An efficient kk-means-type algorithm for clustering datasets with incomplete records

The $k$-means algorithm is arguably the most popular nonparametric clustering method but cannot generally be applied to datasets with incomplete records. The usual practice then is to either impute missing values under an assumed missing-completely-at-random mechanism or to ignore the incomplete records, and apply the algorithm on the resulting dataset. We develop an efficient version of the $k$-means algorithm that allows for clustering in the presence of incomplete records. Our extension is called $k_m$-means and reduces to the $k$-means algorithm when all records are complete. We also provide initialization strategies for our algorithm and methods to estimate the number of groups in the dataset. Illustrations and simulations demonstrate the efficacy of our approach in a variety of settings and patterns of missing data. Our methods are also applied to the analysis of activation images obtained from a functional Magnetic Resonance Imaging experiment.Comment: 21 pages, 12 figures, 3 tables, in press, Statistical Analysis and Data Mining -- The ASA Data Science Journal, 201

Root Type-Specific Reprogramming of Maize Pericycle Transcriptomes by Local High Nitrate Results in Disparate Lateral Root Branching Patterns

The adaptability of root system architecture to unevenly distributed mineral nutrients in soil is a key determinant of plant performance. The molecular mechanisms underlying nitrate dependent plasticity of lateral root branching across the different root types of maize are only poorly understood. In this study, detailed morphological and anatomical analyses together with cell type-specific transcriptome profiling experiments combining laser capture microdissection with RNA-seq were performed to unravel the molecular signatures of lateral root formation in primary, seminal, crown, and brace roots of maize (Zea mays) upon local high nitrate stimulation. The four maize root types displayed divergent branching patterns of lateral roots upon local high nitrate stimulation. In particular, brace roots displayed an exceptional architectural plasticity compared to other root types. Transcriptome profiling revealed root type-specific transcriptomic reprogramming of pericycle cells upon local high nitrate stimulation. The alteration of the transcriptomic landscape of brace root pericycle cells in response to local high nitrate stimulation was most significant. Root type-specific transcriptome diversity in response to local high nitrate highlighted differences in the functional adaptability and systemic shoot nitrogen starvation response during development. Integration of morphological, anatomical, and transcriptomic data resulted in a framework underscoring similarity and diversity among root types grown in heterogeneous nitrate environments

Abemaciclib in Combination With Endocrine Therapy for Patients With Hormone Receptor-Positive, HER2-Negative Metastatic Breast Cancer: A Phase 1b Study

Background Cyclin-dependent kinases (CDK) 4 and 6 regulate G1 to S cell cycle progression and are often altered in cancers. Abemaciclib is a selective inhibitor of CDK4 and CDK6 approved for administration on a continuous dosing schedule as monotherapy or as combination therapy with an aromatase inhibitor or fulvestrant in patients with advanced or metastatic breast cancer. This Phase 1b study evaluated the safety and tolerability, pharmacokinetics, and antitumor activity of abemaciclib in combination with endocrine therapy for metastatic breast cancer (MBC), including aromatase inhibitors (letrozole, anastrozole, or exemestane) or tamoxifen. Patients and Methods Women ≥18 years old with hormone receptor positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) MBC were eligible for enrollment. Eligibility included measurable disease or non-measurable but evaluable bone disease by Response Evaluation Criteria in Solid Tumours (RECIST) v1.1, Eastern Cooperative Oncology Group performance status 0–1, and no prior chemotherapy for metastatic disease. Adverse events were graded by the National Cancer Institute Common Terminology Criteria for Adverse Events v4.0 and tumor response were assessed by RECIST v1.1. Results Sixty-seven patients were enrolled and received abemaciclib 200 mg every 12 hours in combination with letrozole (Part A, n=20), anastrozole (Part B, n=16), tamoxifen (Part C, n=16), or exemestane (Part D, n=15). The most common treatment-emergent adverse events (TEAE) were diarrhea, fatigue, nausea, and abdominal pain. Grade 4 TEAEs were reported in five patients (one each with hyperglycemia, hypertension, neutropenia, procedural hemorrhage, and sepsis). There was no effect of abemaciclib or endocrine therapy on the pharmacokinetics of any combination study drug. Across all treated patients, the median progression-free survival was 25.4 months (95% confidence interval: 18.0, 35.8). The objective response rate was 38.9% in 36 patients with measurable disease. Conclusions Abemaciclib in combination with multiple endocrine therapy options exhibited manageable safety and promising antitumor activity in patients with HR+, HER2- MBC. Clinical Trial Registration https://clinicaltrials.gov/, identifier NCT0205713