Suppressing Unwanted Autobiographical Memories Reduces Their Automatic Influences: Evidence from Electrophysiology and an Implicit Autobiographical Memory Test

The present study investigated the extent to which people can suppress unwanted autobiographical memories in a mock crime memory detection context. Participants encoded sensorimotor-rich memories by enacting a lab crime (stealing a ring) and received direct suppression instructions so as to evade guilt detection in a brainwave-based concealed information test. Aftereffects of suppression on automatic memory processes were measured in an autobiographical implicit association test (aIAT). Results showed that suppression attenuated brainwave activity (P300) that is associated with crime-relevant memory retrieval, rendering innocent and guilty/suppression participants indistinguishable. However, guilty/suppression and innocent participants could nevertheless be discriminated via the late posterior negative slow wave, which may reflect the need to monitor response conflict arising between voluntary suppression and automatic recognition processes. Lastly, extending recent findings that suppression can impair implicit memory processes; we provide novel evidence that suppression reduces automatic cognitive biases that are otherwise associated with actual autobiographical memories

Novel interface-selected waves and their influences on wave competitions

The topic of interface effects in wave propagation has attracted great attention due to their theoretical significance and practical importance. In this paper we study nonlinear oscillatory systems consisting of two media separated by an interface, and find a novel phenomenon: interface can select a type of waves (ISWs). Under certain well defined parameter condition, these waves propagate in two different media with same frequency and same wave number; the interface of two media is transparent to these waves. The frequency and wave number of these interface-selected waves (ISWs) are predicted explicitly. Varying parameters from this parameter set, the wave numbers of two domains become different, and the difference increases from zero continuously as the distance between the given parameters and this parameter set increases from zero. It is found that ISWs can play crucial roles in practical problems of wave competitions, e.g., ISWs can suppress spirals and antispirals

Metabolomic analysis of human oral cancer cells with adenylate kinase 2 or phosphorylate glycerol kinase 1 inhibition.

The purpose of this study was to use liquid chromatography-mass spectrometry (LC-MS) with XCMS for a quantitative metabolomic analysis of UM1 and UM2 oral cancer cells after knockdown of metabolic enzyme adenylate kinase 2 (AK2) or phosphorylate glycerol kinase 1 (PGK1). UM1 and UM2 cells were initially transfected with AK2 siRNA, PGK1 siRNA or scrambled control siRNA, and then analyzed with LC-MS for metabolic profiles. XCMS analysis of the untargeted metabolomics data revealed a total of 3200-4700 metabolite features from the transfected UM1 or UM2 cancer cells and 369-585 significantly changed metabolites due to AK2 or PGK1 suppression. In addition, cluster analysis showed that a common group of metabolites were altered by AK2 knockdown or by PGK1 knockdown between the UM1 and UM2 cells. However, the set of significantly changed metabolites due to AK2 knockdown was found to be distinct from those significantly changed by PGK1 knockdown. Our study has demonstrated that LC-MS with XCMS is an efficient tool for metabolomic analysis of oral cancer cells, and knockdown of different genes results in distinct changes in metabolic phenotypes in oral cancer cells

carat: An R Package for Covariate-Adaptive Randomization in Clinical Trials

Covariate-adaptive randomization is gaining popularity in clinical trials because they enable the generation of balanced allocations with respect to covariates. Over the past decade, substantial progress has been made in both new innovative randomization procedures and the theoretical properties of associated inferences. However, these results are scattered across the literature, and a single tool kit does not exist for use by clinical trial practitioners and researchers to conduct and evaluate these methods. The R package carat is proposed to address this need. It facilitates a broad range of covariate-adaptive randomization and testing procedures, such as the most common and classical methods, and also reflects recent developments in the field. The package contains comprehensive evaluation and comparison tools for use in both randomization procedures and tests. This enables power analysis to be conducted to assist the planning of a covariate-adaptive clinical trial. The package also implements a command-line interface to allow for an interactive allocation procedure, which is typically the case in real-world applications. In this paper, the features and functionalities of carat are presented