecp2 models of Rett syndrome, and a Met-knockout model of non-syndromic forms of autism. In both cases, a dominant theme is changes in synaptic strength, associated with hyper-connectivity or hypo-connectivity in specific microcircuits. Alterations in intrinsic neuronal excitability are also found, but do not appear to be as common. The microcircuit-specific nature of synaptic changes observed in these ASD models indicates that it will be necessary to define mechanisms of circuit dysfunction on a case-by-case basis, not only in neocortex but also in brainstem and other sub-cortical areas. Thus, functional microcircuit analysis is emerging as an important line of investigation, highly complementary to neurogenetic and molecular strategies, and holds promise for generating models of the underlying pathophysiology and for guiding development of novel therapeutic strategies.     

A Delayed Nonlinear PBPK Model for Genistein Dosimetry in Rats

Genistein is an endocrine-active compound (EAC) found in soy products. It has been linked to beneficial effects such as mammary tumor growth suppression and adverse endocrine-related effects such as reduced birth weight in rats and humans. In its conjugated form, genistein is excreted in the bile, which is a significant factor in its pharmacokinetics. Experimental data suggest that genistein induces a concentration-dependent suppression of biliary excretion. In this article, we describe a physiologically based pharmacokinetic (PBPK) model that focuses on biliary excretion with the goal of accurately simulating the observed suppression. The mathematical model is a system of nonlinear differential equations with state-dependent delay to describe biliary excretion. The model was analyzed to examine local existence and uniqueness of a solution to the equations. Furthermore, unknown parameters were estimated, and the mathematical model was compared against published experimental data. This research was supported by the American Chemistry Council (formerly the Chemical Manufacturers Association, CMA Agreement Reference Number 9121).     

The performance of risk prediction models

For medical decision making and patient information, predictions of future status variables play an important role. Risk prediction models can be derived with many different statistical approaches. To compare them, measures of predictive performance are derived from ROC methodology and from probability forecasting theory. These tools can be applied to assess single markers, multivariable regression models and complex model selection algorithms. This article provides a systematic review of the modern way of assessing risk prediction models. Particular attention is put on proper benchmarks and resampling techniques that are important for the interpretation of measured performance. All methods are illustrated with data from a clinical study in head and neck cancer patients.     

Accuracy of rate estimation using relaxed-clock models with a critical focus on the early metazoan radiation

In recent years, a number of phylogenetic methods have been developed for estimating molecular rates and divergence dates under models that relax the molecular clock constraint by allowing rate change throughout the tree. These methods are being used with increasing frequency, but there have been few studies into their accuracy. We tested the accuracy of several relaxed-clock methods (penalized likelihood and Bayesian inference using various models of rate change) using nucleotide sequences simulated on a nine-taxon tree. When the sequences evolved with a constant rate, the methods were able to infer rates accurately, but estimates were more precise when a molecular clock was assumed. When the sequences evolved under a model of auto-correlated rate change, rates were accurately estimated using penalized likelihood and by Bayesian inference using lognormal and exponential models of rate change, while other models did not perform as well. When the sequences evolved under a model of uncorrelated rate change, only Bayesian inference using an exponential rate model performed well. Collectively, the results provide a strong recommendation for using the exponential model of rate change if a conservative approach to divergence time estimation is required. A case study is presented in which we use a simulation-based approach to examine the hypothesis of elevated rates in the Cambrian period, and it is found that these high rate estimates might be an artifact of the rate estimation method. If this bias is present, then the ages of metazoan divergences would be systematically underestimated. The results of this study have implications for studies of molecular rates and divergence dates.     

Use of niche models in invasive species risk assessments

Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species’ invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.     

Estimation of distribution function in bivariate competing risk models

We consider lifetime data involving pairs of study individuals with more than one possible cause of failure for each individual. Non-parametric estimation of cause-specific distribution functions is considered under independent censoring. Properties of the estimators are discussed and an illustration of their application is given.     

Using deterministic models to assess risk in sediment-impacted estuaries

Terrestrial sediments transported off disturbed watersheds can threaten downstream estuarine and coastal environments. Practitioners in the field of environmental management need to be able to assess how activities that disturb the land are likely to impact on downstream estuarine and coastal receiving waters. Such assessments usually take the form of estimating risk, which has two components: the extent of undesirable consequences and the probability of occurrence of those consequences. The consequence in this case is primarily the ecological damage. In order to estimate risk, a methodology was developed around the use of a deterministic computational model of watershed/estuarine sediment transport. Model simulations are run which cover the physically realistic range of the controlling variables (e.g., wind speed, wind direction, sediment runoff). The model results are related to estuary damage and combined with the probability of occurrence for each scenario, providing a means of quantifying risk. In addition, answers to `long-term average', `most likely' and `worse case' type questions can be made. The procedure has the advantages of being easily implemented, transparent and repeatable. It is also more efficient than a standard Monte-Carlo procedure. The risk associated with changes in landuse can be examined without repeating model simulations. The example used to illustrate the method is that of a developing watershed in which proposed building activities are expected to alter the sediment yield to the downstream estuary during floods, which in turn is expected to smother shellfish beds. By elucidating risk associated with each development scenario, the management debate can be focused on choice of an acceptable risk level.     

Performance of reclassification statistics in comparing risk prediction models

Concerns have been raised about the use of traditional measures of model fit in evaluating risk prediction models for clinical use, and reclassification tables have been suggested as an alternative means of assessing the clinical utility of a model. Several measures based on the table have been proposed, including the reclassification calibration (RC) statistic, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI), but the performance of these in practical settings has not been fully examined. We used simulations to estimate the type I error and power for these statistics in a number of scenarios, as well as the impact of the number and type of categories, when adding a new marker to an established or reference model. The type I error was found to be reasonable in most settings, and power was highest for the IDI, which was similar to the test of association. The relative power of the RC statistic, a test of calibration, and the NRI, a test of discrimination, varied depending on the model assumptions. These tools provide unique but complementary information.     

Quasi-likelihood estimation for relative risk regression models

For a prospective randomized clinical trial with two groups, the relative risk can be used as a measure of treatment effect and is directly interpretable as the ratio of success probabilities in the new treatment group versus the placebo group. For a prospective study with many covariates and a binary outcome (success or failure), relative risk regression may be of interest. If we model the log of the success probability as a linear function of covariates, the regression coefficients are log-relative risks. However, using such a log-linear model with a Bernoulli likelihood can lead to convergence problems in the Newton-Raphson algorithm. This is likely to occur when the success probabilities are close to one. A constrained likelihood method proposed by Wacholder (1986, American Journal of Epidemiology 123, 174-184), also has convergence problems. We propose a quasi-likelihood method of moments technique in which we naively assume the Bernoulli outcome is Poisson, with the mean (success probability) following a log-linear model. We use the Poisson maximum likelihood equations to estimate the regression coefficients without constraints. Using method of moment ideas, one can show that the estimates using the Poisson likelihood will be consistent and asymptotically normal. We apply these methods to a double-blinded randomized trial in primary biliary cirrhosis of the liver (Markus et al., 1989, New England Journal of Medicine 320, 1709-1713).     

Two criteria for evaluating risk prediction models

Summary We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q) , is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow‐up, PNF (p) , namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q % of the population at highest risk. PNF (p) assess the feasibility of covering 100p % of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.     

Cancer risk models and preselection for screening

Objective: The invitation to population screening is based on age criteria in many countries. Screening is not offered to younger or older participants, because the benefits in these age groups do not outweigh the harms. One could argue that it is not so much age that determines the benefits but the risk of developing preclinical and treatable cancer. Cancer risk varies with age but is also affected by other factors. Methods: We performed a systematic review for risk models for the three types of cancer for which population screening programs exist: breast, cervical and colon cancer. We used an evaluation scheme that distinguishes three phases of model development: model derivation, validation and impact analysis. Data were collected in August 2010. Results: We identified two colorectal, four breast and three cervix cancer risk models. One colorectal, four breast and none of the cervix cancer models have been externally validated. We could not identify evaluations of the impact on population screening effectiveness. Conclusion: We conclude that risk models for the pre-selection of screening have been developed. These models could improve the pre-selection for screening, help in making personal decisions about participation, and reduce adverse effects of population screening. The validity of this hypothesis, as well as practicalities and issues of equity and reliability, have to be tested in further studies.     

A focus on fixation

Three fixation issues related to immunostaining are discussed here: 1) Generally, a tissue block is fixed, then embedded and sectioned (pre-fixation). The type of fixative applied, crosslinking or coagulating, has an impact on selecting an epitope retrieval method. Individual antigens have a fixation-retrieval characteristic. 2) A long fixation time, especially with crosslinking fixatives, may compromise the result of immunostaining. This negative effect varies among different antigens and can be partially restored by applying a more sensitive/efficient detection system such as tyramide amplification. 3) Sections cut from a fresh frozen tissue block usually are acetone fixed (post-fixation). This was accepted as the “gold standard” for a long time. Post-fixation, however, may have serious consequences for preservation of small peptides leaking from the cut open cells, whereas this is not the case with pre-fixed intact cells. Consequently, the concept of an acetone post-fixed cryostat tissue section as “gold standard” no longer exists and a more appropriate use of the terms immunohistochemistry and immunocytochemistry therefore seems justified. For many antibodies, it is not known whether a formalin fixed, paraffin embedded tissue specimen is appropriate. Suggestions are made for creating a positive control cell block for testing such antibodies.