Unwinding and rewinding: Double faces of helicase

Helicases are enzymes that use ATP-driven motor force to unwind double-stranded DNA or RNA. Recently, increasing evidence demonstrates that some helicases also possess rewinding activity-in other words, they can anneal two complementary singlestranded nucleic acids. All five members of the human RecQ helicase family, helicase PIF1, mitochondrial helicase TWINKLE, and helicase/nuclease Dna2 have been shown to possess strand-annealing activity. Moreover, two recently identified helicases-HARP and AH2 have only ATP-dependent rewinding activity. These findings not only enhance our understanding of helicase enzymes but also establish the presence of a new type of protein: annealing helicases. This paper discusses what is known about these helicases, focusing on their biochemical activity to zip and unzip double-stranded DNA and/or RNA, their possible regulation mechanisms, and biological functions

Enhancing Scene Text Detectors with Realistic Text Image Synthesis Using Diffusion Models

Scene text detection techniques have garnered significant attention due to their wide-ranging applications. However, existing methods have a high demand for training data, and obtaining accurate human annotations is labor-intensive and time-consuming. As a solution, researchers have widely adopted synthetic text images as a complementary resource to real text images during pre-training. Yet there is still room for synthetic datasets to enhance the performance of scene text detectors. We contend that one main limitation of existing generation methods is the insufficient integration of foreground text with the background. To alleviate this problem, we present the Diffusion Model based Text Generator (DiffText), a pipeline that utilizes the diffusion model to seamlessly blend foreground text regions with the background's intrinsic features. Additionally, we propose two strategies to generate visually coherent text with fewer spelling errors. With fewer text instances, our produced text images consistently surpass other synthetic data in aiding text detectors. Extensive experiments on detecting horizontal, rotated, curved, and line-level texts demonstrate the effectiveness of DiffText in producing realistic text images

Identifying Protein-Protein Interactions of DDX41 by BioID

Helicases are known as enzymes that separate double-stranded(ds) nucleic acids to single-strand(ss) nucleic acids by hydrolysis ATP; and some of them also can anneal ss nucleic acids to ds nucleic acids in an ATP-independent manner. DEAD-box helicases are characterized by containing an Asp-Glu-Ala-Asp (DEAD) sequence in their motif II that is required for ATP binding and hydrolysis. DEAD-box helicase 41 (DDX41) is a member of DEAD-box helicases with multiple functions, including acting as a sensor for intracellular DNA in myeloid dendritic cells1 and for bacterial secondary messengers (c-di-GMP or c-di-AMP) to trigger type 1 interferon production2. Recently, the Dr. Wu’s lab discovered that DDX41 modulates the balance of dsDNA and ssDNA, in which regulates the activation of the cyclic GMP–AMP synthase (cGAS)3. Mutations in DDX41 are linked with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML)4, two blood caners. The most recurring mutation in DDX41 that lead to AML or MDS is c.1574G>A (p.R525H). Despite concrete evidence suggests that DDX41 acts as a DNA sensor in innate immunity5,6; no innate immunity-related protein has been identified as a DDX41-binding partner. Therefore, we established a BioID system to identify DDX41-biniding proteins under virus infections

Identifying the relative importance of stock characteristics

There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios

Study on overlying strata movement and surface subsidence of coal workfaces with Karst aquifer water

The overlying strata layers of coal workfaces with karst aquifer water normally causes serious safety problems due to the precipitation, drainage and water inrush, such as a wide range and long term of surface subsidence. In this study, by taking 10,301 working faces of the Daojiao coal mine in Guizhou Province as the engineering background, the numerical model of water-bearing strata with fluid-solid coupling was established by using UDEC to illustrate the laws of overlying strata movement and surface subsidence. A theory model was proposed to calculate the surface settlement caused by the drainage of aquifer based on the principle of effective stress modified by the Biot coefficient αb. The results showed that the corresponding maximum value (0.72 m) and the range of the surface subsidence with the occurrence of karst aquifer water were larger than that of the overlying strata without karst aquifer water (e.g., the maximum value of surface subsidence with 0.1 m). Moreover, the surface subsidence caused by the drainage of aquifer accounted for 17.8% of the total surface subsidence caused by coal mining. According to the field monitoring of surface subsidence in 10,301 working faces, the maximum value was 0.74 m, which was highly consistent with the results of numerical simulation and theoretical analysis. It verified the accuracy and reliability of the numerical model and the theory model in this study

Thermal Error Modeling Method for a CNC Machine Tool Feed Drive System

The disadvantages of the common current thermal error modeling methods for CNC machine tool feed drive systems were analyzed, such as the requirement of many temperature sensors to reach high accuracy and poor applicability of different moving states. A new robust modeling method based on the heat transfer theory is proposed, and the procedure of the thermal tests for a feed drive system is presented. Multiple regression method and robust modeling method based on the heat transfer theory were, respectively, used to establish a thermal error model, and a pointer automatic optimizer was used to optimize the parameters in the robust model. A compensation simulation was conducted under five different moving states using these two modeling methods, and the advantages of the robust modeling method were proved. Finally, the compensation effect of the robust modeling method was verified under a random moving state on a vertical machining center

Estimating the Quality of Reprogrammed Cells Using ES Cell Differentiation Expression Patterns

Somatic cells can be reprogrammed to a pluripotent state by over-expression of defined factors, and pluripotency has been confirmed by the tetraploid complementation assay. However, especially in human cells, estimating the quality of Induced Pluripotent Stem Cell(iPSC) is still difficult. Here, we present a novel supervised method for the assessment of the quality of iPSCs by estimating the gene expression profile using a 2-D “Differentiation-index coordinate”, which consists of two “developing lines” that reflects the directions of ES cell differentiation and the changes of cell states during differentiation. By applying a novel liner model to describe the differentiation trajectory, we transformed the ES cell differentiation time-course expression profiles to linear “developing lines”; and use these lines to construct the 2-D “Differentiation-index coordinate” of mouse and human. We compared the published gene expression profiles of iPSCs, ESCs and fibroblasts in mouse and human “Differentiation-index coordinate”. Moreover, we defined the Distance index to indicate the qualities of iPS cells, which based on the projection distance of iPSCs-ESCs and iPSCs-fibroblasts. The results indicated that the “Differentiation-index coordinate” can distinguish differentiation states of the different cells types. Furthermore, by applying this method to the analysis of expression profiles in the tetraploid complementation assay, we showed that the Distance index which reflected spatial distributions correlated the pluripotency of iPSCs. We also analyzed the significantly changed gene sets of “developing lines”. The results suggest that the method presented here is not only suitable for the estimation of the quality of iPS cells based on expression profiles, but also is a new approach to analyze time-resolved experimental data