Regulation of Autophagy by Lipid Species

Ph.DDOCTOR OF PHILOSOPH

Faithful completion of images of scenic landmarks using internet images

Abstract—Previous works on image completion typically aim to produce visually plausible results rather than factually correct ones. In this paper, we propose an approach to faithfully complete the missing regions of an image. We assume that the input image is taken at a well-known landmark, so similar images taken at the same location can be easily found on the Internet. We first download thousands of images from the Internet using a text label provided by the user. Next, we apply two-step filtering to reduce them to a small set of candidate images for use as source images for completion. For each candidate image, a co-matching algorithm is used to find correspondences of both points and lines between the candidate image and the input image. These are used to find an optimal warp relating the two images. A completion result is obtained by blending the warped candidate image into the missing region of the input image. The completion results are ranked according to combination score, which considers both warping and blending energy, and the highest ranked ones are shown to the user. Experiments and results demonstrate that our method can faithfully complete images

Fault Injection based Failure Analysis of three CentOS-like Operating Systems

The reliability of operating system (OS) has always been a major concern in the academia and industry. This paper studies how to perform OS failure analysis by fault injection based on the fault mode library. Firstly, we use the fault mode generation method based on Linux abstract hierarchy structure analysis to systematically define the Linux-like fault modes, construct a Linux fault mode library and develop a fault injection tool based on the fault mode library (FIFML). Then, fault injection experiments are carried out on three commercial Linux distributions, CentOS, Anolis OS and openEuler, to identify their reliability problems and give improvement suggestions. We also use the virtual file systems of these three OSs as experimental objects, to perform fault injection at levels of Light and Normal, measure the performance of 13 common file operations before and after fault injection.Comment: 9 pages, 8 figure

DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model

We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model incorporates a triplane NeRF representation and can denoise noisy multi-view images via NeRF reconstruction and rendering, achieving single-stage 3D generation in $\sim$30s on single A100 GPU. We train \textbf{DMV3D} on large-scale multi-view image datasets of highly diverse objects using only image reconstruction losses, without accessing 3D assets. We demonstrate state-of-the-art results for the single-image reconstruction problem where probabilistic modeling of unseen object parts is required for generating diverse reconstructions with sharp textures. We also show high-quality text-to-3D generation results outperforming previous 3D diffusion models. Our project website is at: https://justimyhxu.github.io/projects/dmv3d/ .Comment: Project Page: https://justimyhxu.github.io/projects/dmv3d

ESRRB regulates glucocorticoid gene expression in mice and patients with acute lymphoblastic leukemia

Synthetic glucocorticoids (GCs), such as dexamethasone and prednisone, remain key components of therapy for patients with lymphoid malignancies. For pediatric patients with acute lymphoblastic leukemia (ALL), response to GCs remains the most reliable prognostic indicator; failure to respond to GC correlates with poor event-free survival. To uncover GC resistance mechanisms, we performed a genome-wide, survival-based short hairpin RNA screen and identified the orphan nuclear receptor estrogen-related receptor-beta (ESRRB) as a critical transcription factor that cooperates with the GC receptor (GR) to mediate the GC gene expression signature in mouse and human ALL cells. Esrrb knockdown interfered with the expression of genes that were induced and repressed by GR and resulted in GC resistance in vitro and in vivo. Dexamethasone treatment stimulated ESRRB binding to estrogen-related receptor elements (ERREs) in canonical GC-regulated genes, and H3K27Ac Hi-chromatin immunoprecipitation revealed increased interactions between GR- and ERRE-containing regulatory regions in dexamethasone-treated human T-ALL cells. Furthermore, ESRRB agonists enhanced GC target gene expression and synergized with dexamethasone to induce leukemic cell death, indicating that ESRRB agonists may overcome GC resistance in ALL, and potentially, in other lymphoid malignancies

Real-time chirality transfer monitoring from statistically random to discrete homochiral nanotubes

Real time monitoring of chirality transfer processes is necessary to better understand their kinetic properties. Herein, we monitor an ideal chirality transfer process from a statistically random distribution to a diastereomerically pure assembly in real time. The chirality transfer is based on discrete trimeric tubular assemblies of planar chiral pillar[5]arenes, achieving the construction of diastereomerically pure trimers of pillar[5]arenes through synergistic effect of ion pairing between a racemic rim-differentiated pillar[5]arene pentaacid bearing five benzoic acids on one rim and five alkyl chains on the other, and an optically resolved pillar[5]arene decaamine bearing ten amines. When the decaamine is mixed with the pentaacid, the decaamine is sandwiched by two pentaacids through ten ion pairs, initially producing a statistically random mixture of a homochiral trimer and two heterochiral trimers. The heterochiral trimers gradually dissociate and reassemble into the homochiral trimers after unit flipping of the pentaacid, leading to chirality transfer from the decaamine and producing diastereomerically pure trimers

Insight Into the Superlubricity and Self-Assembly of Liquid Crystals

Liquid crystals are promising molecular materials in the application of lubrication. Herein, the microscale solid superlubricity is accomplished by the construction of uniform and ordered self-assembly of several liquid crystals. The self-assembly structures on a highly oriented pyrolytic graphite (HOPG) surface are explicitly revealed by using scanning tunneling microscopy (STM). Meanwhile, the nanotribological performance of the self-assemblies are measured by using atomic force microscopy (AFM), revealing ultralow friction coefficients lower than 0.01. The interaction energies are calculated by density functional theory (DFT) method, indicating the positive correlation between friction coefficients and interaction strength. The effort on the self-assembly and superlubricity of liquid crystals could enhance the understanding of the nanotribological mechanism and benefit the further application of liquid crystals as lubricants

Integrated Analysis of microRNA and mRNA Transcriptome Reveals the Molecular Mechanism of \u3ci\u3eSolanum lycopersicum\u3c/i\u3e Response to \u3ci\u3eBemisia tabaci\u3c/i\u3e and \u3ci\u3eTomato chlorosis virus\u3c/i\u3e

Tomato chlorosis virus (ToCV), is one of the most devastating cultivated tomato viruses, seriously threatened the growth of crops worldwide. As the vector of ToCV, the whitefly Bemisia tabaci Mediterranean (MED) is mainly responsible for the rapid spread of ToCV. The current understanding of tomato plant responses to this virus and B. tabaci is very limited. To understand the molecular mechanism of the interaction between tomato, ToCV and B. tabaci, we adopted a next-generation sequencing approach to decipher miRNAs and mRNAs that are differentially expressed under the infection of B. tabaci and ToCV in tomato plants. Our data revealed that 6199 mRNAs were significantly regulated, and the differentially expressed genes were most significantly associated with the plant-pathogen interaction, the MAPK signaling pathway, the glyoxylate, and the carbon fixation in photosynthetic organisms and photosynthesis related proteins. Concomitantly, 242 differentially expressed miRNAs were detected, including novel putative miRNAs. Sly-miR159, sly-miR9471b-3p, and sly-miR162 were the most expressed miRNAs in each sample compare to control group. Moreover, we compared the similarities and differences of gene expression in tomato plant caused by infection or co-infection of B. tabaci and ToCV. Taken together, the analysis reported in this article lays a solid foundation for further research on the interaction between tomato, ToCV and B. tabaci, and provide evidence for the identification of potential key genes that influences virus transmission in tomato plants