Hybrid Chaplygin gas and phantom divide crossing

Hybrid Chaplygin gas model is put forward, in which the gases play the role of dark energy. For this model the coincidence problem is greatly alleviated. The effective equation of state of the dark energy may cross the phantom divide $w=-1$. Furthermore, the crossing behaviour is decoupled from any gravity theories. In the present model, $w<-1$ is only a transient behaviour. There is a de Sitter attractor in the future infinity. Hence, the big rip singularity, which often afflicts the models with matter whose effective equation of state less than -1, is naturally disappear. There exist stable scaling solutions, both at the early universe and the late universe. We discuss the perturbation growth of this model. We find that the index is consistent with observations.Comment: 11 pages, 4 figures, V3: discussions on the perturbation growth added, V4: minor corrections, to match the published versio

Jmjd3-Mediated H3K27me3 Dynamics Orchestrate Brown Fat Development and Regulate White Fat Plasticity

SummaryProgression from brown preadipocytes to adipocytes engages two transcriptional programs: the expression of adipogenic genes common to both brown fat (BAT) and white fat (WAT), and the expression of BAT-selective genes. However, the dynamics of chromatin states and epigenetic enzymes involved remain poorly understood. Here we show that BAT development is selectively marked and guided by repressive H3K27me3 and is executed by its demethylase Jmjd3. We find that a significant subset of BAT-selective genes, but not common fat genes or WAT-selective genes, are demarcated by H3K27me3 in both brown and white preadipocytes. Jmjd3-catalyzed removal of H3K27me3, in part through Rreb1-mediated recruitment, is required for expression of BAT-selective genes and for development of beige adipocytes both in vitro and in vivo. Moreover, gain- and loss-of-function Jmjd3 transgenic mice show age-dependent body weight reduction and cold intolerance, respectively. Together, we identify an epigenetic mechanism governing BAT fate determination and WAT plasticity

DNA methylation directs genomic localization of Mbd2 and Mbd3 in embryonic stem cells

Cytosine methylation is an epigenetic and regulatory mark that functions in part through recruitment of chromatin remodeling complexes containing methyl-CpG binding domain (MBD) proteins. Two MBD proteins, Mbd2 and Mbd3, were previously shown to bind methylated or hydroxymethylated DNA, respectively; however, both of these findings have been disputed. Here, we investigated this controversy using experimental approaches and re-analysis of published data and find no evidence for methylation-independent functions of Mbd2 or Mbd3. We show that chromatin localization of Mbd2 and Mbd3 is highly overlapping and, unexpectedly, we find Mbd2 and Mbd3 are interdependent for chromatin association. Further investigation reveals that both proteins are required for normal levels of cytosine methylation and hydroxymethylation in murine embryonic stem cells. Furthermore, Mbd2 and Mbd3 regulate overlapping sets of genes that are also regulated by DNA methylation/hydroxymethylation factors. These findings reveal an interdependent regulatory mechanism mediated by the DNA methylation machinery and its readers

The coordinate actions of calcineurin and Hog1 mediate the stress response through multiple nodes of the cell cycle network

Upon exposure to environmental stressors, cells transiently arrest the cell cycle while they adapt and restore homeostasis. A challenge for all cells is to distinguish between stress signals and coordinate the appropriate adaptive response with cell cycle arrest. Here we investigate the role of the phosphatase calcineurin (CN) in the stress response and demonstrate that CN activates the Hog1/p38 pathway in both yeast and human cells. In yeast, the MAPK Hog1 is transiently activated in response to several well-studied osmostressors. We show that when a stressor simultaneously activates CN and Hog1, CN disrupts Hog1-stimulated negative feedback to prolong Hog1 activation and the period of cell cycle arrest. Regulation of Hog1 by CN also contributes to inactivation of multiple cell cycle-regulatory transcription factors (TFs) and the decreased expression of cell cycle-regulated genes. CN-dependent downregulation of G1/S genes is dependent upon Hog1 activation, whereas CN inactivates G2/M TFs through a combination of Hog1-dependent and -independent mechanisms. These findings demonstrate that CN and Hog1 act in a coordinated manner to inhibit multiple nodes of the cell cycle-regulatory network. Our results suggest that crosstalk between CN and stress-activated MAPKs helps cells tailor their adaptive responses to specific stressors

PDE-Based 3D Surface Reconstruction from Multi-View 2D Images

Partial differential equation (PDE) based surfaces own a lot of advantages, compared to other types of 3D representation. For instance, fewer variables are required to represent the same 3D shape; the position, tangent, and even curvature continuity between PDE surface patches can be naturally maintained when certain conditions are satisfied, and the physics-based nature is also kept. Although some works applied implicit PDEs to 3D surface reconstruction from images, there is little work on exploiting the explicit solutions of PDE to this topic, which is more efficient and accurate. In this paper, we propose a new method to apply the explicit solutions of a fourth-order partial differential equation to surface reconstruction from multi-view images. The method includes two stages: point clouds data are extracted from multi-view images in the first stage, which is fol-lowed by PDE-based surface reconstruction from the obtained point clouds data. Our computational experiments show that the reconstructed PDE surfaces exhibit good quality and can recover the ground truth with high accuracy. A comparison between various solutions with different com-plexity to the fourth-order PDE is also made to demonstrate the power and flexibility of our proposed explicit PDE for surface reconstruction from images

Regulation of X-linked gene expression during early mouse development by

Mammalian X-linked gene expression is highly regulated as female cells contain two and male one X chromosome (X). To adjust the X gene dosage between genders, female mouse preimplantation embryos undergo an imprinted form of X chromosome inactivation (iXCI) that requires both Rlim (also known as Rnf12) and the long non-coding RNA Xist. Moreover, it is thought that gene expression from the single active X is upregulated to correct for bi-allelic autosomal (A) gene expression. We have combined mouse genetics with RNA-seq on single mouse embryos to investigate functions of Rlim on the temporal regulation of iXCI and Xist. Our results reveal crucial roles of Rlim for the maintenance of high Xist RNA levels, Xist clouds and X-silencing in female embryos at blastocyst stages, while initial Xist expression appears Rlim-independent. We find further that X/A upregulation is initiated in early male and female preimplantation embryos

ED2IF2-Net: Learning Disentangled Deformed Implicit Fields and Enhanced Displacement Fields from Single Images Using Pyramid Vision Transformer

There has emerged substantial research in addressing single-view 3D reconstruction and the majority of the state-of-the-art implicit methods employ CNNs as the backbone network. On the other hand, transformers have shown remarkable performance in many vision tasks. However, it is still unknown whether transformers are suitable for single-view implicit 3D reconstruction. In this paper, we propose the first end-to-end single-view 3D reconstruction network based on the Pyramid Vision Transformer (PVT), called (Formula presented.) -Net, which disentangles the reconstruction of an implicit field into the reconstruction of topological structures and the recovery of surface details to achieve high-fidelity shape reconstruction. (Formula presented.) -Net uses a Pyramid Vision Transformer encoder to extract multi-scale hierarchical local features and a global vector of the input single image, which are fed into three separate decoders. A coarse shape decoder reconstructs a coarse implicit field based on the global vector, a deformation decoder iteratively refines the coarse implicit field using the pixel-aligned local features to obtain a deformed implicit field through multiple implicit field deformation blocks (IFDBs), and a surface detail decoder predicts an enhanced displacement field using the local features with hybrid attention modules (HAMs). The final output is a fusion of the deformed implicit field and the enhanced displacement field, with four loss terms applied to reconstruct the coarse implicit field, structure details through a novel deformation loss, overall shape after fusion, and surface details via a Laplacian loss. The quantitative results obtained from the ShapeNet dataset validate the exceptional performance of (Formula presented.) -Net. Notably, (Formula presented.) -Net-L stands out as the top-performing variant, exhibiting the highest mean IoU, CD, EMD, ECD-3D, and ECD-2D scores, reaching impressive values of 61.1, 7.26, 2.51, 6.08, and 1.84, respectively. The extensive experimental evaluations consistently demonstrate the state-of-the-art capabilities of (Formula presented.) -Net in terms of reconstructing topological structures and recovering surface details, all while maintaining competitive inference time