DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance

Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided image diffusion models to image-guided video generation models. Nevertheless, these methods often result in either low fidelity or flickering over time due to their limitation to shallow image guidance and poor temporal consistency. To tackle these problems, we propose a high-fidelity image-to-video generation method by devising a frame retention branch based on a pre-trained video diffusion model, named DreamVideo. Instead of integrating the reference image into the diffusion process at a semantic level, our DreamVideo perceives the reference image via convolution layers and concatenates the features with the noisy latents as model input. By this means, the details of the reference image can be preserved to the greatest extent. In addition, by incorporating double-condition classifier-free guidance, a single image can be directed to videos of different actions by providing varying prompt texts. This has significant implications for controllable video generation and holds broad application prospects. We conduct comprehensive experiments on the public dataset, and both quantitative and qualitative results indicate that our method outperforms the state-of-the-art method. Especially for fidelity, our model has a powerful image retention ability and delivers the best results in UCF101 compared to other image-to-video models to our best knowledge. Also, precise control can be achieved by giving different text prompts. Further details and comprehensive results of our model will be presented in https://anonymous0769.github.io/DreamVideo/

DMfold: A Novel Method to Predict RNA Secondary Structure With Pseudoknots Based on Deep Learning and Improved Base Pair Maximization Principle

While predicting the secondary structure of RNA is vital for researching its function, determining RNA secondary structure is challenging, especially for that with pseudoknots. Typically, several excellent computational methods can be utilized to predict the secondary structure (with or without pseudoknots), but they have their own merits and demerits. These methods can be classified into two categories: the multi-sequence method and the single-sequence method. The main advantage of the multi-sequence method lies in its use of the auxiliary sequences to assist in predicting the secondary structure, but it can only successfully predict in the presence of multiple highly homologous sequences. The single-sequence method is associated with the major merit of easy operation (only need the target sequence to predict secondary structure), but its folding parameters are the common features of diversity RNA, which cannot describe the unique characteristics of RNA, thus potentially resulting in the low prediction accuracy in some RNA. In this paper, “DMfold,” a method based on the Deep Learning and Improved Base Pair Maximization Principle, is proposed to predict the secondary structure with pseudoknots, which fully absorbs the advantages and avoids some disadvantages of those two methods. Notably, DMfold could predict the secondary structure of RNA by learning similar RNA in the known structures, which uses the similar RNA sequences instead of the highly homogeneous sequences in the multi-sequence method, thereby reducing the requirement for auxiliary sequences. In DMfold, it only needs to input the target sequence to predict the secondary structure. Its folding parameters are fully extracted automatically by deep learning, which could avoid the lack of folding parameters in the single-sequence method. Experiments show that our method is not only simple to operate, but also improves the prediction accuracy compared to multiple excellent prediction methods. A repository containing our code can be found at https://github.com/linyuwangPHD/RNA-Secondary-Structure-Database

Progress and indication for use of continuous glucose monitoring in patients with diabetes in pregnancy: a review

Gestational diabetes mellitus is one of the most common endocrine diseases that occur during pregnancy. Disorders of blood glucose metabolism during pregnancy can increase the risk of adverse pregnancy outcomes, such as pregnancy-related hypertension, preeclampsia, eclampsia, miscarriage, macrosomia, and neonatal hypoglycemia. Continuous glucose monitoring (CGM) can safely and effectively monitor blood glucose changes in patients with gestational hyperglycemia, thereby reducing adverse pregnancy outcomes. Hence, this article aimed to provide a comprehensive review of the progress and indications for using CGM in pregnant patients with diabetes. CGM can reduce blood glucose fluctuations and the occurrence of serious hypoglycemia and hyperglycemia events and can provide time in range (TIR). TIR is an important indicator of blood glucose level. Patients with a higher TIR during pregnancy have better gestational outcomes

Hypericin Inhibit Alpha-Coronavirus Replication by Targeting 3CL Protease

The porcine epidemic diarrhea virus (PEDV) is an Alphacoronavirus (α-CoV) that causes high mortality in infected piglets, resulting in serious economic losses in the farming industry. Hypericin is a dianthrone compound that has been shown as an antiviral activity on several viruses. Here, we first evaluated the antiviral effect of hypericin in PEDV and found the viral replication and egression were significantly reduced with hypericin post-treatment. As hypericin has been shown in SARS-CoV-2 that it is bound to viral 3CLpro, we thus established a molecular docking between hypericin and PEDV 3CLpro using different software and found hypericin bound to 3CLpro through two pockets. These binding pockets were further verified by another docking between hypericin and PEDV 3CLpro pocket mutants, and the fluorescence resonance energy transfer (FRET) assay confirmed that hypericin inhibits the PEDV 3CLpro activity. Moreover, the alignments of α-CoV 3CLpro sequences or crystal structure revealed that the pockets mediating hypericin and PEDV 3CLpro binding were highly conserved, especially in transmissible gastroenteritis virus (TGEV). We then validated the anti-TGEV effect of hypericin through viral replication and egression. Overall, our results push forward that hypericin was for the first time shown to have an inhibitory effect on PEDV and TGEV by targeting 3CLpro, and it deserves further attention as not only a pan-anti-α-CoV compound but potentially also as a compound of other coronaviral infections

TGF-β1-Mediated Leukocyte Cell-Derived Chemotaxin 2 Is Associated With Liver Fibrosis in Biliary Atresia

ObjectiveBiliary atresia (BA) presents as a severe infantile cholangiopathy disease, characterized by progressive liver fibrosis and the resulting poor prognosis. Leukocyte cell-derived chemotaxin 2 (LECT2) was proposed as the key gene associated with hepatic fibrosis in BA, but the molecular mechanism is unclear. This study aims to investigate the function of LECT2 in BA.MethodsA total of 53 patients were enrolled in this study; 36 patients with BA, and 17 control patients with cholestasis, including congenital biliary dilations, biliary hypoplasia, and inspissated bile syndrome. The role of LECT2 in BA was analyzed using histological and cytological tests. The correlation between LECT2 and infiltrating immune cells was further analyzed by bioinformatics. The analyses were conducted using correlational analyses and ROC curves.ResultsLECT2 was highly expressed in infants with BA and positively related with fibrosis (0.1644 ± 0.0608 vs. 0.0779 ± 0.0053, p < 0.0001; rs = 0.85, p < 0.0001). Serum levels of LECT2 showed high distinguishing features for patients with BA having an AUC of 0.95 (95% CI: 0.90–1.00). CD163 was highly expressed in the aggravation of fibrosis (0.158 ± 0.062 vs. 0.29 ± 0.078, p < 0.0001), and the expression of LECT2 was positively correlated with the accumulation of CD163+ macrophages (r = 0.48, p = 0.003). The bioinformatic analysis also showed that LECT2 was positively correlated with macrophage M2 (r = 0.34, p = 0.03). TGF-β1 and CD163 colocalized to the portal area in the livers of patients with BA. Moreover, TGF-β1 upregulated the expression of LECT2.ConclusionLECT2 is highly expressed in both BA liver tissue and serum, and serum LECT2 is a potential diagnostic biomarker of BA. Meanwhile, TGF-β1 is secreted by macrophages to regulate LECT2 associated with BA liver fibrosis

The impact of gut microbiota on autoimmune thyroiditis and relationship with pregnancy outcomes: a review

Autoimmune thyroiditis (AITD) is a T-cell-mediated, organ- specific autoimmune disease caused by interactions between genetic and environmental factors. Patients with AITD show thyroid lymphocyte infiltration and an increase in the titer of thyroid autoimmune antibodies, thereby altering the integrity of thyroid follicle epithelial cells and dysregulating their metabolism and immune function, leading to a decrease in multi-tissue metabolic activity. Research has shown that patients with AITD have a significantly higher risk of adverse pregnancy outcomes, such as infertility and miscarriage. Levothyroxine(LT4) treatment can improve the pregnancy outcomes of normal pregnant women with thyroid peroxidase antibodies(TPOAb) positivity, but it is not effective for invitro fertilization embryo transfer (IVF-ET) in women with normal thyroid function and positive TPOAb. Other factors may also influence pregnancy outcomes of patients with AITD. Recent studies have revealed that the gut microbiota participates in the occurrence and development of AITD by influencing the gut-thyroid axis. The bacterial abundance and diversity of patients with Hashimoto thyroiditis (HT) were significantly reduced, and the relative abundances of Bacteroides, fecal Bacillus, Prevotella, and Lactobacillus also decreased. The confirmation of whether adjusting the composition of the gut microbiota can improve pregnancy outcomes in patients with AITD is still pending. This article reviews the characteristics of the gut microbiota in patients with AITD and the current research on its impact in pregnancy

A Comprehensive Review of Micro-Inertial Measurement Unit Based Intelligent PIG Multi-Sensor Fusion Technologies for Small-Diameter Pipeline Surveying

It is of great importance for pipeline systems to be is efficient, cost-effective and safe during the transportation of the liquids and gases. However, underground pipelines often experience leaks due to corrosion, human destruction or theft, long-term Earth movement, natural disasters and so on. Leakage or explosion of the operating pipeline usually cause great economical loss, environmental pollution or even a threat to citizens, especially when these accidents occur in human-concentrated urban areas. Therefore, the surveying of the routed pipeline is of vital importance for the Pipeline Integrated Management (PIM). In this paper, a comprehensive review of the Micro-Inertial Measurement Unit (MIMU)-based intelligent Pipeline Inspection Gauge (PIG) multi-sensor fusion technologies for the transport of liquids and gases purposed for small-diameter pipeline (D < 30 cm) surveying is demonstrated. Firstly, four types of typical small-diameter intelligent PIGs and their corresponding pipeline-defects inspection technologies and defects-positioning technologies are investigated according to the various pipeline defects inspection and localization principles. Secondly, the multi-sensor fused pipeline surveying technologies are classified into two main categories, the non-inertial-based and the MIMU-based intelligent PIG surveying technology. Moreover, five schematic diagrams of the MIMU fused intelligent PIG fusion technology is also surveyed and analyzed with details. Thirdly, the potential research directions and challenges of the popular intelligent PIG surveying techniques by multi-sensor fusion system are further presented with details. Finally, the review is comprehensively concluded and demonstrated

Indoor and outdoor low-cost seamless integrated navigation system based on the integration of INS/GNSS/LIDAR system

Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.Peer reviewe

Hydrogeochemistry and delta C-13(DIC) and delta O-18(H2O) composition of three Chinese Tibetan Plateau lakes

This study established the hydrochemistry and stable isotope variations in three lakes, namely brackish Zigetang Co, freshwater Cona and Ranwu lakes located in the central and southeastern Tibetan Plateau of China. Vertical profile fluctuations in the water column, such as temperature and dissolved oxygen (DO) concentration, displayed significant differences which were linked to the thermocline. The hydrochemistry of the three lakes showed that as the dominant anion, whereas Na+ is the main cation in Zigetang Co and Cona lake and Ca2+ is the prevailing cation in Ranwu lake. In Zigetang Co, K+ and Na+ concentrations decreased by 42% from 1999 to 2012, caused by the enlargement of the lake area, documented by field investigations carried out in 1998, 2002, 2006 and 2012. The C-13(DIC) and O-18(H2O) values analysed from the three lakes varied from -6.0 to 2.0 parts per thousand, and from -14.8 to -6.4 parts per thousand, respectively. The closed Zigetang lake showed higher C-13(DIC) and O-18(H2O) values compared to those of the rivers, the semi-closed Cona and open Ranwu lakes. The C-13(DIC) values of lake water in Zigetang Co were mainly controlled by CO2 exchange between lake water and atmosphere; the O-18(H2O) values were dominated by the evaporation/freshwater input ratios

Hydrogeochemistry and delta C-13(DIC) and delta O-18(H2O) composition of three Chinese Tibetan Plateau lakes

This study established the hydrochemistry and stable isotope variations in three lakes, namely brackish Zigetang Co, freshwater Cona and Ranwu lakes located in the central and southeastern Tibetan Plateau of China. Vertical profile fluctuations in the water column, such as temperature and dissolved oxygen (DO) concentration, displayed significant differences which were linked to the thermocline. The hydrochemistry of the three lakes showed that as the dominant anion, whereas Na+ is the main cation in Zigetang Co and Cona lake and Ca2+ is the prevailing cation in Ranwu lake. In Zigetang Co, K+ and Na+ concentrations decreased by 42% from 1999 to 2012, caused by the enlargement of the lake area, documented by field investigations carried out in 1998, 2002, 2006 and 2012. The C-13(DIC) and O-18(H2O) values analysed from the three lakes varied from -6.0 to 2.0 parts per thousand, and from -14.8 to -6.4 parts per thousand, respectively. The closed Zigetang lake showed higher C-13(DIC) and O-18(H2O) values compared to those of the rivers, the semi-closed Cona and open Ranwu lakes. The C-13(DIC) values of lake water in Zigetang Co were mainly controlled by CO2 exchange between lake water and atmosphere; the O-18(H2O) values were dominated by the evaporation/freshwater input ratios