Search

Subspace deformable body simulations can be very fast, but can behave unrealistically when behaviors outside the prescribed subspace such as novel external collisions, are encountered. We address this limitation by presenting a fast, flexible new method that allows full space computation to be activated in the neighborhood of novel events while the rest of the body still computes in a subspace. We achieve this using a method we call subspace condensation , a variant on the classic static condensation precomputation. However, instead of a precomputation, we use the speed of subspace methods to perform the condensation at every frame. This approach allows the full space regions to be specified arbitrarily at runtime, and forms a natural two-way coupling with the subspace regions. While condensation is usually only applicable to linear materials, the speed of our technique enables its application to non-linear materials as well. We show the effectiveness of our approach by applying it to a variety of articulated character scenarios.

Simple Summary: High levels of the transcription factor Grainyhead-like protein 2 (GRHL2) contribute to worse outcomes for patients with breast cancer tumors that express estrogen receptor (ER). Using multiple methods to increase GRHL2 expression in breast cancer cells, we found that high GRHL2 promotes both epithelial and mesenchymal phenotypes. This is indicative of an intermediate state between epithelial and mesenchymal cells, which is associated with metastasis. We also observed that elevated GRHL2 stimulates properties characteristic of cellular plasticity, including a decrease in cellular proliferation with a reciprocal increase in dormancy and stem cell markers. Elevated levels of GRHL2 broadly changed its control of gene expression at the level of DNA and shifted nearby transcription factor binding sites from those associated with development to those associated with disease progression. These results provide a possible explanation for how elevated GRHL2 levels could contribute to poorer prognosis in ER-positive breast cancer. Estrogen receptor (ER)-positive breast cancer is characterized by late recurrences following initial treatment. The epithelial cell fate transcription factor Grainyhead-like protein 2 (GRHL2) is overexpressed in ER-positive breast cancers and is linked to poorer prognosis as compared to ER-negative breast cancers. To understand how GRHL2 contributes to progression, GRHL2 was overexpressed in ER-positive cells. We demonstrated that elevated GRHL2 imparts plasticity with stem cell- and dormancy-associated traits. RNA sequencing and immunocytochemistry revealed that high GRHL2 not only strengthens the epithelial identity but supports a hybrid epithelial to mesenchymal transition (EMT). Proliferation and tumor studies exhibited a decrease in growth and an upregulation of dormancy markers, such as NR2F1 and CDKN1B. Mammosphere assays and flow cytometry revealed enrichment of stem cell markers CD44 and ALDH1, and increased self-renewal capacity. Cistrome analyses revealed a change in transcription factor motifs near GRHL2 sites from developmental factors to those associated with disease progression. Together, these data support the idea that the plasticity and properties induced by elevated GRHL2 may provide a selective advantage to explain the association between GRHL2 and breast cancer progression. [ABSTRACT FROM AUTHOR]

The primary function of vitamin D in higher vertebrates is to regulate mineral homeostasis through direct actions on intestinal calcium (Ca) and phosphate (P) absorption, bone mineral resorption, and renal [...]

Historical functional linear models or HFLMs are a class of function‐on‐function regression models that seek to restrict the relationship between two or more time‐dependent functions, or curves, of data where one function is a natural outcome and the others are natural predictors. A natural predictor is a predictor that occurs in time before, or at most concurrently with, an outcome. The primary challenge in developing methods for HFLMs is ensuring that the time‐dependent relationship between the outcome and predictors is enforced and that no "unnatural" relationships are allowed, for example, where estimation, inference, or prediction are conducted on or using coefficients such that the outcome occurs before the predictor. A number of authors consider a variety of modeling frameworks for HFLMs. This work seeks to introduce the basic HFLM, explore the various approaches for its estimation, and discuss recent advances. This article is categorized under:Statistical Models > Linear ModelsData: Types and Structure > Time Series, Stochastic Processes, and Functional DataStatistical Models > Model Selection [ABSTRACT FROM AUTHOR]

Introduction In the early 1970s, 1,25-dihydroxyvitamin [D.sub.3] [1,25[(OH).sub.2][D.sub.3]] was identified as both the exclusive, metabolically active form of vitamin D and a key component of what proved to be an [...], The vitamin D receptor (VDR) is the single known regulatory mediator of hormonal 1,25-dihydroxyvitamin [D.sub.3] [1,25[(OH).sub.2][D.sub.3]] in higher vertebrates. It acts in the nucleus of vitamin D target cells to regulate the expression of genes whose products control diverse, cell type-specific biological functions that include mineral homeostasis. In this Review we describe progress that has been made in defining new cellular sites of action of this receptor, the mechanisms through which this mediator controls the expression of genes, the biology that ensues, and the translational impact of this receptor on human health and disease. We conclude with a brief discussion of what comes next in understanding vitamin D biology and the mechanisms that underlie its actions.