We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positively associated, which is modeled by the so‐called tail ...dependent coefficient. We construct an estimator of the marginal expected shortfall, which is shown to be asymptotically normal. The finite sample performance of the estimator is investigated in a small simulation study. The method is also applied to estimate the expected amount of rainfall at a weather station given that there is a once every 100 years rainfall at another weather station nearby.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Random forest is a popular prediction approach for handling high dimensional covariates. However, it often becomes infeasible to interpret the obtained high dimensional and non-parametric model. ...Aiming for an interpretable predictive model, we develop a forward variable selection method using the continuous ranked probability score (CRPS) as the loss function. eOur stepwise procedure selects at each step a variable that minimizes the CRPS risk and a stopping criterion for selection is designed based on an estimation of the CRPS risk difference of two consecutive steps. We provide mathematical motivation for our method by proving that in a population sense, the method attains the optimal set. In a simulation study, we compare the performance of our method with an existing variable selection method, for different sample sizes and correlation strength of covariates. Our method is observed to have a much lower false positive rate. We also demonstrate an application of our method to statistical post-processing of daily maximum temperature forecasts in the Netherlands. Our method selects about 10% covariates while retaining the same predictive power.
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3.
Rodent models of AKI-CKD transition Fu, Ying; Tang, Chengyuan; Cai, Juan ...
American journal of physiology. Renal physiology,
10/2018, Volume:
315, Issue:
4
Journal Article
Peer reviewed
Open access
Acute kidney injury (AKI) is a contributing factor in the development and progression of chronic kidney disease (CKD). Despite rapid progresses, the mechanism underlying AKI-CKD transition remains ...largely unclear. Animal models recapitulating this process are crucial to the research of the pathophysiology of AKI-CKD transition and the development of effective therapeutics. In this review, we present the commonly used rodent models of AKI-CKD transition, including bilateral ischemia-reperfusion injury (IRI), unilateral IRI, unilateral IRI with contralateral nephrectomy, multiple episodes of IRI, and repeated treatment of low-dose cisplatin, diphtheria toxin, aristolochic acid, or folic acid. The main merits and pitfalls of these models are also discussed. This review provides helpful information for establishing reliable and clinically relevant models for studying post-AKI development of chronic renal pathologies and the progression to CKD.
Aiming to estimate extreme precipitation forecast quantiles, we propose a nonparametric regression model that features a constant extreme value index. Using local linear quantile regression and an ...extrapolation technique from extreme value theory, we develop an estimator for conditional quantiles corresponding to extreme high probability levels. We establish uniform consistency and asymptotic normality of the estimators. In a simulation study, we examine the performance of our estimator on finite samples in comparison with a method assuming linear quantiles. On a precipitation data set in the Netherlands, these estimators have greater predictive skill compared to the upper member of ensemble forecasts provided by a numerical weather prediction model.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This article focuses on the finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering problem for discrete‐time singular systems with randomly occurring nonlinear perturbations. The ...main purpose is to design a filter, which ensures the singular error system is stochastically finite‐time bounded and satisfies mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive performance. By constructing an augmented matrix, the properties of matrix determinant and rank are used to prove that the singular system is regular and causal, Finsler's lemma and Projection lemma are used in the design process to acquire additional slack variable matrices, thereby enhancing the solution space with extra degrees of freedom. Then, the unknown parameters of the filter are obtained by solving the less conservative linear matrix inequalities. Finally, the feasibility of the proposed method is verified through a common numerical example and by controlling a DC motor for an inverted pendulum.
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Long non-coding RNAs (lncRNAs) possess significant regulatory functions in multiple biological and pathological processes, especially in cancer. Dysregulated lncRNAs in hepatocellular carcinoma (HCC) ...and their therapeutic applications remain unclear.
Differentially expressed lncRNA profile in HCC was constructed using TCGA data. LINC00958 expression level was examined in HCC cell lines and tissues. Univariate and multivariate analyses were performed to demonstrate the prognostic value of LINC00958. Loss-of-function and gain-of-function experiments were used to assess the effects of LINC00958 on cell proliferation, motility, and lipogenesis. Patient-derived xenograft model was established for in vivo experiments. RNA immunoprecipitation, dual luciferase reporter, biotin-labeled miRNA pull-down, fluorescence in situ hybridization, and RNA sequencing assays were performed to elucidate the underlying molecular mechanisms. We developed a PLGA-based nanoplatform encapsulating LINC00958 siRNA and evaluated its superiority for systemic administration.
We identified a lipogenesis-related lncRNA, LINC00958, whose expression was upregulated in HCC cell lines and tissues. High LINC00958 level independently predicted poor overall survival. Functional assays showed that LINC00958 aggravated HCC malignant phenotypes in vitro and in vivo. Mechanistically, LINC00958 sponged miR-3619-5p to upregulate hepatoma-derived growth factor (HDGF) expression, thereby facilitating HCC lipogenesis and progression. METTL3-mediated N
-methyladenosine modification led to LINC00958 upregulation through stabilizing its RNA transcript. A PLGA-based nanoplatform loaded with si-LINC00958 was developed for HCC systemic administration. This novel drug delivery system was controlled release, tumor targeting, safe, and presented satisfactory antitumor efficacy.
Our results delineate the clinical significance of LINC00958 in HCC and the regulatory mechanisms involved in HCC lipogenesis and progression, providing a novel prognostic indicator and promising nanotherapeutic target.
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Denote the loss return on the equity of a financial institution as X and that of the entire market as Y. For a given very small value of p>0, the marginal expected shortfall (MES) is defined as ...E{X|Y>QY(1−p)}, where QY(1−p) is the (1−p)th quantile of the distribution of Y. The MES is an important factor when measuring the systemic risk of financial institutions. For a wide non‐parametric class of bivariate distributions, we construct an estimator of the MES and establish the asymptotic normality of the estimator when p↓0, as the sample size n→∞. Since we are in particular interested in the case p=O(1/n), we use extreme value techniques for deriving the estimator and its asymptotic behaviour. The finite sample performance of the estimator and the relevance of the limit theorem are shown in a detailed simulation study. We also apply our method to estimate the MES of three large US investment banks.
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BFBNIB, FZAB, GIS, IJS, INZLJ, IZUM, KILJ, NLZOH, NMLJ, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
Three unusual austins-type meroterpenoids penicianstinoids C-E (
-
) were obtained from the mangrove-derived fungus
sp. TGM112. The structures of
-
including absolute configurations were determined ...by detailed NMR, MS spectroscopic data, X-ray diffraction analysis, and calculated electronic circular dichroism data. Penicianstinoid C (
) was the first austins-type meroterpenoid with a unique 6/6/6/5 rearranged tetracyclic skeleton possessing two unusual spirocyclic moieties (2-oxaspiro5.5undeca-4,7-dien-3-one and 6-methylene-2-oxaspiro4.5decane-1,4-dione). Penicianstinoid D (
) was an unusual austins-type meroterpenoid with a 6/6/6/6 tetracyclic skeleton containing an octahydro-2
-chromen-2-one unit. Penicianstinoid E (
) possessed a 6/5/6/6/6/5 fused hexacyclic skeleton with an uncommon five-membered ether ring system. The plausible biosynthetic pathway of
-
is also proposed. Compounds
and
inhibited the growth of newly hatched
Hubner larvae with IC
values of 100 and 200 μg/mL, respectively.
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Background Exercise intervention (EI) is a promising and economical way for elderly patients with hip fracture, but the evidence regarding effective EIs remains fragmented and controversial, and it ...is unclear which type of exercise is optimal. The purpose of this Bayesian network meta-analysis (NMA) is to compare and rank the efficacy of various EIs in elderly patients with hip fracture. Materials and methods A comprehensive literature search was performed using a systematic approach across various databases including Medline (via PubMed), CINAHL, CNKI, Web of Science, Wan Fang, Embase, VIP, Cochrane Central Register of Controlled Trials and CBM databases. The search encompasses all available records from the inception of each database until December 2022. The Inclusion literature comprises randomized controlled trials that incorporate at least one EI for elderly patients with hip fracture. We will assess the risk of bias of the studies in accordance with the Cochrane Handbook for Systematic Reviews of Interventions, and assess each evidence of outcome quality in accordance with the Grading of Recommendations Assessment, Development and Evaluation framework. The NMA will be performed by STATA 15.0 software and OpenBUGS version 3.2.3. The identification of publication bias will be accomplished through the utilization of a funnel plot. We will rank the EIs effects according to the cumulative ranking probability curve (surface under the cumulative ranking area, SUCRA). The primary outcomes will be hip function in elderly patients, and the secondary outcomes will be activities of daily living, walking capacity and balance ability of elderly patients. Trial registration PROSPERO registration number: CRD4202022340737.
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Extreme quantile regression provides estimates of conditional quantiles outside the range of the data. Classical quantile regression performs poorly in such cases since data in the tail region are ...too scarce. Extreme value theory is used for extrapolation beyond the range of observed values and estimation of conditional extreme quantiles. Based on the peaks-over-threshold approach, the conditional distribution above a high threshold is approximated by a generalized Pareto distribution with covariate dependent parameters. We propose a gradient boosting procedure to estimate a conditional generalized Pareto distribution by minimizing its deviance. Cross-validation is used for the choice of tuning parameters such as the number of trees and the tree depths. We discuss diagnostic plots such as variable importance and partial dependence plots, which help to interpret the fitted models. In simulation studies we show that our gradient boosting procedure outperforms classical methods from quantile regression and extreme value theory, especially for high-dimensional predictor spaces and complex parameter response surfaces. An application to statistical post-processing of weather forecasts with precipitation data in the Netherlands is proposed.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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