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In this paper, we use elementary linear algebra methods to explore possible Hopf algebra structures within the generalized quaternion algebra. The sufficient and necessary conditions that make the generalized quaternion algebra a Hopf algebra are given. It is proven that not all of the generalized quaternion algebras have Hopf algebraic structures. When the generalized quaternion algebras have Hopf algebraic structures, we describe all the Hopf algebra structures. Finally, we shall prove that all the Hopf algebra structures on the generalized quaternion algebras are isomorphic to Sweedler Hopf algebra, which is consistent with the classification of 4-dimensional Hopf algebras.

Abstract Introduction Hepatitis B Virus (HBV) is widely recognized as a “metabolic virus” that disrupts hepatic metabolic homeostasis, rendering it one of the foremost risk factors for hepatocellular carcinoma (HCC). Except for antiviral therapy, the fundamental principles underlying HBV− and HBV+ HCC have remained unchanged, limiting HCC treatment options. Objectives In this study, we aim to identify the distinctive metabolic profile of HBV-associated HCC, with the promise of identifying novel metabolic targets that confer survival advantages and ultimately impede cancer progression. Methods We employed a comprehensive methodology to evaluate metabolic alterations systematically. Initially, we analyzed transcriptomic and proteomic data obtained from a public database, subsequently validating these findings within our test cohort at both the proteomic and transcriptomic levels. Additionally, we conducted a comprehensive analysis of tissue metabolomics profiles, lipidomics, and the activity of the MAPK and AKT signaling pathway to corroborate the abovementioned changes. Results Our multi-omics approach revealed distinct metabolic dysfunctions associated with HBV-associated HCC. Specifically, we observed upregulated steroid hormone biosynthesis, primary bile acid metabolism, and sphingolipid metabolism in HBV-associated HCC patients’ serum. Notably, metabolites involved in primary bile acid and sphingolipids can activate the MAPK/mTOR pathway. Tissue metabolomics and lipidomics analyses further validated the serum metabolic alterations, particularly alterations in lipid composition and accumulation of unsaturated fatty acids. Conclusion Our findings emphasize the pivotal role of HBV in HCC metabolism, elucidating the activation of a unique MAPK/mTOR signaling axis by primary bile acids and sphingolipids. Moreover, the hyperactive MAPK/mTOR signaling axis transduction leads to significant reprogramming in lipid metabolism within HCC cells, further triggering the activation of the MAPK/mTOR pathway in turn, thereby establishing a self-feeding circle driven by primary bile acids and sphingolipids.

Abstract Non‐alcoholic fatty liver disease (NAFLD) is a prominent cause of various chronic metabolic hepatic diseases with limited therapeutics. Rubicon, an essential regulator in lysosomal degradation, is reported to exacerbate hepatic steatosis in NAFLD mice and patients, indicating its probability of being a therapeutic target for NAFLD treatment. In this study, the therapeutic potential of Rubicon blockage is investigated. Lipid nanoparticles carrying Rubicon‐specific CRISPR‐Cas9 components exhibited liver accumulation, cell internalization, and Rubicon knockdown. A single administration of the nanoparticles results in attenuated lipid deposition and hepatic steatosis, with lower circulating lipid levels and decreased adipocyte size in NAFLD mice. Furthermore, the increase of phosphatidylcholine and phosphatidylethanolamine levels can be observed in the NAFLD mice livers after Rubicon silencing, along with regulatory effects on metabolism‐related genes such as CD36, Gpcpd1, Chka, and Lpin2. The results indicate that knockdown of Rubicon improves glycerophospholipid metabolism and thereby ameliorates the NAFLD progression, which provides a potential strategy for NAFLD therapy via the restoration of Rubicon.

Background and aimsContrast-associated acute kidney injury (CA-AKI) may occur in patients undergoing medical procedures involving x-rays and radiocontrast media, potentially resulting in prolonged renal impairment. However, no effective treatments are available. Therefore, this study aimed to investigate the efficacy of evolocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, in reducing CA-AKI incidence among patients with atherosclerotic cardiovascular disease (ASCVD) undergoing percutaneous coronary intervention.MethodsThis retrospective cohort study included patients who underwent percutaneous coronary intervention between January 2020 and December 2021 at Tianjin Chest Hospital. The study endpoint was CA-AKI incidence, and the impact of selection bias and other potential confounding factors was mitigated using bias matching. Overall, 1,642 patients were included in this study: 821 patients received evolocumab treatment before contrast agent application, and 821 did not receive such treatment.ResultsCA-AKI incidence was 6.21% and 8.04% in the evolocumab and control groups, respectively. After propensity-score matching, the incidence rate was 5.09% and 14.16% in the evolocumab and control groups, respectively. Evolocumab treatment significantly reduced CA-AKI incidence (p

Objective: To develop and validate nomograms for predicting the OS and CSS of patients with Solitary Hepatocellular Carcinoma (HCC). Methods: Using the TRIPOD guidelines, this study identified 5206 patients in the Surveillance, Epidemiology, and End Results (SEER) 17 registry database. All patients were randomly divided in a ratio of 7:3 into a training cohort (n = 3646) and a validation cohort (n = 1560), and the Chinese independent cohort (n = 307) constituted the external validation group. The prognosis-related risk factors were selected using univariate Cox regression analysis, and the independent prognostic factors of OS and CSS were identified using the Lasso-Cox regression model. The nomograms for predicting the OS and CSS of the patients were constructed based on the identified prognostic factors. Their prediction ability was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve in both the training and validation cohorts. Results: We identified factors that predict OS and CSS and constructed two nomograms based on the data. The ROC analysis, C-index analysis, and calibration analysis indicated that the two nomograms performed well over the 1, 3, and 5-year OS and CSS periods in both the training and validation cohorts. Additionally, these results were confirmed in the external validation group. Decision curve analysis (DCA) demonstrated that the two nomograms were clinically valuable and superior to the TNM stage system. Conclusion: We established and validated nomograms to predict 1,3, and 5-year OS and CSS in solitary HCC patients, and our results may also be helpful for clinical decision-making.

To increase the accuracy of indoor visible light positioning, a novel indoor visible light localization technique based on the marine predator algorithm-optimized least squares support vector machine (MPA-LSSVM) is suggested. The light signals of each reference point are recorded in the first place and a fingerprint database is created. Introduced thereafter is the marine predator algorithm, which, through iterative optimization of the hyperparameters of the least squares support vector machine, aims to establish an optimal localization model using finely-tuned hyperparameters. This culminated in the development of a positioning model, successfully attaining the objective of enhancing accuracy in positioning while minimizing time expenditure. In an indoor-positioning scene (size: 1 m × 1 m × 1 m), the average positioning error of the proposed positioning method is 0.041 m, and the proportion of test points with positioning errors less than 0.1 m is 96.7%.

High entropy alloys have excellent wear resistance, so they have great application prospects in the fields of wear resistance and surface protection. In this study, the wear resistance of the FeNiCrCoCu high entropy alloy coating was systematically analyzed by the molecular dynamics method. FeNiCrCoCu high entropy alloy was used as a coating material to adhere to the surface of a Cu matrix. The friction and nanoindentation simulation of this coating material were carried out by controlling the ambient temperature. The influence of temperature on its friction properties was analyzed on five aspects: lattice structure, dislocation evolution, friction coefficient, hardness, and elastic modulus. The results show that with the increase of temperature, the disorder of the lattice structure increases, which leads to an increase of the tangential force and friction coefficient in the friction process. At 300 K and 600 K, the ordered lattice structure of the high entropy alloy coating material is basically the same, and thus its hardness is basically the same. However, the dislocation density at 600 K is significantly reduced compared with that at 300 K, resulting in an increase of the elastic modulus of the material from 173 GPa to 219 GPa. At temperatures of 900 K and 1200 K, lattice disorder takes place rapidly, and dislocation density also decreases significantly, resulting in a significant decrease in the hardness and elastic modulus of the material. When the temperature reaches 900 K, the wear resistance of the FeNiCrCoCu high entropy alloy coating decreases sharply. This work is of great value in the analysis of wear resistance of high entropy alloys at high temperature.

Plant health states may influence the distribution of rhizosphere microorganisms, which regulate plant growth and development. In this study, the response of rhizosphere bacteria and fungi of healthy and diseased plants compared to bulk microbes was analyzed using high-throughput sequencing. Plant adaptation strategies of plants under potato virus Y (PVY) infection have been studied from a microbial perspective. The diversity and community structure of bacteria and fungi varied between bulk and rhizosphere soils, but not between healthy and diseased rhizosphere soils. A LEfSe analysis revealed the significant differences between different treatments on bacterial and fungal community compositions and identified Roseiflexaceae, Sphingomonas, and Sphingobium as the bacterial biomarkers of bulk (BCK), healthy rhizosphere (BHS), and diseased rhizosphere (BIS) soils, respectively; Rhodotorula and Ascomycota_unidentified_1_1 were identified as the fungal biomarkers of bulk (FCK) and healthy rhizosphere (FHS) soils. Bacterial networks were found to be more complex and compact than fungal networks and revealed the roles of biomarkers as network keystone taxa. PVY infection further increased the connectedness among microbial taxa to improve rhizosphere microbial community stability and resistance to environmental stress. Additionally, water content (WC) played an apparent influence on bacterial community structure and diversity, and pH showed significant effects on fungal community diversity. WC and pH greatly affected the biomarkers of bacterial rhizosphere communities, whereas the biomarkers of bulk bacterial communities were significantly affected by soil nutrients, especially for Sphingobium. Overall, the rhizosphere microbial community enrichment processes were different between healthy and diseased plants by changing the community compositions and identifying different biomarkers. These findings provide insight into the assemblage of rhizosphere microbial communities and soil physicochemical properties, which contributes to a deeper understanding of the establishment of an artificial core root microbiota to facilitate plant growth and bolstering resistance mechanisms. This knowledge contributes to a deeper understanding of the establishment of an artificial core root microbiota, thereby facilitating plant growth and bolstering resistance mechanisms.

The research aimed to study an Avian polyomavirus strain that was isolated in Shandong, China. To study the pathogenicity of APV in SPF chickens, and provide references for epidemiological research and disease prevention and control of APV. The genetic characterization of APV strain (termed APV-20) was analyzed and the pathogenicity of APV was investigated from two aspects: different age SPF chickens, and different infection doses. The results revealed that the APV-20 exhibits a nucleotide homology of 99% with the other three APV strains, and the evolution of APV In China was slow. In addition, the APV-20 infection in chickens caused depression, drowsiness, clustering, and fluffy feathers, but no deaths occurred in the infected chickens. The main manifestations of necropsy, and Hematoxylin and Eosin staining (HE) showed that one-day-old SPF chickens were the most susceptible, and there was a positive correlation between viral load and infection dose in the same tissue. This study showed that SPF chickens were susceptible to APV, and an experimental animal model was established. This study can provide a reference for the pathogenic mechanism of immune prevention and control of APV.

Abstract Background Besides fibre production, Corchorus olitorius is considered a nutritional and medicinal plant in traditional medicine. Its leaves possess different antioxidant compounds and display various biological properties. This study optimized the ultrasound-assisted extraction (UAE) parameters like temperature, time, solvent concentration, and liquid–solid ratio for total flavonoids (TFC) and total polyphenols content (TPC) from leaves employing response surface methodology (RSM). Results Findings demonstrated that under the optimized conditions, the highest extraction yield of total flavonoids (7.17 mg QE/g DW) and total polyphenol content (13.92 mg GAE/g DW) were recorded with the ethanol concentration 70.92%, temperature 68.06 °C, liquid–solid ratio 48.80 mL/mg, and ultrasound irradiation time 37.20 min. The optimum value of TFC (6.96 mg QE/g DW) and TPC (13.38 mg GAE/g DW) from the experiment of verification of optimized conditions was close to the predicted value and significantly superior to the conventional heat reflux extraction (HRE). LC–MS and HPLC analysis of the optimized extract from UAE demonstrated the existence of six major phenolic compounds, including chlorogenic acid, isoquercetin, hyperoside, adhyperforin, 1,3-di-O-caffeoylquinic acid, and 3,4-di-O-caffeoylquinic acid. Furthermore, the antioxidant test of the UAE leaves extract revealed an excellent 2,2-diphenyl-1-picrylhydrazyl (DPPH•), 2,2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS+•) and hydroxyl radical scavenging with IC50 values of 226.29, 199.53 and 402.02 µg/mL, respectively, compared to HRE with 336.31 µg/mL, 253.86 µg/mL, 520.08 µg/mL. Conclusions The developed optimization method could contribute to the good recovery of natural antioxidants from C. olitorius in the pharmaceuticals and food industries. Graphical Abstract

Abstract Rutting is a typical distress of asphalt pavement related to material, structural, loading, and environmental conditions of the pavement. This work presents a thorough and targeted synthesis of literature on current predictive models for rutting development in asphalt pavement, including the mechanical model, empirical model, machine learning model, and their combinations. By introducing and comparing the characteristics, advantages, and limitations of different model types, we focused on suitable approaches that predict rutting given the available information in the corresponding studies. Furthermore, we conducted a practitioner survey to identify performance deterioration models used by various highway agencies for asphalt pavement and to capture insights and experiences of users on the existing models in terms of reliability, precision, input and output parameters, consideration of maintenance and rehabilitation history, implementation considerations, etc. This review sheds light on the developing trend of predictive models for rutting and other distresses of asphalt pavement.

Research on the interaction between depositional evolution process and marine transgression is critical to understanding the transform mechanism of sedimentary systems and guiding hydrocarbon exploration. The early Miocene witnessed the most significant sea-level rise since the Cenomanian, which resulted in extensive marine-influenced deposits worldwide. However, the relationship between the process of depositional evolution and long-term marine transgressions (>1 Ma) remains poorly understood. The Pearl River Mouth Basin in the South China Sea offers a comprehensive deposition record of the early Miocene marine transgression. This study employs high-quality 3D seismic, well-logging, and core data to investigate the impact of the early Miocene transgression on the evolutionary dynamics of the sedimentary system. The regional sea level exhibited a prolonged rise of at least 100 m during the deposition period of the Miocene Zhujiang Formation, corresponding to the long-term marine transgressive in the South China Sea. Throughout this marine transgression, depositional systems developed in the study area include tidal flats, fan deltas, meandering river deltas, and shallow marine shelf sand bodies. The marine transgression process resulted in a significant change in depositional system types, which can be divided into seven units from Unit 1 at the bottom to Unit 7 at the top. The predominant deposition environment transitioned from tidal flats in Units 1-3 to meandering river deltas in Units 4-5, and finally to shallow marine shelf systems in Units 6-7. In the early stage (Units 1-3), the regional uplifts hindered sea level transgression and caused erosion, leading to the development of small-scale proximal fan deltas. In the middle stage (Units 4-5), these regional uplifts submerged, and meandering river deltas dominated with sediments derived from distant extrabasinal sources. During the late stage (Units 6-7), regional sea levels reached their peak, transforming the entire basin into a shallow marine shelf system. Additionally, this marine transgression significantly influenced the distribution of hydrocarbon resources. Notably, the shallow marine shelf sand bodies in Units 6-7 warrant substantial attention for future exploration. This study outlines the complicated transitional processes within depositional systems during long-term marine transgression events, holding relevance for the global evolution of marginal sea basins.

Caituozi Island is located in Changhai County of Dalian, which is an uninhabited island with the function of fishery. According to the characteristics of uninhabited island ecosystem and the function of fishery island, the pressure-state-response (PSR) model with three-layer index was built to evaluate the ecological status of Caituozi Island. Expert evaluation method, environmental quality index of single element method and comprehensive evaluation index method were applied to calculate weight value and index value of each level indexes. Based on field investigation data in 2015, ecological status score of Caituozi Island was calculated by using the analytic hierarchy process of PSR model. The result showed that the status of Caituozi Island was "Excellent" (The score was 0.811 1) . In addition, the evaluation method could be extended to assess the ecological status of other uninhabited islands for fishery by further optimizing the evaluation indexes.

Polysaccharides exhibit multiple pharmacological activities which are closely related to their structural features. Therefore, quantitatively quality control of polysaccharides based on their chemical characteristics is important for their application in biomedical and functional food sciences. However, polysaccharides are mixed macromolecular compounds that are difficult to isolate and lack standards, making them challenging to quantify directly. In this study, we proposed an improved saccharide mapping method based on the release of specific oligosaccharides for the assessment of Hericium erinaceus polysaccharides from laboratory cultured and different regions of China. Briefly, a polysaccharide from H. erinaceus was digested by β-(1-3)-glucanase, and the released specific oligosaccharides were labeled with 8-aminopyrene-1,3,6-trisulfonic-acid (APTS) and separated by using micellar electrokinetic chromatography (MEKC) coupled with laser induced fluorescence (LIF), and quantitatively estimated. MEKC presented higher resolution compared to polysaccharide analysis using carbohydrate gel electrophoresis (PACE), and provided great peak capacity between oligosaccharides with polymerization degree of 2 (DP2) and polymerization degree of 6 (DP6) in a dextran ladder separation. The results of high performance size exclusion chromatography coupled with multi-angle laser light scattering and refractive index detector (HPSEC-MALLS-RI) showed that 12 h was sufficient for complete digestion of polysaccharides from H. erinaceus. Laminaritriose (DP3) was used as an internal standard for quantification of all the oligosaccharides. The calibration curve for DP3 showed a good linear regression (R2 > 0.9988). The limit of detection (LOD) and limit of quantification (LOQ) values were 0.05 μg/mL and 0.2 μg/mL, respectively. The recovery for DP3 was 87.32 (±0.03)% in the three independent injections. To sum up, this proposed method is helpful for improving the quality control of polysaccharides from H. erinaceus as well as other materials.

Developing new varieties of natural fibers that can grow throughout the year is very crucial to replace and avoid the bad effect of synthetic fiber. As a result of its beneficial role in protecting plants from abiotic stressors, melatonin (N-acetyl-5-methoxytryptamine) has gained recognition as a novel plant growth regulator. This study aimed to investigates the role of exogenous melatonin (200 μM) on two varieties of Corchorous olitorius and Corchorous capsularis in response to low-temperature stress (8 °C) for different periods of treatment (0, 12, 24, 36, and 48 h) based on biochemical properties, and antioxidant system. The results demonstrated that exogenous melatonin had inhibitory effects of low-temperature stress on seedlings at different period of treatment when compared to non-melatonin treated seedlings, potentially improved photosynthetic apparatus (total chlorophyll up to 29.93 and 33.37%; total carotenoid up to 29.93 and 19.05%; anthocyanin up to 40.47 and 31.94% in M33 and Y49, respectively), reduced oxidative damage (MDA up to 53.59 and 44.28%; H2O2 up to 41.04 and 16.88% in M33 and Y49, respectively) by boosting the antioxidant enzymes (SOD up to 12.75 and 4.65%; POD up to 39.08 and 81.39%; total phenolic up to 43.38 and 56.48% in M33 and Y49, respectively) reduced electrolyte leakage (EL) up to 15.37 and 13.64% in M33 and Y49, respectively) and increased osmoregulation (soluble sugars up to 25.86 and 25.86%; proline up to 105.19 and 172.07%; FAA up to 48.50 and 30.06% in M33 and Y49, respectively) content. Thus, this study showed that exogenous melatonin effectively mitigated the low-temperature-induced oxidative in C. olitorius and C. capsularis seedlings by regulating the antioxidant system and improving the low-temperature resistance.

ObjectivesThe aim of this study was to explore the effects of a virtual reality (VR)-based motivational reinforcement + desensitization intervention program on psychological craving and addiction memory in female methamphetamine (MA)-dependent young adults.MethodsWe recruited 60 female MA-dependent young adults in a compulsory isolation drug rehabilitation facility in Sichuan Province, and randomly assigned them to intervention (mean age = 23.24 ± 2.06) and control groups (mean age = 23.33 ± 2.09). The intervention group received a VR-based motivational enhancement + desensitization intervention (total of eight sessions over a 4-week period), while the control group received regular detoxification management during the same period. Assessments were conducted before, immediately after, and 1 month after the intervention, with a visual analogue scale (VAS) being used to assess subjective craving, electronic sphygmomanometer employed to measure physiological parameters, and the Addiction Memory Intensity Scale (AMIS) applied to assess addiction memory intensity.ResultsGeneralized estimating equation analysis showed significant main effects of group on changes in heart rate difference, systolic blood pressure difference, VAS and AMIS scores (all p

Practical application of a Si anode in a high-energy-density battery cannot be achieved due to the huge volume expansion of these anodes. Researchers have focused on binders of the anode to restrict volume expansion in order to address this issue, as the hydrogen bonds and mechanical properties of binders can be used to enhance adhesion and accommodate the volume changes of a Si anode. Herein, we comprehensively consider binders’ hydrogen bonds, mechanical properties, stability, and compatibility with the electrolyte solution, and design an ether-/ester-/fluorine-rich composite polymer, named P(TFEMA-co-IBVE). The proposed binder formula possesses outstanding stability, adhesion, and mechanical strength; moreover, it can accommodate the dramatic volume changes of a Si electrode and exhibits excellent electrochemical performance, achieving a high areal capacity of about 5.4 mA∙h∙cm−2. This novel polymer design may be applied to other electrode materials in the next generation of lithium-ion batteries.

The moderate deep and deeplayers of the Ledong area in the Yinggehai Basin is regarded as the main districts in recent exploration. The reservoirs in L10 zone are generally characterized by low-porosity and low-permeability, suggesting that the high-quality reservoir is the main focus restricting the further research and exploration. Through the analysis of regional petrophysical features, we established AVO template of velocity of overburden mudstones and porosity, to improve the effectiveness of AVO technology in predicting reservoir physical properties. Aiming at the large errors of porosity predicting in thin reservoirs, a new porosity prediction method based on impedance correction formula was proposed, which improved the prediction accuracy of thin layers. Numerical simulation and drilling data verified the validity and reliability of this new method and provided new directions for subsequent high-quality reservoir exploration in the Yinggehai Basin.

Different parts of Corchorus olitorius and C. capsularis possess different antioxidant compounds. This study investigated the phytochemical components and antioxidant capacities of ultrasound-assisted extraction of different plant parts of both species using spectrophotometry at various phenological stages. Results also indicate that leaves, stems and roots of C. olitorius at various growth stages showed higher phytochemical components and antioxidant potential compared to C. capsularis. The phytochemical components from roots to leaves in C. olitorius including total polyphenol 0.97–11.11 mg GAE/g DW, total flavonoid 0.99–7.78 mg QE/g DW and total tannin 4.02–26.89 TA E/g DW, whereas C. capsularis total polyphenol 1.04–7.93 mg GAE/g DW, total flavonoid 0.77–5.5.92 mg QE/g DW and total tannin content 3.17–22.73 TA E/g DW. C. olitorius produced overall 22.23%, 13.61%, 12.24% higher total polyphenol, total flavonoid and total tannin, respectively compare to C. capsularis. Different parts extract also significantly affected antioxidant capacities including DPPH, ABTS, and FRAP activity with values of 22.03–79.46% inhibition, 10.84–104.10 μmol TE/g DW, and 10.84–104.10 μmol Fe2+/g DW respectively for C. olitorius, while C. capsularis demonstrated 14.03–70.97% of DPPH inhibition, 9.16–95.60 μmol TE/g DW of ABTS and 5.31–71.82 μmol Fe2+/g DW of FRAP activity. Moreover, leaves of the flowering stage, young stems and aged roots of both species displayed a higher content of phytochemical and antioxidant activities than other growth stages. A positive correlation between the phytochemical and antioxidant potential indicated that phenolic constituents solely affected antioxidant activity. Thus, this study established that the plant's parts and phenological growth stages significantly influence the concentration of phytoconstituents and antioxidant activities, and determine the harvesting stages of the different organs of C. olitorius and C. capsularis for considerable medicinal importance as folk and industry.

Kenaf (Hibiscus cannabinus L.) is considered suitable for the remediation of cadmium (Cd)-contaminated farmlands, because of its large biomass and resistance to Cd stress. The addition of nitrogen (N) fertilizer is an important measure used to increase crop yields, and it may also affect Cd accumulation in plants. To clarify the effects of different forms and concentrations of N on plant growth and Cd absorption in kenaf, a hydroponic experiment was conducted using three N forms (NH4+–N, NO3−–N and urea–N) at four concentrations (0, 2, 4 and 8 mM, 0 mM as control) under Cd stress (30 μM). The plant growth, the antioxidant enzyme activity and the Cd contents of various parts of the kenaf seedlings were measured. The results showed that the N form had the greatest impact on the growth of the kenaf and the absorption and transport of the Cd, followed by the interaction effect between the N type and the concentration. Compared to the control, the addition of N fertilizer promoted the growth of kenaf to varying degrees. Among all the treatments, the use of 2 mM of NO3−–N enhanced the biomass and Cd accumulation to the greatest extent compared to CK from 2.02 g to 4.35 g and 341.30 μg to 809.22 μg per plant, respectively. The NH4+–N significantly reduced the Cd contents of different parts but enhanced the translocation factors of Cd stem to root (TF S/R) and leaf to stem (TF L/S) by 34.29~78.57% and 45.10~72.55%, respectively. The peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT) enzyme activities of the kenaf increased with the N treatments, especially with NH4+–N. Overall, applying low concentrations of NO3−–N can better promote the extraction of Cd by kenaf.

The fully automatic registration of 3D terrestrial laser scanning (TLS) point clouds, which is the first step in the usage of point clouds, is a highly challenging task in Light Detection and Ranging (LiDAR) remote sensing applications. Here, an automatic algorithm for pairwise coarse registration of TLS point clouds using 3D line features is proposed. First, the 3D line sets were extracted from the original pair of point clouds respectively, and two arbitrary lines from a point cloud were used to construct a 2-line base; Then, a pair of conjugate 2-line bases were identified from the source and target 3D line sets at a time, based on which a 3D rotation matrix together with its corresponding overlap between the pairwise 3D line sets was calculated; Third, a series of 3D rotation matrixes together with their overlaps were obtained using the traversing strategy to identify conjugate 2-line base pairs, and the 3D rotation matrix with the highest overlap was outputted as the final 3D rotation matrix, which was further used to compute the corresponding lines set from the pairwise 3D line sets; Next, based on the set of common perpendicular midpoints between the line correspondences, the 3D translation vector was computed; Finally, the 3D transformation matrix between pairwise point clouds was obtained by combining the 3D rotation matrix and the 3D translation vector. The proposed method was tested on three different TLS datasets, with experimental results demonstrating that the proposed algorithm could perform well on registering pairwise TLS point clouds. The rotation and translation errors of aligning the nine experimental pairwise point clouds were all less than 0.50° and 0.55m, respectively. This registration framework was also shown to be superior to state-of-the-art methods in terms of registration accuracy.

A novel series of chalcone-Vitamin E-donepezil hybrids was designed and developed based on multitarget-directed ligands (MTDLs) strategy for treating Alzheimer’s disease (AD). The biological results revealed that compound 17f showed good AChE inhibitory potency (ratAChE IC50 = 0.41 µM; eeAChE IC50 = 1.88 µM). Both the kinetic analysis and docking study revealed that 17f was a mixed type AChE inhibitor. 17f was also a good antioxidant (ORAC = 3.3 eq), selective metal chelator and huMAO-B inhibitor (IC50 = 8.8 µM). Moreover, it showed remarkable inhibition of self- and Cu2+-induced Aβ1–42 aggregation with a 78.0 and 93.5% percentage rate at 25 µM, respectively, and disassembled self-induced and Cu2+-induced aggregation of the accumulated Aβ1–42 fibrils with 72.3 and 84.5% disaggregation rate, respectively. More importantly, 17f exhibited a good neuroprotective effect on H2O2-induced PC12 cell injury and presented good blood-brain barrier permeability in vitro. Thus, 17f was a promising multi-target-directed ligand for treating AD.

Abstract This study established a systematic simulation framework to predict the anti-icing longevity of a thin overlay of asphalt pavement with salt-storage additive (APSSA). The water and chloride transport in the overlay when subjected to varying precipitation, temperature, thermal cracking, and fatigue cracking over time were modeled using a Finite Element Method based software. The simulation included two parts: water transport followed by chloride transport. Water transport that obeys the law of conservation of mass was modeled using the phase transport in porous media (phtr) interface of COMSOL, while chloride transport based on Fick’s second law was modeled with the transport of diluted species (tds) interface. The simulation results show that the anti-icing function of a 16-mm thick overlay was fully effective in 2 years and 5 years for the minimum pavement temperature above -3.4 °C and -2.4 °C, respectively. These two pavement temperatures are equivalent to 97.4-percentile and 96.3-percentile of historical hourly pavement temperature near Pullman, Washington. Graphical abstract

After dissection of a large blast furnace, the erosion mechanism of carbon bricks after service in a blast furnace (BF) hearth was studied. Obvious “elephant foot” erosion characteristics emerged in the height direction of the BF. The existing forms of carbon bricks after service were characterized by X-ray diffraction (XRD), scanning electron microscopy–energy dispersive spectroscopy (SEM-EDS), and chemical analysis. The results showed that Zn and iron erosion above and below the taphole was observed in the BF, while iron and Zn erosion acted only as a key factor of carbon brick erosion. The convective heat transfer coefficient in the lower part of the hearth of the BF was large, which increased the temperature of the hearth sidewall, resulting in the increase in the carbon-unsaturation of the molten iron at the sidewall, and intensified erosion to the hearth sidewall. The average pore size (1.083 μm) of the carbon bricks on the hot-face of the hearth sidewall was smaller than the critical size (2.12 μm) of the molten iron that penetrated the pores of the carbon bricks, which was not conducive to the penetration of molten iron.

Abstract Background In the widespread adoption of chemotherapy, drug resistance has been the major obstacle to tumor elimination in cancer patients. Our aim was to explore the role of TGF-β in osteosarcoma-associated chemoresistance. Methods We performed a cytotoxicity analysis of methotrexate (MTX) and cisplatin (CIS) in TGF-β-treated osteosarcoma cells. Then, the metabolite profile of the core metabolic energy pathways in Saos-2 and MG-63 cell extracts was analyzed by 1H-NMR. We detected the expression of succinate dehydrogenase (SDH), STAT1, and hypoxia-inducible factor 1α (HIF1α) in TGF-β-treated osteosarcoma cells and further tested the effects of these molecules on the cytotoxicity induced by chemotherapeutic agents. Using in vivo experiments, we examined the tumor growth and survival time of Saos-2-bearing mice treated with a combination of chemotherapeutic agents and a HIF1α inhibitor. Results The metabolic analysis revealed enhanced succinate production in osteosarcoma cells after TGF-β treatment. We further found a decrease in SDH expression and an increase in HIF1α expression in TGF-β-treated osteosarcoma cells. Consistently, blockade of SDH efficiently enhanced the resistance of Saos-2 and MG-63 cells to MTX and CIS. Additionally, a HIF1α inhibitor significantly strengthened the anticancer efficacy of the chemotherapeutic drugs in mice with osteosarcoma cancer. Conclusion Our study demonstrated that TGF-β attenuated the expression of SDH by reducing the transcription factor STAT1. The reduction in SDH then caused the upregulation of HIF1α, thereby rerouting glucose metabolism and aggravating chemoresistance in osteosarcoma cells. Linking tumor cell metabolism to the formation of chemotherapy resistance, our study may guide the development of additional treatments for osteosarcoma.

As a new type of reflective display technology with paper-like display performance, electrowetting display (EWD) can realize ultra-low power consumption, wide viewing angle and fast response speed. In order to apply the EWD to the large-size display field, an extensible driving model for multiple grayscales colorful EWDs was proposed in this paper. The proposed driving model consisted of a grayscale model, a colorful display model and an extensible driving model. With the grayscale model and the colorful display model, the driving waveform of the colorful grayscale display was designed based on limited output voltage levels of a general-purpose graphic driver chip. And then, the extensible driving model was used to realize the large-size display large-scale display based on a matrix of small-size EWD panels. In addition, an experimental platform, which was composed of the display panel and the driving board with a data interface, was designed based on the proposed models. Experimental results showed that it could realize an 18-bit colorful dynamic display on the extended display matrix with a resolution of 48*16. It was indicated that the display matrix could be used for multiple grayscales and colorful dynamic displays by applying the proposed driving models. The research has brought about a way of enlarging the size of the EWD, which is conducive to broadening the scope of application of EWDs.

Abstract Background Cannabis sativa L., a dioecious plant derived from China, demonstrates important medicinal properties and economic value worldwide. Cannabis properties have been usually harnessed depending on the sex of the plant. To analyse the genetic structure of Chinese Cannabis and identify sex-linked makers, genome-wide insertion-deletion (InDel) markers were designed and used. Results In this study, a genome-wide analysis of insertion-deletion (InDel) polymorphisms was performed based on the recent genome sequences. In total, 47,558 InDels were detected between the two varieties, and the length of InDels ranged from 4 bp to 87 bp. The most common InDels were tetranucleotides, followed by pentanucleotides. Chromosome 5 exhibited the highest number of InDels among the Cannabis chromosomes, while chromosome 10 exhibited the lowest number. Additionally, 31,802 non-redundant InDel markers were designed, and 84 primers evenly distributed in the Cannabis genome were chosen for polymorphism analysis. A total of 38 primers exhibited polymorphisms among three accessions, and of the polymorphism primers, 14 biallelic primers were further used to analyse the genetic structure. A total of 39 fragments were detected, and the PIC value ranged from 0.1209 to 0.6351. According to the InDel markers and the flowering time, the 115 Chinese germplasms were divided into two subgroups, mainly composed of cultivars obtained from the northernmost and southernmost regions, respectively. Additional two markers, “Cs-I1–10” and “Cs-I1–15”, were found to amplify two bands (398 bp and 251 bp; 293 bp and 141 bp) in the male plants, while 389-bp or 293-bp bands were amplified in female plants. Using the two markers, the feminized and dioecious varieties could also be distinguished. Conclusion Based on the findings obtained herein, we believe that this study will facilitate the genetic improvement and germplasm conservation of Cannabis in China, and the sex-linked InDel markers will provide accurate sex identification strategies for Cannabis breeding and production.

To improve the protective performance of old combined bridge barriers with non-standard sections, this article has improved the guardrail scheme. The newly improved guardrail is evaluated by finite element simulation, yield line theory calculation, and a crash test to see whether it reaches class SA protection. The results show that the blocking, redirecting, and buffering functions of the improved scheme meet the Standard for Safety Performance Evaluation of Highway Barriers (JTG B05-01-2013), and its protection class reaches class SA. The bridge barrier with strict deformation control cannot be evaluated by the yield line theory calculation alone. Thus, the evaluation should be assisted with finite element simulation and a crash test. The improved scheme has been successfully applied to engineering practice. With simple construction, safety, and reliability, the scheme effectively reduces engineering costs and improves the protective performance of old combined bridge barriers with non-standard sections.

In this work, a physics-based analytical model without any fitting parameters for fracture toughness depending on temperature was proposed. The quantitative relationship between fracture toughness, melting point, Young’s modulus, Poisson’s ratio, and temperature was established. Furthermore, the effect of notch root radius on fracture toughness was investigated, and then we developed a simple theoretical model to characterize the combined effect of temperature and notch root radius on the fracture toughness. Satisfactory agreement between the available experimental measurements and our model predictions was achieved. This study not only advances our in-depth understanding of the quantitative relationship between the temperature and fracture toughness but also provides a powerful and convenient tool to predict the temperature-dependent fracture toughness at different notch root radius.

PurposeAs local recurrence remains a challenge and the advantages of the simultaneous integrated boost (SIB) technique have been validated in photon radiotherapy, we applied the SIB technique to CIRT. The aim was to investigate the metabolomic changes of the CIRT with concurrent androgen deprivation therapy (ADT) in localized prostate cancer (PCa) and the unique metabolic effect of the SIB technique.Material and MethodsThis study enrolled 24 pathologically confirmed PCa patients. All patients went through CIRT with concurrent ADT. The gross target volume (GTV) boost was defined as positive lesions on both 68Ga-PSMA PET/CT and mpMRI images. Urine samples collected before and after CIRT were analyzed by the Q-TOF UPLC-MS/MS system. R platform and MetDNA were used for peak detection and identification. Statistical analysis and metabolic pathway analysis were performed on Metaboanalyst.ResultsThe metabolite profiles were significantly altered after CIRT. The most significantly altered metabolic pathway is PSMA participated alanine, aspartate and glutamate metabolism. Metabolites in this pathway showed a trend to be better suppressed in the SIB group. A total of 11 identified metabolites were significantly discriminative between two groups and all of them were better down-regulated in the SIB group. Meanwhile, among these metabolites, three metabolites in DNA damage and repair related purine metabolism were down-regulated to a greater extent in the SIB group.ConclusionMetabolic dysfunction was one of the typical characteristics of PCa. CIRT with ADT showed a powerful inhibition of PCa metabolism, especially in PSMA participated metabolic pathway. The SIB CIRT showed even better performance on down-regulation of most metabolism than uniform-dose-distribution CIRT. Meanwhile, the SIB CIRT also showed its unique superiority to inhibit purine metabolism. PSMA PET/CT guided SIB CIRT showed its potentials to further benefit PCa patients.

Due to the extensive use of xylooligosaccharides (XOS) as functional food ingredients, many inferior goods and even adulterants are generally found in the market, which may pose a health hazard to certain populations. Chromatography method such as high-performance liquid chromatography (HPLC) and high-performance thin-layer chromatography (HPTLC) is traditionally applied for the quality analysis of XOS. However, it is time consuming due to the prolonged separation and pre- or post- derivatization procedure. In this study, a fast saccharide mapping method based on matrix-assisted laser desorption/time-of-flight mass spectrometry (MALDI-TOF-MS) was developed for the quality consistency analysis of 22 batches of XOS collected from different manufacturers in China. The time needed for saccharides analysis using MALDI-MS was less than 30 min for one plate, at least 6 times faster than that by the traditional HPTLC chromatography method. In addition, MALDI-MS possessed higher resolution for XOS with DP4-DP7 based on the difference of m/z, which is hardly separated using HPTLC. The results showed that XOS were present only in samples XY01-XY11, samples XY12-XY14 only consisted of hex oligosaccharides, and samples XY15-XY22 were free of oligosaccharides. These indicate that the quality consistency of XOS products in the China market was poor, which should be carefully investigated.

Abstract Background Long noncoding RNAs (lncRNAs) contribute to multiple biological processes in human glioblastoma (GBM). However, identifying a specific lncRNA target remains a challenge. In this study, bioinformatics methods and competing endogenous RNA (ceRNA) network regulatory rules were used to identify GBM-related lncRNAs and revealed that OXCT1 antisense RNA 1 (OXCT1-AS1) is a potential therapeutic target for the treatment of glioma. Methods Based on the Gene Expression Omnibus (GEO) dataset, we identified differential lncRNAs, microRNAs and mRNAs and constructed an lncRNA-associated ceRNA network. The novel lncRNA OXCT1-AS1 was proposed to function as a ceRNA, and its potential target miRNAs were predicted through the database LncBase Predicted v.2. The expression patterns of OXCT1-AS1 in glioma and normal tissue samples were measured. The effect of OXCT1-AS1 on glioma cells was checked using the Cell Counting Kit 8 assay, cell colony formation assay, Transwell assay and flow cytometry in vitro. The dual-luciferase activity assay was performed to investigate the potential mechanism of the ceRNA network. Finally, orthotopic mouse models of glioma were created to evaluate the influence of OXCT1-AS1 on tumour growth in vivo. Results In this study, it was found that the expression of lncRNA OXCT1-AS1 was upregulated in both The Cancer Genome Atlas (TCGA) GBM patients and GBM tissue samples, and high expression of OXCT1-AS1 predicted a poor prognosis. Suppressing OXCT1-AS1 expression significantly decreased GBM cell proliferation and inhibited cell migration and invasion. We further investigated the potential mechanism and found that OXCT1-AS1 may act as a ceRNA of miR-195 to enhance CDC25A expression and promote glioma cell progression. Finally, knocking down OXCT1-AS1 notably attenuated the severity of glioma in vivo. Conclusion OXCT1-AS1 inhibits glioma progression by regulating the miR-195-5p/CDC25A axis and is a specific tumour marker and a novel potential therapeutic target for glioma treatment.

Given the rising domestic demand and increasing global prices of corn and soybean, China is looking for alternatives for these imports to produce animal fodder. Kenaf (Hibiscus cannabinus L.) has great potential as a new forage source, due to abundant proteins, phenols and flavonoids in its leaves. However, few studies have evaluated the mechanism of protein synthesis in kenaf leaves. In the current work, compared with kenaf material “L332,” the percentage of crude protein content in leaves of material “Q303” increased by 6.13%; combined with transcriptome and proteome data, the kenaf samples were systematically studied to obtain mRNA-protein correlation. Then, the genes/proteins related to protein synthesis in the kenaf leaves were obtained. Moreover, this work detected mRNA expression of 20 differentially expressed genes (DEGs). Meanwhile, 20 differentially expressed proteins (DEPs) related to protein synthesis were performed parallel reaction monitoring. Fructose-1,6-bisphosphatase (FBP), nitrite reductase (NirA), prolyl tRNA synthase (PARS) and glycine dehydrogenase (GLDC) presented increased mRNA and protein levels within kenaf leaves with high protein content. Based on the obtained findings, FBP, NirA, PARS, and GLDC genes may exert a vital function in the protein synthesis of kenaf leaves. The results provide a new idea for further studying the potential genes affecting the quality trait of protein content in kenaf leaves and provide gene resources and a theoretical foundation for further cultivating high protein kenaf varieties.

Abstract Background Cannabis, an important industrial crop, has a high sensitivity to photoperiods. The flowering time of cannabis is one of its important agronomic traits, and has a significant effect on its yield and quality. The CONSTANS-like (COL) gene plays a key role in the regulation of flowering in this plant. However, the specific roles of the COL gene family in cannabis are still unknown. Results In this study, 13 CsCOL genes were identified in the cannabis genome. Phylogenetic analysis implied that the CsCOL proteins were divided into three subgroups, and each subgroup included conserved intron/exon structures and motifs. Chromosome distribution analysis showed that 13 CsCOL genes were unevenly distributed on 7 chromosomes, with chromosome 10 having the most CsCOL members. Collinearity analysis showed that two syntenic gene pairs of CsCOL4 and CsCOL11 were found in both rice and Gossypium raimondii. Of the 13 CsCOL genes, CsCOL6 and CsCOL12 were a pair of tandem duplicated genes, whereas CsCOL8 and CsCOL11 may have resulted from segmental duplication. Furthermore, tissue-specific expression showed that 10 CsCOL genes were preferentially expressed in the leaves, 1 CsCOL in the stem, and 2 CsCOL in the female flower. Most CsCOL exhibited a diurnal oscillation pattern under different light treatment. Additionally, sequence analysis showed that CsCOL3 and CsCOL7 exhibited amino acid differences among the early-flowering and late flowering cultivars. Conclusion This study provided insight into the potential functions of CsCOL genes, and highlighted their roles in the regulation of flowering time in cannabis. Our results laid a foundation for the further elucidation of the functions of COL genes in cannabis.

In order to achieve resource conservation, protect the environment and realize the sustainable development of the construction industry, the low energy resource utilization of construction waste was explored. In this paper, the effect of air bubble swarm admixture, recycled brick powder admixture, water to material ratio, and HPMC content on the physical and mechanical properties of recycled brick powder foam concrete was investigated by conducting a 4-factor, 5-level orthogonal test with recycled brick powder as fine aggregate, and the effect of each factor on the physical and mechanical properties of recycled brick powder foam concrete was derived, and the optimum ratio of recycled brick powder foam concrete was determined by analysing the specific strength. Five machine learning models, namely, back propagation neural network improved by particle swarm optimization (PSO-BP), support vector machine (SVM), multiple linear regression (MLR), random forest (RF), and back propagation neural network (BP), were used to predict the compressive strength of recycled brick powder foam concrete, and the PSO-BP model was found to have obvious advantages in terms of prediction accuracy and model stability. The experimental results and prediction models can provide experimental and theoretical references for the research and application of recycled brick powder foam concrete.

Recently time series prediction based on network analysis has become a hot research topic. However, how to more accurately forecast time series with good efficiency is still an open question. To address this issue, we propose an efficient time series forecasting method based on the DC algorithm and visibility relations on the vertexes set. Firstly, the time series is mapped into the network by the DC algorithm, which is a more efficient approach to generate the visibility graph. Then, we use the variation trends (slope) of those nodes that have visibility relation with the last node to get the preliminary predictive values. Afterward, the value of the last node is adopted to obtain the revised predictive values, which are assigned different weights according to node degree and time distance to get the final weighted result. To better demonstrate the prediction performance and applicability of the proposed method, the proposed method is applied to different time series data sets. The empirical results show that the proposed method could provide a higher level of forecasting accuracy than many methods with relatively lower time complexity.

Rapid development of railway has heightened the need for the researches on hypereutectoid heavy rail steels. Artificial intelligence method has become an effective tool to realize materials composition design. In this paper, BP neural network models are constructed to determine the relationship among (Cr, P, S, V) alloying elements, mechanical performance and microstructure of hypereutectoid rail steels. Analysis based on this model reveals that Cr is the most prominent element for mechanical properties. The tensile strength, yield strength and hardness can be improved with the increasing content of Cr and V. The addition of P and S seems to decrease the strength and hardness of rail steels. Furthermore, the addition of (Cr, P, S, V) has a slight impact on the content of pearlite dual phases. The increase of (Cr, V) and decrease of (P, S) can contribute to an increase in ferrite content with the associated decrease in cementite. Experimental results agree well with the prediction based on the BP neural network model. This work provides an excellent basis for assessing the mechanical performance and microstructure of hypereutectoid heavy rail steels.

Uncertainty measurement of the basic probability assignment function has always been a hot issue in Dempster-Shafer evidence. Many existing studies mainly consider the influence of the mass function itself and the size of the frame of discernment, so that the correlation between the subsets is ignored in the power set of the frame of discernment. Without making full use of the information contained in the evidence, the existing methods are less effective in some cases given in the paper. In this paper, inspired by Shannon entropy and Deng entropy, we propose an improved entropy that not only inherits the many advantages of Shannon entropy and Deng entropy, but also fully considers the relationship between subsets, which makes the improved entropy overcome the shortcomings of existing methods and have greater advantages in uncertainty measurement. Many numerical examples are used to demonstrate the validity and superiority of our proposed entropy in this paper.

To measure conflict between two basic probability assignment functions plays the key role of conflict management in Dempster-shafer evidence theory. In this paper, a new conflict measure is proposed. First, the classical pignistic probability transform (PPT) is generalized as pignistic belief transform (PBT). One of the advantages of PBT is that it can assign belief to multiple sets. When the belief is assigned to single element, the proposed PBT is degenerated as classical PPT. Then, the betting distance of two pignistic belief transforms is proposed, which can be used as a new conflict degree of BPAs. Finally, a numerical example is illustrated to show the use of the proposed method to combine conflicting evidence.

In order to predict the high-temperature deformation behavior of hypereutectoid steel, the hot compression tests were conducted in the strain rate range of (0.001~1) s-1 and the deformation temperature range of (950~1100)°C. The experimental data were employed to develop the Arrhenius constitutive model and BP neural network model, and their predictability for high temperature flow stress of hypereutectoid steel was further evaluated. Comparatively, a higher correlation coefficient (R) can be obtained for the BP neural network model compared with the Arrhenius constitutive equations. And the relative error within ±1% was more than 68.75% for the BP neural network model, while only 18.75% for the constitutive equations. The BP neural network model is considered more efficient and accurate to predict the hot deformation behavior than the Arrhenius constitutive equations. Moreover, the well-trained BP neural network model is employed to predict the flow stress varying with the deformation temperature and strain rate. The flow stress decreases with the increasing deformation temperature and decreasing strain rate, which is in accordance with the experimental evaluation. The results indicate that BP neural network model is an efficient tool for modelling and predicting the flow behavior of hypereutectoid steels in high temperature applications.

Surface defect detection is a critical task in product quality assurance for manufacturing lines. The deep learning-based methods recently developed for defect detection are typically trained using a supervised learning strategy and large defect sample sets. Conventional methods often require additional pixel-level labeling or bounding boxes to predict the location of defects. However, the number of required samples and the time-intensive annotation process limits the practical use of these algorithms. As such, this study proposes a weakly supervised detection framework in which a CNN model is trained to identify surface cracks in motor commutators. The model was trained using small subsets of defect samples (~5-30) and does not require a pre-trained network. This approach consists of localization and decision networks that simultaneously predict both the location and probability of defects. A new loss function was also developed to identify abnormal regions in a sample with accessible image-level labels. A collaboration learning strategy was then applied to utilize the loss function and compensate for imbalances at the pixel level. Experimental results using a small number of image-level training labels from a real industrial dataset exhibited a 99.5% recognition accuracy, which is comparable to relevant methods using pixel-level labels.

The identification of critical nodes in complex networks is an open issue. Many scholars have tried to address it from different perspectives, but their methods are often not as effective as usual especially when meeting some specific graphs or limited to only one aspect. Evidence theory can consider the results from different sources comprehensively and the Shannon entropy can measure the uncertainty of information. In this paper, we use these two methods to rate the results gained from different measures and combine them to generate a new ranking result, namely Evidence Theory Centrality (ETC). The Susceptible-infected (SI) model and Kendall’s tau coefficient are used on six real networks to examine the effectiveness of our method.

Introduction: Carbon ion radiotherapy (CIRT) is a novel treatment for prostate cancer (PCa). However, the underlying mechanism for the individualized response to CIRT is still not clear. Metabolic reprogramming is essential for tumor growth and proliferation. Although changes in metabolite profiles have been detected in patients with cancer treated with photon radiotherapy, there is limited data regarding CIRT-induced metabolic changes in PCa. Therefore, the study aimed to investigate the impact of metabolic reprogramming on individualized response to CIRT in patients with PCa.Materials and Methods: Urine samples were collected from pathologically confirmed patients with PCa before and after CIRT. A UPLC-MS/MS system was used for metabolite detection. XCMS online, MetDNA, and MS-DIAL were used for peak detection and identification of metabolites. Statistical analysis and metabolic pathway analysis were performed on MetaboAnalyst.Results: A total of 1,701 metabolites were monitored in this research. Principal component analysis (PCA) revealed a change in the patient's urine metabolite profiles following CIRT. Thirty-five metabolites were significantly altered, with the majority of them being amino acids. The arginine biosynthesis and histidine metabolism pathways were the most significantly altered pathways. Hierarchical cluster analysis (HCA) showed that after CIRT, the patients could be clustered into two groups according to their metabolite profiles. The arginine biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis pathways are the most significantly discriminated pathways.Conclusion: Our preliminary findings indicate that metabolic reprogramming and inhibition are important mechanisms involved in response to CIRT in patients with PCa. Therefore, changes in urine metabolites could be used to timely assess the individualized response to CIRT.

Electro-fluidic display (EFD) is a new reflective display based on electrowetting phenomenon which is applied to the outdoor billboard. Organic dyes are the most important materials for the color gamut and reliability of the EFD devices, which are always synthesized based on mono-chromophore dye in previous work. In this paper, we report our research on azopyrazolone as the chromophore to construct a polychromic macromolecular dye system. The light stability and photo-electric properties of these new dyes are researched detailed. It is found that the light stability of multi-chromophore dyes and backflow properties are much better than corresponding mono-chromophore dye.

Investigating the deposition evolution and stratal stacking patterns in continental rift basins is critical not only to better understand the mechanism of basin fills but also to reveal the enrichment regularity of hydrocarbon reservoirs. The Pearl River Mouth Basin (PRMB) is a petroliferous continental rift basin located in the northern continental shelf of the South China Sea. In this study, the depositional evolution process and stacking pattern of the Zhu III Depression, western PRMB were studied through the integration of 3D seismic data, core data, and well logs. Five types of depositional systems formed from the Eocene to the Miocene, including the fan delta, meandering river delta, tidal flat, lacustrine system, and neritic shelf system. The representative depositional systems changed from the proximal fan delta and lacustrine system in the Eocene–early Oligocene, to the tidal flat and fan delta in the late Oligocene, and then the neritic shelf system in the Miocene. The statal stacking pattern varied in time and space with a total of six types of slope break belts developed. The diversity of sequence architecture results from the comprehensive effect of tectonic activities, sediment supply, sea/lake level changes, and geomorphic conditions. In addition, our results suggest that the types of traps are closely associated with stratal stacking patterns. Structural traps were developed in the regions of tectonic slope breaks, whereas lithological traps occurred within sedimentary slope breaks. This study highlights the diversity and complexity of sequence architecture in the continental rift basin, and the proposed hydrocarbon distribution patterns are applicable to reservoir prediction in the PRMB and the other continental rift basins.

Salinity stress is a major environmental threat in agricultural systems. Kenaf is a promising crop for the future for cultivation in salinity-affected soils because of its high phytoremediation potential. The current study aimed to investigate the effects of salt stress using six different sodium chloride (NaCl) concentrations (0, 50, 100, 150, 200, and 250 mM) on the plant growth, physiological characteristics, bioactive constituents, and antioxidant capacity of H. cannabinus. The results indicated that the NaCl stress induced significant reductions in plant height and in the dry and fresh weights of the leaf tissue. In addition, the K, Ca, Mg, and P concentrations in this tissue also decreased under NaCl stress treatment conditions. In contrast, the NaCl stress led to the accumulation of hydrogen peroxide (H2O2), superoxide anion (O2•−), malondialdehyde (MDA), proline, total soluble sugar, and total soluble protein. Under NaCl stress, the levels of antioxidants, including phenolics and flavonoids, also increased. The gas chromatography–mass spectrometry (GC-MS) results showed that the volatile compounds, including heptacosane, 1-octadecanesulphonyl chloride, and tetratetracontane, were induced under the NaCl stress treatment. Furthermore, the salt stress significantly improved the antioxidant capacity of the leaf extracts. These findings may provide insight into how H. cannabinus plants respond to salt stress and may help improve its medicinal value under salt stress.

With the increasing interest in value-added maize products, the interaction of zein with bioactive molecules to become more nutritional and beneficial to human health has gained a lot of attention. To broaden the application of ellagic acid (EA) in maize flour products, we investigated the interaction between zein and EA. The fluorescence quenching type of zein interacting with EA was mainly static quenching through hydrophobic interaction, as demonstrated by quenching behavior modeling, and ultraviolet-visible spectroscopy confirmed the formation of zein–EA complexes. Synchronous fluorescence spectroscopy showed that EA reduced the polarity of zein around tyrosine residues, which were exposed to a more hydrophobic microenvironment. Meanwhile, circular dichroism suggested that EA noticeably changed the secondary structure of zein, which was mainly reflected in the increase of α-helix and β-sheet content and the decrease of random coil content. Finally, the molecular docking simulation found that zein could have five active sites binding to EA and there was hydrogen bond interaction besides hydrophobic interaction. The findings of this study provided a basis for a theory for the interaction mechanism between zein and EA, which could be essential for developing value-added plant-derived protein products using EA as a functional component.

Plant bioactive compounds have gained global significance in terms of both medicinal and economic ramifications due to being easily accessible and are believed to be effective with fewer side effects. Growing relevant clinical and scientific evidence has become an important criterion for accepting traditional health claims of medicinal plants and also supports the traditional uses of Corchorus as folk medicine. C. capsularis and C. olitorius have broad applications ranging from textile to biocomposite, and young leaves and shoots are used as healthy vegetables and have long been used as traditional remedies for fever, ascites, algesia, liver disorders, piles, and tumors in many cultures. This review systematically summarized and emphasized the nutritional attributes, mostly available bioactive compounds, and biological and potential pharmaceutical properties of C. capsularis and C. olitorius, disclosed to users and non-users. Results suggest that various phytochemicals such as cardiac glycosides, phenols, flavonoids, sterols, lipids, and fatty acids were found or analytically identified in different plant parts (leaf, stem, seed, and root), and many of them are responsible for pharmacological properties and their antitumor, anticancer, antioxidant, antinociceptive, anti-inflammatory, analgesic, antipyretic, antiviral, antibacterial, anticonvulsant, antidiabetic and antiobesity, and cardiovascular properties help to prevent and cure many chronic diseases. In addition to their use in traditional food and medicine, their leaves have also been developed for skin care products, and some other possible uses are described. From this review, it is clear that the isolated compounds of both species have great potential to prevent and treat various diseases and be used as functional foods. In conclusion, this comprehensive review establishes a significant reference base for future research into various medical and functional food applications.

Software risk management is an important factor in ensuring software quality. Therefore, software risk assessment has become a significant and challenging research area. The aim of this study is to establish a data-driven software risk assessment model named DDERM. In the proposed model, experts’ risk assessments of probability and severity can be transformed into basic probability assignments (BPAs). Deng entropy was used to measure the uncertainty of the evaluation and to calculate the criteria weights given by experts. In addition, the adjusted BPAs were fused using the rules of Dempster–Shafer evidence theory (DST). Finally, a risk matrix was used to get the risk priority. A case application demonstrates the effectiveness of the proposed method. The proposed risk modeling framework is a novel approach that provides a rational assessment structure for imprecision in software risk and is applicable to solving similar risk management problems in other domains.