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Cancer is a heterogeneous disease. Finite mixture of regression (FMR)—as an important heterogeneity analysis technique when an outcome variable is present—has been extensively employed in cancer research, revealing important differences in the associations between a cancer outcome/phenotype and covariates. Cancer FMR analysis has been based on clinical, demographic, and omics variables. A relatively recent and alternative source of data comes from histopathological images. Histopathological images have been long used for cancer diagnosis and staging. Recently, it has been shown that high-dimensional histopathological image features, which are extracted using automated digital image processing pipelines, are effective for modeling cancer outcomes/phenotypes. Histopathological imaging–environment interaction analysis has been further developed to expand the scope of cancer modeling and histopathological imaging-based analysis. Motivated by the significance of cancer FMR analysis and a still strong demand for more effective methods, in this article, we take the natural next step and conduct cancer FMR analysis based on models that incorporate low-dimensional clinical/demographic/environmental variables, high-dimensional imaging features, as well as their interactions. Complementary to many of the existing studies, we develop a Bayesian approach for accommodating high dimensionality, screening out noises, identifying signals, and respecting the “main effects, interactions” variable selection hierarchy. An effective computational algorithm is developed, and simulation shows advantageous performance of the proposed approach. The analysis of The Cancer Genome Atlas data on lung squamous cell cancer leads to interesting findings different from the alternative approaches.

Two adjacent groundwater wells on the North China Platform are used to study how earthquakes impacted aquifers. We use the response of water level to solid Earth tides to document changes after earthquakes and how aquifer and fracture properties recovered to pre‐earthquake properties. We consider two models for the phase and amplitude of water level response to the lunar diurnal (O₁) and semidiurnal (M₂) tides: a leaky aquifer model, and a model in which fracture orientation determines the response. In the leaky aquifer model, changes arise from changes in permeability and storage; in the fracture model, changes are due to changes in apparent orientation of transmissive fractures. Responses in one well are best explained by the leaky aquifer model, and can explain the large amplitude coseismic water level and permeability changes and the non‐recoverable changes after the largest earthquake. Responses in the other well are consistent with the fracture model and show little coseismic change in water level but changes in apparent fracture orientation. Larger ground motions lead to larger coseismic water level changes and longer recovery times. We propose that the well in the more permeable and shallow aquifer has less variable pore‐pressures around the well. Larger coseismic strains from water level changes may enable longer‐lasting changes in aquifer properties. We conclude that relatively high permeability aquifers are less susceptible to impacts from seismic waves, and thus have small changes in water levels and hydrogeological properties.

Gene duplication is increasingly recognized as an important mechanism for the origination of new genes, as revealed by comparative genomic analysis. However, how new duplicate genes contribute to phenotypic evolution remains largely unknown, especially in plants. Here, we identified the new gene EXOV, derived from a partial gene duplication of its parental gene EXOVL in Arabidopsis thaliana. EXOV is a species-specific gene that originated within the last 3.5 million years and shows strong signals of positive selection. Unexpectedly, RNA-sequencing analyses revealed that, despite its young age, EXOV has acquired many novel direct and indirect interactions in which the parental gene does not engage. This observation is consistent with the high, selection-driven substitution rate of its encoded protein, in contrast to the slowly evolving EXOVL, suggesting an important role for EXOV in phenotypic evolution. We observed significant differentiation of morphological changes for all phenotypes assessed in genome-edited and T-DNA insertional single mutants and in double T-DNA insertion mutants in EXOV and EXOVL. We discovered a substantial divergence of phenotypic effects by principal component analyses, suggesting neofunctionalization of the new gene. These results reveal a young gene that plays critical roles in biological processes that underlie morphological evolution in A. thaliana.

The development of pyridylidene‐Cu‐complexes and their application in Cu/Pd‐catalyzed heteroarylboration of alkenylheteroarenes is reported. The significance of 1,1′‐heteroarylalkanes as building blocks for drug discovery, as well as the straightforward and modular sequence to prepare the pyridylidene‐Cu‐complexes, makes this catalyst and it applications attractive for chemical synthesis. Furthermore, chiral variants of the pyridylidene‐Cu‐complexes have been prepared and utilized in the enantioselective arylboration of E‐alkenes, further demonstrating the value and potential of this class of catalysts.