Pollen's practically-indestructible shell structure has long inspired the biomimetic design of organic materials. However, there is limited understanding of how the mechanical, chemical, and adhesion properties of pollen are biologically controlled and whether strategies can be devised to manipulate pollen beyond natural performance limits. Here, we report a facile approach to transform pollen grains into soft microgel by remodeling pollen shells. Marked alterations to the pollen substructures led to environmental stimuli responsiveness, which reveal how the interplay of substructure-specific material properties dictates microgel swelling behavior. Our investigation of pollen grains from across the plant kingdom further showed that microgel formation occurs with tested pollen species from eudicot plants. Collectively, our experimental and computational results offer fundamental insights into how tuning pollen structure can cause dramatic alterations to material properties, and inspire future investigation into understanding how the material science of pollen might influence plant reproductive success.

Ceiling and floor effects are often observed in social and behavioral science. The current study examines ceiling/floor effects in the context of the t-test and ANOVA, two frequently used statistical methods in experimental studies. Our literature review indicated that most researchers treated ceiling or floor data as if these data were true values, and that some researchers used statistical methods such as discarding ceiling or floor data in conducting the t-test and ANOVA. The current study evaluates the performance of these conventional methods for t-test and ANOVA with ceiling or floor data. Our evaluation also includes censored regression with regard to its capacity for handling ceiling/floor data. Furthermore, we propose an easy-to-use method that handles ceiling or floor data in t-tests and ANOVA by using properties of truncated normal distributions. Simulation studies were conducted to compare the performance of the methods in handling ceiling or floor data for t-test and ANOVA. Overall, the proposed method showed greater accuracy in effect size estimation and better-controlled Type I error rates over other evaluated methods. We developed an easy-to-use software package and web applications to help researchers implement the proposed method. Recommendations and future directions are discussed.

Natural compounds derived from plants have been an important source of numerous clinically useful anticancer agents. Nevertheless, limited studies indicate that xanthohumol (XN), a major prenylated flavonoid in hop plants (Humulus lupulus), may possess anticarcinogenic properties. The purpose of the present study was to clarify the antitumorigenic effects and the underlying mechanism of XN on breast cancer in vivo and in vitro. A 4T1 breast tumor mouse model was used in the present study to investigate XN suppression of tumor growth as detected by tumorigenicity assays in vivo. In addition, in vitro studies revealed that XN significantly decreased cell viability, induced G0/G1 cell cycle arrest and apoptosis in MCF-7 and MDA-MB-231 cells, as confirmed by an MTT assay, flow cytometry and western blot analysis, indicating anticarcinogenic activity of XN against breast cancer. Furthermore, immunohistochemistry was performed to confirm the inactivation of the Notch signaling pathway, Notch 1 and Ki-67, in vivo; consistently, XN caused decreased activation of the Notch signaling pathway and apoptotic regulators B-cell lymphoma-2 (Bcl-2), Bcl-extra large and caspase 3, as determined by western blot analysis in vitro. This study suggests that XN may potentially be useful as a chemopreventive agent during breast hyperplasia and carcinogenesis, acting via the regulation of Notch associated apoptotic regulators in vivo and in vitro.

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