U-Spin Tests of the Standard Model and New Physics

Within the standard model, a relation involving branching ratios and direct CP asymmetries holds for the B-decay pairs that are related by U-spin. The violation of this relation indicates new physics (NP). In this paper, we assume that the NP affects only the Delta S = 1 decays, and show that the NP operators are generally the same as those appearing in B -> pi K decays. The fit to the latest B -> pi K data shows that only one NP operator is sizeable. As a consequence, the relation is expected to be violated for only one decay pair: Bd -> K0 pi0 and Bs -> Kbar0 pi0.Comment: 12 pages, latex, no figures. References changed to follow MPL guidelines; info added about U-spin breaking and small NP strong phases; discussion added about final-state pi-K rescattering; analysis and conclusions unaltere

Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma.

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 (HK2) and Enolase 1 (ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an approach for identifying novel potential therapeutic targets in human HCC with mutated p53. These approaches can take advantage of the massive next-generation sequencing (NGS) data generated worldwide and make more out of it by exploring new potential therapeutic targets

Using Prospect Theory To Explain The Setting Of The Expected Rate Of Return On Pension Assets

Studies often use earnings management to explain the setting of assumed expected rate of return (ERRs) on pension assets in the defined benefit plans. In this paper, we argue that a manager’s risk attitude toward investment may have an impact on setting ERRs on pension assets. Prospect theory is a theory of decision making under risk and is used to explain firms’ behavior with regard to earnings management. We believe that prospect theory also can be used to explain firms’ setting of ERRs, which critically depends on managers’ expectations regarding risky investment. Empirical evidence shows that prospect theory can explain how firms set their ERRs on pension assets. We find that firms in the high-ERR group are risk-averters; that is, there is a positive relationship between risk and return. On the other hand, firms in the low-ERR group are risk-lovers and have an inverse risk-return relationship. Our findings contribute to the literature by suggesting that managers’ risk attitudes also affect the choice of ERR

Determinants of Health-Promoting Lifestyle among Nurses in Taiwan

This two-phase study was undertaken to: (1) determine the relationships of self-efficacy, perceived health status, perceived social support, age, marital status, education, work shift, work setting, and years employed as a registered nurse (RN) to the practice of a health-promoting lifestyle; (2) determine the combination of predictor variables explaining the variance in the practice of a health-promoting lifestyle; and (3) investigate other personal and environmental cues and characteristics related to health-promoting lifestyles among nurses (N = 218) in Taiwan. Findings of the quantitative approach in Phase One indicated that a health-promoting lifestyle was significantly related to self-efficacy, perceived health status, perceived social support, age, and years employed as an RN. Four predictor variables, namely, self-efficacy, perceived health status, perceived social support, and working the evening shift, explained 40.4% of the variance in health-promoting lifestyle in this sample. Responses to open-ended questions revealed other factors that contribute to health-promoting lifestyle among the nurses. In Phase Two, nine subjects who scored very high and 10 who scored very low on the Health-Promoting Lifestyle Profile (HPLP) were interviewed regarding health beliefs, behaviors and factors influencing the practice of a health-promoting lifestyle. The interview data partly validate the findings from Phase One. In many situations, the subjects in Phase Two of this study cited predictor variables investigated such as social supports and rotating shift. Subjects also stressed the importance of energy, perseverance and partners in initiating and maintaining a health-promoting lifestyle. The interview data revealed other personal and environmental cues and characteristics of a health-promoting lifestyle. The high group had initiated less lifestyle changes, but maintained the changes longer than subjects in the low group. They also identified more enabling characteristics than did the low group. Subjects in the low group used more stress management techniques and identified more hindrances for lifestyle changes than the high HPLP group. A revised model was developed for testing in future studies