High dimensional mediation analysis with latent variables

We propose a model for high dimensional mediation analysis that includes latent variables. We describe our model in the context of an epidemiologic study for incident breast cancer with one exposure and a large number of biomarkers (i.e., potential mediators). We assume that the exposure directly influences a group of latent, or unmeasured, factors which are associated with both the outcome and a subset of the biomarkers. The biomarkers associated with the latent factors linking the exposure to the outcome are considered “mediators.” We derive the likelihood for this model and develop an expectation‐maximization algorithm to maximize an L1‐penalized version of this likelihood to limit the number of factors and associated biomarkers. We show that the resulting estimates are consistent and that the estimates of the nonzero parameters have an asymptotically normal distribution. In simulations, procedures based on this new model can have significantly higher power for detecting the mediating biomarkers compared with the simpler approaches. We apply our method to a study that evaluates the relationship between body mass index, 481 metabolic measurements, and estrogen‐receptor positive breast cancer.     

Local cryostimulation acutely preserves maximum isometric handgrip strength following fatigue in young women

Several types of cryostimulation have been recently proposed to rapidly lower skin temperature therefore gaining a possible neuro/muscular recovery after strenuous exercise or, more generally, in sports. Local cryostimulation may be a viable and relatively portable tool to obtain physiological benefits in previously-efforted muscular districts. However, cohesive and standardized cryo-exposure protocols are lacking as well as the righteous procedure to efficaciously combine duration, treatments and temperature in relation to desirable effects on muscular strength. In this randomized-controlled study, fifty young women were tested for maximum isometric handgrip strength, before and after exhausting contractions.Following the fatiguing protocol, the intervention group (cryo, n = 25, 24.7 ± 2.5 years, BMI 21.7 ± 1.8 kg/m²) underwent a 6-min local cryostimulation (−160 °C) on the extensor-flexor muscles of the dominant arm, while control-matched peers sat rested in a thermo-neutral room (22 ± 0.5 °C). Handgrip tests were repeated at baseline (T0), after cryostimulation (T1), and 15 min after T1 (T2). Throughout the protocol, the AUC of the strength performance was significantly higher in the cryo- compared to control group (P = 0.006). In particular, following fatigue and cryostimulation, the cryo group preserved higher strength at T1 with respect to controls (26.8 ± 2.8 vs 23.9 ± 2.8 kg, Bonferroni's post-hoc, P < 0.01). Likewise, ventral and dorsal temperature, recorded with a thermal camera, were lower in cryo- than control group (P < 0.0001).In conclusion, a brief session of local cryostimulation may acutely preserve maximal isometric force in young women following a fatiguing protocol. These findings may have implications in orchestrating strategies of district muscular recovery.     

Novel quinazolin-4-one derivatives as potentiating agents of doxorubicin cytotoxicity

We report the design, synthesis and biological evaluation of 17 novel 8-aryl-2-morpholino-3,4-dihydroquinazoline derivatives based on the standard model of DNA-PK and PI3K inhibitors. Novel compounds are sub-divided into two series where the second series of five derivatives was designed to have a better solubility profile over the first one. A combination of in vitro and in silico techniques suggested a plausible synergistic effect with doxorubicin of the most potent compound 14d on cell proliferation via DNA-PK and poly(ADP-ribose) polymerase-1 (PARP-1) inhibition, while alone having a negligible effect on cell proliferation.     

气候变化背景下基于MaxEnt模型的刺梨潜在适生区分布预测

为阐明气候变化背景下刺梨(Rosa roxburghii)在中国的潜在适生区分布,该研究基于刺梨的自然分布数据及当代(1960～1990)、未来(21世纪50年代及70年代)气候因子数据,采用最大熵(MaxEnt)模型模拟了当前和未来气候情景下刺梨在中国的潜在适生区,并确定影响其地理分布的主要气候因子.结果表明:(1)...     

Two‐sample nonparametric likelihood inference based on incomplete data with an application to a pneumonia study

The clinical pulmonary infection score (CPIS) and bronchoalveolar lavage (BAL) are important diagnostic variables of pneumonia for forcefully ventilated patients who are susceptible to nosocomial infection. Because of its invasive nature, BAL is performed for patients only if the CPIS is greater than a certain threshold value. Thus, CPIS and BAL are closely related, yet BAL values are substantially missing. In a randomized clinical trial, the control and oral treatment groups were compared based on the outcomes from these procedures. Because of the relevance of both outcomes with respect to evaluating the efficacy of treatments, we propose and examine a nonparametric test based on these outcomes, which employs the empirical likelihood methodology. While efficient parametric methods are available when data are observed incompletely, performing appropriate goodness‐of‐fit tests to justify the parametric assumptions is difficult. Our motivation is to provide an approach based on no particular distributional assumption, which enables us to use all observed bivariate data, whether completed or not in an approximate likelihood manner. A broad Monte Carlo study evaluates the asymptotic properties and efficiency of the proposed method based on various sample sizes and underlying distributions. The proposed technique is applied to a data set from a pneumonia study demonstrating its practical worth.     

Modeling continuous auxiliary covariate data in generalized linear mixed models using the kernel smoother

Auxiliary covariate data are often collected in biomedical studies when the primary exposure variable is only assessed on a subset of the study subjects. In this study, we investigate a semiparametric‐estimated likelihood estimation for the generalized linear mixed models (GLMM) in the presence of a continuous auxiliary variable. We use a kernel smoother to handle continuous auxiliary data. The method can be used to deal with missing or mismeasured covariate data problems in a variety of applications when an auxiliary variable is available and cluster sizes are not too small. Simulation study results show that the proposed method performs better than that which ignores the random effects in GLMM and that which only uses data in the validation data set. We illustrate the proposed method with a real data set from a recent environmental epidemiology study on the maternal serum 1,1‐dichloro‐2,2‐bis(p‐chlorophenyl) ethylene level in relationship to preterm births.     

Heat stress adaptation of Escherichia coli under dynamic conditions: effect of inoculum size*

Aims: When subjected to dynamic temperatures surpassing the expected maximum growth temperature, Escherichia coli K12 MG1655 shows disturbed growth curves. These irregular population dynamics were explained by considering two subpopulations, i.e. a thermoresistant and a thermosensitive one ( Van Derlinden et al. 2010a ). In this paper, the influence of the initial cell concentration on the subpopulations’ dynamics is evaluated. Methods and Results: Experiments were performed in a bioreactor with the temperature increasing from 42 to 65·2°C (1 and 4°C h^?1) with varying initial cell concentrations [6, 12 and 18 ln(CFU ml^?1)]. When started from the highest cell concentration, the population was characterized by a higher overall maximum growth temperature and a higher inactivation temperature. For all experimental set‐ups, resistant cells were still growing at the final temperature of 65·2°C. Conclusions: The initial cell concentration had no effect on temperature resistance. The increase in temperature resistance of the sensitive subpopulation was because of the change of the physiological state to the stationary phase. Significance and Impact of the Study: A higher initial cell concentration leads to higher heat stress adaptation when cultures reach a maximum cell concentration. The observed growth at a temperature of 65·2°C is very important for food safety and the temperature treatment of micro‐organisms.