This Letter reports on the experimental observation of a topologically protected edge state and exceptional point in an open and non-Hermitian (lossy) acoustic system. Although the theoretical ...underpinning is generic to wave physics, the simulations and experiments are performed for an acoustic system. It has nontrivial topological properties that can be characterized by the Chern number provided that a synthetic dimension is introduced. Unidirectional reflectionless propagation, a hallmark of exceptional points, is unambiguously observed in both simulations and experiments.
HMGA2, a high-mobility group protein, is oncogenic in a variety of tumors, including benign mesenchymal tumors and lung cancers. Knockdown of Dicer in HeLa cells revealed that the HMGA2 gene is ...transcriptionally active, but its mRNA is destabilized in the cytoplasm through the microRNA (miRNA) pathway. HMGA2 was derepressed upon inhibition of let-7 in cells with high levels of the miRNA. Ectopic expression of let-7 reduced HMGA2 and cell proliferation in a lung cancer cell. The effect of let-7 on HMGA2 was dependent on multiple target sites in the 3' untranslated region (UTR), and the growth-suppressive effect of let-7 on lung cancer cells was rescued by overexpression of the HMGA2 ORF without a 3'UTR. Our results provide a novel example of suppression of an oncogene by a tumor-suppressive miRNA and suggest that some tumors activate the oncogene through chromosomal translocations that eliminate the oncogene's 3'UTR with the let-7 target sites.
MicroRNAs in cancer Lee, Yong Sun; Dutta, Anindya
Annual review of pathology,
01/2009, Volume:
4
Journal Article
Peer reviewed
Open access
Within the past few years, studies on microRNA (miRNA) and cancer have burst onto the scene. Profiling of the miRNome (global miRNA expression levels) has become prevalent, and abundant miRNome data ...are currently available for various cancers. The pattern of miRNA expression can be correlated with cancer type, stage, and other clinical variables, so miRNA profiling can be used as a tool for cancer diagnosis and prognosis. miRNA expression analyses also suggest oncogenic (or tumor-suppressive) roles of miRNAs. miRNAs play roles in almost all aspects of cancer biology, such as proliferation, apoptosis, invasion/metastasis, and angiogenesis. Given that many miRNAs are deregulated in cancers but have not yet been further studied, it is expected that more miRNAs will emerge as players in the etiology and progression of cancer. Here we also discuss miRNAs as a tool for cancer therapy.
Due to the obvious advantage in potassium reserves, potassium‐ion batteries (PIBs) are now receiving increasing research attention as an alternative energy storage system for lithium‐ion batteries ...(LIBs). Unfortunately, the large size of K+ makes it a challenging task to identify suitable electrode materials, particularly cathode ones that determine the energy density of PIBs, capable of tolerating the serious structural deformation during the continuous intercalation/deintercalation of K+. It is therefore of paramount importance that proper design principles of cathode materials be followed to ensure stable electrochemical performance if a practical application of PIBs is expected. Herein, the current knowledge on the structural engineering of cathode materials acquired during the battle against its performance degradation is summarized. The K+ storage behavior of different types of cathodes is discussed in detail and the structure–performance relationship of materials sensitive to their different lattice frameworks is highlighted. The key issues facing the future development of different categories of cathode materials are also highlighted and perspectives for potential approaches and strategies to promote the further development of PIBs are provided.
Potassium‐ion batteries (PIBs) are now receiving increasing research attention due to their obvious advantage regarding the potassium reserves. Cathode materials, which determine the energy density of PIBs, usually suffer from serious structural deformation during continuous K+ (de)intercalation. Therefore, proper structural‐design principles of cathode materials should be focused on to ensure high performance to promote the further development of PIBs.
•We explore the Russian-Ukrainian conflict's impact on the global financial markets.•We find that their relationship has changed due to the conflict.•European equities and Russian bonds are the net ...transmitters of shocks.•The war affected the returns and volatility connectedness among them.•This effect was in terms of short- and long-term frequencies.
We investigate the impact of geopolitical risks caused by the Russian-Ukrainian conflict on Russia, European financial markets, and the global commodity markets. We measure the dynamic connectedness among them using time- and frequency-based time-varying parameter vector autoregression (TVP-VAR) approaches. The empirical findings indicate that (i) their relationship has changed due to the conflict; (ii) European equities and Russian bonds are the net transmitters of shocks; and (iii) the conflict affects returns and volatility connectedness among them in terms of short- and long-term frequencies, respectively.
We investigate the relationship between crude oil prices and stock markets. Unlike prior studies, we use implied volatility indices and evaluate the change in the relationship between the volatility ...indices through a sub-period analysis. Specifically, we examine the causal relationships among the crude oil, S&P 500 index, and KOSPI 200 index volatilities by using the autoregressive distributed lag (ARDL) bounds and the Toda-Yamamoto Granger causality tests. In addition, a BEKK-GARCH model is employed to enhance the robustness of the causality test results. These experiments indicate that the OVX and VIX show bi-directional causality in the period that includes the shale gas revolution and no causality in the period that does not. Further, the OVX Granger causes the VKOSPI in the former period, but there is no causality between them in the latter period. Finally, we find strong unidirectional causality from the VIX to the VKOSPI in both sub-periods. These results have important implications for the analysis of portfolio risk management and for assisting energy policymakers and traders in making effective decisions and investments, respectively.
Plant growth-promoting rhizobacteria (PGPR) actively colonize the plant rhizosphere, which not only stimulates plants’ growth and development but also mitigates the adverse effects of abiotic ...stressors. Besides other techniques and approaches used for the alleviation of abiotic stress conditions, the utilization of PGPR with multiplant growth-promoting traits is desirable because the application of PGPR is pragmatic, sustainable, and environmentally friendly. In the past four decades, numerous ACC deaminase-producing PGPR have been reported for the improvement of crop plants’ growth and development under different abiotic stress conditions. Since 1-aminocyclopropane-1-carboxylate (ACC) deaminase producing PGPR regulates ethylene production by utilizing the exuded ACC, which is an immediate precursor of ethylene biosynthesis. However, little is known about the basic mechanism involved in the acquisition of ACC by ACC deaminase-producing bacteria since the enzyme ACC deaminase is localized inside the bacterial cells and ACC is exuded into the rhizosphere from plant roots. In the present article, we proposed candidate attractants involved in the transfer of ACC into ACC deaminase-producing bacteria. Additionally, we discussed the importance and relation of these candidate attractants with ACC deaminase under abiotic stress conditions.
Key points
•
The ethylene precursor, ACC, exude from plant tissues under abiotic stresses
•
ACC deaminase activity of PGPR localized in the cytoplasm and periplasm of bacteria
•
Proposed candidate attractants for the transfer and equilibrium of exuded ACC
Abstract
We present a performance test of the point-spread function (PSF) deconvolution algorithm applied to astronomical integral field unit (IFU) spectroscopy data for restoration of galaxy ...kinematics. We deconvolve the IFU data by applying the Lucy–Richardson algorithm to the 2D image slice at each wavelength. We demonstrate that the algorithm can effectively recover the true stellar kinematics of the galaxy, by using mock IFU data with a diverse combination of surface brightness profile, signal-to-noise ratio, line-of-sight geometry, and line-of-sight velocity distribution (LOSVD). In addition, we show that the proxy of the spin parameter
λ
R
e
can be accurately measured from the deconvolved IFU data. We apply the deconvolution algorithm to the actual SDSS-IV MaNGA IFU survey data. The 2D LOSVD, geometry, and
λ
R
e
measured from the deconvolved MaNGA IFU data exhibit noticeable differences compared to the ones measured from the original IFU data. The method can be applied to any other regular-grid IFU data to extract the PSF-deconvolved spatial information.
Since the breakdown of the Bretton Woods system in the early 1970s, the foreign exchange (FX) market has become an important focus of both academic and practical research. There are many reasons why ...FX is important, but one of most important aspects is the determination of foreign investment values. Therefore, FX serves as the backbone of international investments and global trading. Additionally, because fluctuations in FX affect the value of imported and exported goods and services, such fluctuations have an important impact on the economic competitiveness of multinational corporations and countries. Therefore, the volatility of FX rates is a major concern for scholars and practitioners. Forecasting FX volatility is a crucial financial problem that is attracting significant attention based on its diverse implications. Recently, various deep learning models based on artificial neural networks (ANNs) have been widely employed in finance and economics, particularly for forecasting volatility. The main goal of this study was to predict FX volatility effectively using ANN models. To this end, we propose a hybrid model that combines the long short-term memory (LSTM) and autoencoder models. These deep learning models are known to perform well in time-series prediction for forecasting FX volatility. Therefore, we expect that our approach will be suitable for FX volatility prediction because it combines the merits of these two models. Methodologically, we employ the Foreign Exchange Volatility Index (FXVIX) as a measure of FX volatility. In particular, the three major FXVIX indices (EUVIX, BPVIX, and JYVIX) from 2010 to 2019 are considered, and we predict future prices using the proposed hybrid model. Our hybrid model utilizes an LSTM model as an encoder and decoder inside an autoencoder network. Additionally, we investigate FXVIX indices through subperiod analysis to examine how the proposed model’s forecasting performance is influenced by data distributions and outliers. Based on the empirical results, we can conclude that the proposed hybrid method, which we call the autoencoder-LSTM model, outperforms the traditional LSTM method. Additionally, the ability to learn the magnitude of data spread and singularities determines the accuracy of predictions made using deep learning models. In summary, this study established that FX volatility can be accurately predicted using a combination of deep learning models. Our findings have important implications for practitioners. Because forecasting volatility is an essential task for financial decision-making, this study will enable traders and policymakers to hedge or invest efficiently and make policy decisions based on volatility forecasting.
In this paper, a new (
3
+
1
)-dimensional generalized KP (gKP) equation is presented, and two classes of lump solutions, rationally localized in all directions in the space, to the dimensionally ...reduced cases in (
2
+
1
)-dimensions are derived as well. The proposed method in this work is based on a Hirota bilinear differential equation, which implies that we can build the lump solutions to the presented reduced gKP equation from positive quadratic function solutions to the aforementioned bilinear equation. Moreover, there are totally six free parameters in the resulting lump solutions, so that we can get the sufficient and necessary conditions guaranteeing analyticity and rational localization of the solutions by using these six free parameters. In the meantime, two special cases are plotted as illustrative examples and some contour plots with different determinant values are given to show that the corresponding lump solution tends to zero when the determinant approaches zero.
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