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We present a personalized multiscale mechanics model of the left atrium (LA) to simulate its deformation throughout the cardiac cycle and drive blood flow. Our patient data-driven model tightly integrates 3D structural mechanics of the LA myocardium, incorporating both passive and active components, with a 0D closed-loop lumped parameter network (LPN)-based circulatory system model. A finite element (FE) model of LA tissue is constructed from the patient’s images, assuming uniform thickness and employing rule-based fiber directions. We then adopted a multi-step personalization approach, in which the LPN parameters with a surrogate LA model are first optimized to match cuff-based blood pressures and cardiac lumen volumes derived from time-resolved 3D gated computed tomography angiography (CTA) images. The surrogate LA pressure during passive expansion is used to estimate myocardial passive mechanics parameters and the reference unloaded configuration using an inverse finite element analysis (iFEA) framework. Finally, a robust multiscale coupling is applied between the iFEA-optimized FE model and the tuned 0D LPN model to characterize LA contraction. This effectively captures the physiological LA pressure-volume curve and reasonably aligns with the image-based cavity volumes and deformation. We then imposed the resulting simulation-predicted deformation as a moving-wall boundary condition to model atrial hemodynamics. We analyzed the model sensitivities to various simplifications to demonstrate its robustness and versatility and discussed potential future improvements. Overall, this comprehensive digital twinning platform could be applied to study LA biomechanics in health and disease and assist in devising personalized treatment plans. 

Abstract Neyman’s seminal work in 1923 has been a milestone in statistics over the century, which has motivated many fundamental statistical concepts and methodology. In this review, we delve into Neyman’s groundbreaking contribution and offer technical insights into the design and analysis of randomized experiments. We shall review the basic setup of completely randomized experiments and the classical approaches for inferring the average treatment effects. We shall, in particular, review more efficient design and analysis of randomized experiments by utilizing pretreatment covariates, which move beyond Neyman’s original work without involving any covariate. We then summarize several technical ingredients regarding randomizations and permutations that have been developed over the century, such as permutational central limit theorems and Berry–Esseen bounds, and we elaborate on how these technical results facilitate the understanding of randomized experiments. The discussion is also extended to other randomized experiments including rerandomization, stratified randomized experiments, matched pair experiments, and cluster randomized experiments. 

Abstract While enantioenriched alcohols are highly significant in medicinal chemistry, total synthesis, and materials science, the stereoselective synthesis of tertiary alcohols with two adjacent stereocenters remains a formidable challenge. In this study, we present a dual catalysis approach utilizing photoredox and nickel catalysts to enable the unprecedented chemoselective functionalization of tertiary allylic C−H bonds in allyl ethers instead of cleaving the C−O bond. The resulting allyl‐Ni intermediates can undergo coupling with various aldehydes, facilitating a novel enantioconvergent approach to access extensively functionalized homoallylicsec,tert‐vicinal diols frameworks. This protocol exhibits nice tolerance towards functional groups, a broad scope of substrates, excellent diastereo‐ and enantioselectivity (up to 20 : 1 dr, 99 %ee). Mechanistic studies suggested that allyl‐Ni^IIacts as the nucleophilic species in the coupling reaction with carbonyls. 

Abstract The tree shrew (Tupaia belangeri) is a promising emerging model organism in biomedical studies, notably due to their evolutionary proximity to primates. To enhance our understanding of how DNA methylation is implicated in regulation of gene expression and the X chromosome inactivation (XCI) in tree shrew brains, here we present their first genome-wide, single-base-resolution methylomes integrated with transcriptomes from prefrontal cortices. We discovered both divergent and conserved features of tree shrew DNA methylation compared to that of other mammals. DNA methylation levels of promoter and gene body regions are negatively correlated with gene expression, consistent with patterns in other mammalian brains studied. Comparing DNA methylation patterns of the female and male X chromosomes, we observed a clear and significant global reduction (hypomethylation) of DNA methylation across the entire X chromosome in females. Our data suggests that the female X hypomethylation does not directly contribute to the gene silencing of the inactivated X chromosome nor does it significantly drive sex-specific gene expression of tree shrews. However, we identified a putative regulatory region in the 5’ end of the X inactive specific transcript (Xist)gene, a key gene for XCI, whose pattern of differential DNA methylation strongly relate to its differential expression between male and female tree shrews. We show that differential methylation of this region is conserved across different species. Moreover, we provide evidence suggesting that the observed difference between human and tree shrew X-linked promoter methylation is associated with the difference in genomic CpG contents. Our study offers novel information on genomic DNA methylation of tree shrews, as well as insights into the evolution of X chromosome regulation in mammals.