Nonparametric Estimation of the Bivariate Recurrence Time Distribution

This paper considers statistical models in which two different types of events, such as the diagnosis of a disease and the remission of the disease, occur alternately over time and are observed subject to right censoring. We propose nonparametric estimators for the joint distribution of bivariate recurrence times and the marginal distribution of the first recurrence time. In general, the marginal distribution of the second recurrence time cannot be estimated due to an identifiability problem, but a conditional distribution of the second recurrence time can be estimated non-parametrically. In literature, statistical methods have been developed to estimate the joint distribution of bivariate recurrence times based on data of the first pair of censored bivariate recurrence times. These methods are efficient in the current model because recurrence times of higher orders are not used. Asymptotic properties of the estimators are established. Numerical studies demonstrate the estimator performs well with practical sample sizes. We apply the proposed method to a Denmark psychiatric case register data set for illustration of the methods and theory

Joint Modeling and Estimation for Recurrent Event Processes and Failure Time Data

Recurrent event data are commonly encountered in longitudinal follow-up studies related to biomedical science, econometrics, reliability, and demography. In many studies, recurrent events serve as important measurements for evaluating disease progression, health deterioration, or insurance risk. When analyzing recurrent event data, an independent censoring condition is typically required for the construction of statistical methods. Nevertheless, in some situations, the terminating time for observing recurrent events could be correlated with the recurrent event process and, as a result, the assumption of independent censoring is violated. In this paper, we consider joint modeling of a recurrent event process and a failure time in which a common subject-specific latent variable is used to model the association between the intensity of the recurrent event process and the hazard of the failure time. The proposed joint model is flexible in that no parametric assumptions on the distributions of censoring times and latent variables are made and, under the model, informative censoring is allowed for observing both the recurrent events and failure times. We propose a ‘borrow-strength estimation procedure’ by first estimating the value of the latent variable from recurrent event data, and next using the estimated value in the failure time model. Some interesting implications and trajectories of the proposed model will be presented. Properties of the regression parameter estimates and the estimated baseline cumulative hazard functions are also studied

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users

Internationalization propensity in family-controlled public firms in emerging markets: The effects of family ownership, governance, and top management team heterogeneity

Internationalization propensity is a growing issue faced by family firms. This study contributes to the family business literature by developing a conceptual framework that can identify the family and managerial determinants that affect the extensiveness of internationalization. Drawing on the socioemotional wealth and upper echelon perspectives, it empirically examines the association among family heterogeneity (i.e., family participation is heterogeneous in terms of ownership and governance oversight), top management team (TMT) heterogeneity (i.e., the TMT’s background is heterogeneous in terms of its overseas education and industry experience), and internationalization propensity in publicly traded enterprises. The analysis of data collected from 105 public firms in Taiwan shows that active family participation in ownership and governance oversight and TMT overseas industry experience heterogeneity are significantly and positively associated with internationalization propensity. However, family ownership is found to be significantly but negatively associated with internationalization propensity. We finally discuss the implications of the presented findings for practitioners and organizational theorists

Ferulic Acid Induces Th1 Responses by Modulating the Function of Dendritic Cells and Ameliorates Th2-Mediated Allergic Airway Inflammation in Mice

This study investigated the immunomodulatory effects of ferulic acid (FA) on antigen-presenting dendritic cells (DCs) in vitro and its antiallergic effects against ovalbumin- (OVA-) induced Th2-mediated allergic asthma in mice. The activation of FA-treated bone marrow-derived DCs by lipopolysaccharide (LPS) stimulation induced a high level of interleukin- (IL-) 12 but reduced the expression levels of the proinflammatory cytokines IL-1β, IL-6, and tumor necrosis factor- (TNF-) α. Compared to control-treated DCs, FA significantly enhanced the expressions of Notch ligand Delta-like 4 (Dll4), MHC class II, and CD40 molecules by these DCs. Furthermore, these FA-treated DCs enhanced T-cell proliferation and Th1 cell polarization. In animal experiments, oral administration of FA reduced the levels of OVA-specific immunoglobulin E (IgE) and IgG1 and enhanced IgG2a antibody production in serum. It also ameliorated airway hyperresponsiveness and attenuated eosinophilic pulmonary infiltration in dose-dependent manners. In addition, FA treatment inhibited the production of eotaxin, Th2 cytokines (IL-4, IL-5, and IL-13), and proinflammatory cytokines but promoted the Th1 cytokine interferon- (IFN-) γ production in bronchoalveolar lavage fluid (BALF) and the culture supernatant of spleen cells. These findings suggest that FA exhibits an antiallergic effect via restoring Th1/Th2 imbalance by modulating DCs function in an asthmatic mouse model

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington’s Disease

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington’s Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts. To further assess the associated gray matter damage, diffusion tensor-derived indices were measured from regions of interest located in the basal ganglia. Diffusion weighted images were acquired from 12 patients with HD and 12 healthy unrelated controls using a 3 Tesla scanner. Reductions in fixel-derived metrics occurs in major white matter tracts, noticeably in corpus callosum, internal capsule, and the corticospinal tract, which were closely co-localized with the regions of increased diffusivity in basal ganglia. These changes in diffusion can be attributed to potential axonal degeneration. Fixel-based analysis is effective in studying white matter tractography and fiber changes in HD

Deactivation of TBP contributes to SCA17 pathogenesis

Spinocerebellar ataxia type 17 (SCA17) is an autosomal dominant cerebellar ataxia caused by the expansion of polyglutamine (polyQ) within the TATA box-binding protein (TBP). Previous studies have shown that polyQexpanded TBP forms neurotoxic aggregates and alters downstream genes. However, how expanded polyQ tracts affect the function of TBP and the link between dysfunctional TBP and SCA17 is not clearly understood. In this study, we generated novel Drosophila models for SCA17 that recapitulate pathological features such as aggregate formation, mobility defects and premature death. In addition to forming neurotoxic aggregates, we determined that polyQ-expanded TBP reduces its own intrinsic DNA-binding and transcription abilities. Dysfunctional TBP also disrupts normal TBP function. Furthermore, heterozygous dTbp amorph mutant flies exhibited SCA17-like phenotypes and flies expressing polyQ-expanded TBP exhibited enhanced retinal degeneration, suggesting that loss of TBP function may contribute to SCA17 pathogenesis. We further determined that the downregulation of TBP activity enhances retinal degeneration in SCA3 and Huntington's disease fly models, indicating that the deactivation of TBP is likely to play a common role in polyQ-induced neurodegeneration

Genome Features and Secondary Metabolites Biosynthetic Potential of the Class Ktedonobacteria

The prevalence of antibiotic resistance and the decrease in novel antibiotic discovery in recent years necessitates the identification of potentially novel microbial resources to produce natural products. Ktedonobacteria, a class of deeply branched bacterial lineage in the ancient phylum Chloroflexi, are ubiquitous in terrestrial environments and characterized by their large genome size and complex life cycle. These characteristics indicate Ktedonobacteria as a potential active producer of bioactive compounds. In this study, we observed the existence of a putative “megaplasmid,” multiple copies of ribosomal RNA operons, and high ratio of hypothetical proteins with unknown functions in the class Ktedonobacteria. Furthermore, a total of 104 antiSMASH-predicted putative biosynthetic gene clusters (BGCs) for secondary metabolites with high novelty and diversity were identified in nine Ktedonobacteria genomes. Our investigation of domain composition and organization of the non-ribosomal peptide synthetase and polyketide synthase BGCs further supports the concept that class Ktedonobacteria may produce compounds structurally different from known natural products. Furthermore, screening of bioactive compounds from representative Ktedonobacteria strains resulted in the identification of broad antimicrobial activities against both Gram-positive and Gram-negative tested bacterial strains. Based on these findings, we propose the ancient, ubiquitous, and spore-forming Ktedonobacteria as a versatile and promising microbial resource for natural product discovery

Osteoporosis Recovery by Antrodia camphorata

Antrodia camphorata has previously demonstrated the efficacy in treating cancer and anti-inflammation. In this study, we are the first to evaluate Antrodia camphorata alcohol extract (ACAE) for osteoporosis recovery in vitro with preosteoblast cells (MC3T3-E1) and in vivo with an osteoporosis mouse model established in our previous studies, ovariectomized senescence accelerated mice (OVX-SAMP8). Our results demonstrated that ACAE treatment was slightly cytotoxic to preosteoblast at 25 μg/mL, by which the osteogenic gene expression (RUNX2, OPN, and OCN) was significantly upregulated with an increased ratio of OPG to RANKL, indicating maintenance of the bone matrix through inhibition of osteoclastic pathway. Additionally, evaluation by Alizarin Red S staining showed increased mineralization in ACAE-treated preosteoblasts. For in vivo study, our results indicated that ACAE inhibits bone loss and significantly increases percentage bone volume, trabecular bone number, and bone mineral density in OVX-SAMP8 mice treated with ACAE. Collectively, in vitro and in vivo results showed that ACAE could promote osteogenesis and prevent bone loss and should be considered an evidence-based complementary and alternative medicine for osteoporosis therapy through the maintenance of bone health