Testing homogeneity in Weibull-regression models

In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.     

Modeling random effects for censored data by a multivariate normal regression model

A normal distribution regression model with a frailty-like factor to account for statistical dependence between the observed survival times is introduced. This model, as opposed to standard hazard-based frailty models, has survival times that, conditional on the shared random effect, have an accelerated failure time representation. The dependence properties of this model are discussed and maximum likelihood estimation of the model's parameters is considered. A number of examples are considered to illustrate the approach. The estimated degree of dependence is comparable to other models, but the present approach has the advantage that the interpretation of the random effect is simpler than in the frailty model.     

Mixture Hazard Models for Lifetime Data

We propose a general family of mixture hazard models to analyze lifetime data associated with bathtub and multimodal hazard functions. With this model we have a great flexibility for fitting lifetime data. Its version with covariates has the proportional hazard and the accelerated failure time models as special cases. A Bayesian analysis is presented for the model using informative priors, using sampling‐based approaches to perform the Bayesian computations. A real example with a medical data illustrates the methodology.     

Modulation of gramicidin A open channel lifetime by ion occupancy.

The hypothesis that the gramicidin A channel stability depends on the level of ion occupancy of the channel was used to derive a mathematical model relating channel lifetime to channel occupancy. Eyring barrier permeation models were examined for their ability to fit the zero-voltage conductance, current-voltage, as well as lifetime data. The simplest permeation model required to explain the major features of the experimental data consists of three barriers and four sites (3B4S) with a maximum of two ions occupying the channel. The average lifetime of the channel was calculated from the barrier model by assuming the closing rate constant to be proportional to the probability of the internal channel sites being empty. The link between permeation and lifetime has as its single parameter the experimentally determined averaged lifetime of gramicidin A channels in the limit of infinitely dilute solutions and has therefore no adjustable parameters. This simple assumption that one or more ions inside the channel completely stabilize the dimer conformation is successful in explaining the experimental data considering the fact that this model for stabilization is independent of ion species and configurational occupancy. The model is used to examine, by comparison with experimental data, the asymmetrical voltage dependence of the lifetime in asymmetrical solutions, the effects of blockers, and the effects of elevated osmotic pressure.     

Mixture and nonmixture cure fraction models assuming discrete lifetimes: Application to a pelvic sarcoma dataset

Different cure fraction models have been used in the analysis of lifetime data in presence of cured patients. This paper considers mixture and nonmixture models based on discrete Weibull distribution to model recurrent event data in presence of a cure fraction. The novelty of this study is the use of a discrete lifetime distribution in place of usual existing continuous lifetime distributions for lifetime data in presence of cured fraction, censored data, and covariates. In the verification of the fit of the proposed model it is proposed the use of randomized quantile residuals. An extensive simulation study is considered to evaluate the properties of the estimates of the parameters related to the proposed model. As an illustration of the proposed methodology, it is considered an application considering a medical dataset related to lifetimes in a retrospective cohort study conducted by Puchner et al. (2017) that consists of 147 consecutive cases with surgical treatment of a sarcoma of the pelvis between the years of 1980 and 2012.     

A Novel Approach for Identifying Causal Models of Complex Diseases from Family Data

Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal–normal, normal–disease, and disease–disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene–environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene–environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.     

Rapid Global Fitting of Large Fluorescence Lifetime Imaging Microscopy Datasets

Fluorescence lifetime imaging (FLIM) is widely applied to obtain quantitative information from fluorescence signals, particularly using Förster Resonant Energy Transfer (FRET) measurements to map, for example, protein-protein interactions. Extracting FRET efficiencies or population fractions typically entails fitting data to complex fluorescence decay models but such experiments are frequently photon constrained, particularly for live cell or in vivo imaging, and this leads to unacceptable errors when analysing data on a pixel-wise basis. Lifetimes and population fractions may, however, be more robustly extracted using global analysis to simultaneously fit the fluorescence decay data of all pixels in an image or dataset to a multi-exponential model under the assumption that the lifetime components are invariant across the image (dataset). This approach is often considered to be prohibitively slow and/or computationally expensive but we present here a computationally efficient global analysis algorithm for the analysis of time-correlated single photon counting (TCSPC) or time-gated FLIM data based on variable projection. It makes efficient use of both computer processor and memory resources, requiring less than a minute to analyse time series and multiwell plate datasets with hundreds of FLIM images on standard personal computers. This lifetime analysis takes account of repetitive excitation, including fluorescence photons excited by earlier pulses contributing to the fit, and is able to accommodate time-varying backgrounds and instrument response functions. We demonstrate that this global approach allows us to readily fit time-resolved fluorescence data to complex models including a four-exponential model of a FRET system, for which the FRET efficiencies of the two species of a bi-exponential donor are linked, and polarisation-resolved lifetime data, where a fluorescence intensity and bi-exponential anisotropy decay model is applied to the analysis of live cell homo-FRET data. A software package implementing this algorithm, FLIMfit, is available under an open source licence through the Open Microscopy Environment.     

Analysis of the anisotropy decay of trans-parinaric acid in lipid bilayers.

An analysis is presented of the complex anisotropy behavior of trans-parinaric acid in single component DEPC lipid bilayers. It is shown that a model involving two species with distinct lifetime and motional behavior is required, and is adequate, to explain the observed data. In particular, the observed increase in the anisotropy at long times demonstrates the presence of a species with a long fluorescence lifetime that has a high anisotropy. The time dependence of the anisotropy for these two environments is treated using both a purely mathematical sum of exponentials and a constrained fit based on an approximate solution of the anisotropic diffusion problem. In this latter model the anisotropy is described in terms of the second and fourth rank order parameters, (P2) and (P4), and a single dynamical parameter, D1, the perpendicular diffusion coefficient for this uniaxial probe. The parameters of both models are accurately determined from the fits to the data when two environments coexist and an association is made between lifetime components and distinct rotational sites. The values of the parameters obtained demonstrate the "solid-like" and "fluidlike" nature of these two coexisting environments.     

Fluorescence Lifetime Readouts of Troponin-C-Based Calcium FRET Sensors: A Quantitative Comparison of CFP and mTFP1 as Donor Fluorophores

We have compared the performance of two Troponin-C-based calcium FRET sensors using fluorescence lifetime read-outs. The first sensor, TN-L15, consists of a Troponin-C fragment inserted between CFP and Citrine while the second sensor, called mTFP-TnC-Cit, was realized by replacing CFP in TN-L15 with monomeric Teal Fluorescent Protein (mTFP1). Using cytosol preparations of transiently transfected mammalian cells, we have measured the fluorescence decay profiles of these sensors at controlled concentrations of calcium using time-correlated single photon counting. These data were fitted to discrete exponential decay models using global analysis to determine the FRET efficiency, fraction of donor molecules undergoing FRET and calcium affinity of these sensors. We have also studied the decay profiles of the donor fluorescent proteins alone and determined the sensitivity of the donor lifetime to temperature and emission wavelength. Live-cell fluorescence lifetime imaging (FLIM) of HEK293T cells expressing each of these sensors was also undertaken. We confirmed that donor fluorescence of mTFP-TnC-Cit fits well to a two-component decay model, while the TN-L15 lifetime data was best fitted to a constrained four-component model, which was supported by phasor analysis of the measured lifetime data. If the constrained global fitting is employed, the TN-L15 sensor can provide a larger dynamic range of lifetime readout than the mTFP-TnC-Cit sensor but the CFP donor is significantly more sensitive to changes in temperature and emission wavelength compared to mTFP and, while the mTFP-TnC-Cit solution phase data broadly agreed with measurements in live cells, this was not the case for the TN-L15 sensor. Our titration experiment also indicates that a similar precision in determination of calcium concentration can be achieved with both FRET biosensors when fitting a single exponential donor fluorescence decay model to the fluorescence decay profiles. We therefore suggest that mTFP-based probes are more suitable for FLIM experiments than CFP-based probes.     

A 3-Component Mixture of Rayleigh Distributions: Properties and Estimation in Bayesian Framework

To study lifetimes of certain engineering processes, a lifetime model which can accommodate the nature of such processes is desired. The mixture models of underlying lifetime distributions are intuitively more appropriate and appealing to model the heterogeneous nature of process as compared to simple models. This paper is about studying a 3-component mixture of the Rayleigh distributionsin Bayesian perspective. The censored sampling environment is considered due to its popularity in reliability theory and survival analysis. The expressions for the Bayes estimators and their posterior risks are derived under different scenarios. In case the case that no or little prior information is available, elicitation of hyperparameters is given. To examine, numerically, the performance of the Bayes estimators using non-informative and informative priors under different loss functions, we have simulated their statistical properties for different sample sizes and test termination times. In addition, to highlight the practical significance, an illustrative example based on a real-life engineering data is also given.     

Flexible maximum likelihood methods for bivariate proportional hazards models

This article presents methodology for multivariate proportional hazards (PH) regression models. The methods employ flexible piecewise constant or spline specifications for baseline hazard functions in either marginal or conditional PH models, along with assumptions about the association among lifetimes. Because the models are parametric, ordinary maximum likelihood can be applied; it is able to deal easily with such data features as interval censoring or sequentially observed lifetimes, unlike existing semiparametric methods. A bivariate Clayton model (1978, Biometrika 65, 141-151) is used to illustrate the approach taken. Because a parametric assumption about association is made, efficiency and robustness comparisons are made between estimation based on the bivariate Clayton model and "working independence" methods that specify only marginal distributions for each lifetime variable.     

A Nonrecursive Estimator for the Cox Model

The Cox regression model is one of the most widely used models to incorporate covariates. The frequently used partial likelihood estimator of the regression parameter has to be computed iteratively. In this paper we propose a noniterative estimator for the regression parameter and show that under certain conditions it dominates another noniterative estimator derived by Kalbfleish and Prentice. The new estimator is demonstrated on lifetime data of rats having been subject to insult with a carcinogen.     

Catch-bond model derived from allostery explains force-activated bacterial adhesion

High shear enhances the adhesion of Escherichia coli bacteria binding to mannose coated surfaces via the adhesin FimH, raising the question as to whether FimH forms catch bonds that are stronger under tensile mechanical force. Here, we study the length of time that E. coli pause on mannosylated surfaces and report a double exponential decay in the duration of the pauses. This double exponential decay is unlike previous single molecule or whole cell data for other catch bonds, and indicates the existence of two distinct conformational states. We present a mathematical model, derived from the common notion of chemical allostery, which describes the lifetime of a catch bond in which mechanical force regulates the transitions between two conformational states that have different unbinding rates. The model explains these characteristics of the data: a double exponential decay, an increase in both the likelihood and lifetime of the high-binding state with shear stress, and a biphasic effect of force on detachment rates. The model parameters estimated from the data are consistent with the force-induced structural changes shown earlier in FimH. This strongly suggests that FimH forms allosteric catch bonds. The model advances our understanding of both catch bonds and the role of allostery in regulating protein activity.     

On the use of multi-objective evolutionary algorithms for survival analysis

This paper proposes and evaluates a multi-objective evolutionary algorithm for survival analysis. One aim of survival analysis is the extraction of models from data that approximate lifetime/failure time distributions. These models can be used to estimate the time that an event takes to happen to an object. To use of multi-objective evolutionary algorithms for survival analysis has several advantages. They can cope with feature interactions, noisy data, and are capable of optimising several objectives. This is important, as model extraction is a multi-objective problem. It has at least two objectives, which are the extraction of accurate and simple models. Accurate models are required to achieve good predictions. Simple models are important to prevent overfitting, improve the transparency of the models, and to save computational resources. Although there is a plethora of evolutionary approaches to extract models for classification and regression, the presented approach is one of the first applied to survival analysis. The approach is evaluated on several artificial datasets and one medical dataset. It is shown that the approach is capable of producing accurate models, even for problems that violate some of the assumptions made by classical approaches.     

Status change during adulthood: life-history by-product or kin selection based on reproductive value?

When dominance status predicts fitness, most adaptive models of dominance relationships among cercopithecine primate females predict lifetime maintenance of status. These models and alternative ones positing rank decline as a non-adaptive by-product have remained largely untested, however, because lifetime status of older adults has been virtually unknown for natural populations. In a 25-year study of adult female savannah baboons (Papio cynocephalus), in each of three social groups, rank losses were common among the 66 females that lived past median adult age. These losses were not accounted for by loss in relative rank from group growth or by loss in absolute rank from reversals in rank between members of different maternal families or between sisters. Rather, females that had mature daughters experienced loss of dominance status to these offspring, a characteristic of all but the top-ranking matriline of each group. Among proposed hypotheses for rank reversals between adults, that of kin selection based on relative reproductive value is most clearly supported by these data. In contrast, observed patterns of rank loss are not consistent with alternative models that postulate that changes during adult lifespan are a product of accumulated risk, physical decline during ageing, or coalitionary support among females within or between matrilines.     

High-Throughput Exposure Assessment Tool (HEAT) for exposure-based prioritization of chemicals

Abstract

High-throughput methods are now routinely used to rapidly screen chemicals for potential hazard. However, hazard-based decision-making excludes important exposure considerations resulting in an incomplete estimation of chemical safety. Models to estimate exposure exist, but are generally unsuited to keep up with high-throughput demands. The High-Throughput Exposure Assessment Tool (HEAT) is designed to efficiently predict near-field exposure to consumers and workers via inhalation, oral and dermal routes. HEAT is based on well-known modeling algorithms and provides default model parameters to support reasonably conservative exposure estimates. Underlying chemical-specific data are uploaded or entered by the end user. HEAT’s main strength is the flexible tiered screening functionality, which enables exposure estimates for single or multiple chemicals simultaneously. Hypothetical case examples highlighting the application of HEAT to more complex exposure estimates for alternative and aggregate assessments are provided.     

Modeling Radiological Risks to Human Health from Contaminated Soils: Comparing MEPAS,MMSOILS, and RESRAD

Computer-based multimedia models are key analytical tools for assessing potential exposure to environmental contaminants as the U.S. Department of Energy remediates its sites at the nuclear weapons complex. This study applies MEPAS, MMSOILS, and RESRAD to actual release site data from the 903 Pad Source Area within Operating Unit 2 at the Rocky Flats Environmental Technology Site using a common set of assumptions. The analysis compares the similarity of multimedia model output in terms of (1) prediction of transport, (2) determination of an individual's lifetime exposure, and (3) estimation of radiological risks to human health from contaminated soils. This case study presents fairly routine exposure pathways and offers a good illustration of the way in which multimedia models can be used to assess potential radiological risk to human health from contaminated soils.