BACKGROUND Despite the well-defined role of minimal residual disease (MRD) monitoring by real-time quantitative polymerase chain reaction (RT-PCR) for RUNX1/RUNX1T1 and CBFB-MYH11 transcripts in core binding factor (CBF) acute myeloid leukemia (AML) after intensive chemotherapy, there has been a paucity of data assessing the utility of MRD monitoring at and after allogeneic hematopoietic stem cell transplantation (HSCT). METHODS Patients with CBF AML who underwent HSCT in complete remission (first or second) from January 2007 through December 2018 were included in this analysis. RESULTS MRD by polymerase chain reaction at HSCT was assessed in 50 of 76 patients, and 44 (88%) had evidence of MRD (MRDpos). MRDpos patients had 3-year overall survival (OS) and leukemia-free survival (LFS) rates of 69.3% and 66.3%, respectively. Six MRD-negative patients had 3-year OS and LFS rates of 100% and 100%, respectively. Thirty-five of the 70 evaluable patients (50%) had a day +100 MRD assessment by RT-PCR, and 14 (40%) were MRDpos. The presence of MRD by RT-PCR on day +100 was not associated with lower estimates of LFS (75% vs 82.2%; P = .3) but was associated with a higher relapse incidence, although the difference did not reach statistical significance (27.6% vs 9.7%; P = .2). CONCLUSIONS Durable complete remissions can be achieved in patients with CBF AML with HSCT even if they are MRDpos by RT-PCR at HSCT. The clinical impact of frequent MRD monitoring for identifying a group at high risk for early relapse and then for determining the best time point for therapeutic interventions to prevent impending relapse warrants investigation in prospectively designed clinical trials. © 2020 American Cancer Society.BACKGROUND Approximately 60% to 80% of people with Parkinson’s disease (PD) experience cognitive impairment that impacts on their quality of life. Cognitive decline is a core feature of the disease and can often present before the onset of motor symptoms. Cognitive training may be a useful non-pharmacological intervention that could help to maintain or improve cognition and quality of life for people with PD dementia (PDD) or PD-related mild cognitive impairment (PD-MCI). OBJECTIVES To determine whether cognitive training (targeting single or multiple domains) improves cognition in people with PDD and PD-MCI or other clearly defined forms of cognitive impairment in people with PD. SEARCH METHODS We searched the Cochrane Dementia and Cognitive Improvement Group Trials Register (8 August 2019), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, and PsycINFO. We searched reference lists and trial registers, searched relevant reviews in the area and conference proceedings. We aof cognitive training before conclusions can be drawn about the effectiveness of cognitive training for people with PDD and PD-MCI. Studies should use formal criteria to diagnose cognitive impairments, and there is a particular need for more studies testing the efficacy of cognitive training in people with PDD. Copyright © 2020 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.The statistical practice of modeling interaction with two linear main effects and a product term is ubiquitous in the statistical and epidemiological literature. Most data modelers are aware that the misspecification of main effects can potentially cause severe type I error inflation in tests for interactions, leading to spurious detection of interactions. However, modeling practice has not changed. In this article, we focus on the specific situation where the main effects in the model are misspecified as linear terms and characterize its impact on common tests for statistical interaction. We then propose some simple alternatives that fix the issue of potential type I error inflation in testing interaction due to main effect misspecification. We show that when using the sandwich variance estimator for a linear regression model with a quantitative outcome and two independent factors, both the Wald and score tests asymptotically maintain the correct type I error rate. However, if the independence assumption doetwo examples of interaction analysis in support of our results. © 2020 John Wiley & Sons, Ltd.Catalytic diastereo- and enantioselective preparation of complex tertiary homoallylic alcohols containing a vicinal quaternary carbon stereogenic center and a versatile alkenylboronic ester is disclosed. Transformations are promoted by 5 mol % of a readily available copper catalyst bearing a bulky monodentate phosphoramidite ligand, which is essential for attaining both high dr and er. Reactions proceed with a wide variety of ketones and allylic 1,1-diboronate reagents that allows for the efficient preparation of diverse array of molecular scaffolds. selleck © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.We outline a methodology for efficiently computing the electromagnetic response of molecular ensembles. The methodology is based on the link that we establish between quantum-chemical simulations and the transfer matrix (T-matrix) approach, a common tool in physics and engineering. We exemplify and analyze the accuracy of the methodology by computing the T-matrix of a cross-like arrangement of four copies of a chiral molecule from the time-dependent Hartree-Fock theory simulation data of a single molecule, and then computing the circular dichroism of the cross. The results are in very good agreement with full quantum-mechanical calculations on the cross. Importantly, the choice of computing circular dichroism is arbitrary Any kind of electromagnetic response of an object can be computed from its T-matrix. We also show, by means of another example, how the methodology can be used to predict experimental measurements on a molecular material of macroscopic dimensions. This is possible because, once the T-matrices of the individual components of an ensemble are known, the electromagnetic response of the ensemble can be efficiently computed. This holds for arbitrary arrangements of a large number of molecules, as well as for periodic or aperiodic molecular arrays. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.