Effect of nickel chloride on Arabidopsis genomic DNA and methylation of 18S rDNA

AbstractBackgroundIn recent years, nickel (Ni) has been widely applied in industrial and agricultural production and has become a kind of environmental pollution. In this study, the effect of nickel chloride (NiCl2) with different concentrations on Arabidopsis genomic stability and DNA methylation has been demonstrated. The nucleolus variation and 18S rDNA methylation after NiCl2 treatment have been analyzed.ResultsThe results are as follows: (1) The NiCl2 could result in heritable genomic methylation variations. The genomic DNA methylation variations have been detected by methylation-sensitive amplified polymorphism (MSAP) molecular markers, and the result showed that after NiCl2 treatment, there was methylation variation in T0 generation seedlings, and partial site changes maintained in T1 generation, which suggested that the effects of NiCl2 on DNA methylation could be heritable in offspring. (2) NiCl2 brought deformity and damage to nucleolar structure in Arabidopsis root tip cells, and the damage was positively correlated with the NiCl2 concentration. 3. In the nucleolus, there was an increased cytosine methylation in 18S rDNA. The plant nucleolus variation and 18S rDNA methylation may be used as an examination indicator for Ni pollution in soil or plant.ConclusionsNiCl2 application caused variation of DNA methylation of the Arabidopsis genomic and offspring's. NiCl2 also resulted in nucleolar injury and deformity of root tip cells. The methylation rate of 18S rDNA also changed by adding NiCl2

Effect of nickel chloride on Arabidopsis genomic DNA and methylation of 18S rDNA

Background: In recent years, nickel (Ni) has beenwidely applied in industrial and agricultural production and has become a kind of environmental pollution. In this study, the effect of nickel chloride (NiCl2) with different concentrations on Arabidopsis genomic stability and DNA methylation has been demonstrated. The nucleolus variation and 18S rDNA methylation after NiCl2 treatment have been analyzed. Results: The results are as follows: (1) The NiCl2 could result in heritable genomic methylation variations. The genomic DNA methylation variations have been detected by methylation-sensitive amplified polymorphism (MSAP) molecular markers, and the result showed that after NiCl2 treatment, there was methylation variation in T0 generation seedlings, and partial site changes maintained in T1 generation, which suggested that the effects of NiCl2 on DNA methylation could be heritable in offspring. (2) NiCl2 brought deformity and damage to nucleolar structure in Arabidopsis root tip cells, and the damage was positively correlated with the NiCl2 concentration. 3. In the nucleolus, there was an increased cytosine methylation in 18S rDNA. The plant nucleolus variation and 18S rDNA methylation may be used as an examination indicator for Ni pollution in soil or plant. Conclusions: NiCl2 application caused variation of DNA methylation of the Arabidopsis genomic and offspring's. NiCl2 also resulted in nucleolar injury and deformity of root tip cells. The methylation rate of 18S rDNA also changed by adding NiCl2

Association between the gut microbiota, inflammatory factors, and colorectal cancer: evidence from Mendelian randomization analysis

BackgroundColorectal cancer (CRC) is one of the most common malignant tumors primarily affecting individuals over the age of 50 years. Recent studies have suggested that the dysbiosis of the gut microbiota, a community of microorganisms in the human gut, is closely associated with the occurrence and development of CRC. Additionally, inflammatory factors (IFs) have also been reported to play a significant role in the development of CRC. However, the causal relationships between the gut microbiota, IFs, and CRC remain unclear.MethodsIn this study, we performed Mendelian randomization (MR) analysis using publicly available genome-wide association study (GWAS) data to explore the causal relationship between the gut microbiota, IFs, and CRC. The gut microbiota GWAS data were obtained from the MiBioGen study, while the IFs GWAS data were derived from the comprehensive analysis of three independent cohorts. Causal relationship analysis was conducted using appropriate instrumental variables (IVs) and statistical models.ResultsMR analysis of the gut microbiota and CRC revealed a negative correlation between the Lachnospiraceae species in the gut and CRC risk, while a positive correlation was observed between Porphyromonadaceae species, Lachnospiraceae UCG010 genus, Lachnospira genus, and Sellimonas genus in the gut, and CRC risk. Additionally, we observed a causal relationship between IL-10 and CRC risk. These findings suggest that the dysbiosis of the gut microbiota might be associated with an increased risk of CRC and that specific bacterial groups may play a crucial role in the occurrence and development of CRC.ConclusionUsing MR analysis, this study revealed the causal relationships between the gut microbiota, IFs, and CRC. The negative correlation between the Lachnospiraceae species in the gut and CRC risk, as well as the causal relationship between IL-10 and CRC, provide important clues for the potential roles of gut microbiota regulation and inflammatory factor control in the prevention and treatment of CRC

MPS-NeRF: Generalizable 3D Human Rendering from Multiview Images

There has been rapid progress recently on 3D human rendering, including novel view synthesis and pose animation, based on the advances of neural radiance fields (NeRF). However, most existing methods focus on person-specific training and their training typically requires multi-view videos. This paper deals with a new challenging task -- rendering novel views and novel poses for a person unseen in training, using only multiview images as input. For this task, we propose a simple yet effective method to train a generalizable NeRF with multiview images as conditional input. The key ingredient is a dedicated representation combining a canonical NeRF and a volume deformation scheme. Using a canonical space enables our method to learn shared properties of human and easily generalize to different people. Volume deformation is used to connect the canonical space with input and target images and query image features for radiance and density prediction. We leverage the parametric 3D human model fitted on the input images to derive the deformation, which works quite well in practice when combined with our canonical NeRF. The experiments on both real and synthetic data with the novel view synthesis and pose animation tasks collectively demonstrate the efficacy of our method.Comment: This submission has been removed by arXiv administrators because the submitter did not have the authority to grant the license at the time of submissio

Multiobjective Collaborative Optimization of Argon Bottom Blowing in a Ladle Furnace Using Response Surface Methodology

In order to consider both the refining efficiency of the ladle furnace (LF) and the quality of molten steel, the water model experiment is carried out. In this study, the single factor analysis, central composite design principle, response surface methodology, visual analysis of response surface, and multiobjective optimization are used to obtain the optimal arrangement scheme of argon blowing of LF, design the experimental scheme, establish the prediction models of mixing time (MT) and slag eye area (SEA), analyze the comprehensive effects of different factors on MT and SEA, and obtain the optimal process parameters, respectively. The results show that when the identical porous plug radial position is 0.6R and the separation angle is 135°, the mixing behavior is the best. Moreover, the optimized parameter combination is obtained based on the response surface model to simultaneously meet the requirements of short MT and small SEA in the LF refining process. Meanwhile, compared with the predicted values, the errors of MT and SEA for different conditions from the experimental values are 1.3% and 2.1%, 1.3% and 4.2%, 2.5% and 3.4%, respectively, which is beneficial to realizing the modeling of argon bottom blowing in the LF refining process and reducing the interference of human factors

Wide-bandwidth triboelectric energy harvester combining impact nonlinearity and multi-resonance method

This paper presents a novel wide-bandwidth triboelectric energy harvester (WBTEH) that takes advantage of impact nonlinearity and multi-resonance. The harvester features a triboelectric transducer that operates in contact and separation mode, with two cantilever beams of different resonant frequencies connected to it. By exploiting the relative motion of the beams, the harvester achieves a broad bandwidth through the resonance shift caused by the impact and multi-resonance. A WBTEH prototype with a 3 mm gap between the triboelectric pair shows a total bandwidth of 4.3 Hz even at a low base excitation of 3 m/s2. The matched peaks and bandwidth in the frequency up-sweep and down-sweep tests demonstrate the excellent stability of the WBTEH. The frequency locking phenomenon with strong resonance occurs in the WBTEH when the displacement amplitude/gap ratio exceeds 1.48, which is beneficial for obtaining a continuous bandwidth and a high power output. An electromechanical model is formulated for parametric studies that investigate the effects of contact stiffness and damping on the performance of WBTEH. It is found that large impact stiffness and small damping can cause quasi-periodic motion, leading to a non-constant voltage output that should be prevented in the harvester design. The WBTEH is capable of powering wireless sensors, making it a potential candidate for Internet of Things (IoT) applications.Submitted/Accepted versio

Comprehensive integration of single-cell RNA and transcriptome RNA sequencing to establish a pyroptosis-related signature for improving prognostic prediction of gastric cancer

Cell pyroptosis, a Gasdermin-dependent programmed cell death characterized by inflammasome, plays a complex and dynamic role in Gastric cancer (GC), a serious threat to human health. Therefore, the value of pyroptosis-related genes (PRGs) as prognostic biomarkers and therapeutic indicators for patients needs to be exploited in GC. This study integrates single-cell RNA sequencing (scRNA-seq) dataset GSE183904 with GC transcriptome data from the TCGA database, focusing on the expression and distribution of PRGs in GC at the single-cell level. The prognostic signature of PRGs was established by using Cox and LASSO analyses. The differences in long-term prognosis, immune infiltration, mutation profile, CD274 and response to chemotherapeutic drugs between the two groups were analyzed and evaluated. A tissue array was used to verify the expression of six PRGs, CD274, CD163 and FoxP3. C12orf75, VCAN, RGS2, MKNK2, SOCS3 and TNFAIP2 were successfully screened out to establish a signature to potently predict the survival time of GC patients. A webserver (https://pumc.shinyapps.io/GastricCancer/) for prognostic prediction in GC patients was developed based on this signature. High-risk score patients typically had worse prognoses, resistance to classical chemotherapy, and a more immunosuppressive tumor microenvironment. VCAN, TNFAIP2 and SOCS3 were greatly elevated in the GC while RGS2 and MKNK2 were decreased in the tumor samples. Further, VCAN was positively related to the infiltrations of Tregs and M2 TAMs in GC TME and the CD274 in tumor cells. In summary, a potent pyroptosis-related signature was established to accurately forecast the survival time and treatment responsiveness of GC patients

Methanol Steam Reforming over La1-xSrxCeO3-δ Catalysts for Hydrogen Production: Optimization of Operating Parameters

In this study, a series of A-site strontium-doped La1-xSrxCeO3-δ (x = 0.2, 0.4, 0.6, 0.8) perovskite catalysts were synthesized via the ethylenediaminetetraacetic acid (EDTA) sol-gel method for hydrogen production by methanol steam reforming. The fresh and the reduced catalysts are characterized by scanning X-ray (XRD), energy dispersive X-ray spectroscopy (EDS) and scanning electron microscopy (SEM) techniques. Results showed that La0.6Sr0.4CeO3-δ exhibited the best performance among the La1-xSrxCeO3-δ catalysts. The operating parameters were optimized to study the catalytic performance of La0.6Sr0.4CeO3-δ, including catalytic temperature, water–methanol ratio (W/M) and liquid hourly space velocity (LHSV). However, the excessive strontium content led to a decrease in hydrogen production amount per unit time, and the high W/M promoted the reverse water–gas shift reaction (RWGS), which resulted in a decrease in CO selectivity and an increase in CO2 selectivity. In addition, the optimal reaction parameters are as follows: reforming temperature of 700 °C; W/M of 3:1; LHSV of 20 h−1. Furthermore, the methanol conversion rate of La0.6Sr0.4CeO3-δ can reach approximately 82%, the hydrogen production can reach approximately 3.26 × 10−3 mol/g(cat)/min under the optimum reaction conditions. Furthermore, La0.6Sr0.4CeO3-δ exhibits high hydrogen selectivity (85%), which is a promising catalyst for MSR application