The effects of cue competition on timing in pigeons

We studied the effects of cue competition on timing in both overshadowing and blocking operant procedures with pigeons. A white center key delivered reward when pecked 30 s after a red or green sidekey was presented and 10 s after presentation of the alternate color on the other sidekey. In Experiment 1, key presentations were concurrent during training trials for overshadow-condition pigeons, while side key presentations were separated across training trials for control birds. In Experiment 2, half of the birds (Blocking group) were given pre-exposure trials to either the 10-s or 30-s sidekey condition. Both blocking-condition and control birds were then given trials of concurrent side key presentations. Peak time curves were compared between experimental and control conditions. The results showed blocking of timing accuracy of a long (30-s) stimulus by a short (10-s) stimulus, but no evidence for overshadowing of timing accuracy.     

A Comprehensive Analysis of Symmetric Arginine Dimethylation in Colorectal Cancer Tissues Using Immunoaffinity Enrichment and Mass Spectrometry

Protein arginine methyltransferase 5 (PRMT5) is a major enzyme responsible for generating monomethyl and symmetric dimethyl arginine in proteins. PRMT5 is essential for cell viability and development, and its overexpression is observed in a variety of cancers. In the present study, it is found that levels of PRMT5 protein and symmetric arginine dimethylation in colorectal cancer (CRC) tissues are increased compared to those in adjacent noncancerous tissues. Using immunoaffinity enrichment of methylated peptides combined with high‐resolution mass spectrometry, a total of 147 symmetric dimethyl‐arginine (SDMA) sites in 94 proteins are identified, many of which are RNA binding proteins and enzymes. Quantitative analysis comparing CRC and normal tissues reveals significant increase in the symmetric dimethylation of 70 arginine sites in 46 proteins and a decrease in that of four arginine sites in four proteins. Among the 94 proteins identified in this study, it is confirmed that KH‐type splicing regulatory protein is a target of PRMT5 and highly expressed in CRC tissues compared to noncancerous tissues. This study is the first comprehensive analysis of symmetric arginine dimethylation using clinical samples and extends the number of known in vivo SDMA sites. The data obtained are available via ProteomeXchange with the identifier PXD015653.     

Emerging Roles and Research Tools of Atypical Ubiquitination

Ubiquitination is a posttranslational modification characterized by the covalent attachment of ubiquitin molecules to protein substrates. The ubiquitination modification process is reversible, dynamic, and involved in the regulation of various biological processes, such as autophagy, inflammatory responses, and DNA damage responses. The forms of ubiquitin modification are very diverse, incorporating either a single ubiquitin molecule or a complicated ubiquitin polymer, and different types of ubiquitination usually elicit corresponding cellular responses. The development of research tools and strategies has afforded more detailed insight into atypical ubiquitin signaling pathways that were previously poorly understood. Here, an update on the understanding of atypical ubiquitin chain signaling pathways is provided and the recent development of representative research tools for ubiquitin systems is discussed. In addition, the future challenges in ubiquitin research are reflected on and summarized.     

基于CRISPR/Cas9的基因分析方法研究进展

自2012年首次证明了CRISPR/Cas9可以在体外进行DNA切割试验以来,CRISPR技术逐渐在基因编辑研究中获得了迅速的发展,除了应用于基因编辑领域之外,它在基因表达调控、基因成像、基因分析等方面也展现出了巨大的应用潜力。尤其在基因分析领域,CRISPR技术由于其精确的基因识别、室温的反应条件、易设计性和操作性等特色,使得一系列新型的基因检测技术得以发展,并取得了超越常规技术的一些检测参数。本文以Cas9蛋白为对象,综述了近些年来在该领域取得的研究进展。主要论述Cas9蛋白的功能、改造、引导RNA(sgRNA)的设计及其在基因分析方法上的应用。     

Efficient screening of predictive biomarkers for individual treatment selection

The development of molecular diagnostic tools to achieve individualized medicine requires identifying predictive biomarkers associated with subgroups of individuals who might receive beneficial or harmful effects from different available treatments. However, due to the large number of candidate biomarkers in the large‐scale genetic and molecular studies, and complex relationships among clinical outcome, biomarkers, and treatments, the ordinary statistical tests for the interactions between treatments and covariates have difficulties from their limited statistical powers. In this paper, we propose an efficient method for detecting predictive biomarkers. We employ weighted loss functions of Chen et al. to directly estimate individual treatment scores and propose synthetic posterior inference for effect sizes of biomarkers. We develop an empirical Bayes approach, namely, we estimate unknown hyperparameters in the prior distribution based on data. We then provide efficient screening methods for the candidate biomarkers via optimal discovery procedure with adequate control of false discovery rate. The proposed method is demonstrated in simulation studies and an application to a breast cancer clinical study in which the proposed method was shown to detect the much larger numbers of significant biomarkers than existing standard methods.