Five Simple Sequence Repeats (SSRs) were used to assess the relationship between inflorescence characteristics and their allelic variation in 53 Brassica oleracea and Brassica wild relatives (n = 9). Curd morphometric traits, such as weight (CW), height (CH), diameter (CD1), shape (CS) inflorescence curvature angle (CA), and its curd stem diameter (CD2), were measured. The aim of the work was to analyze the relationships among the allelic patterns of the SSRs primers utilized, and their status of homo or heterozygosity registered at each locus, as well as the inflorescence morphometric traits in order to individuate genomic regions stimulating the hypertrophy of this reproductive organ. The relationships found explain the diversity among B. oleracea complex species (n = 9) for the inflorescence size and structure, allowing important time reduction during the breeding process by crossing wild species, transferring useful resistance, and organoleptic and nutraceutical traits. The five SSRs loci were BoABI1, BoAP1, BoPLD1, BoTHL1, and PBCGSSRBo39. According to the allelic variation ascertained, we evaluated the heterozygosity index (H) for each SSR above cited. The results showed a significant interaction between the H index of the BoPLD1 gene and the inflorescence characteristics, summarized by the First Principal Component (PC1) (p-value = 0.0244); we ascertained a negative correlation between the H index and inflorescence characteristics, namely CW, CH, CD1, CD2, CA. The homozygosity BoPLD1 alelles, indicated by the H index, affect the inflorescence characteristics and broccoli and cauliflower yields.

Adaptive enrichment designs in clinical trials have been developed to enhance drug developments. They permit, at interim analyses during the trial, to select the sub‐populations that benefits the most from the treatment. Because of this selection, the naive maximum likelihood estimation of the treatment effect, commonly used in classical randomized controlled trials, is biased. In the literature, several methods have been proposed to obtain a better estimation of the treatments' effects in such contexts. To date, most of the works have focused on normally distributed endpoints, and some estimators have been proposed for time‐to‐event endpoints but they have not all been compared side‐by‐side. In this work, we conduct an extensive simulation study, inspired by a real case‐study in heart failure, to compare the maximum‐likelihood estimator (MLE) with an unbiased estimator, shrinkage estimators, and bias‐adjusted estimators for the estimation of the treatment effect with time‐to‐event data. The performances of the estimators are evaluated in terms of bias, variance, and mean squared error. Based on the results, along with the MLE, we recommend to provide the unbiased estimator and the single‐iteration bias‐adjusted estimator: the former completely eradicates the selection bias, but is highly variable with respect to a naive estimator; the latter is less biased than the MLE estimator and only slightly more variable.

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