A novel procedure for absolute real-time quantification of gene expression patterns

<p>Abstract</p> <p>Background</p> <p>Temporal and tissue-specific patterns of gene expression play important roles in functionality of a biological system. Real-time quantitative polymerase chain reaction (qPCR) technique has been widely applied to single gene expressions, but its potential has not been fully released as most results have been obtained as fold changes relative to control conditions. Absolute quantification of transcripts as an alternative method has yet to gain popularity because of unresolved issues.</p> <p>Results</p> <p>We propose a solution here with a novel procedure, which may accurately quantify the total cDNA conventionally prepared from a biological sample at the resolution of ~70 pg/μl, and reliably estimate the absolute numbers of transcripts in a picogram of cDNA. In comparison to the relative quantification, cDNA-based absolute (CBA) qPCR method is found to be more sensitive to gene expression variations caused by factors such as developmental and environmental variations. If the number of target transcript copies is further normalized by reference transcripts, cell-level variation pattern of the target gene expression may also be detectable during a developmental process, as observed here in cases across species (<it>Ipomoea purpurea, Nicotiana benthamiana</it>) and tissues (petals and leaves).</p> <p>Conclusion</p> <p>By allowing direct comparisons of results across experiments, the new procedure opens a window to make inferences of gene expression patterns across a broad spectrum of living systems and tissues. Such comparisons are urgently needed for biological interpretations of gene expression variations in diverse cells.</p

Wetting transition energy curves for a droplet on a square-post patterned surface

Due to the property of water repellence, biomimetic superhydrophobic surfaces have been widely applied to green technologies, in turn inducing wider and deeper investigations on superhydrophobic surfaces. Theoretical, experimental and numerical studies on wetting transitions have been carried out by researchers, but the mechanism of wetting transitions between Cassie-Baxter state and Wenzel state, which is crucial to develop a stable superhydrophobic surface, is still not fully understood. In this paper, the free energy curves based on the transition processes are presented and discussed in detail. The existence of energy barriers with or without consideration of the gravity effect, and the irreversibility of wetting transition are discussed based on the presented energy curves. The energy curves show that different routes of the Cassie-to-Wenzel transition and the reverse transition are the main reason for the irreversibility. Numerical simulations are implemented via a phase field lattice Boltzmann method of large density ratio, and the simulation results show good consistency with the theoretical analysis

Effects of bolt slippage on the wind induced responses of transmission tower line system

The wind induced responses of transmission tower line system are studied by finite element method. Firstly, a slip model considering eccentricity and bolt joint slippage in diagonal bracings, tower legs and tower head is built by ANSYS. The slip model has a more accurate result compared with conventional models. Secondly, the finite element models of tower line systems are established and the wind speed time histories are simulated using MATLAB. Finally, the wind induced responses of different tower line systems are studied. The results of a single tower and the tower line systems are compared to study the effects of tower-line coupling effects and bolt slippage on wind induced responses of transmission tower line systems

Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videos

Generating text-editable and pose-controllable character videos have an imperious demand in creating various digital human. Nevertheless, this task has been restricted by the absence of a comprehensive dataset featuring paired video-pose captions and the generative prior models for videos. In this work, we design a novel two-stage training scheme that can utilize easily obtained datasets (i.e.,image pose pair and pose-free video) and the pre-trained text-to-image (T2I) model to obtain the pose-controllable character videos. Specifically, in the first stage, only the keypoint-image pairs are used only for a controllable text-to-image generation. We learn a zero-initialized convolu- tional encoder to encode the pose information. In the second stage, we finetune the motion of the above network via a pose-free video dataset by adding the learnable temporal self-attention and reformed cross-frame self-attention blocks. Powered by our new designs, our method successfully generates continuously pose-controllable character videos while keeps the editing and concept composition ability of the pre-trained T2I model. The code and models will be made publicly available.Comment: Project page: https://follow-your-pose.github.io/; Github repository: https://github.com/mayuelala/FollowYourPos

Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of existing video clips and synthesize a coherent storytelling video by customizing their appearances. We achieve this by developing a framework comprised of two functional modules: (i) Motion Structure Retrieval, which provides video candidates with desired scene or motion context described by query texts, and (ii) Structure-Guided Text-to-Video Synthesis, which generates plot-aligned videos under the guidance of motion structure and text prompts. For the first module, we leverage an off-the-shelf video retrieval system and extract video depths as motion structure. For the second module, we propose a controllable video generation model that offers flexible controls over structure and characters. The videos are synthesized by following the structural guidance and appearance instruction. To ensure visual consistency across clips, we propose an effective concept personalization approach, which allows the specification of the desired character identities through text prompts. Extensive experiments demonstrate that our approach exhibits significant advantages over various existing baselines.Comment: Github: https://github.com/VideoCrafter/Animate-A-Story Project page: https://videocrafter.github.io/Animate-A-Stor

VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source models available for researchers and engineers. In this work, we introduce two diffusion models for high-quality video generation, namely text-to-video (T2V) and image-to-video (I2V) models. T2V models synthesize a video based on a given text input, while I2V models incorporate an additional image input. Our proposed T2V model can generate realistic and cinematic-quality videos with a resolution of $1024 \times 576$, outperforming other open-source T2V models in terms of quality. The I2V model is designed to produce videos that strictly adhere to the content of the provided reference image, preserving its content, structure, and style. This model is the first open-source I2V foundation model capable of transforming a given image into a video clip while maintaining content preservation constraints. We believe that these open-source video generation models will contribute significantly to the technological advancements within the community.Comment: Tech Report; Github: https://github.com/AILab-CVC/VideoCrafter Homepage: https://ailab-cvc.github.io/videocrafter

TaleCrafter: Interactive Story Visualization with Multiple Characters

Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable layout of objects in images. Most previous works endeavor to meet these requirements by fitting a text-to-image (T2I) model on a set of videos in the same style and with the same characters, e.g., the FlintstonesSV dataset. However, the learned T2I models typically struggle to adapt to new characters, scenes, and styles, and often lack the flexibility to revise the layout of the synthesized images. This paper proposes a system for generic interactive story visualization, capable of handling multiple novel characters and supporting the editing of layout and local structure. It is developed by leveraging the prior knowledge of large language and T2I models, trained on massive corpora. The system comprises four interconnected components: story-to-prompt generation (S2P), text-to-layout generation (T2L), controllable text-to-image generation (C-T2I), and image-to-video animation (I2V). First, the S2P module converts concise story information into detailed prompts required for subsequent stages. Next, T2L generates diverse and reasonable layouts based on the prompts, offering users the ability to adjust and refine the layout to their preference. The core component, C-T2I, enables the creation of images guided by layouts, sketches, and actor-specific identifiers to maintain consistency and detail across visualizations. Finally, I2V enriches the visualization process by animating the generated images. Extensive experiments and a user study are conducted to validate the effectiveness and flexibility of interactive editing of the proposed system.Comment: Github repository: https://github.com/VideoCrafter/TaleCrafte

GSK-3β inhibition by curcumin mitigates amyloidogenesis via TFEB activation and anti-oxidative activity in human neuroblastoma cells

© 2020 Informa UK Limited, trading as Taylor & Francis Group.The translocation of transcription factor EB (TFEB) to the nucleus plays a pivotal role in the regulation of basic cellular processes, such as lysosome biogenesis and autophagy. Autophagy is an intracellular degradation system that delivers cytoplasmic constituents to the lysosome, which is important in maintaining cellular homeostasis during environmental stress. Furthermore, oxidative stress is a critical cause for the progression of neurodegenerative diseases. Curcumin has anti-oxidative and anti-inflammatory activities, and is expected to have potential therapeutic effects in various diseases. In this study, we demonstrated that curcumin regulated TFEB export signalling via inhibition of glycogen synthase kinase-3β (GSK-3β); GSK-3β was inactivated by curcumin, leading to reduced phosphorylation of TFEB. We further showed that H2O2-induced oxidative stress was reduced by curcumin via the Nrf2/HO-1 pathway in human neuroblastoma cells. In addition, we showed that curcumin induced the degradation of amyloidogenic proteins, including amyloid-β precursor protein and α-synuclein, through the TFEB-autophagy/lysosomal pathway. In conclusion, curcumin regulates autophagy by controlling TFEB through the inhibition of GSK-3β, and increases antioxidant gene expression in human neuroblastoma cells. These results contribute to the development of novel cellular therapies for neurodegenerative diseases.

CO ameliorates cellular senescence and aging by modulating the miR-34a/Sirt1 pathway

Oxidative stress is recognised as a key factor that can lead to cellular senescence and aging. Carbon monoxide (CO) is produced by haemoxygenase-1 (HO-1), which exerts cytoprotective effects in aging-related diseases, whereas the effect of CO on cellular senescence and aging has not been elucidated. In the current study, we clearly demonstrated that CO delays the process of cellular senescence and aging through regulation of miR-34a and Sirt1 expression. CO reduced H2O2-induced premature senescence in human diploid fibroblast WI-38 cells measured with SA-beta-Gal-staining. Furthermore, CO significantly decreased the expression of senescence-associated secretory phenotype (SASP), including TNF-alpha IL-6, and PAI-1 and increased the transcriptional levels of antioxidant genes, such as HO-1 and NQO1. Moreover, CO apparently enhanced the expression of Sirt1 through down-regulation of miR-34a. Next, to determine whether Sirt1 mediates the inhibitory effect of CO on cellular senescence, we pre-treated WI-38 cells with the Sirt1 inhibitor Ex527 and a miR-34a mimic followed by the administration of H2O2 and evaluated the expression of SASP and antioxidant genes as well as ROS production. According to our results, Sirt1 is crucial for the antiaging and antioxidant effects of CO. Finally, CO prolonged the lifespan of Caenorhabditis elegans and delayed high-fat diet-induced liver aging. Taken together, these findings demonstrate that CO reduces cellular senescence and liver aging through the regulation of miR-34a and Sirt1.

Carbon Monoxide Attenuates Dextran Sulfate Sodium-Induced Colitis via Inhibition of GSK-3 β

Endogenous carbon monoxide (CO) is produced by heme oxygenase-1 (HO)-1 which mediates the degradation of heme into CO, iron, and biliverdin. Also, CO ameliorates the human inflammatory bowel diseases and ulcerative colitis. However, the mechanism for the effect of CO on the inflammatory bowel disease has not yet been known. In this study, we showed that CO significantly increases survival percentage, body weight, colon length as well as histologic parameters in DSS-treated mice. In addition, CO inhalation significantly decreased DSS induced pro-inflammatory cytokines by inhibition of GSK-3β in mice model. To support the in vivo observation, TNF-α, iNOS and IL-10 after CO and LiCl treatment were measured in mesenteric lymph node cells (MLNs) and bone marrow-derived macrophages (BMMs) from DSS treated mice. In addition, we determined that CO potentially inhibited GSK-3β activation and decreased TNF-α and iNOS expression by inhibition of NF-κB activation in LPS-stimulated U937 and MLN cells pretreated with CO. Together, our findings indicate that CO attenuates DSS-induced colitis via inhibition of GSK-3β signaling in vitro and in vivo. Importantly, this is the first report that investigated the molecular mechanisms mediated the novel effects of CO via inhibition GSK-3β in DSS-induced colitis model