Objectives Isradipine is a dihydropyridine calcium channel inhibitor that has demonstrated concentration‐dependent neuroprotective effects in animal models of Parkinson’s disease (PD) but failed to show efficacy in a phase 3 clinical trial. The objectives of this study were to model the plasma pharmacokinetics of isradipine in study participants from the phase 3 trial; and, to investigate associations between drug exposure and longitudinal clinical outcome measures of PD progression. Methods Plasma samples from nearly all study participants randomized to immediate‐release isradipine 5‐mg twice daily (166 of 170) were collected for population pharmacokinetic modeling. Estimates of isradipine exposure included apparent oral clearance and area under the concentration‐time curve. Isradipine exposure parameters were tested for correlations with 36‐month changes in disease severity clinical assessment scores, and time‐to‐event analyses for initiation of antiparkinson therapy. Results Isradipine exposures did not correlate with the primary clinical outcome, changes in the antiparkinson therapy‐adjusted Unified Parkinson’s Disease Rating Scale parts I–III score over 36 months (Spearman rank correlation coefficient, rs: 0.09, P = 0.23). Cumulative levodopa equivalent dose at month 36 was weakly correlated with isradipine plasma clearance (rs: 0.18, P = 0.035). This correlation was sex dependent and significant in males, but not females. Those with higher isradipine exposure had decreased risk of needing antiparkinson treatment over 36 months compared with placebo (hazard ratio: 0.87, 95% CI: 0.78–0.98, P = 0.02). Interpretation In this clinical trial, higher isradipine plasma exposure did not affect clinical assessment measures of PD severity but modestly decreased cumulative levodopa equivalent dose and the time needed for antiparkinson treatment initiation. Trial Registration http://ClinicalTrials.gov NCT02168842.
Women have always been underrepresented in movies and not until recently has the representation of women in movies improved. To investigate the improvement of female representation and its relationship with a movie's success, we propose a new measure, the female cast ratio, and compare it to the commonly used Bechdel test result. We employ generalized linear regression with L 1 penalty and a Random Forest model to identify the predictors that influence female representation, and evaluate the relationship between female representation and a movie's success in three aspects: revenue/budget ratio, rating, and popularity. Three important findings in our study have highlighted the difficulties women in the film industry face both upstream and downstream. First, female filmmakers, especially female screenplay writers, are instrumental for movies to have better female representation, but the percentage of female filmmakers has been very low. Second, movies that have the potential to tell insightful stories about women are often provided with lower budgets, and this usually causes the films to in turn receive more criticism. Finally, the demand for better female representation from moviegoers has also not been strong enough to compel the film industry to change, as movies that have poor female representation can still be very popular and successful in the box office.
We propose a model‐based clustering method for high‐dimensional longitudinal data via regularization in this paper. This study was motivated by the Trial of Activity in Adolescent Girls (TAAG), which aimed to examine multilevel factors related to the change of physical activity by following up a cohort of 783 girls over 10 years from adolescence to early adulthood. Our goal is to identify the intrinsic grouping of subjects with similar patterns of physical activity trajectories and the most relevant predictors within each group. The previous analyses conducted clustering and variable selection in two steps, while our new method can perform the tasks simultaneously. Within each cluster, a linear mixed‐effects model (LMM) is fitted with a doubly penalized likelihood to induce sparsity for parameter estimation and effect selection. The large‐sample joint properties are established, allowing the dimensions of both fixed and random effects to increase at an exponential rate of the sample size, with a general class of penalty functions. Assuming subjects are drawn from a Gaussian mixture distribution, model effects and cluster labels are estimated via a coordinate descent algorithm nested inside the Expectation‐Maximization (EM) algorithm. Bayesian Information Criterion (BIC) is used to determine the optimal number of clusters and the values of tuning parameters. Our numerical studies show that the new method has satisfactory performance and is able to accommodate complex data with multilevel and/or longitudinal effects.
Women have always been underrepresented in movies and not until recently do women representation in movies improve. To investigate the improvement of women representation and its relationship with a movie's success, we propose a new measure, the female cast ratio, and compare it to the commonly used Bechdel test result. We employ generalized linear regression with L1 penalty and a Random Forest model to identify the predictors that are influential on women representation, and evaluate the relationship between women representation and a movie's success in three aspects: revenue/budget ratio, rating and popularity. Three important findings in our study have highlighted the difficulties women in the film industry face in both upstream and downstream. First, female filmmakers especially female screenplay writers are instrumental for movies to have better women representation, but the percentage of female filmmakers has been very low. Second, lower budgets are often made to support movies that could tell good stories about women, and this usually cause the films to in turn receive more criticisms. Finally, the demand for better women presentation from moviegoers has also not been strong enough to compel the film industry for a change, as movies that have poor women representation can still be very popular and successful in the box office.
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