Discovery of Long Non-Coding RNA MALAT1 Amplification in Precancerous Colorectal Lesions

A colorectal adenoma, an aberrantly growing tissue, arises from the intestinal epithelium and is considered as precursor of colorectal cancer (CRC). In this study, we investigated structural and numerical chromosomal aberrations in adenomas, hypothesizing that chromosomal instability (CIN) occurs early in adenomas. We applied array comparative genomic hybridization (aCGH) to fresh frozen colorectal adenomas and their adjacent mucosa from 16 patients who underwent colonoscopy examination. In our study, histologically similar colorectal adenomas showed wide variability in chromosomal instability. Based on the obtained results, we further stratified patients into four distinct groups. The first group showed the gain of MALAT1 and TALAM1, long non-coding RNAs (lncRNAs). The second group involved patients with numerous microdeletions. The third group consisted of patients with a disrupted karyotype. The fourth group of patients did not show any CIN in adenomas. Overall, we identified frequent losses in genes, such as TSC2, COL1A1, NOTCH1, MIR4673, and GNAS, and gene gain containing MALAT1 and TALAM1. Since long non-coding RNA MALAT1 is associated with cancer cell metastasis and migration, its gene amplification represents an important event for adenoma development.     

Generalized ordering-search for learning directed probabilistic logical models

Recently, there has been an increasing interest in directed probabilistic logical models and a variety of formalisms for describing such models has been proposed. Although many authors provide high-level arguments to show that in principle models in their formalism can be learned from data, most of the proposed learning algorithms have not yet been studied in detail. We introduce an algorithm, generalized ordering-search, to learn both structure and conditional probability distributions (CPDs) of directed probabilistic logical models. The algorithm is based on the ordering-search algorithm for Bayesian networks. We use relational probability trees as a representation for the CPDs. We present experiments on a genetics domain, blocks world domains and the Cora dataset. Editors: Stephen Muggleton, Ramon Otero, Simon Colton.     

Dyadic spatial resolution reduction transcoding for H.264/AVC

In this paper, we examine spatial resolution downscaling transcoding for H.264/AVC video coding. A number of advanced coding tools limit the applicability of techniques, which were developed for previous video coding standards. We present a spatial resolution reduction transcoding architecture for H.264/AVC, which extends open-loop transcoding with a low-complexity compensation technique in the reduced-resolution domain. The proposed architecture tackles the problems in H.264/AVC and avoids visual artifacts in the transcoded sequence, while keeping complexity significantly lower than more traditional cascaded decoder–encoder architectures. The refinement step of the proposed architecture can be used to further improve rate-distortion performance, at the cost of additional complexity. In this way, a dynamic-complexity transcoder is rendered possible. We present a thorough investigation of the problems related to motion and residual data mapping, leading to a transcoding solution resulting in fully compliant reduced-size H.264/AVC bitstreams.     

Effects of three‐dimensional virtual reality and traditional training methods on mental workload and training performance

Industries will implement effective training programs to improve training performance, and an ideal training performance occurs under proper mental workload (MWL). Virtual reality (VR) has recently been widely utilized in training; however, only a few studies have investigated its effects on MWL and training performance simultaneously. The purpose of this study is to investigate the effects of VR training and traditional training methods, such as technical manuals (TM) and multimedia films (MF), on training performance and MWL. The results of the performance measurement show that VR training is considered the best training method compared to TM and MF, particularly in the case of complex tasks. The results of physiological measurements (GSR [galvanic skin response], LF% [low frequency], and LF/HF [high frequency] ratio) show a significant difference between reading TM and using computer (MF and VR), wherein the latter has a lower MWL. However, no significant difference in subjective MWL assessment (NASA‐TLX [task load index]) and HF% measurement is found.     

Classifying and Formally Verifying Integer Constant Folding

Constant folding is a well-known optimization of compilers which evaluates constant expressions already at compile time. Constant folding is valid only if the results computed by the compiler are exactly the same as the results which would be computed at run-time by the target machine arithmetic. We classify different arithmetics by deriving a general condition under which a target-machine arithmetic can be replaced by a compiler arithmetic. Furthermore, we consider integer arithmetics as a special case. They can be described by residue class arithmetics. We show that these arithmetics form a lattice. Using the order relation in this lattice, we establish a necessary and sufficient criterion under which constant folding can be done in a residue class arithmetic that is different from the one of the target machine. Concerning formal verification, we have formalized our proofs in the Isabelle/HOL system. As examples, we discuss the Java and C integer arithmetics and show which compiler arithmetics are valid for constant folding. This discussion reveals also potential sources of incorrect behavior of C compilers.     

民众战争态度构型演化建模与仿真研究

在战争的演化模型的研究中,为了控制和引导社会舆论,民众战争态度演化是战争复杂系统研究的莺要内容之一.考虑持不同战争态度的社会个体之间的相互作用率与其态度距离的关系和从众心理,提出了度量持不同态度社会个体相遇的相互作用率.分析了态度演化的三种过程,确定了不同态度之间转变的转移概率密度,建立了战争态度演化的动力学方程模型.引入一个序参量度量持各种战争态度人数的动态变化,定义了战争态度构型演化的相.仿真结果表明,得到外界支持的态度,最终持有的人数在社会中占多数,外界作用对社会民众态度转变,对大多数人是有效的,但有极少数人仍会坚持原来的态度.     

Blue-Green (~480 nm) versus Blue (~460 nm) Light for Newborn Phototherapy—Safety Considerations

We have previously shown that the phototherapy of hyperbilirubinemic neonates using blue-green LED light with a peak wavelength of ~478 nm is 31% more efficient for removing unconjugated bilirubin from circulation than blue LED light with a peak wavelength of ~452 nm. Based on these results, we recommended that the phototherapy of hyperbilirubinemic newborns be practiced with light of ~480 nm. Aim: Identify and discuss the most prominent potential changes that have been observed in the health effects of phototherapy using either blue fluorescent- or blue LED light and speculate on the expected effects of changing to blue-green LED light phototherapy. Search the phototherapy literature using the terms neonate, hyperbilirubinemia, and phototherapy in the PubMed and Embase databases. Transitioning from blue fluorescent light to blue-green LED light will expose neonates to less light in the 400–450 nm spectral range, potentially leading to less photo-oxidation and geno-/cytotoxicity, reduced risk of cancer, and decreased mortality in extremely low-birthweight neonates. The riboflavin level may decline, and the increased production and retention of bronze pigments may occur in predisposed neonates due to enhanced lumirubin formation. The production of pre-inflammatory cytokines may rise. Hemodynamic responses and transepidermal water loss are less likely to occur. The risk of hyperthermia may decrease with the use of blue-green LED light and the risk of hypothermia may increase. Parent–neonate attachment and breastfeeding will be positively affected because of the shortened duration of phototherapy. The latter may also lead to a significant reduction in the cost of phototherapy procedures as well as the hospitalization process.     

Modulation of Muscarinic Signalling in the Central Nervous System by Steroid Hormones and Neurosteroids

Muscarinic acetylcholine receptors expressed in the central nervous system mediate various functions, including cognition, memory, or reward. Therefore, muscarinic receptors represent potential pharmacological targets for various diseases and conditions, such as Alzheimer’s disease, schizophrenia, addiction, epilepsy, or depression. Muscarinic receptors are allosterically modulated by neurosteroids and steroid hormones at physiologically relevant concentrations. In this review, we focus on the modulation of muscarinic receptors by neurosteroids and steroid hormones in the context of diseases and disorders of the central nervous system. Further, we propose the potential use of neuroactive steroids in the development of pharmacotherapeutics for these diseases and conditions.