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Numerical simulation and analysis are effective means to explore the basic laws of the world, in which a synthetic model provides a model basis for research. A random medium model can effectively characterize the small-scale heterogeneity in artificial or natural complex media and has been widely used in reservoir, deposit, material, engineering, and other fields. Many efficient and accurate modeling methods have been proposed for stationary random medium models. However, the modeling efficiency of a random medium with nonstationary statistical characteristics is very low. In this paper, an efficient nonstationary random medium modeling method based on Fast Fourier transform moving average (FFT-MA) method and convolutional neural network is proposed. FFT-MA is used to quickly simulate a low-resolution random medium model, which satisfies the change of large-scale statistical characteristics. Then we transform the low-resolution model into a high-resolution model by a convolutional neural network. The convolutional neural network is trained using a set of stationary random medium models. The modeling experiments show that this method can accurately construct a nonstationary random medium model meeting the nonstationary statistical characteristics and improves the modeling efficiency.

Although the functions of metabolic enzymes and nuclear receptors in controlling physiological homeostasis have been established, their crosstalk in modulating metabolic disease has not been explored. Genetic ablation of the xenobiotic-metabolizing cytochrome P450 enzyme CYP2E1 in mice markedly induced adipose browning and increased energy expenditure to improve obesity. CYP2E1 deficiency activated the expression of hepatic peroxisome proliferator-activated receptor alpha (PPARα) target genes, including fibroblast growth factor (FGF) 21, that upon release from the liver, enhanced adipose browning and energy expenditure to decrease obesity. Nineteen metabolites were increased in Cyp2e1-null mice as revealed by global untargeted metabolomics, among which four compounds, lysophosphatidylcholine and three polyunsaturated fatty acids were found to be directly metabolized by CYP2E1 and to serve as PPARα agonists, thus explaining how CYP2E1 deficiency causes hepatic PPARα activation through increasing cellular levels of endogenous PPARα agonists. Translationally, a CYP2E1 inhibitor was found to activate the PPARα–FGF21–beige adipose axis and decrease obesity in wild-type mice, but not in liver-specific Ppara-null mice. The present results establish a metabolic crosstalk between PPARα and CYP2E1 that supports the potential for a novel anti-obesity strategy of activating adipose tissue browning by targeting the CYP2E1 to modulate endogenous metabolites beyond its canonical role in xenobiotic-metabolism.

Abstract Background Dried fruits of Psoralea corylifolia L. (Psoraleae Fructus) is one of the most popular traditional Chinese medicine with treatment for nephritis, spermatorrhea, pollakiuria, asthma, and various inflammatory diseases. Bakuchiol is main meroterpenoid with bioactive diversity from Psoraleae Fructus. This study was designed to seek structural diverse bakuchiol derivants with anti-inflammatory activities from this plant. Methods Various column chromatography methods were used for isolation experiment. Structures and configurations of these compounds were determined by spectroscopic methods and single-crystal X-ray diffraction. Their inhibition on nitric oxide (NO) production in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages were evaluated by the Griess reaction. Results Twelve unpresented bakuchiol dimmers, bisbakuchiols M–U (1–9) and bisbakuchiol ethers A–C (10–12), along with five known compounds (13–17), were isolated from the fruits of Psoralea corylifolia L. Compounds 1–3, 10–12, 16 and 17 exhibited inhibitory activities against LPS-induced NO production in RAW264.7 macrophages, and the inhibition of compound 1 (half maximal inhibitory concentration (IC50) value = 11.47 ± 1.57 μM) was equal to that of L-N(6)-(1-iminoethyl)-lysine (IC50 = 10.29 ± 1.10 μM) as a positive control. Conclusions Some compounds exhibited inhibitory activities against NO production, and the study of structure–activity relationship suggested that uncyclized compounds with oxygen substitution at C-12/12′ showed strong inhibitory activities, and carbonyl units contributed to enhanced activities.

Dendranthema zawadskii Herbich is one of 17 species of Dendranthema in China, and it is often used as an ornamental plant. The chloroplast genome size of Dendranthema zawadskii Herbich is 150,995 bp, including a large single-copy region (82,771 bp), a small single-copy region (18,308 bp), and a pair of inverted repeats regions (24,958 bp). Total 112 genes were annotated, including 79 protein-coding genes, four ribosomal RNA genes, and 29 transfer RNA genes. The phylogenetic position of Dendranthema zawadskii Herbich is close to Dendranthema indicum.

Abstract Background Fukeqianjin formula (FKQJF) is a Chinese medicine prescription, which has been widely used individually or in combination with other western medicine for the treatment of various gynecological inflammatory diseases, including chronic cervicitis, chronic pelvic inflammatory disease and endometritis, so on and so force. Methods The ultra-fast liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UFLC–MS/MS), a quick and efficient method was established and applied to quantify the major constituents of Fukeqianjin formula in rat plasma, and its pharmacokinetics of oral absorption was studied. Nineteen components in Fukeqianjin formula were detected and identified as the major compounds absorbed into the blood according to their chromatographic behavior, molecular weight, ion fragments and other information of these compounds. Furthermore, the plasma drug concentration–time curves were established and the related kinetic parameters were analyzed. Results The results showed that all the 19 compounds could be rapidly absorbed by the gastrointestinal tract, the plasma drug concentration of most compounds could reach a peak at around 1–2 h, and the double-peaks on behalf of the enterohepatic circulation were found in most drug concentration–time curves. The method used in this experiment was validated comprehensively including specificity, linearity, precision, accuracy, stability, matrix effect, and recovery. Conclusions These results showed that the developed method was suitable for pharmacokinetic analysis of the main components of Fukeqianjin formula in rat plasma, and may provide useful information for the subsequent distribution studies in vivo.

Abstract Background Maize (Zea mays L.) is one of the main agricultural crops with the largest yield and acreage in the world. However, maize germplasm is very sensitive to low temperatures, mainly during germination, and low temperatures significantly affect plant growth and crop yield. Therefore, the identification of genes capable of increasing tolerance to low temperature has become necessary. Results In this study, fourteen phenotypic traits related to seed germination were used to assess the genetic diversity of maize through genome-wide association study (GWAS). A total of 30 single-nucleotide polymorphisms (SNPs) linked to low-temperature tolerance were detected (−log10(P) > 4), fourteen candidate genes were found to be directly related to the SNPs, further additional 68 genes were identified when the screen was extended to include a linkage disequilibrium (LD) decay distance of r 2 ≥ 0.2 from the SNPs. RNA-sequencing (RNA-seq) analysis was then used to confirm the linkage between the candidate gene and low-temperature tolerance. A total of ten differentially expressed genes (DEGs) (|log2 fold change (FC)| ≥ 0.585, P

Seismic impedance inversion is an important method to identify the spatial characteristics of underground rock physical properties. Seismic inversion results and uncertainty evaluation are the important scientific basis for risk decision-making in oil and gas development. Under the assumption that the impedance and the error of the observed seismic data meet the Gaussian distribution or log–Gaussian distribution, the Bayesian linear seismic inversion can analytically obtain the posterior probability distribution of impedance. However, errors from observation, calculation, model and other factors can lead to an inaccurate and incomplete uncertainty evaluation. In this paper, the noise variance is used to represent the noise level of seismic data and the uncertainties from seismic wavelet extraction and noise level estimation are considered in inversion. Assuming that the probability distribution of the noise variance meets the inverse gamma distribution and the seismic wavelet meets the Gaussian distribution, we could obtain the conditional distribution for one variable given another analytically using well-log data and seismic data. In order to integrate the uncertainty from noise level estimation and wavelet extraction into the seismic impedance inversion, the Gibbs sampler algorithm was applied to draw a set of realizations of noise variance and wavelet. For each realization, the corresponding posterior probability model of impedance was achieved by Bayesian linear inversion and the final posterior probability of the impedance model was obtained by integrating all the single posterior probabilities for each pair of wavelet and noise variance. Synthetic and real data experiments showed that the uncertainties of seismic wavelet extraction and noise level estimation have an important influence on inversion results and their uncertainties. The proposed method could effectively integrate the uncertainty of wavelet and noise estimation to obtain a more accurate and comprehensive uncertainty evaluation. Under the assumption that the model meets the linear relationship and the parameters meet some specified distribution, the proposed method has high calculation efficiency. However, it also loses some accuracy when the assumptions are not completely consistent with the actual situation.

Terahertz (THz) nondestructive testing (NDT) technology has been increasingly applied to the internal defect detection of composite materials. However, the THz image is affected by background noise and power limitation, leading to poor THz image quality. The recognition rate based on traditional machine vision algorithms is not high. The above methods are usually unable to determine surface defects in a timely and accurate manner. In this paper, we propose a method to detect the internal defects of composite materials by using terahertz images based on a faster region-convolutional neural networks (faster R-CNNs) algorithm. Terahertz images showing internal defects in composite materials are first acquired by a terahertz time-domain spectroscopy system. Then the terahertz images are filtered, the blurred images are removed, and the remaining images are enhanced with data and annotated with image defects to create a dataset consistent with the internal defects of the material. On the basis of the above work, an improved faster R-CNN algorithm is proposed in this paper. The network can detect various defects in THz images by changing the backbone network, optimising the training parameters, and improving the prior box algorithm to improve the detection accuracy and efficiency of the network. By taking the commonly used composite sandwich structure as a representative, a sample with typical defects is designed, and the image data are obtained through the test. Comparing the proposed method with other existing network methods, the former proves to have the advantages of a short training time and high detection accuracy. The results show that the mean average precision (mAP) without data enhancement reached 95.50%, and the mAP with data enhancement reached 98.35% and exceeded the error rate of human eye detection (5%). Compared with the original faster R-CNN algorithm of 84.39% and 85.12%, the improvement is 11.11% and 10.23%, respectively, which demonstrates superb feature extraction capability and reduces the occurrence of network errors and omissions.

Dracaena fragrans is a shrub native to tropical Africa classified in the family Asparagaceae. It is a common horticultural plant grown as a hedge as well as an ornamental house plant for its green leaves, attractive shape and fragrant flowers. The species has been used for many medicinal purposes including inducing labor, treating malnutrition and fighting illness. Here, we investigated the complete plastid genome of D. fragrans using Illumina 150 bp next-generation sequencing technologies. De novo assembly and annotation showed that the chloroplast genome is a typical quadripartite structure with 37.5% GC content. A pair of inverted repeats (IRs, 26,507 bp each) were separated by one large single-copy region (LSC, 83,703 bp) and one small single-copy region (SSC, 18,466 bp). The chloroplast genome is 155,183 bp in length and contained 131 genes of which 12 are intron-containing genes, comprising 85 protein-coding, 38 tRNA, and 8 rRNA genes. Phylogenetic analysis of D. fragrans and 11 plastomes obtained from GenBank shows that it is closely related to D. elliptica.

Compound Kushen Injection (CKI) is a bis-herbal formulation extracted from Kushen (Radix Sophorae Flavescentis) and Baituling (Rhizoma Heterosmilacis Yunnanensis). Clinically, it is used as the adjuvant treatment of cancer. However, with the increased application, the cases of immediate hypersensitivity reactions (IHRs) also gradually rise. In this study, we investigated the underlying mechanism(s) and active constituent(s) for CKI-induced IHRs in experimental models. The obtained results showed that CKI did not elevate serum total IgE (tIgE) and mouse mast cell protease 1 (MMCP1) after consecutive immunization for 5 weeks, but could induce Evans blue extravasation (local) and cause obvious hypothermia (systemic) after a single injection. Further study showed that alkaloids in Kushen, especially matrine, were responsible for CKI-induced IHRs. Mechanism study showed that various platelet-activating factor (PAF) receptor antagonists could significantly counter CKI-induced IHRs locally or systemically. In cell system, CKI was able to promote PAF production in a non-cell-selective manner. In cell lysate, the effect of CKI on PAF production became stronger and could be abolished by blocking de novo pathway. In conclusion, our study identifies, for the first time, that CKI is a PAF inducer. It causes non-immunologic IHRs, rather than IgE-dependent IHRs, by promoting PAF production through de novo pathway. Alkaloids in Kushen, especially matrine, are the prime culprits for IHRs. Our findings may provide a potential approach for preventing and treating CKI-induced IHRs.

BackgroundGrowing evidence demonstrates that the initiation and progression of colorectal carcinoma (CRC) is related to the presence of cancer stem cells (CSCs). However, the mechanism through which the stem cell features of CRC cells are maintained is poorly understood. In this study, we identified the oncogenic histone cluster 2 H2B family member F (HIST2H2BF) and aimed to investigate the function of upregulated HIST2H2BF expression in maintaining the stem cell features of CRC cells, which accelerate the progression of CRC.MethodsHIST2H2BF expression was quantified using real-time polymerase chain reaction, immunohistochemistry, and western blotting. The correlation between CpG island methylation status and HIST2H2BF re-expression was assessed through bisulfite sequencing polymerase chain reaction, methylation-specific polymerase chain reaction, and 5-Aza-dC treatment. Functional assays were performed on CRC cells and mice to investigate the HIST2H2BF-induced stem cell-like and cancer properties of CRC. Using the Notch pathway inhibitor FLI-06, the regulatory effect of HIST2H2BF on downstream Notch signaling was confirmed.ResultsHIST2H2BF was highly expressed in CRC tissues and cell lines. The reactivation of HIST2H2BF in CRC stems at least in part from the hypomethylated CpG islands. CRC patients with high HIST2H2BF expression have poor survival outcomes. Functional studies have shown that HIST2H2BF promotes CSC phenotype, malignancy, and liver metastasis through the activation of Notch signaling in CRC. Blockage of the Notch pathway reduced the stem cell-like and cancer properties.ConclusionOur study suggests that HIST2H2BF upregulation enhances the CSC phenotype, malignancy, and liver metastasis through the activation of Notch signaling in CRC. These results identified a new perspective on the mechanism by which the stem cell features of CRC cells are maintained and highlighted the potential novel therapeutic targets for CRC.

Ceramic adhesive structures have been increasingly used in aerospace applications. However, the peaks of the signal on the upper and lower surface of the adhesive layer are difficult to measure directly due to the thin thickness of the adhesive layer and the effect of the attenuation dispersion of the ceramic layer. Thus, the existing non-destructive testing techniques have been ineffective in detecting adhesive quality. In this paper, the thickness of the adhesive layer is measured using terahertz time-domain spectroscopy. A sparse deconvolution method is proposed for the terahertz time-domain spectral signal of ceramic adhesive structures with different adhesive layer thicknesses. The results show that the methods proposed in this paper can realize the separation of reflection signals for glue layers with a thickness of 0.20 mm. By comparing with a wavelet denoising method and a modified covariance method (AR/MCM), the effectiveness of the sparse deconvolution method in estimating the thickness of the glue layer is demonstrated. This work will provide the theoretical and experimental basis for using terahertz time-domain spectroscopy to detect the homogeneity of ceramic adhesive structures.

High-Frequency Pressure Fluctuation (HFPF) is an extensively observed hydraulic phenomenon in pumped-storage power stations and water conveyance projects. The investigation of the propagation characteristics of the pressure perturbation is of great significance for the safe operation of hydraulic facilities. In this study, a one-dimensional (1D)–three-dimensional (3D) coupling model is established based on the combination of the Method of Characteristics (MOC) and Computational Fluid Dynamics (CFD) and implanted in the open source software OpenFOAM. The established model in this study implants the dynamic mesh module into the original OpenFOAM solver sonicLiquidFoam and presents the complete solution procedure of the CFD model with the dynamic mesh considered. The vibration of the pipe walls modeled by the mesh motion is employed to numerically generate the HFPF in the hydraulic system, which could not be implemented in the traditional MOC model. The independence of the pressure perturbation in the pipeline system is validated by the time-domain pressure variation. The graphical method is applied to describe the multiple reflection and superposition characteristics of the traveling wave in a simplified hydraulic system. Based on this, the mechanism of the superimposed characteristic of the traveling and standing pressure waves in the hydraulic system are analyzed, and the theoretical superimposed time-domain processes and the variations of the pressure oscillation magnitude are analyzed and presented. The 1D–3D coupling method and the theoretical analysis method could be referenced by other complex hydraulic systems.

BackgroundThe role of ferroptosis in tumorigenesis has been confirmed in previous studies. However, the comprehensive analysis of ferroptosis-related gene (FRG) to study the role of FRG in soft tissue sarcoma (STS) is lacking.MethodsRNA sequencing profile of TCGA-SARC cohort and GTEx were used to select differentially expressed FRGs (DEFRGs). Univariate, LASSO, and multivariate Cox analyses were selected to determine overall survival (OS)- and disease-free survival (PFS)-related FRGs. Two prognostic signatures were established and validated in two independent sets from Gene Expression Omnibus (GEO). Finally, the expression of key FRGs were validated with RT-qPCR.ResultsIn total, 198 FRGs (90.4%) were abnormally expressed in STS. Twelve DEFRGs were incorporated in the final signatures and showed favorable discrimination in both training and validation cohorts. Patients in the different risk groups not only showed different prognosis, but also showed different infiltration of immune cells. Two nomograms combining signature and clinical variables were established and the C-indexes were 0.852 and 0.752 for the OS and DFS nomograms, respectively. Finally, the expression of NOX5, HELLS, and RPL8 were validated with RT-qPCR.ConclusionThis comprehensive analysis of the FRG landscape in STS revealed novel FRGs related to carcinogenesis and prognosis. These findings have implications for prognosis and therapeutic responses, which revealed potential prognostic biomarkers and promote precision medicine.

A method based on high performance liquid chromatography with evaporative light scattering detection (HPLC-ELSD) was developed for the quantitative analysis of three active compounds and chemical fingerprint analyses of saccharides in Morindae officinalis radix. Ten batches of Morindae officinalis radix were collected from different plantations in the Guangdong region of China and used to establish the fingerprint. The samples were separated with a COSMOIL Sugar-D column (4.6 mm × 250 mm, 5 μm) by using gradient elution with water (A) and acetonitrile (B). In addition, Trapped-Ion-Mobility (tims) Time-Of-Flight (tims TOF) was used to identify saccharides of Morindae officinalis radix. Fingerprint chromatogram presented 26 common characteristic peaks in the roots of Morinda officinalis How, and the similarities were more than 0.926. In quantitative analysis, the three compounds showed good regression (r = 0.9995–0.9998) within the test ranges, and the recoveries of the method were in the range of 96.7–101.7%. The contents of sucrose, kestose and nystose in all samples were determined as 1.21–7.92%, 1.02–3.37%, and 2.38–6.55%, respectively. The developed HPLC fingerprint method is reliable and was validated for the quality control and identification of Morindae officinalis radix and can be successfully used to assess the quality of Morindae officinalis radix.

Granular sludge is the key to the efficient operation of the UASB reactor, which directly affects the treatment efficiency of the reactor. The ordinary flocculent sludge is lighter, and it is easy to be flushed out of the reactor under the action of the influent water flushing in the UASB reactor and the gas scouring generated by the anaerobic reaction of the reactor sludge layer, resulting in reducing in the sludge concentration in the reactor, thus affecting the removal effect. Granular sludge has good settle ability and is not easily lost in the UASB reactor. In this paper, the performance of seed sludge inoculated by two different UASB process is studied to propose the best seed sludge inoculated under the condition of no anaerobic reactor sludge inoculation, which provides references for anaerobic biological treatment of high concentration wastewater.

Proper utilisation of non-destructive testing (NDT) methods is crucial for ensuring the engineering safety of composites. Ultrasonic testing (UT) and X-ray computed tomography (CT) are two commonly used NDT methods for inspecting glass fibre-reinforced polymer (GFRP) composites, each with its unique advantages and limitations. In a previous study, the authors found that UT has lower resolution in detecting delamination and inclusion defects compared to X-ray CT, which has a lower contrast. Both methods also lack the ability to perform automated quantitative testing. To overcome these limitations, this paper proposes a fusion algorithm that combines data from UT and X-my CT imaging to detect hidden delamination and inclusion defects in GFRP composites. The proposed fusion method based on significant region enhancement and block fusion combines the strengths of UT and X-ray CT to enhance the precision and efficiency of material detection. By further utilising image segmentation methods, defects can be automatically quantified. This method not only aids scholars in characterising composite materials more comprehensively but also has the potential to facilitate the development and application of novel composite materials. It serves as a valuable supplement to traditional inspection techniques and has the capability to promote the advancement of materials science. [ABSTRACT FROM AUTHOR]

To investigate the molecular mechanisms of Buxue Yimu Pills (BYP) on postpartum abdominal pain (PAP) through network pharmacology and experimental validation, we filtered the main active components of BYP using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Symptom Mapping (SymMap), Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) database, and Pharmacopoeia of the People's Republic of China (ChP). The targets related to PAP were obtained from Genecards, and an intersection of genes was discovered. Subsequently, protein-protein interaction (PPI) networks were constructed using Cytoscape 3.9.0 and the String database. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to analyze the intersection of targets using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8. We constructed a compound-target (C-T) network based on the above analysis. Animal experiments were performed to verify the core targets, and immunohistochemistry was used to detect protein expression in incomplete abortion rats. Network pharmacology analysis suggested that 40 potentially active ingredients in BYP might affect 40 potential disease-related targets, such as ESR1, PGR, and MMP2, and regulate pathways, such as the HIF-1 signaling pathway, TNF signaling pathway, and Estrogen signaling pathway. According to immunohistochemistry, the protein expression levels of ER α, PR, and MMP2 in the model rats were significantly increased (P < 0.01). After administration of BYP, the expression level of PR was increased ( P < 0.01), and the expression levels of ERα and MMP2 were decreased significantly (P < 0.05 or P < 0.01). BYP could treat PAP through a multi-component, multi-target, and multi-pathway approach, regulating estrogen and progesterone receptors and improving collagen metabolism, thereby promoting postpartum uterine recovery. [ABSTRACT FROM AUTHOR]

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Oxidative damage and neuroinflammation are associated with numerous neurological diseases. In recent years, Psoraleae Fructus (dried fruits of Psoralea corylifolia L.), a traditional Chinese medicine, has been found to have medicinal properties in ameliorating central nervous system (CNS) injury. This study aimed to evaluate two neuroprotective compounds of Psoraleae Fructus: corylin and psoralidin, and reveal their underlying mechanisms. The results showed that corylin and psoralidin suppressed reactive oxygen species (ROS) production in H2O2-induced HT22 cells and nitric oxide (NO) production in lipopolysaccharide (LPS)-induced BV2 cells. Further mechanism research of corylin was carried out owing to its better safety and efficacy. In H2O2-induced HT22 cells, corylin significantly increased catalase (CAT), superoxide dismutase (SOD) activity, and glutathione (GSH) expression, while it inhibited mitochondrial membrane potential (MMP) reduction. Meanwhile, the expressions of Nrf2 and HO-1 were up-regulated. In LPS-induced BV2 cells, corylin markedly inhibited IL-1β, IL-6, and TNF-α expressions and specifically suppressed NF-κB p65 nuclear translocation. Furthermore, the docking analysis showed that corylin penetrated well into the hydrophobic pockets of Keap 1 and NF-KB protein. This study demonstrated that corylin alleviated oxidative damage and neuroinflammation by activating Nrf2/HO-1 and inhibiting NF-κB pathways, suggesting its potential ability to treat neurological diseases. [ABSTRACT FROM AUTHOR]