CRIT:Identifying RNA-binding protein regulator in circRNA life cycle via non-negative matrix factorization

Circular RNAs (circRNAs) are endogenous non-coding RNAs that regulate gene expression and participate in carcinogenesis. However, the RNA-binding proteins (RBPs) involved in circRNAs biogenesis and modulation remain largely unclear. We developed the circRNA regulator identification tool (CRIT), a non-negative matrix-factorization-based pipeline to identify regulating RBPs in cancers. CRIT uncovered 73 novel regulators across thousands of samples by effectively leveraging genomics data and functional annotations. We demonstrated that known RBPs involved in circRNA control are significantly enriched in these predictions. Analysis of circRNA-RBP interactions using two large cross-linking immunoprecipitation (CLIP) databases, we validated the consistency between CRIT prediction and the CLIP experiments. Furthermore, newly discovered RBPs are functionally connected with authentic circRNA regulators by various biological associations, such as physical interaction, similar binding motifs, common transcription factor modulation, and co-expression. When analyzing RNA sequencing (RNA-seq) datasets after short hairpin RNA (shRNA)/small interfering RNA (siRNA) knockdown, we found several novel RBPs that can affect global circRNA expression, which strengthens their role in the circRNA life cycle. The above evidence provided independent confirmation that CRIT is a useful tool to capture RBPs in circRNA processing. Finally, we show that authentic regulators are more likely the core splicing proteins and peripheral factors and usually harbor more alterations in the vast majority of cancers

Splicing factor TRA2A contributes to esophageal cancer progression via a noncanonical role in lncRNA m⁶A methylation

Transformer 2 alpha homolog (TRA2A), a member of the serine/arginine-rich splicing factor family, has been shown to control mRNA splicing in development and cancers. However, it remains unclear whether TRA2A is involved in lncRNA regulation. In the present study, we found that TRA2A was upregulated and correlated with poor prognosis in esophageal cancer. Downregulation of TRA2A suppressed the tumor growth in xenograft nude mice. Epitranscriptomic microarray showed that depletion of TRA2A affected global lncRNA methylation similarly to the key m6A methyltransferase, METTL3, by silencing. MeRIP-qPCR, RNA pull-down, CLIP analyses, and stability assays indicated that ablation of TRA2A reduced m6A-modification of the oncogenic lncRNA MALAT1, thus inducing structural alterations and reduced stability. Furthermore, Co-IP experiments showed TRA2A directly interacted with METTL3 and RBMX, which also affected the writer KIAA1429 expression. Knockdown of TRA2A inhibited cell proliferation in a manner restored by RBMX/KIAA1429 overexpression. Clinically, MALAT1, RBMX, and KIAA1429 were prognostic factors of worse survival in ESCA patients. Structural similarity-based virtual screening in FDA-approved drugs repurposed nebivolol, a β1-adrenergic receptor antagonist, as a potent compound to suppress the proliferation of esophageal cancer cells. Cellular thermal shift and RIP assay indicated that nebivolol may compete with MALAT1 to bind TRA2A. In conclusion, our study revealed the noncanonical function of TRA2A, which coordinates with multiple methylation proteins to promote oncogenic MALAT1 during ESCA carcinogenesis.</p

LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models

With the recent significant advancements in large multi-modal models (LMMs), the importance of their grounding capability in visual chat is increasingly recognized. Despite recent efforts to enable LMMs to support grounding, their capabilities for grounding and chat are usually separate, and their chat performance drops dramatically when asked to ground. The problem is the lack of a dataset for grounded visual chat (GVC). Existing grounding datasets only contain short captions. To address this issue, we have created GVC data that allows for the combination of grounding and chat capabilities. To better evaluate the GVC capabilities, we have introduced a benchmark called Grounding-Bench. Additionally, we have proposed a model design that can support GVC and various types of visual prompts by connecting segmentation models with language models. Experimental results demonstrate that our model outperforms other LMMs on Grounding-Bench. Furthermore, our model achieves competitive performance on classic grounding benchmarks like RefCOCO/+/g and Flickr30K Entities. Our code will be released at https://github.com/UX-Decoder/LLaVA-Grounding

Crushing Characteristics of Coarse Aggregates for Asphalt Mixtures under Simulated Laboratory Compaction Loads and Repeated Traffic Loads

The crushing characteristics of coarse aggregates for asphalt concrete were investigated under static and dynamic aggregate crushing value tests (ACVTs). The effect of various compaction loads was also examined by using a Marshall hammer, gyratory compactor and steel roller. Six types of coarse aggregates were tested, including basalt aggregate, steel slag, limestone aggregate, marble aggregate, recycled concrete aggregate and slightly weathered limestone aggregate. Test results indicate that static ACVT failed to reflect the crushing behavior of coarse aggregates under traditional traffic and compaction loads. The type of aggregate strongly influenced the crushing resistance, independent of type of load. The compaction loads simulated by using a Marshall hammer, gyratory compactor and steel roller resulted in a high aggregate breakage ratio and can distinguish the coarse aggregates with high crushing susceptibility. The crushing resistance was evaluated by using various crushing parameters and the corresponding critical value of these parameters was established. Gyratory compactor compaction resulted in more serious aggregate crushing when compared to Marshall hammer and steel roller compaction. Finite element modelling results on roller compaction and Marshall hammer compaction are in agreement with the aggregate crushing results. The aggregate crushing mechanism was found to be controlled by the fracture mode; the contribution of the attrition and abrasion modes was relatively small. When coarse aggregates with low crushing resistance are considered for the use for asphalt mixture, proper compaction is proved to be vital to prevent excessive aggregate breakage during mixture preparation and construction

fRNC: Uncovering the dynamic and condition-specific RBP-ncRNA circuits from multi-omics data

The RNA binding protein (RBP) and non-coding RNA (ncRNA) interacting networks are increasingly recognized as the main mechanism in gene regulation, and are tightly associated with cellular malfunction and disease. Here, we present fRNC, a systems biology tool to uncover the dynamic spectrum of RBP-ncRNA circuits (RNC) by integrating transcriptomics, interactomics and proteomics data. fRNC constructs the RBP-ncRNA network derived from CLIP-seq or PARE experiments. Given scoring on nodes and edges according to differential analysis of expression data, it finds an RNC containing global maximum significant RBPs and ncRNAs. Alternatively, it can also capture the locally maximum scoring RNC according to user-defined starting nodes with the greedy search. When compared with existing tools, fRNC can detect more accurate and robust sub-network with scalability. As shown in the cases of esophageal carcinoma, breast cancer and Alzheimer’s disease, fRNC enables users to analyze the collective behaviors between RBP and the interacting ncRNAs, and reveal novel insights into the disease-associated processes. The fRNC R package is available at https://github.com/BioinformaticsSTU/fRNC

Experimental Study on Hydraulic Fracturing of High Asphalt Concrete Core Rock-Fill Dam

In this paper, we experiment on the hydraulic fracturing of asphalt concrete with a voids content higher than 3%, which has arisen from the possible local shear dilatancy of Quxue asphalt&rsquo;s core wall of concrete core dam, the highest one of the sort constructed in the world. The model test has shown that under the sole water pressure 0.13 MPa&mdash;relevant to the pressure where the dilatancy could appear at core wall of Quxue dam&mdash;the asphalt concrete with a voids content of 3.5% underwent hydraulic fracturing. Furthermore, the asphalt concrete with a voids content of 3.0% was tested for nearly 500 h and no sign of hydraulic fracturing was found, which again confirmed the threshold requirement for a 3% voids content to the impervious asphalt concrete to the hydraulic fracture concern. According to the analysis of the test result, the theory of fracture mechanics could be applied to the hydraulic fracture of asphalt concrete with a voids content between 3.4~4.0%, which behaved during hydraulic fracturing like a quasi-brittle material, similar to concrete. Because the hydraulic fracturing could occur in the shear dilatant asphalt concrete, a proper mix proportion of asphalt concrete to a project with adverse stress state should be carefully designed to rule out the possibility of shear dilatancy

PPARγ overexpression regulates cholesterol metabolism in human L02 hepatocytes

Peroxisome proliferator-activator receptor (PPAR) γ is a nuclear hormone receptor that regulates glucose homeostasis, lipid metabolism, and adipocyte function. It has been shown that activation of PPARγ can reduce the incidence of gallstone. Herein we aimed to clarify the role of PPARγ in the reduction of gallstones. The plasmid containing the coding sequence of PPARγ was constructed and transfected in the human liver cell line (L02 cells). Western blot and RT-PCR were used to detect hydroxyl-methyl-glutaryl-CoA reductase (HMGCR), sterol regulatory element-binding proteins 2 (SREBP2), 7α-hydroxylase (CYP7A1), adenosine triphosphate-binding cassette (ABC) sterol transporters G5 and G8 (ABCG5, ABCG8) and liver X receptor α (LXRα). The Amplex Red cholesterol assay kit was used to detect the intracellular or extracellular cholesterol level. Our data showed that PPARγ overexpression caused significant decreases in both extracellular and intracellular cholesterol in the L02 cells. The further studies indicated PPARγ overexpression substantially decreased expression of HMGCR and SREBP-2, increased expression of CYP7A1, ABCG5, ABCG8 and LXRα. These results indicated that upregulation of PPARγ may reduce cholesterol levels through multiple-pathways including HMGCR/SREBP2-mediated biosynthesis, CYP7A1-mediated transformation, and ABCG5/ABCG8-mediated efflux. We thus suggest that PPARγ might have beneficial effects for cholesterol gallstones diseases. Keywords: PPARγ, Cholesterol, HMGCR, CYP7A1 and ABCG5/

A Review of the Methods for Detection of Staphylococcus aureus Enterotoxins

Food safety has attracted extensive attention around the world, and food-borne diseases have become one of the major threats to health. Staphylococcus aureus is a major food-borne pathogen worldwide and a frequent contaminant of foodstuffs. Staphylococcal enterotoxins (SEs) produced by some S. aureus strains will lead to staphylococcal food poisoning (SFP) outbreaks. The most common symptoms caused by ingestion of SEs within food are nausea, vomiting, diarrhea and cramps. Children will suffer SFP by ingesting as little as 100 ng of SEs, and only a few micrograms of SEs are enough to cause SPF in vulnerable populations. Therefore, it is a great challenge and of urgent need to detect and identify SEs rapidly and accurately for governmental and non-governmental agencies, including the military, public health departments, and health care facilities. Herein, an overview of SE detection has been provided through a comprehensive literature survey

miR-21/SMAD2 Is Involved in the Decrease in Progesterone Synthesis Caused by Lipopolysaccharide Exposure in Follicular Granulosa Cells of Laying Goose

Lipopolysaccharide (LPS) is one of the important pathogenic substances of E. coli and Salmonella, which causes injury to the reproductive system. Ovarian dysfunction due to Gram-negative bacterial infections is a major cause of reduced reproductive performance in geese. However, the specific molecular mechanisms of LPS-induced impairment of sex steroid hormone synthesis have not been determined. The regulatory mechanism of miRNA has been proposed in many physiological and pathogenic mechanisms. Therefore, the role of miRNA in breeding geese exposed to LPS during the peak laying period was investigated. In this study, twenty Yangzhou geese at peak laying period were injected with LPS for 0 h, 24 h, and 36 h. The follicular granulosa layer was taken for RNA-seq and analyzed for differentially expressed miRNAs. It was observed that LPS changed the appearance of hierarchical follicles. miRNA sequencing analysis was applied, and miR-21 and SMAD2 (SMAD family member 2) were selected from 51 differentially expressed miRNAs through bioinformatics prediction. The results showed that miR-21 down-regulated SMAD2 expression and progesterone (P4) production in LPS-treated goose granulosa cells (GCs). It also determined that overexpression of miR-21 or silence of SMAD2 suppressed the sex steroid biosynthesis pathway by decreasing STAR and CYP11A1 expression. Down-regulation of miR-21 exacerbates the LPS-induced decline in P4 synthesis and vice versa. The findings indicated that miR-21 was involved in LPS regulation of P4 synthesis in goose granulosa cells by down-regulating SMAD2. This study provides theoretical support for the prevention of LPS-induced ovarian dysfunction in geese

Improving Automatic Fetal Biometry Measurement with Swoosh Activation Function

The measurement of fetal thalamus diameter (FTD) and fetal head circumference (FHC) are crucial in identifying abnormal fetal thalamus development as it may lead to certain neuropsychiatric disorders in later life. However, manual measurements from 2D-US images are laborious, prone to high inter-observer variability, and complicated by the high signal-to-noise ratio nature of the images. Deep learning-based landmark detection approaches have shown promise in measuring biometrics from US images, but the current state-of-the-art (SOTA) algorithm, BiometryNet, is inadequate for FTD and FHC measurement due to its inability to account for the fuzzy edges of these structures and the complex shape of the FTD structure. To address these inadequacies, we propose a novel Swoosh Activation Function (SAF) designed to enhance the regularization of heatmaps produced by landmark detection algorithms. Our SAF serves as a regularization term to enforce an optimum mean squared error (MSE) level between predicted heatmaps, reducing the dispersiveness of hotspots in predicted heatmaps. Our experimental results demonstrate that SAF significantly improves the measurement performances of FTD and FHC with higher intraclass correlation coefficient scores in FTD and lower mean difference scores in FHC measurement than those of the current SOTA algorithm BiometryNet. Moreover, our proposed SAF is highly generalizable and architecture-agnostic. The SAF’s coefficients can be configured for different tasks, making it highly customizable. Our study demonstrates that the SAF activation function is a novel method that can improve measurement accuracy in fetal biometry landmark detection. This improvement has the potential to contribute to better fetal monitoring and improved neonatal outcomes