Analysis on Structural Benefit of Jilin Cultural and Creative Industries

Cultural Creative Industry is a new industry in 21 century, and is also a new growth point in the local economic development. In recent years, Cultural Creative Industry in Jilin Province has made remarkable development and has greatly promoted the local economic growth. The paper estimates the structural benefit of Cultural Creative Industry in Jilin Province by using the structural deviation and comparable labor productivity index, and researches the allocation proportion and correlations of the elements of labor and capital in the industry, accordingly unearth the problems existed in the internal structure of the industry and provide counter planes to the coordinated growth of the industry. Key words: Cultural Creative Industry; Structural Benefit; Structural Deviation; Comparative Labor Productivit

Matrine inhibits hepatocellular carcinoma cell malignancy through the circ_0013290/miR-139-5p/MMP16 pathway

Background. Previous studies have shown the anticancer effect of Matrine on hepatocellular carcinoma (HCC); however, the underlying mechanism is still indistinct. Methods. The expression of circular RNA_0013290 (circ_0013290), microRNA-139-5p (miR-139-5p), matrix metallopeptidase 16 (MMP16), CyclinD1 and N-cadherin was analyzed by quantitative real-time polymerase chain reaction, Western blotting or immuno-histochemistry assay. Cell viability, proliferation, apoptosis, invasion and tube formation were analyzed by cell counting kit-8, 5-Ethynyl-2’-deoxyuridine, flow cytometry analysis, transwell invasion and tube formation assays, respectively. The associations among circ_0013290, miR-139-5p and MMP16 were predicted by starbase online database, and identified by dual-luciferase reporter and RNA pull-down assays. A xenograft mouse model assay was conducted to disclose the effects of circ_0013290 and Matrine on tumor tumorigenesis in vivo. Results. Circ_0013290 and MMP16 expression were significantly upregulated, while miR-139-5p was downregulated in HCC tissues and cells compared with the matched normal liver tissues and cells. Matrine treatment inhibited HCC cell proliferation, invasion and tube formation but induced cell apoptosis, accompanied by the decrease of CyclinD1 and N-cadherin expression; however, these effects were counteracted when circ_0013290 expression was increased. MiR-139-5p depletion or MMP16 introduction relieved Matrine-induced effects in HCC cells. The regulation of circ_0013290 toward HCC cell processes involved MMP16. With respect to the mechanism, circ_0013290 acted as a miR-139-5p sponge, and miR-139-5p targeted MMP16 in HCC cells. Besides, circ_0013290 regulated MMP16 expression through miR-139-5p. Further, circ_0013290 depletion enhanced the inhibitory effects of Matrine on tumor tumorigenesis. Conclusion. Matrine inhibited HCC cell malignancy through the circ_0013290/miR-139-5p/MMP16 pathway, suggesting that Matrine is a potential therapeutic agent for HC

Images Speak in Images: A Generalist Painter for In-Context Visual Learning

In-context learning, as a new paradigm in NLP, allows the model to rapidly adapt to various tasks with only a handful of prompts and examples. But in computer vision, the difficulties for in-context learning lie in that tasks vary significantly in the output representations, thus it is unclear how to define the general-purpose task prompts that the vision model can understand and transfer to out-of-domain tasks. In this work, we present Painter, a generalist model which addresses these obstacles with an "image"-centric solution, that is, to redefine the output of core vision tasks as images, and specify task prompts as also images. With this idea, our training process is extremely simple, which performs standard masked image modeling on the stitch of input and output image pairs. This makes the model capable of performing tasks conditioned on visible image patches. Thus, during inference, we can adopt a pair of input and output images from the same task as the input condition, to indicate which task to perform. Without bells and whistles, our generalist Painter can achieve competitive performance compared to well-established task-specific models, on seven representative vision tasks ranging from high-level visual understanding to low-level image processing. In addition, Painter significantly outperforms recent generalist models on several challenging tasks.Comment: Accepted to CVPR 2023. Code and model is available at: https://github.com/baaivision/Painte

AutoStory: Generating Diverse Storytelling Images with Minimal Human Effort

Story visualization aims to generate a series of images that match the story described in texts, and it requires the generated images to satisfy high quality, alignment with the text description, and consistency in character identities. Given the complexity of story visualization, existing methods drastically simplify the problem by considering only a few specific characters and scenarios, or requiring the users to provide per-image control conditions such as sketches. However, these simplifications render these methods incompetent for real applications. To this end, we propose an automated story visualization system that can effectively generate diverse, high-quality, and consistent sets of story images, with minimal human interactions. Specifically, we utilize the comprehension and planning capabilities of large language models for layout planning, and then leverage large-scale text-to-image models to generate sophisticated story images based on the layout. We empirically find that sparse control conditions, such as bounding boxes, are suitable for layout planning, while dense control conditions, e.g., sketches and keypoints, are suitable for generating high-quality image content. To obtain the best of both worlds, we devise a dense condition generation module to transform simple bounding box layouts into sketch or keypoint control conditions for final image generation, which not only improves the image quality but also allows easy and intuitive user interactions. In addition, we propose a simple yet effective method to generate multi-view consistent character images, eliminating the reliance on human labor to collect or draw character images.Comment: 19 page

Object-aware Inversion and Reassembly for Image Editing

By comparing the original and target prompts in editing task, we can obtain numerous editing pairs, each comprising an object and its corresponding editing target. To allow editability while maintaining fidelity to the input image, existing editing methods typically involve a fixed number of inversion steps that project the whole input image to its noisier latent representation, followed by a denoising process guided by the target prompt. However, we find that the optimal number of inversion steps for achieving ideal editing results varies significantly among different editing pairs, owing to varying editing difficulties. Therefore, the current literature, which relies on a fixed number of inversion steps, produces sub-optimal generation quality, especially when handling multiple editing pairs in a natural image. To this end, we propose a new image editing paradigm, dubbed Object-aware Inversion and Reassembly (OIR), to enable object-level fine-grained editing. Specifically, we design a new search metric, which determines the optimal inversion steps for each editing pair, by jointly considering the editability of the target and the fidelity of the non-editing region. We use our search metric to find the optimal inversion step for each editing pair when editing an image. We then edit these editing pairs separately to avoid concept mismatch. Subsequently, we propose an additional reassembly step to seamlessly integrate the respective editing results and the non-editing region to obtain the final edited image. To systematically evaluate the effectiveness of our method, we collect two datasets for benchmarking single- and multi-object editing, respectively. Experiments demonstrate that our method achieves superior performance in editing object shapes, colors, materials, categories, etc., especially in multi-object editing scenarios.Comment: Project Page: https://aim-uofa.github.io/OIR-Diffusion

GenDeF: Learning Generative Deformation Field for Video Generation

We offer a new perspective on approaching the task of video generation. Instead of directly synthesizing a sequence of frames, we propose to render a video by warping one static image with a generative deformation field (GenDeF). Such a pipeline enjoys three appealing advantages. First, we can sufficiently reuse a well-trained image generator to synthesize the static image (also called canonical image), alleviating the difficulty in producing a video and thereby resulting in better visual quality. Second, we can easily convert a deformation field to optical flows, making it possible to apply explicit structural regularizations for motion modeling, leading to temporally consistent results. Third, the disentanglement between content and motion allows users to process a synthesized video through processing its corresponding static image without any tuning, facilitating many applications like video editing, keypoint tracking, and video segmentation. Both qualitative and quantitative results on three common video generation benchmarks demonstrate the superiority of our GenDeF method.Comment: Project page: https://aim-uofa.github.io/GenDeF

Differential contributory roles of nucleotide excision and homologous recombination repair for enhancing cisplatin sensitivity in human ovarian cancer cells

<p>Abstract</p> <p>Background</p> <p>While platinum-based chemotherapeutic agents are widely used to treat various solid tumors, the acquired platinum resistance is a major impediment in their successful treatment. Since enhanced DNA repair capacity is a major factor in conferring cisplatin resistance, targeting of DNA repair pathways is an effective stratagem for overcoming cisplatin resistance. This study was designed to delineate the role of nucleotide excision repair (NER), the principal mechanism for the removal of cisplatin-induced DNA intrastrand crosslinks, in cisplatin resistance and reveal the impact of DNA repair interference on cisplatin sensitivity in human ovarian cancer cells.</p> <p>Results</p> <p>We assessed the inherent NER efficiency of multiple matched pairs of cisplatin-sensitive and -resistant ovarian cancer cell lines and their expression of NER-related factors at mRNA and protein levels. Our results showed that only the cisplatin-resistant ovarian cancer cell line PEO4 possessed an increased NER capacity compared to its inherently NER-inefficient parental line PEO1. Several other cisplatin-resistant cell lines, including CP70, CDDP and 2008C13, exhibited a normal and parental cell-comparable NER capacity for removing cisplatin-induced DNA intrastrand cross-links (Pt-GG). Concomitant gene expression analysis revealed discordance in mRNA and protein levels of NER factors in various ovarian cancer cell lines and NER proteins level were unrelated to the cisplatin sensitivity of these cell lines. Although knockdown of NER factors was able to compromise the NER efficiency, it only caused a minimal effect on cisplatin sensitivity. On the contrary, downregulation of BRCA2, a critical protein for homologous recombination repair (HRR), significantly enhanced the efficacy of cisplatin in killing ovarian cancer cell line PEO4.</p> <p>Conclusion</p> <p>Our studies indicate that the level of NER factors in ovarian cancer cell lines is neither a determinant of their NER capacity nor of the sensitivity to cisplatin, and suggest that manipulation of the HRR but not the NER factor expression provides an effective strategy for sensitizing cisplatin-resistant tumors to platinating agents.</p

Salivary signatures of oral-brain communication in sleep bruxers

IntroductionMicrobiota and their interaction with hosts have been of great interest in brain research in recent years. However, the role of oral microbiota in mental illness and the underlying mechanism of oral-brain communication remains elusive. Sleep bruxism (SB) is an oral parafunctional activity related to the nervous system and is considered a risk factor for harmful clinical consequences and severe systemic conditions. Exploring the connection between oral microbiota and sleep bruxism may deepen our understanding of the complex relationship between oral-brain axis and provide insights for treatment.MethodsIn this study, salivary samples were collected from 22 individuals with SB and 21 healthy controls, and metagenomics with metabolomics was performed. Nonparametric Wilcoxon test were applied for the statistical analysis between the two groups. Microbial dysbiosis and altered oral metabolites were found in the SB individuals.ResultsThe characteristic metabolite N-acetylglucosamine (GlcNAc) (VIP=8.4823, P&lt;0.05) was correlated to a statistically lower Streptococcus mitis level in SB individuals. Salivary IFN-g level and IFN-g/IL-4 ratio were detected with significant changes in a chip assay. Amino acid metabolism pathways were upregulated, and the pathway with the largest number of differentially expressed genes is related to amino-tRNA charging pathway, while the most significantly enriched pathway is related to arginine biosynthesis. Neurotransmitter-associated pathways with glutamatergic and GABAergic synapses and cardiovascular system-related pathways were enriched in the SB group.DiscussionThese results indicate a possible neuroimmune regulatory network of oral-brain communication in SB, which helps explain the mechanism of the oral microbiome with the host in sleep bruxers and provides a reference for early clinical and therapeutic intervention to improve the diagnosis and treatment of SB and similar diseases

Determining the optimal biomass of macrophytes during the ecological restoration process of eutrophic shallow lakes

Many studies have shown that macrophytes play a significant role in controlling eutrophication; however, only a few of these are based on macrophyte biomass. Based on the growth characteristic of macrophytes, we propose an approach for the assessment of the optimal biomass of macrophytes in the decay and growth periods in Lake Datong (a shallow lake), using a lake ecological model. The results showed that the pollution load of the lake should be reduced by 50% while conforming to the Environmental Quality Standards for Surface Water (EQSSW) Class Ⅲ. In contrast, with an increase in the pollution load of 5%, the results indicate that the lake may deteriorate to a turbid state over the next few years. The macrophyte biomass should be harvested during the decay period, when 80% biomass is beneficial to the water quality of the eutrophic shallow lake. Based on macrophyte simulation from 2020–2024, the wet biomass of macrophytes should be controlled at 5.5 kg/m2. The current macrophyte biomass in Lake Datong is four-fold higher than the simulated optimal biomass. This study provides a reference for the adequate ecological restoration of the lake and its subsequent maintenance, as well as scientific support for improving the comprehensive evaluation standard of healthy lakes and the theoretical basis of lake ecological restoration