Bayesian survival analysis using a MARS model

A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is described to obtain the estimate of the hazard function as well as the survival curve.     

Effect of exhausting stretch-shortening cycle exercise on the time course of mechanical behaviour in the drop jump: possible role of muscle damage

The purpose of the present study was to investigate the effect of stretch-shortening-cycle-induced muscle damage on the time course of mechanical behaviour in the drop jump. Ten healthy male subjects performed submaximal stretch-shortening cycle (SSC) exercise on a special sledge apparatus. Exhaustion occurred on average within 3 min. A drop jump (DJ) test from a 50-cm height was performed before and immediately after the sledge exercise as well as 2 h, 2 days and 4 days later. The fatigue exercise showed relatively high blood lactate concentration [12.5 (SD 2.6) mmol x l(-1)] and an increase of serum creatine kinase (CK) activity delayed by 2 days [540 (SD 407) U x l(-1)]. The initial decline in the jump performance (before - immediately after) was related negatively to the early recovery in performance (immediately after 2 h) (P < 0.05). The early recovery of the knee joint moment at the end of stretch showed a negative correlation to the delayed decrease in DJ performance (2 h 2 days) (P < 0.01). Thus, the DJ performance showed an initial decline followed by an early recovery and a secondary decline. Both the initial decline and early recovery in the knee joint moment at the end of stretch were related to the corresponding initial (after 2 h) (P < 0.05) and secondary increases (2 h - 2 days) (P < 0.01) in CK. It is suggested that the early recovery as well as the initial decline in the knee joint function could depend on the degree of muscle damage. Delayed decrease in initial stiffness (2 h - 2 days) was negatively related to the corresponding changes in the knee joint angle at touch down in DJ (P < 0.001). These interactions would imply that the decrease in the stiffness regulation and the modulation of the prelanding motor control might be attributable to secondary muscle damage during 2 days after the SSC exercise. Therefore, it may be suggested that the changes in the DJ performance after the exhausting SSC exercise accompany the progress of muscle damage observed by the corresponding increase in serum CK concentration and the corresponding deterioration of stiffness regulation and motor control in DJ.     

Statistical inference and model selection for the 1861 Hagelloch measles epidemic

A stochastic epidemic model is proposed which incorporates heterogeneity in the spread of a disease through a population. In particular, three factors are considered: the spatial location of an individual's home and the household and school class to which the individual belongs. The model is applied to an extremely informative measles data set and the model is compared with nested models, which incorporate some, but not all, of the aforementioned factors. A reversible jump Markov chain Monte Carlo algorithm is then introduced which assists in selecting the most appropriate model to fit the data.     

蹲跳、反向跳和下落跳的膝关节屈伸肌群肌电信号分析

目的：通过观察肌电图（EMG）的变化,了解运动员与普通中学生在纵跳过程中,膝关节屈伸肌群工作特点,为运动员科学选材提供依据。方法：30名男女青少年运动员和30名男女普通中学生进行各种形式纵跳（蹲跳、反向跳、下落跳）,测试膝关节屈伸肌群的EMG变化情况。结果：主动肌（股外肌）EMG的变化存在性别差异,随着下肢工作强度的增加,男运动员积分肌电图（iEMG)和平均功率频率（Fmean)均没有显著变化,女运动员iEMG增加,Fmean没有显著变化,对抗肌（股二头肌）,随着下肢工作强度的增加。青少年运动员EMG活动变化较小,而普通中学生的EMG活动明显增加。结论：在增加工作负荷的过程中,男运动员膝关节伸肌群以提高效率为主,女运动员以提高肌肉的募集数量为主;运动员的对抗肌协调水平高于普通中学生。     

Experimental tests of villin subdomain folding simulations

We have used laser temperature-jump to investigate the kinetics and mechanism of folding the 35 residue subdomain of the villin headpiece. The relaxation kinetics are biphasic with a sub-microsecond phase corresponding to a helix-coil transition and a slower microsecond phase corresponding to overall unfolding/refolding. At 300 K, the folding time is 4.3(+/-0.6) micros, making it the fastest folding, naturally occurring protein, with a rate close to the theoretical speed limit. This time is in remarkable agreement with the prediction of 5 (+11,-3) micros by Zagrovic et al. from atomistic molecular dynamics simulations using an implicit solvent model. We test their prediction that replacement of the C-terminal phenylalanine residue with alanine will increase the folding rate by removing a transient non-native interaction. We find that the alanine substitution has no effect on the folding rate or on the equilibrium constant. Implications of this result for the validity of the simulated folding mechanism are discussed.     

Bayesian meta-analysis for longitudinal data models using multivariate mixture priors

We propose a class of longitudinal data models with random effects that generalizes currently used models in two important ways. First, the random-effects model is a flexible mixture of multivariate normals, accommodating population heterogeneity, outliers, and nonlinearity in the regression on subject-specific covariates. Second, the model includes a hierarchical extension to allow for meta-analysis over related studies. The random-effects distributions are decomposed into one part that is common across all related studies (common measure), and one part that is specific to each study and that captures the variability intrinsic between patients within the same study. Both the common measure and the study-specific measures are parameterized as mixture-of-normals models. We carry out inference using reversible jump posterior simulation to allow a random number of terms in the mixtures. The sampler takes advantage of the small number of entertained models. The motivating application is the analysis of two studies carried out by the Cancer and Leukemia Group B (CALGB). In both studies, we record for each patient white blood cell counts (WBC) over time to characterize the toxic effects of treatment. The WBCs are modeled through a nonlinear hierarchical model that gathers the information from both studies.     

Catastrophe Bond and Risk Modeling: A Review and Calibration Using Chinese Earthquake Loss Data

Earthquake risks are attracting increased attention as a result of recent catastrophic events such as the Wenchuan earthquake in China. This article aims to select, tailor, and develop loss modeling methods for catastrophic insurance. We review the state-of-the-art approaches in modeling catastrophe losses for catastrophe bonds’ modeling and pricing. The methods are applied to the 1966–2008 losses resulted from the earthquakes in China. Various error measures are proposed for validating catastrophe modeling. Results suggest that the double exponential jump-diffusion model fits the data well.     

Tuning lambda6-85 towards downhill folding at its melting temperature

The five-helix bundle lambda6-85* is a fast two-state folder. Several stabilized mutants have been reported to fold kinetically near-downhill or downhill. These mutants undergo a transition to two-state folding kinetics when heated. It has been suggested that this transition is caused by increased hydrophobicity at higher temperature. Here we investigate two histidine-containing mutants of lambda6-85* to see if a weaker hydrophobic core can extend the temperature range of downhill folding. The very stable lambdaHA is the fastest-folding lambda repressor to date (k(f)(-1) approximately k(obs)(-1)=2.3 micros at 44 degrees C). It folds downhill at low temperature, but transits back to two-state folding at its unfolding midpoint. lambdaHG has a weakened hydrophobic core. It is less stable than some slower folding mutants of lambda6-85*, and it has more exposed hydrophobic surface area in the folded state. This mutant nonetheless folds very rapidly, and has the non-exponential folding kinetics of an incipient downhill folder even at the unfolding midpoint (k(m)(-1) approximately 2 micros, k(a)(-1)=15 micros at 56 degrees C). We also compare the thermodynamic melting transition of lambdaHG with the nominal two-state folding mutant lambdaQG, which has a similar melting temperature. Unlike lambdaQG, lambdaHG yields fluorescence wavelength-dependent cooperativities and probe-dependent melting temperatures. This result combined with previous work shows that the energy landscapes of lambda repressor mutants support all standard folding mechanisms.     

Bayesian inference for stochastic epidemic models with time-inhomogeneous removal rates

Stochastic compartmental models of the SEIR type are often used to make inferences on epidemic processes from partially observed data in which only removal times are available. For many epidemics, the assumption of constant removal rates is not plausible. We develop methods for models in which these rates are a time-dependent step function. A reversible jump MCMC algorithm is described that permits Bayesian inferences to be made on model parameters, particularly those associated with the step function. The method is applied to two datasets on outbreaks of smallpox and a respiratory disease. The analyses highlight the importance of allowing for time dependence by contrasting the predictive distributions for the removal times and comparing them with the observed data.      

Calculating spatial statistics for velocity jump processes with experimentally observed reorientation parameters

Mathematical modelling of the directed movement of animals, microorganisms and cells is of great relevance in the fields of biology and medicine. Simple diffusive models of movement assume a random walk in the position, while more realistic models include the direction of movement by assuming a random walk in the velocity. These velocity jump processes, although more realistic, are much harder to analyse and an equation that describes the underlying spatial distribution only exists in one dimension. In this communication we set up a realistic reorientation model in two dimensions, where the mean turning angle is dependent on the previous direction of movement and bias is implicitly introduced in the probability distribution for the direction of movement. This model, and the associated reorientation parameters, is based on data from experiments on swimming microorganisms. Assuming a transport equation to describe the motion of a population of random walkers using a velocity jump process, together with this realistic reorientation model, we use a moment closure method to derive and solve a system of equations for the spatial statistics. These asymptotic equations are a very good match to simulated random walks for realistic parameter values.