Enhancing microRNA167A expression in seed decreases the α-linolenic acid content and increases seed size in Camelina sativa.

Despite well established roles of microRNAs in plant development, few aspects have been addressed to understand their effects in seeds especially on lipid metabolism. In this study, we showed that overexpressing microRNA167A (miR167OE) in camelina (Camelina sativa) under a seed-specific promoter changed fatty acid composition and increased seed size. Specifically, the miR167OE seeds had a lower α-linolenic acid with a concomitantly higher linoleic acid content than the wild-type. This decreased level of fatty acid desaturation corresponded to a decreased transcriptional expression of the camelina fatty acid desaturase3 (CsFAD3) in developing seeds. MiR167 targeted the transcription factor auxin response factor (CsARF8) in camelina, as had been reported previously in Arabidopsis. Chromatin immunoprecipitation experiments combined with transcriptome analysis indicated that CsARF8 bound to promoters of camelina bZIP67 and ABI3 genes. These transcription factors directly or through the ABI3-bZIP12 pathway regulate CsFAD3 expression and affect α-linolenic acid accumulation. In addition, to decipher the miR167A-CsARF8 mediated transcriptional cascade for CsFAD3 suppression, transcriptome analysis was conducted to implicate mechanisms that regulate seed size in camelina. Expression levels of many genes were altered in miR167OE, including orthologs that have previously been identified to affect seed size in other plants. Most notably, genes for seed coat development such as suberin and lignin biosynthesis were down-regulated. This study provides valuable insights into the regulatory mechanism of fatty acid metabolism and seed size determination, and suggests possible approaches to improve these important traits in camelina

A Sarcoplasmic Reticulum Localized Protein Phosphatase Regulates Phospholamban Phosphorylation and Promotes Ischemia Reperfusion Injury in the Heart.

Phospholamban (PLN) is a key regulator of sarcolemma calcium uptake in cardiomyocyte, its inhibitory activity to SERCA is regulated by phosphorylation. PLN hypophosphorylation is a common molecular feature in failing heart. The current study provided evidence at molecular, cellular and whole heart levels to implicate a sarcolemma membrane targeted protein phosphatase, PP2Ce, as a specific and potent PLN phosphatase. PP2Ce expression was elevated in failing human heart and induced acutely at protein level by β -adrenergic stimulation or oxidative stress in cardiomyocytes. PP2Ce expression in mouse heart blunted β-adrenergic response and exacerbated ischemia/reperfusion injury. Therefore, PP2Ce is a new regulator for cardiac function and pathogenesis

Phase-Resolved Timing Analysis of GRS 1915+105 in Its {\rho} State

We made a phase-resolved timing analysis of GRS 1915+105 in its {\rho} state and obtained detailed {\rho} cycle evolutions of the frequency, the amplitude and the coherence of low-frequency quasi-periodic oscillation (LFQPO). We combined our timing results with the spectral study by Neilsen et al. to perform an elaborate comparison analysis. Our analyses show that the LFQPO frequency does not scale with the inner disk radius, but it is related to the spectral index, indicating a possible correlation between the LFQPOs and the corona. The LFQPO amplitude spectrum and other results are naturally explained by tying the LFQPO to the corona. The similarities of the spectra of variability parameters between the LFQPO from {\rho} state and those from more steady states indicate that the LFQPOs of GRS 1915+105 in very different states seem to share the same origin.Comment: 21 pages, 4 figures, accepted for publication in Ap

Personalized Multidimensional Process Framework For Dynamic Risk Analysis In The Real Estate Industry

The risk analysis for real estate property investment is subject to high risk. It is qualitatively and quantitatively assessed by various techniques such as the analytical hierarchy process (AHP) and the analytic network process (ANP) which determine the risk factors based on expert survey, weight and rank the factors using algorithm and mathematical formula and decide the best investment based on performance index of the alternatives given. However, experts from the field have different opinions and judgments about the environment of the real estate industry and this scenario will affect the result of the risk factor weight and ranking. Moreover, different investors have different goals and objectives to be achieve. Thus, this paper will propose a new personalized multidimensional process (PMP) framework based on knowledge discovery. This framework comprises of two new methods namely the personalized association mapping (PAM) method and the personalized multidimensional sensitivity analysis (PM-SA) method. The innovations of this research are the justification of risk factor weight and ranking. It will be based on deterministic approach using historical data driven to decision support using knowledge discovery in database and the heuristic approach which is refers to investors personalization of the risk factors which fulfil their requirements