Tail Dependence Measure for Examining Financial Extreme Co-movements

Modeling and forecasting extreme co-movements in financial market is important for conducting stress test in risk management. Asymptotic independence and asymptotic dependence behave drastically different in modeling such co-movements. For example, the impact of extreme events is usually overestimated whenever asymptotic dependence is wrongly assumed. On the other hand, the impact is seriously underestimated whenever the data is misspecified as asymptotic independent. Therefore, distinguishing between asymptotic independence/dependence scenarios is very informative for any decision-making and especially in risk management. We investigate the properties of the limiting conditional Kendall’s tau which can be used to detect the presence of asymptotic independence/dependence. We also propose nonparametric estimation for this new measure and derive its asymptotic limit. A simulation study shows good performances of the new measure and its combination with the coefficient of tail dependence proposed by Ledford and Tawn (1996, 1997). Finally, applications to financial and insurance data are provided

Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Statistical Inference for a Relative Risk Measure

<p>For monitoring systemic risk from regulators’ point of view, this article proposes a relative risk measure, which is sensitive to the market comovement. The asymptotic normality of a nonparametric estimator and its smoothed version is established when the observations are independent. To effectively construct an interval without complicated asymptotic variance estimation, a jackknife empirical likelihood inference procedure based on the smoothed nonparametric estimation is provided with a Wilks type of result in case of independent observations. When data follow from AR-GARCH models, the relative risk measure with respect to the errors becomes useful and so we propose a corresponding nonparametric estimator. A simulation study and real-life data analysis show that the proposed relative risk measure is useful in monitoring systemic risk.</p

N6-Methyladenosine Regulates the Expression and Secretion of TGFβ1 to Affect the Epithelial–Mesenchymal Transition of Cancer Cells

N6-methyladenosine (m6A) is the most abundant modification on eukaryotic mRNA, which regulates all steps of the mRNA life cycle. An increasing number of studies have shown that m6A methylation plays essential roles in tumor development. However, the relationship between m6A and the progression of cancers remains to be explored. Here, we reported that transforming growth factor-&beta; (TGF&beta;1)-induced epithelial&ndash;mesenchymal transition (EMT) was inhibited in methyltransferase-like 3 (METTL3) knockdown (Mettl3Mut/&minus;) cells. The expression of TGF&beta;1 was up-regulated, while self-stimulated expression of TGF&beta;1 was suppressed in Mettl3Mut/&minus; cells. We further revealed that m6A promoted TGFB1 mRNA decay, but impaired TGFB1 translation progress. Besides this, the autocrine of TGF&beta;1 was disrupted in Mettl3Mut/&minus; cells via interrupting TGF&beta;1 dimer formation. Lastly, we found that Snail, which was down-regulated in Mettl3Mut/&minus; cells, was a key factor responding to TGF&beta;1-induced EMT. Together, our research demonstrated that m6A performed multi-functional roles in TGF&beta;1 expression and EMT modulation, suggesting the critical roles of m6A in cancer progression regulation

Developing a Clustering-Based Empirical Bayes Analysis Method for Hotspot Identification

Hotspot identification (HSID) is a critical part of network-wide safety evaluations. Typical methods for ranking sites are often rooted in using the Empirical Bayes (EB) method to estimate safety from both observed crash records and predicted crash frequency based on similar sites. The performance of the EB method is highly related to the selection of a reference group of sites (i.e., roadway segments or intersections) similar to the target site from which safety performance functions (SPF) used to predict crash frequency will be developed. As crash data often contain underlying heterogeneity that, in essence, can make them appear to be generated from distinct subpopulations, methods are needed to select similar sites in a principled manner. To overcome this possible heterogeneity problem, EB-based HSID methods that use common clustering methodologies (e.g., mixture models, K-means, and hierarchical clustering) to select “similar” sites for building SPFs are developed. Performance of the clustering-based EB methods is then compared using real crash data. Here, HSID results, when computed on Texas undivided rural highway cash data, suggest that all three clustering-based EB analysis methods are preferred over the conventional statistical methods. Thus, properly classifying the road segments for heterogeneous crash data can further improve HSID accuracy

Recent Advances in Wearable Tactile Sensors Based on Electrospun Nanofiber Platform

Abstract Wearable electronics have triggered the great development of flexible tactile sensors for promising applications such as healthcare monitoring, motion detection, and human‐machine interaction. However, most of the flexible sensors are constructed on compact and airtight polymer films with inferior flexibility and no breathability, hindering the wearability and comfortability for long‐time continuous operation usage. To address such challenges, flexible sensors based on the electrospun polymer platform with comprehensive advantages of ultrathin thickness, superior flexibility, excellent stretchability, high porosity, low density, and surface functionality are emerging. It has become a hot research direction, and considerable progress has been made. Therefore, it is necessary to timely review the latest findings on the rapidly developing electrospun nanofiber‐based tactile sensors. Firstly, the principle of the electrospinning technique, the factors affecting the nanofiber morphology, and the engineering of the nanofibers are briefly introduced, and the key material and structural factors affecting the sensing performance are analyzed. Secondly, representative work on the electrospun nanofiber‐based tactile sensors is discussed in detail according to the sensing mechanism. Thirdly, unique properties of electrospun nanofibers, such as superior flexibility, breathability, hydrophobicity, anti‐bacterial, and self‐cleaning, are highlighted. Finally, the remaining challenges and future development trends are outlined

Selective deoxygenation of carbonyl groups at room temperature and atmospheric hydrogen pressure over nitrogen-doped carbon supported Pd catalyst

In this study, we have reported that a new catalyst of Pd nanoparticles supported on nitrogen-doped, highly porous carbon (Pd/NC-BT) could promote quantitative deoxygenation of carbonyl groups in a wide variety of aromatic compounds to give the fully saturated side-chain. The catalyst is unique in that it works under mild conditions at room temperature and standard hydrogen pressures. Examination of the catalytic process indicates that the presence of nitrogen atoms at the support surface and the highly porous catalyst structure are key factors contributing to the excellent catalytic performance. The nitrogen atoms act as Lewis bases sites to promote the heterolytic cleavage of H2 in coordination with the Pd nanoparticles and the porous structure facilitates the mass transfer of the substrates to the catalytic sites. Hence, the catalyst exhibits sufficient power to reduce the alcohol groups of the intermediates to give alkyl groups under mild conditions while other functional groups in the substrate molecules remain unaffected. Furthermore, the Pd/NC-BT catalyst can be recycled without observable decrease in its activity (over at least after six cycles).</p

Loss of TET2 impairs endothelial angiogenesis via downregulating STAT3 target genes

Abstract Background Ischemic diseases represent a major global health care burden. Angiogenesis is critical in recovery of blood flow and repair of injured tissue in ischemic diseases. Ten–eleven translocation protein 2 (TET2), a member of DNA demethylases, is involved in many pathological processes. However, the role of TET2 in angiogenesis is still unrevealed. Methods TET2 was screened out from three DNA demethylases involved in 5-hydroxylmethylcytosine (5-hmC) regulation, including TET1, TET2 and TET3. Knockdown by small interfering RNAs and overexpression by adenovirus were used to evaluate the role of TET2 on the function of endothelial cells. The blood flow recovery and density of capillary were analyzed in the endothelial cells-specific TET2-deficient mice. RNA sequencing was used to identify the TET2-mediated mechanisms under hypoxia. Co-immunoprecipitation (Co-IP), chromatin immunoprecipitation-qPCR (ChIP-qPCR) and glucosylated hydroxymethyl-sensitive-qPCR (GluMS-qPCR) were further performed to reveal the interaction of TET2 and STAT3. Results TET2 was significantly downregulated in endothelial cells under hypoxia and led to a global decrease of 5-hmC level. TET2 knockdown aggravated the hypoxia‐induced dysfunction of endothelial cells, while TET2 overexpression alleviated the hypoxia‐induced dysfunction. Meanwhile, the deficiency of TET2 in endothelial cells impaired blood flow recovery and the density of capillary in the mouse model of hindlimb ischemia. Mechanistically, RNA sequencing indicated that the STAT3 signaling pathway was significantly inhibited by TET2 knockdown. Additionally, Co-IP, ChIP-qPCR and GluMS-qPCR further illustrated that STAT3 recruited and physically interacted with TET2 to activate STAT3 target genes. As expected, the effects of TET2 overexpression were completely suppressed by STAT3 silencing in vitro. Conclusions Our study suggests that the deficiency of TET2 in endothelial cells impairs angiogenesis via suppression of the STAT3 signaling pathway. These findings give solid evidence for TET2 to be a therapeutic alternative for ischemic diseases. Graphical Abstrac