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Abstract Thermoelectrics converting heat and electricity directly attract broad attentions. To enhance the thermoelectric figure of merit, zT, one of the key points is to decouple the carrier-phonon transport. Here, we propose an entropy engineering strategy to realize the carrier-phonon decoupling in the typical SrTiO3-based perovskite thermoelectrics. By high-entropy design, the lattice thermal conductivity could be reduced nearly to the amorphous limit, 1.25 W m−1 K−1. Simultaneously, entropy engineering can tune the Ti displacement, improving the weighted mobility to 65 cm2 V−1 s−1. Such carrier-phonon decoupling behaviors enable the greatly enhanced μ W/κ L of ~5.2 × 103 cm3 K J−1 V−1. The measured maximum zT of 0.24 at 488 K and the estimated zT of ~0.8 at 1173 K in (Sr0.2Ba0.2Ca0.2Pb0.2La0.2)TiO3 film are among the best of n-type thermoelectric oxides. These results reveal that the entropy engineering may be a promising strategy to decouple the carrier-phonon transport and achieve higher zT in thermoelectrics.

Abstract Purpose To summarize the abdominal computed tomography (CT) imaging and clinicopathological data of patients with SPNs of the pancreas and analyze the accuracy of preoperative CT diagnosis and features. Materials and methods Between June 2006 and June 2023, CT images of 120 histopathologically proven SPNs in the pancreas were retrospectively reviewed. Fifteen features, including age, sex, and CT-determined features, were included in a multiple stepwise regression analysis. The correlations between features and SPNs, including odds ratios (ORs) and 95% confidence intervals (CIs), were evaluated. Results Among the 120 patients, the diagnostic accuracy of CT was 43.3%. The baseline CT results of patients with a correct diagnosis and misdiagnosis revealed significant differences in sex (P = 0.043), age (P = 0.004), boundary (P = 0.037) and encapsulation (P = 0.002) between the two groups. The preoperative imaging diagnostic accuracy was significantly greater in females than in males (47.9% vs. 25.0%, P = 0.043). The immunohistochemical indices did not significantly differ between the two groups. The results of univariate analysis revealed significant differences in sex (P = 0.048), age (P = 0.014), tumor length (P = 0.023), tumor boundaries (P = 0.039) and capsule type (P = 0.003). The results of multivariate analysis revealed that encapsulation was closely related to the diagnostic accuracy of CT (P = 0.04). Conclusions The accuracy of CT in the diagnosis of SPNs is low, but a length‒diameter ratio of the tumor approaching 1.0, encapsulation and clear boundaries are important CT-determined features. The capsule is an independent CT predictor in the diagnosis of SPNs.

Abstract The realization and control of exchange bias (EB) are highly desirable for spintronic applications. All-oxide heterostructures comprised of ferromagnetic and antiferromagnetic/multiferroic oxides provide an ideal platform to enable the electric-field control of EB, promising for energy-efficient memory and logic devices. However, the low block temperature (TB) and small bias field (HEB) hinder further advances towards room-temperature applications. Here, we report an alternative approach to enhance the interface-induced EB by using ferrimagnetic double-perovskite with B-site cation ordering. In heterostructures comprised of double-perovskite Sr2FeReO6 (SFRO) and LaFeO3 (LFO), a high TB (about 250 K) and large HEB are observed, which is significantly larger than the counterparts with LFO and ferromagnetic oxides. Further analysis suggests that the cation-ordering and ferrimagnetic spin structure of the double-perovskite could contribute significantly to the enhanced exchanged bias when interfacing with G-type antiferromagnets. Our results open a new avenue for developing all-oxides heterostructures for future magnetic technologies.

Abstract Background Spring viremia of carp virus (SVCV) infects a wide range of fish species and causes high mortality rates in aquaculture. This viral infection is characterized by seasonal outbreaks that are temperature-dependent. However, the specific mechanism behind temperature-dependent SVCV infectivity and pathogenicity remains unclear. Given the high sensitivity of the composition of intestinal microbiota to temperature changes, it would be interesting to investigate if the intestinal microbiota of fish could play a role in modulating the infectivity of SVCV at different temperatures. Results Our study found that significantly higher infectivity and pathogenicity of SVCV infection in zebrafish occurred at relatively lower temperature. Comparative analysis of the intestinal microbiota in zebrafish exposed to high- and low-temperature conditions revealed that temperature influenced the abundance and diversity of the intestinal microbiota in zebrafish. A significantly higher abundance of Parabacteroides distasonis and its metabolite secondary bile acid (deoxycholic acid, DCA) was detected in the intestine of zebrafish exposed to high temperature. Both colonization of Parabacteroides distasonis and feeding of DCA to zebrafish at low temperature significantly reduced the mortality caused by SVCV. An in vitro assay demonstrated that DCA could inhibit the assembly and release of SVCV. Notably, DCA also showed an inhibitory effect on the infectious hematopoietic necrosis virus, another Rhabdoviridae member known to be more infectious at low temperature. Conclusions This study provides evidence that temperature can be an important factor to influence the composition of intestinal microbiota in zebrafish, consequently impacting the infectivity and pathogenicity of SVCV. The findings highlight the enrichment of Parabacteroides distasonis and its derivative, DCA, in the intestines of zebrafish raised at high temperature, and they possess an important role in preventing the infection of SVCV and other Rhabdoviridae members in host fish. Video Abstract

ABSTRACT The decline in biodiversity poses a serious threat to natural ecosystems and has become one of the most pressing global environmental issues. Establishing conservation priorities for protected areas (PAs) is one of the most direct and effective biodiversity conservation measures. However, conservation gaps arise as a result of existing problems in spatial layout of PAs, including overlapping protection scopes, artificial fragmentation of natural ecological regions, as well as “over‐protection” and “over‐exploitation.” To optimize the spatial layout of PAs and improve the efficiency of biodiversity conservation, we employed the Habitat Quality module of the Integrated Assessment of Ecosystem Services and Tradeoffs (InVEST) model and the Maximum Entropy (MaxEnt) model to assess the PAs in the Songnen Plain, China. The combined model (MaxEnt‐InVEST) revealed that the conservation priorities for PAs in the Songnen Plain occupied a total area of 14,764.14 km2 (10.24% of the total area of the Songnen Plain). The conservation priorities outside PAs occupied a total area of 7858.45 km2 (5.45% of the total area of the Songnen Plain) and were primarily distributed in the northeastern, central, and southwestern regions of the Songnen Plain. This indicated that existing PAs did not offer adequate protection for local biodiversity. The consistency of our combined modeling framework was 72.11%, which enabled a more accurate assessment of biodiversity hotspots and respects the land uses of the Songnen Plain. In addition, the modeling framework successfully created maps of conservation gaps of biodiversity hotspots based on actual species distribution data and considers current land uses. Our study was aimed at optimizing the spatial conservation efficiency of the Songnen Plain by assessing the conservation gaps in the Songnen Plain. It could provide a reference for the future development of a PA system centering on national parks.

Abstract Real‐time polymerase chain reaction (RT‐PCR) remains the most prevalent molecular detection technology for sewage analysis but is plagued with numerous disadvantages, such as time consumption, high manpower requirements, and susceptibility to false negatives. In this study, an automated robot‐driven photoelectrochemical (PEC) biosensing platform is constructed, that utilizes the CRISPR/Cas12a system to achieve fast, ultrasensitive, high specificity detection of biological loads in sewage. The Shennong‐1 robot integrates several functional modules, involving sewage sampling and pretreatment to streamline the sewage monitoring. A screen‐printed electrode is employed with a vertical graphene‐based working electrode and enhanced with surface‐deposited Au nanoparticles (NPs). CdTe/ZnS quantum dots (QDs) are further fabricated through the double‐stranded DNA (dsDNA) anchored on Au NPs. Using the cDNA template of Omicron BA.5 spike gene as a model, the PEC biosensor demonstrates excellent analytical performance, with a lower detection limit of 2.93 × 102 zm and an outstanding selectivity at the level of single‐base mutation recognition. Furthermore, the rapid, accurate detection of BA.5 in sewage demonstrates the feasibility of the PEC platform for sewage monitoring. In conclusion, this platform allows early detection and tracking of infectious disease outbreaks, providing timely data support for public health institutions to take appropriate prevention and control measures.

Background: Observational studies have established an association between serum uric acid and cardiovascular disease (CVD). However, these studies are susceptible to uncontrolled confounders and reverse causality bias. To overcome these challenges, we employed a two-sample Mendelian randomization (MR) approach to investigate the causal link between serum uric acid and CVD. Methods: We utilized Genome-wide association study (GWAS) data for serum uric acid and six CVD: coronary artery disease (CAD), hypertension, myocardial infarction (MI), heart failure (HF), angina, and coronary heart disease (CHD). MR analyses employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model. Sensitivity analyses were conducted to assess result reliability, including Cochrane’s Q test, MR-Egger intercept, MR-PRESSO, and the leave-one-out approach. Results: IVW analysis revealed that a genetic predisposition to elevated serum uric acid levels significantly increases the risk of CVD, with higher odds ratios (ORs) observed for CAD (OR: 1.227; 95 % CI: 1.107–1.360, P = 0.0002), hypertension (OR: 1.318, 95 %CI: 1.184–1.466, P = 2.13E-06), MI (OR: 1.184, 95 %CI: 1.108–1.266, P = 2.13E-06), HF (OR: 1.158, 95 %CI: 1.066–1.258, P = 2.13E-06), angina (OR: 1.150, 95 %CI: 1.074–1.231, P = 0.0002) and CHD (OR: 1.170, 95 %CI: 1.072–1.276, P = 0.0005). Sensitivity analysis research results have robustness. Conclusion: This MR study robustly demonstrates a significant causal relationship between genetically elevated serum uric acid and various cardiovascular diseases, suggesting that higher levels may enhance the risk of cardiovascular events. Consequently, patients with elevated uric acid levels warrant early and aggressive interventions to mitigate cardiovascular risks.

Abstract Background and aim An increasing amount of research has indicated obesity greatly affects individuals with overactive bladder (OAB). However, traditional anthropometric methods present challenges in accurately assessing the likelihood of OAB. Hence, this study’s objective was to identify the correlation between the body roundness index (BRI) and OAB. Methods The research included 12,401 individuals who participated in the National Health and Nutrition Examination Survey spanning 2005–2018. The correlation between BRI and OAB was explored by using weighted multiple logistic regression and weighted restricted cubic spline (RCS). Subgroup analyses showed the associations based on different population types. The study also analyzed the predictive capability of various anthropometric indices, including BRI, body mass index, waist circumference, and weight, in assessing the likelihood of OAB through Receiver-operating characteristic (ROC) curves. Results An independent positive correlation between OAB and BRI was identified after adjusting for potential confounders in weighted multivariate logistic models[odds ratio (OR) = 1.15, 95% confidence interval (CI), 1.12–1.17]. Weighted RCS analysis found a positive dose-response correlation between OAB and BRI. The effect size of BRI on OAB remained stable across all prespecified subgroups (all P for interactions > 0.05). In ROC analysis, BRI showed better discriminatory ability for OAB compared with other anthropometric measures for both genders (all P

Abstract In order to increase the precision and effectiveness of power system analysis and fault diagnosis, this study aims to assess the power systems in the energy sector while utilizing artificial intelligence (AI) and environmental social governance (ESG). First, the ESG framework is presented in this study to fully account for the effects of the power system on the environment, society, and governance. Second, to coordinate the operation of various components and guarantee the balance and security of the power system, the CNN-BiLSTM power load demand forecasting model is built by merging convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM). Lastly, the particle swarm optimization (PSO) algorithm is used to introduce and optimize the deep belief network (DBN), and a power grid fault diagnostic model is implemented using the PSO technique and DBN. The model’s performance is assessed through experimentation. The outcomes demonstrate how the CNN-BiLSTM algorithm significantly increases forecasting accuracy while overcoming the drawback of just having one dimension of power load data. The values of 0.054, 0.076, and 0.102, respectively, are the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Effective processing of large-scale nonlinear data is achieved in the area of power grid fault diagnosis, resulting in prediction accuracy of 96.22% and prediction time of only 129.94 s. This is clearly better than other algorithms and increases fault prediction efficiency and accuracy. Consequently, the model presented in this study not only produces impressive results in fault diagnosis and load demand forecasting, but also advances the field of power system analysis in the energy industry and offers a significant amount of support for the sustainable and intelligent growth of the energy industry.

In order to address the issue of high development of hard overlying rock water-conducting fracture zones in deep coal mining and achieve water-preserved coal mining by reducing the height of water-conducting fracture zones, a new method is proposed in this study, which combines the techniques of pre-fracturing and weakening of hard main controlling overlying strata. This study comprehensively investigates the modification effect of pre-fracturing and weakening of hard main controlling overlying strata through laboratory experiments, theoretical analysis, and numerical simulation. The control mechanisms of different weakening layers on water-conducting fracture zones are elaborated and validated through field measurements. The results demonstrate that pre-existing fractures can induce the rock mass to shift its failure mode from intact rock fracturing to tension-shear failure controlled by pre-existing fractures, leading to a reduction in the severity of rock mass failure. The weakening effect of pre-existing fractures on the hard rock mass is revealed, and the damage variables coupled with stress and fractures are calculated. The relationship between the degree of weakening and the transformation of rock properties is qualitatively analyzed. It is found that the energy storage capacity of the rock mass is reduced while the dissipation capacity is enhanced after the modification. Numerical simulations are conducted to evaluate the control effect of different weakening layers on water-conducting fracture zones. By comparing the dynamic evolution of overlying rock failure modes, fracture counts, and failure heights, it is observed that the “saddle-shaped” failure mode gradually weakens with the increase of weakening layer height, and the evolution trend of fracture counts follows a pattern of “slow increase-sudden increase”. The dynamic evolution of failure height for unweakened and moderately to highly weakened overlying strata approximately exhibits an “S” shape, while the moderately weakened overlying strata exhibit a “semi-ejection” shape. Based on the analysis of the characteristics of failure in hard rock layers at different positions, the mechanisms of controlling the development of water-conducting fracture zones by different pre-fracturing weakening layers are revealed. Furthermore, using the borehole measurement method, the development height of the “two zones” under the condition of top plate fracturing in Mengcun mine is obtained. It is observed that the fracture extraction ratio is reduced under the condition of pre-fracturing weakening, thus preliminarily validating the inhibitory effect of top plate pre-fracturing weakening on the development of water-conducting fracture zones.It provides theoretical and scientific basis for coupling disaster prevention and control, water resources and ecological protection。

Background and objective: The intrinsic link between the compositional and structural attributes and the biomechanical functionality is evident in intervertebral discs. However, it remains unclear from a biomechanical perspective whether cartilage endplate (CEP) degeneration exacerbates intervertebral disc degeneration. Methods: This study developed and quantitatively validated four biphasic swelling-based finite element models. We then applied four quasi-static tests and simulated daily loading scenarios to examine the effects of CEP degradation. Results: Under free-swelling conditions, short-term responses were prevalent, with CEP performance changes not significantly impacting response proportionality. The creep test results showed the more than 50 % of the strain was attributed to long-term responses. Stress-relaxation testing indicated that all responses increased with disc degeneration, yet CEP degeneration's impact was minimal. Daily load analyses revealed that disc degeneration significantly reduces nucleus pulposus pressure and disc height, whereas CEP degeneration marginally increases nucleus pressure and slightly decreases disc height. Conclusions: Glycosaminoglycan content and CEP permeability are critical to the fluid-dependent viscoelastic response of intervertebral discs. Our findings suggest that CEP contributes to disc degeneration under daily loading conditions.

To explore the influence of the working face excavation rate on the rock deformation mechanism and seepage characteristics, deformation and seepage tests of sandstone under different loading and unloading stress paths, such as constant axial pressure unloading confining pressure and loading axial pressure unloading confining pressure, were carried out. Particle Flow Code in 3 Dimensions (PFC3D) and Python were used to realize fluid-solid coupling, and numerical simulation calculations were performed along the test path to analyze the influence of the unloading rate on the fine-scale deformation mechanism and permeability characteristics of sandstone, and the relationship between crack type and permeability was obtained. A sandstone fracture mechanics model is established to analyze the stress concentration degree at the end of the branch crack of the test path. The results show that the rate of confining pressure unloading is inversely proportional to the strain. Additionally, permeability correlates with the principal stress difference in an exponential manner. Interestingly, the sensitivity of permeability to stress shows an inverse trend with the unloading rate of confining pressure. Furthermore, there exists a linear relationship between permeability and the number of cracks. During the unloading process, tensile cracks predominate, and the propagation of shear cracks lags behind that of tensile cracks. The proportion of tensile cracks decreases with the increase of the unloading rate when the axial pressure is unchanged but increases when axial pressure is added, resulting in axial compression deformation and expansion deformation along the unloading direction. These research outcomes offer theoretical insights for the prudent selection of mining rates, and they hold significant implications for mitigating water inrush disasters in deep mining operations.

BackgroundAtrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways.MethodsWe obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A “Veen” diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis.ResultsThe combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956–0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934–0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875–0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943–0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004–1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017–1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010–0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003–1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils.ConclusionBy integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

Background: Osteoarthritis (OA) is a degenerative joint disease characterized by the breakdown of joint cartilage and underlying bone. Macrophages are a type of white blood cell that plays a critical role in the immune system and can be found in various tissues, including joints. Research on the relationship between OA and macrophages is essential to understand the mechanisms underlying the development and progression of OA. Objective: This study was performed to analyze the functions of the IRF1-GCN5-SETD2-SMARCC1 axis in osteoarthritis (OA) development. Methods: A single-cell RNA sequencing (scRNA-seq) dataset, was subjected to a comprehensive analysis aiming to identify potential regulators implicated in the progression of osteoarthritis (OA). In order to investigate the role of IRF1 and SMARCC1, knockdown experiments were conducted in both OA-induced rats and interleukin (IL)-1β-stimulated chondrocytes, followed by the assessment of OA-like symptoms, secretion of inflammatory cytokines, and polarization of macrophages. Furthermore, the study delved into the identification of aberrant epigenetic modifications and functional enzymes responsible for the regulation of SMARCC1 by IRF1. To evaluate the clinical significance of the factors under scrutiny, a cohort comprising 13 patients diagnosed with OA and 7 fracture patients without OA was included in the analysis. Results: IRF1 was found to exert regulatory control over the expression of SMARCC1, thus playing a significant role in the development of osteoarthritis (OA). The knockdown of either IRF1 or SMARCC1 disrupted the pro-inflammatory effects induced by IL-1β in chondrocytes, leading to a mitigation of OA-like symptoms, including inflammatory infiltration, cartilage degradation, and tissue injury, in rat models. Additionally, this intervention resulted in a reduction in the predominance of M1 macrophages both in vitro and in vivo. Significant epigenetic modifications, such as abundant H3K27ac and H3K4me3 marks, were observed near the SMARCC1 promoter and 10 kb upstream region. These modifications were attributed to the recruitment of GCN5 and SETD2, which are functional enzymes responsible for these modifications. Remarkably, the overexpression of either GCN5 or SETD2 restored SMARCC1 expression in rat cartilages or chondrocytes, consequently exacerbating the OA-like symptoms. Conclusion: This research postulates that the transcriptional activity of SMARCC1 can be influenced by IRF1 through the recruitment of GCN5 and SETD2, consequently regulating the H3K27ac and H3K4me3 modifications in close proximity to the SMARCC1 promoter and 10 kb upstream region. These modifications, in turn, facilitate the M1 skewing of macrophages and contribute to the progression of osteoarthritis (OA). The Translational Potential of this Article: The study demonstrated that the regulation of SMARCC1 by IRF1 plays a crucial role in the development of OA. Knocking down either IRF1 or SMARCC1 disrupted the pro-inflammatory effects induced by IL-1β in chondrocytes, leading to a mitigation of OA-like symptoms in rat models. These symptoms included inflammatory infiltration, cartilage degradation, and tissue injury. These findings suggest that targeting the IRF1-SMARCC1 regulatory axis, as well as the associated epigenetic modifications, could potentially be a novel approach in the development of OA therapies, offering new opportunities for disease management and improved patient outcomes.

The article investigates the issue of fixed-time control with adaptive output feedback for a twin-roll inclined casting system (TRICS) with disturbance. First, by using the mean value theorem, the nonaffine functions are decoupled to simplify the system. Second, radial basis function neural networks (RBFNNs) are introduced to approximate an unknown term, and a nonlinear neural state observer is created to handle the effects of unmeasured states. Then, the backstepping design framework is combined with prescribed performance and command filtering techniques to demonstrate that the scheme proposed in this article guarantees system performance within a fixed-time. The control design parameters determine the upper bound of settling time, regardless of the initial state of the system. Meanwhile, it ensures that all signals in the closed-loop system (CLS) remain bounded, and it can also maintain the tracking error within a predefined range within a fixed time. Finally, simulation results assert the effectiveness of the method.

The degeneration of intervertebral discs is strongly associated with the occurrence of pyroptosis in nucleus pulposus (NP) cells. This pyroptosis is characterized by abnormal metabolism of fatty acids in the degenerative pathological state, which is further exacerbated by the inflammatory microenvironment and degradation of the extracellular matrix. In order to address this issue, we have developed a fibrin hydrogel complex (FG@PEV). This intricate formulation amalgamates the beneficial attributes of platelet extravasation vesicles, contributing to tissue repair and regeneration. Furthermore, this complex showcases exceptional stability, gradual-release capabilities, and a high degree of biocompatibility. In order to substantiate the biological significance of FG@PEV in intervertebral disc degeneration (IVDD), we conducted a comprehensive investigation into its potential mechanism of action through the integration of RNA-seq sequencing and metabolomics analysis. Furthermore, these findings were subsequently validated through experimentation in both in vivo and in vitro models. The experimental results revealed that the FG@PEV intervention possesses the capability to reshape the inflammatory microenvironment within the disc. It also addresses the irregularities in fatty acid metabolism of nucleus pulposus cells, consequently hindering cellular pyroptosis and slowing down disc degeneration through the regulation of extracellular matrix synthesis and degradation. As a result, this injectable gel system represents a promising and innovative therapeutic approach for mitigating disc degeneration.

Abstract To construct an injectable fibrin glue system loaded with kaempferol (FG@F) to improve the bioavailability of kaempferol and observe its efficacy in the treatment of intervertebral disc degeneration (IVDD). Kaempferol-loaded fibrin glue was first synthesized in advance. Subsequently, the materials were characterized by various experimental methods. Then, nucleus pulposus cells (NPCs) were stimulated with lipopolysaccharide (LPS) to establish a degenerative cell model, and the corresponding intervention treatment was conducted to observe the effect in vitro. Finally, the tail disc of rats was punctured to establish a model of IVDD, and the therapeutic effect of the material in vivo was observed after intervertebral disc injection. The FG@F system has good injectability, sustained release and biocompatibility. This treatment reduced the inflammatory response associated with IVDD and regulated matrix synthesis and degradation. Animal experimental results showed that the FG@F system can effectively improve needle puncture-induced IVDD in rats. The FG@F system has better efficacy than kaempferol or FG alone due to its slow release and mechanical properties. The drug delivery and biotherapy platform based on this functional system might also serve as an alternative therapy for IVDD.

Abstract Tumor growth requires elevated ribosome biogenesis. Targeting ribosomes is an important strategy for cancer therapy. The ribosome inhibitor, homoharringtonine (HHT), is used for the clinical treatment of leukemia, yet it is ineffective for the treatment of solid tumors, the reasons for which remain unclear. Here we show that Snail1, a key factor in the regulation of epithelial-to-mesenchymal transition, plays a pivotal role in cellular surveillance response upon ribotoxic stress. Mechanistically, ribotoxic stress activates the JNK-USP36 signaling to stabilize Snail1 in the nucleolus, which facilitates ribosome biogenesis and tumor cell survival. Furthermore, we show that HHT activates the JNK-USP36-Snail1 axis in solid tumor cells, but not in leukemia cells, resulting in solid tumor cell resistance to HHT. Importantly, a combination of HHT with the inhibition of the JNK-USP36-Snail1 axis synergistically inhibits solid tumor growth. Together, this study provides a rationale for targeting the JNK-USP36-Snail1 axis in ribosome inhibition-based solid tumor therapy.

Recently, in China, during the period of transition between spring and summer, the combination of sandstorms and ozone (O3) pollution has posed a significant challenge to the strategy of coordinated control of fine particulate matters (PM2.5) and O3. On the one hand, the dust invasion brings many primary aerosols and causes a large range of transboundary transport. On the other hand, the high concentration of aerosol causes a severe disturbance to the distribution of O3. Traditionally, high-resolution assessments of the spatial distribution of aerosols and O3 can be carried out using LiDAR technology. However, the negligence of the influence of aerosols in the process of O3 retrieval in traditional differential absorption lidar (DIAL) leads to an error in the accuracy of ozone concentration. Especially when dust transit occurs, the errors become bigger. In this study, a self-customized four-wavelength differential-absorption LiDAR system was used to synchronously obtain the accurate vertical distributions of ozone and high-concentration aerosol. The wavelength index of concentrated aerosol was inverted and applied to the differential equation framework for O3 calculation. This novel approach to retrieving the vertical profile of O3 was proposed and verified by applying it to a dust pollution event that occurred from April to May 2021 in Anyang City Henan Province, which is located in Northern China. It was found that the extinction coefficient of aerosol reached 2.5 km−1 during the dust period, and O3 was mainly distributed between 500 m and 1500 m. The O3 error exceeded over 10% arising from the high-concentration aerosol below 1.5 km during the dust storm event. By employing the inversion algorithm while considering the aerosol effects, the ozone concentration error was improved by over 10% compared with the error recorded without considering the aerosol influence especially in dust events. Through this study, it was found that the algorithm could effectively realize the synchronous and accurate inversion of high-concentration aerosols and O3 and can provide key technical support for air pollution control in China in the future.

As urbanization accelerates worldwide, understanding the impact of urban expansion on habitat quality has become increasingly critical in environmental science research. This study examines the impact of urban expansion on habitat quality in Beijing, forecasting land cover changes and ecological effects by 2030. Using CA–Markov and FLUS models, the research analyzes habitat quality from 2000 to 2030 through the InVEST model, revealing a significant urban land increase of 1316.47 km2 and a consequent habitat quality decline. Predictions for 2030 indicate varying habitat quality outcomes across three scenarios: ecological priority (0.375), natural growth (0.373), and urban development (0.359). We observed that the natural growth scenario forecasts a further decline in habitat quality, primarily due to increased low–value habitat regions. Conversely, the ecological priority scenario projects a notable improvement in habitat quality. To mitigate habitat degradation in Beijing and enhance regional habitat quality and ecological conditions, it is recommended to control urban land cover expansion, adopt effective ecological conservation policies, and systematically carry out national spatial restructuring and ecological restoration. This research provides vital decision–making support for urban planning and ecological conservation, emphasizing the need for comprehensive land cover and ecological strategies in urban development. Additionally, our findings and methodologies are applicable to other rapidly urbanizing cities worldwide. This demonstrates the broader applicability and relevance of our research, providing a framework for sustainable urban planning in diverse global contexts.

This study investigated the antibacterial effects of S-nitroso-N-acetylcysteine (SNAC) and sodium nitrite (NaNO2) against Escherichia coli and their application in beef sausages. Both SNAC and NaNO2 demonstrated pH-responsive antibacterial activity, with SNAC showing greater efficacy than NaNO2 (p < 0.05) at the same pH (3, 5, and 7). The reactive oxygen species (ROS) and reactive nitrogen species (RNS) induced in E. coli by SNAC were significantly higher than those induced by NaNO2 (p < 0.05), and both ROS and RNS values increased as the pH decreased. In addition, a lower pH led to more pores on the E. coli cell surface and increased membrane permeability, resulting in a more pronounced inhibitory effect. When applied to a beef sausage, SNAC-treated sausages had significantly lower total colony counts and carbonyl content compared to NaNO2-treated ones (p < 0.05). Consequently, SNAC shows great potential as a replacement for NaNO2 in meat products.

Seed endophytes in maize, which facilitate the transmission of microorganisms from one plant generation to the next, may play a crucial role in plant protection and growth promotion. This study aimed to investigate the effects of various maize varieties on the communities of endophytic bacteria in seeds and germinating roots. This study utilized Illumina high-throughput sequencing technology to examine the structural and diversity differences of endophytic bacterial communities within seed maize (BY1507), silage maize (QQ446), and wild maize (Teosinte) in both seeds and germinating roots. The results showed that 416 bacterial genera were detected, with Pantoea, Lachnospiraceae, Pararhizobium, Enterobacteriaceae, Stenotrophomonas, and Pseudonocardia being the most prevalent (relative abundance > 10%) at the genus level. No significant difference was observed in diversity indices (Chao1, ACE, Shannon, and Simpson) of seed endophytes among BY1507, QQ446, and Teosinte. The Shannon and Simpson indices for the germinating root endophyte from the wild variety (Teosinte) were significantly higher than the domesticated varieties (BY1507 and QQ446). PCoA revealed a notable overlap in the endophytic bacterial communities from the seeds of BY1507, QQ446, and Teosinte. Yet, clustering patterns were found. Co-occurrence network analysis showed that BY1507, QQ446, and Teosinte share a notable proportion of shared endophytic bacteria (>30%) between the seeds and germinating roots. This investigation elucidates the characteristics of endophytic microbial communities of seeds and germinating roots with seed maize, silage maize, and wild maize, offering data for future research on the physiological ecological adaptation of these endophytic microbial communities.

With global climate change leading to increasing intensity and frequency of droughts, as well as the growing problem of soil salinization, these factors significantly affect crop growth, yield, and resilience to adversity. Oats are a cereal widely grown in temperate regions and are rich in nutritive value; however, the scientific literature on the response of oat to drought and salt stress has not yet been analyzed in detail. This study comprehensively analyzed the response of oat to drought stress and salt stress using data from the Web of Science core database and bibliometric methods with R (version4.3.1), VOSviewer (version 1.6.19), and Citespace (version6.3.1.0) software. The number of publications shows an increasing trend in drought stress and salt stress in oat over the past 30 years. In the field of drought-stress research, China, the United States, and Canada lead in terms of literature publication, with the most academic achievements being from China Agricultural University and Canadian Agricultural Food University. The journal with the highest number of published papers is Field Crops Research. Oat research primarily focuses on growth, yield, physiological and biochemical responses, and strategies for improving drought resistance. Screening of drought-tolerant genotypes and transformation of drought-tolerant genes may be key directions for future oat drought research. In the field of salt-stress research, contributions from China, the United States, and India stand out, with the Chinese Academy of Agricultural Sciences and Inner Mongolia Agricultural University producing the most significant research results. The largest number of published articles has been found in the Physiologia Plantarum journal. Current oat salt-stress research primarily covers growth, physiological and biochemical responses, and salt-tolerance mechanisms. It is expected that future oat salt research will focus more on physiological and biochemical responses, as well as gene-editing techniques. Despite achievements under single-stress conditions, combined drought and salt-stress effects on oat remain understudied, necessitating future research on their interaction at various biological levels. The purpose of this study is to provide potential theoretical directions for oat research on drought and salt stress.

Abstract Current induced spin-orbit torque (SOT) holds great promise for next generation magnetic-memory technology. Field-free SOT switching of perpendicular magnetization requires the breaking of in-plane symmetry, which can be artificially introduced by external magnetic field, exchange coupling or device asymmetry. Recently it has been shown that the exploitation of inherent crystal symmetry offers a simple and potentially efficient route towards field-free switching. However, applying this approach to the benchmark SOT materials such as ferromagnets and heavy metals is challenging. Here, we present a strategy to break the in-plane symmetry of Pt/Co heterostructures by designing the orientation of Burgers vectors of dislocations. We show that the lattice of Pt/Co is tilted by about 1.2° when the Burgers vector has an out-of-plane component. Consequently, a tilted magnetic easy axis is induced and can be tuned from nearly in-plane to out-of-plane, enabling the field-free SOT switching of perpendicular magnetization components at room temperature with a relatively low current density (~1011 A/m2) and excellent stability (> 104 cycles). This strategy is expected to be applicable to engineer a wide range of symmetry-related functionalities for future electronic and magnetic devices.

Ceramics are highly regarded in dental restorations owing to their favorable mechanical properties, chemical resistance, biocompatibility, and aesthetic features. Ceramic additive manufacturing (AM) technology has emerged as a promising solution that offers advantages over traditional techniques such as injection molding, die pressing, tape casting, and milling. Ceramic AM is, however, still under development, with new technologies and devices continuously emerging. This paper provides a comprehensive review of the latest research and applications of ceramic AM in dental restoration, focusing on the progress made within the past five years. Three perspectives are discussed: ceramic AM technologies, commonly used printable ceramic materials, and different types of dental restorations. Among these, vat photopolymerization is the most widely researched and promising AM technology for large-scale applications. ZrO2 remains the primary material used in AM research, whereas crowns and bridges are the most frequently studied and are the closest to industrialized dental restorations. Currently, ceramic AM satisfies the clinical requirements of accuracy, mechanical performance, and biocompatibility. However, compared with traditional methods, it lacks significant advantages in terms of cost and manufacturing efficiency, limiting its large-scale application. Further improvements are necessary in all stages, including raw materials, equipment, post-processing, and standardization.

Introduction and Objectives: Cholangiocarcinoma (CCA) is characterized by early distant invasion and metastasis, whereas the underlying mechanism is still obscure. Increasing evidence shows that collagen type Ι alpha 1 (COL1A1) is a gene associated with the progression of multiple diseases. Here, we attempted to investigate the role of COL1A1 in CCA. Materials and Methods: The expression of COL1A1 between tumor tissues and adjacent normal tissues obtained from CCA patients was detected by Western blot and immunofluorescence, followed by analysis of its clinical significance. Then, the biological effects of COL1A1 overexpression or knockdown on CCA cells were evaluated in vitro and in vivo. Finally, molecular mechanism of COL1A1 in regulating the invasion and metastasis of CCA cells was determined by a series of experiments. Results: COL1A1 expression was significantly higher in CCA pathological tissues than in corresponding adjacent normal tissues. Analysis of 83 CCA patients showed that higher expression of COL1A1 was correlated with poorer patient prognosis. Notably, overexpression or knockdown experiments revealed that COL1A1 contributed to the migration and invasion, as well as epithelial-to-mesenchymal transition (EMT), in CCA cells. Further investigations demonstrated that matrix metalloproteinase-2 (MMP2) promoted COL1A1 upregulation via the integrin alpha Ⅴ pathway, therefore affecting ECM remodelling and inducing EMT in CCA cells. Moreover, COL1A1 expression was positively related to PD-1 and PD-L1 in CCA, and COL1A1 increased PD-L1 expression by activating the NF-κB pathway. Conclusions: COL1A1 plays an important role in regulating CCA progression and may act as a promising biomarker and therapeutic target for CCA.

This paper presents a novel approach—an efficient closed-form approximation iterative fitting algorithm based on laser absorption spectra. Through this closed-form approximation iterative fitting, key parameters such as peak value, spectral line width, and normalized signal area serve as indicators for iteration completion, improving the speed without compromising accuracy. Furthermore, it employs the spectral signal of n cycles as a window for further processing, minimizing external interference. The results show that the proposed method averages 9.75 iterations, while the Levenberg–Marquardt fitting method averages 60.17 iterations. The average iteration time for the proposed method is 588.83 ms, a substantial 81.7% reduction compared to the 3210.5 ms required by the Levenberg–Marquardt fitting. These results decisively demonstrate the efficacy of the proposed method in reducing iteration time and enhancing measurement precision.

The lack of obvious difference between germinated seeds and non-germinated seeds will cause the low accuracy of detecting rice seed germination rate, remains a challenging issue in the field. In view of this, a new model named Rice Seed Germination-YOLOV8 (RSG-YOLOV8) is proposed in this paper. This model initially incorporates CSPDenseNet to streamline computational processes while preserving accuracy. Furthermore, the BRA, a dynamic and sparse attention mechanism is integrated to highlight critical features while minimizing redundancy. The third advancement is the employment of a structured feature fusion network, based on GFPN, aiming to reconfigure the original Neck component of YOLOv8, thus enabling efficient feature fusion across varying levels. An additional detection head is introduced, improving detection performance through the integration of variable anchor box scales and the optimization of regression losses. This paper also explores the influence of various attention mechanisms, feature fusion techniques, and detection head architectures on the precision of rice seed germination rate detection. Experimental results indicate that RSG-YOLOV8 achieves a mAP50 of 0.981, marking a 4% enhancement over the mAP50 of YOLOv8 and setting a new benchmark on the RiceSeedGermination dataset for the detection of rice seed germination rate.

This study investigates the role of abscisic acid (ABA) in bolstering drought resistance in plants, employing “Panjiang Sophora viciifolia” as the subject. A simulated drought scenario was created using polyethylene glycol (PEG-6000) to examine the impact of varying drought intensities (0%, 5%, 20% PEG) and ABA concentrations (0, 10, 50, 100, 200 mg·L−1) on the germination and physiological parameters of Sophora viciifolia. The results showed that in the absence of ABA, the germination rate (GR), germination potential (GP), and germination index (GI) of S. viciifolia seeds initially increased and then decreased with escalating PEG-induced drought stress. At PEG-induced drought stress levels of 5% and 20%, the activities of peroxidase (POD) and catalase (CAT), along with the malondialdehyde (MDA) content, were significantly higher than in the control (CK) (p < 0.05). In response to drought stress, S. viciifolia seeds adapted by modulating germination behavior, augmenting the content of osmoregulatory substances, and boosting the activity of protective enzymes. The addition of ABA markedly enhanced GR, GE, GI, activities of POD, superoxide dismutase (SOD), and CAT, as well as the levels of MDA and proline (Pro) under drought conditions (p < 0.05). Relative to CK, low ABA concentrations (10–100 mg·L−1) resulted in increased GR, GP, GI, POD, SOD, CAT, MDA, and Pro levels; whereas, at a higher concentration (200 mg·L−1), although GR, GP, and GI decreased, POD, SOD, CAT, MDA, and Pro levels increased. Through principal component analysis and membership function comprehensive evaluation, it was determined that administering 50 mg·L−1 ABA was most effective in enhancing drought resistance in S. viciifolia seedlings.

Objective: The aim of our study was to investigate whether the Dietary Inflammatory Index (DII) correlated with gout in American adults. Method: The study used data from the 2007–2018 National Health and Nutrition Examination Survey, with 27,710 adults participating. Initially, multivariable analysis was performed, with controls for covariates, to assess the link of DII and gout. Then, restricted cubic splines (RCS) were applied to model the nonlinear relationship of DII and gout. Furthermore, propensity score matching (PSM) as a further study of potential relationships was established. Eventually, subgroup analysis was performed. Result: Participants within the highest DII quartile would be more susceptible to increased risk of gout in the univariate regression model (Q4 vs. Q1, OR = 1.31, CI: 1.05–1.63). Additionally, a positive correlation was detected between gout risk and DII after adjusting on drinking, smoking, gender, race, age, and BMI. Based on RCS analysis, we observed that the risk of gout raised sharply as DII values increased, then flattened, and increased sharply again when the DII was greater than approximately 2.5. After performing the PSM, it was observed that DII correlated in a positive way to the presence of gout on a fully adjusted multivariable model. Subgroup analysis revealed that the link of DII and gout showed no statistical significance in females, blacks, Mexicans, nor in the population that smoked. Conclusion: Greater degrees of pro-inflammation correlate with a higher risk of gout and might be a predisposing factor for gout. Hence, tactics fostering an anti-inflammatory diet for preventing and improving gout in adults should be regarded.

Melphalan is an efficient chemotherapeutic agent for retinoblastoma (RB) in clinical practice. However, the problems of drug resistance and poor prognosis caused by long-term treatment of melphalan should not be ignored. At present, it is urgent to find a therapeutic strategy to enhance the curative effect to solve the need for clinical treatment of RB to protect eyesight. Herein, we propose an effective strategy to encapsulate melphalan and black phosphorus quantum dots (BPQDs) with high-biocompatibility liposomes for photothermal therapy (PTT) to enhance cell killing. BPQDs and melphalan were encapsulated using liposomes with a similar structure to the cell membrane, and a lipid nanoparticle with both photothermal and chemical inhibition effects was prepared. The obtained nanoparticle has a spherical shape (particle size range of 82–180 nm) and good stability (encapsulation efficiencies of melphalan of 40 % and BPQDs of 43.7 %). Its temperature increased to 65 °C within 10 min under a 2 W/cm2 laser at 808 nm, exerting photothermal and synergistic effects with melphalan to induce apoptosis of tumor cells. As expected, the prepared nanoparticle effectively inhibits tumor proliferation, upregulates the ki67 expression level, and has an excellent PTT effect on the orthotopic xenograft of WERI-RB-1 cells.

The aquila optimization algorithm (AO) is an efficient swarm intelligence algorithm proposed recently. However, considering that AO has better performance and slower late convergence speed in the optimization process. For solving this effect of AO and improving its performance, this paper proposes an enhanced aquila optimization algorithm with a velocity-aided global search mechanism and adaptive opposition-based learning (VAIAO) which is based on AO and simplified Aquila optimization algorithm (IAO). In VAIAO, the velocity and acceleration terms are set and included in the update formula. Furthermore, an adaptive opposition-based learning strategy is introduced to improve local optima. To verify the performance of the proposed VAIAO, 27 classical benchmark functions, the Wilcoxon statistical sign-rank experiment, the Friedman test and five engineering optimization problems are tested. The results of the experiment show that the proposed VAIAO has better performance than AO, IAO and other comparison algorithms. This also means the introduction of these two strategies enhances the global exploration ability and convergence speed of the algorithm.

Elevated SOX2 protein levels correspond to the poor prognosis of patients with esophageal squamous cell carcinoma (ESCC). Poor prognosis is closely correlated with the loss or disruption of cellular polarity; however, the relationships between SOX2 protein and polarity proteins in ESCC remain elusive. Herein, we found that the knockdown of SOX2 significantly decreased miR-142-3p expression and can regulate the translation of LLGL2 protein, a member of the Scribble complex. LLGL2 protein levels in ESCC are negatively correlated with miR-142-3p and SOX2 levels. Moreover, LLGL2 protein expression increased upon SOX2 knockdown in ESCC cell lines, and mutating the binding site for this miRNA in the LLGL2 3’-UTR disrupted its ability to inhibit LLGL2 expression. When LLGL2 was overexpressed, ESCC cell proliferation and invasion were inhibited in vitro and in vivo, which could be elucidated based on changes in gene expression after RNA sequencing, targeted proteomic analysis and bioinformatic assays. However, SOX2 protein did not directly bind to the promoter of miR-142-3p after ChIP sequencing. Together, these findings indicate that a SOX2 regulatory axis governs ESCC proliferation, migration, invasiveness, and apoptosis, thereby providing a potential avenue for future therapeutic intervention. Abbreviations CCK-8, Cell Counting Kit 8; Chip, Chromatin Immunoprecipitation; EC, Esophageal cancer; EMT, epithelial-to-mesenchymal transition; ESCC, Esophageal squamous cell carcinomas; LLGL2, lethal (2) giant larvae protein homolog 2; LLGL2ov, LLGL2 overexpression; MET, mesenchymal-epithelial transition; miRNAs, MicroRNAs; PRM-MS, Parallel reaction monitoring-Mass spectrometry; SD, Standard deviation; SOX, sex determining region Y (SRY)-like box; SOX2-Kd, SOX2-knockdwon; TUNEL, TdT-mediated dUTP Nick-End Labeling.

In order to study the failure mechanism of deep coal seam floor under unloading, pseudo-triaxial mechanical tests were carried out under different loading and unloading stress paths. The relationship between rock elastic modulus, generalized Poisson ratio and confining pressure under different stress paths was analyzed and fitted. The rock fracture mechanics model was constructed, and the stress concentration at the end of the branch crack under different loading and unloading paths was analyzed. The deterioration mechanism of rock mechanical parameters during unloading was analyzed from the aspects of deviatoric stress, energy and acoustic emission events. ① The research showed that the degree of deterioration of the elastic modulus of the sample and the change range of Poisson ratio under different axial compression loading methods were in the order of axial compression> axial compression remain unchanged> unloading axial pressure. Under the same axial pressure and different confining pressure unloading rates, the elastic modulus deterioration degree and Poisson ratio change of the sample were in a positive correlation with the unloading rate. ② Compared with the increase of the deviator stress at the unloading point, it changed in a positive correlation with the deterioration degree of the elastic modulus of the rock sample and the change of Poisson's ratio. During the unloading process of the confining pressure, the energy accumulated in the path that the axial load or remain unchanged was larger than the stress path of axial unloading. When the confining pressure was unloaded to a certain extent, the internal closed micro-cracks and primary fissures were reopened, and the energy used for crack propagation increased rapidly, and the ratio of change to elastic modulus and the Poisson’s ratio increased significantly, and the number of acoustic emission event ringing showed a characteristic of non-linear growth. ③ Under different loading and unloading paths, the deviatoric stress was the fundamental cause of rock instability and failure. The faster the deviatoric stress increased, the more obvious the degradation degree of rock elastic modulus and Poisson ratio changed. Under the action of loading and unloading, the deterioration degree of rock mass was the most serious under the influence of advanced abutment pressure, which was consistent with the fact that the water inrush accidents in the floor of working face mostly occur near the working face.

Oncogene-induced senescence (OIS) occurs in premalignant lung adenomas, but infrequently in malignant adenocarcinomas. Here the authors show that USP5-Beclin 1 axis overcomes OIS in Kras-driven lung cancer by enhancing MDM2-mediated p53 degradation.

The J-TEXT capability is enhanced compared to two years ago with several upgrades of its diagnostics and the increase of electron cyclotron resonance heating (ECRH) power to 1 MW. With the application of electron cyclotron wave (ECW), the ECW assisted plasma startup is achieved; the tearing mode is suppressed; the toroidal injection of 300 kW ECW drives around 24 kA current; fast electrons are generated with toroidal injected ECW and the runaway current conversion efficiency increases with ECRH power. The mode coupling between 2/1 and 3/1 modes are extensively studied. The coupled 2/1 and 3/1 modes usually lead to major disruption. Their coupling can be either suppressed or avoided by external resonant magnetic perturbation fields and hence avoids the major disruption. It is also found that the 2/1 threshold of external field is significantly reduced by a pre-excited 3/1 mode, which can be either a locked island or an external kink mode. The disruption control is studied by developing prediction methods capable of cross tokamak application and by new mitigation methods, such as the biased electrode or electromagnetic pellet injector. The high-density operation and related disruptions are studied from various aspects. Approaching the density limit, the collapse of the edge shear layer is observed and such collapse can be prevented by applying edge biasing, leading to an increased density limit. The density limit is also observed to increase, if the plasma is operated in the poloidal divertor configuration or the plasma purity is increased by increasing the pre-filled gas pressure or ECRH power during the start-up phase.

Kernel-using apricot (Prunus armeniaca L.) is an economically important fruit tree species in arid areas owing to its hardiness and cold and drought tolerance. However, little is known about its genetic background and trait inheritances. In the present study, we first evaluated the population structure of 339 apricot accessions and the genetic diversity of kernel-using apricots using whole genome re-sequencing. Second, the phenotypic data of 222 accessions were investigated for two consecutive seasons (2019 and 2020) for 19 traits, including kernel and stone shell traits and the pistil abortion rate of flowers. Heritability and correlation coefficient of traits were also estimated. The stone shell length (94.46%) showed the highest heritability, followed by the length/width ratio (92.01%) and length/thickness ratio (92.00%) of the stone shell, whereas breaking force of the nut (17.08%) exhibited a very low heritability. A genome-wide association study (GWAS) using general linear model and generalized linear mixed model revealed 122 quantitative trait loci (QTLs). The QTLs of the kernel and stone shell traits were unevenly assigned on the eight chromosomes. Out of the 1,614 candidate genes identified in the 13 consistently reliable QTLs found using the two GWAS methods and/or in the two seasons, 1,021 were annotated. The sweet kernel trait was assigned to chromosome 5 of the genome, similar to the almond, and a new locus was also mapped at 17.34–17.51 Mb on chromosome 3, including 20 candidate genes. The loci and genes identified here will be of significant use in molecular breeding efforts, and the candidate genes could play essential roles in exploring the mechanisms of genetic regulation.

Glioma is a malignant tumor of the central nervous system with complex pathogenesis, difficult operation, and a high postoperative recurrence rate. At present, there is still a lack of effective treatment. Long non-coding RNA DDX11 antisense RNA 1 (DDX11-AS1) has been shown to promote tumor development, such as hepatocellular carcinoma, esophageal cancer, etc. However, its molecular mechanism in glioma is poorly understood. In this study, we found that the expression of DDX11-AS1 was elevated in glioma tissues, and patients with high expression of DDX11-AS1 had poor prognosis. DDX11-AS1 was a potential prognostic marker. Functionally, DDX11-AS1 promoted glioma cell proliferation and migration. Mechanistically, DDX11-AS1 interacted with RNA-binding protein heterogeneous nuclear ribonucleoprotein C (HNRNPC) to promote Wnt/β-catenin and AKT pathways and the epithelial-mesenchymal transition process. In summary, our study manifests that the DDX11-AS1/HNRNPC axis may play a vital part in the occurrence and development of glioma, which provides new ideas and therapeutic targets for the diagnosis, treatment, and prognosis of glioma.

Ultrafast magnetisation dynamics can reveal transient magnetic states and enable the observation of exotic physics not accessible on shorter timescales. Here, the authors investigate a photo-induced antiferromagnetic-ferromagnetic transition in a strongly correlated thin film using time resolved X-ray based techniques.

In order to maximize the acquisition of photovoltaic energy when applying photovoltaic systems, the efficiency of photovoltaic system depends on the accuracy of unknown parameters in photovoltaic models. Therefore, it becomes a challenge to extract the unknown parameters in the photovoltaic model. It is well known that the equations of photovoltaic models are nonlinear, and it is very difficult for traditional methods to accurately extract its unknown parameters such as analytical extraction method and key points method. Therefore, with the aim of extracting the parameters of the photovoltaic model more efficiently and accurately, an enhanced hybrid JAYA and Rao-1 algorithm, called EHRJAYA, is proposed in this paper. The evolution strategies of the two algorithms are initially mixed to improve the population diversity and an improved comprehensive learning strategy is proposed. Individuals with different fitness are given different selection probabilities, which are used to select different update formulas to avoid insufficient using of information from the best individual and overusing of information from the worst individual. Therefore, the information of different types of individuals is utilized to the greatest extent. In the improved update strategy, there are two different adaptive coefficient strategies to change the priority of information. Finally, the combination of the linear population reduction strategy and the dynamic lens opposition-based learning strategy, the convergence speed of the algorithm and ability to escape from local optimum can be improved. The results of various experiments prove that the proposed EHRJAYA has superior performance and rank in the leading position among the famous algorithms.

In order to have the highest efficiency in real-life photovoltaic power generation systems, how to model, optimize and control photovoltaic systems has become a challenge. The photovoltaic power generation systems are dominated by photovoltaic models, and its performance depends on its unknown parameters. However, the modeling equation of the photovoltaic model is nonlinear, leading to the difficulty in parameter extraction. To extract the parameters of the photovoltaic model more accurately and efficiently, a chaotic self-adaptive JAYA algorithm, called AHJAYA, was proposed, where various improvement strategies are introduced. First, self-adaptive coefficients are introduced to change the priority of information from the best search agent and the worst search agent. Second, by combining the linear population reduction strategy with the chaotic opposition-based learning strategy, the convergence speed of the algorithm is improved as well as avoid falling into local optimum. To verify the performance of the AHJAYA, four photovoltaic models are selected. The experimental results prove that the proposed AHJAYA has superior performance and strong competitiveness.

Abstract The anomalous Hall effect (AHE) is a quantum coherent transport phenomenon that conventionally vanishes at elevated temperatures because of thermal dephasing. Therefore, it is puzzling that the AHE can survive in heavy metal (HM)/antiferromagnetic (AFM) insulator (AFMI) heterostructures at high temperatures yet disappears at low temperatures. In this paper, an unconventional high‐temperature AHE in HM/AFMI is observed only around the Néel temperature of AFM, with large anomalous Hall resistivity up to 40 nΩ cm is reported. This mechanism is attributed to the emergence of a noncollinear AFM spin texture with a non‐zero net topological charge. Atomistic spin dynamics simulation shows that such a unique spin texture can be stabilized by the subtle interplay among the collinear AFM exchange coupling, interfacial Dyzaloshinski–Moriya interaction, thermal fluctuation, and bias magnetic field.

IntroductionRepair and regeneration of the peripheral nerve are important for the treatment of peripheral nerve injury (PNI) caused by mechanical tears, external compression injuries and traction injuries. Pharmacological treatment can promote the proliferation of fibroblasts and Schwann cells (SCs), which longitudinally fill the endoneurial canal and form Bungner’s band, helping the repair of peripheral nerves. Therefore, the development of new drugs for the treatment of PNI has become a top priority in recent years.MethodsHere, we report that small extracellular vesicles (sEVs) produced from umbilical cord mesenchymal stem cells (MSC-sEVs) cultured under hypoxia promote repair and regeneration of the peripheral nerve in PNI and may be a new therapeutic drug candidate.ResultsThe results showed that the amount of secreted sEVs was significantly increased in UC-MSCs compared with control cells after 48 h of culture at 3% oxygen partial pressure in a serum-free culture system. The identified MSC-sEVs could be taken up by SCs in vitro, promoting the growth and migration of SCs. In a spared nerve injury (SNI) mouse model, MSC-sEVs accelerated the recruitment of SCs at the site of PNI and promoted peripheral nerve repair and regeneration. Notably, repair and regeneration in the SNI mouse model were enhanced by treatment with hypoxic cultured UC-MSC-derived sEVs.DiscussionTherefore, we conclude that hypoxic cultured UC-MSC-derived sEVs may be a promising candidate drug for repair and regeneration in PNI.

IntroductionLong-term grazing profoundly affects grassland ecosystems, whereas how the soil microbiome and multiple soil ecosystem functions alter in response to two-decades of grazing, especially how soil microbiome (diversity, composition, network complexity, and stability) forms soil multifunctionality is rarely addressed.MethodsWe used a long-term buffalo grazing grassland to measure the responses of soil physicochemical attributes, stoichiometry, enzyme activities, soil microbial niche width, structure, functions, and networks to grazing in a subtropical grassland of Guizhou Plateau, China.ResultsThe evidence from this work suggested that grazing elevated the soil hardness, available calcium content, and available magnesium content by 6.5, 1.9, and 1.9 times (p = 0.00015–0.0160) and acid phosphatase activity, bulk density, pH by 59, 8, and 0.5 unit (p = 0.0014–0.0370), but decreased the soil water content, available phosphorus content, and multifunctionality by 47, 73, and 9–21% (p = 0.0250–0.0460), respectively. Grazing intensified the soil microbial carbon limitation (+78%, p = 0.0260) as indicated by the increased investment in the soil β-glucosidase activity (+90%, p = 0.0120). Grazing enhanced the complexity and stability of the bacterial and fungal networks but reduced the bacterial Simpson diversity (p < 0.05). The bacterial diversity, network complexity, and stability had positive effects, while bacterial and fungal compositions had negative effects on multifunctionality.DiscussionsThis work is an original attempt to show that grazing lowered multifunctionality via the reduced bacterial diversity and shifted soil bacterial and fungal compositions rather than the enhanced bacterial and fungal network complexities and stability by grazing. Protecting the bacterial diversity from decreasing, optimizing the composition of bacteria and fungi, and enhancing the complexity and stability of bacterial network may be conducive to improving the soil multifunction of grazing grassland, on a subtropical grassland.

Aberrant EGFR activation is commonly found in non-small cell lung cancer (NSCLC). Here the authors show that E3 ubiquitin ligase FBXL2 targets EGFR and EGFR tyrosine kinase inhibitor (TKI)-resistant mutants for proteasome-mediated degradation to inhibit EGFR-driven NSCLC growth and TKI resistance.

Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus. Postherpetic neuralgia (PHN) is the most common chronic complication of HZ. In this study, we examined the metabolomic and proteomic signatures of disease progression in patients with HZ and PHN. We identified differentially expressed metabolites (DEMs), differentially expressed proteins (DEPs), and key signaling pathways that transition from healthy volunteers to the acute or/and chronic phases of herpetic neuralgia. Moreover, some specific metabolites correlated with pain scores, disease duration, age, and pain in sex dimorphism. In addition, we developed and validated three optimal predictive models (AUC > 0.9) for classifying HZ and PHN from healthy individuals based on metabolic patterns and machine learning. These findings may reveal the overall metabolomics and proteomics landscapes and proposed the optimal machine learning predictive models, which provide insights into the mechanisms of HZ and PHN.

Perilla is a young allotetraploid species within the mint family Lamiaceae. Here, the authors assemble the genomes of a tetraploid species and its diploid progenitor, characterize the incipient diploidization of the tetraploid, conduct population genetics analyses, and identify loci associate with pigmentation and oil content.

Abstract Background Epidermal growth factor receptor‐tyrosine kinase inhibitor (EGFR‐TKI) has been considered as an effective treatment in epidermal growth factor receptor‐mutant (EGFR‐mutant) advanced non‐small cell lung cancer (NSCLC). However, most patients develop acquired resistance eventually. Here, we compared and analyzed the genetic alterations between tissue assay and circulating tumor DNA (ctDNA) and further explored the resistance mechanisms after EGFR‐TKI treatment. Methods and Materials Amplification refractory mutation system‐polymerase chain reaction (ARMS‐PCR), Cobas® ARMS‐PCR and next‐generation sequencing (NGS) were performed on tissue samples after pathological diagnosis. Digital droplet PCR (ddPCR) and NGS were performed on plasma samples. The association between genetic alterations and clinical outcomes was analyzed retrospectively. Results Thirty‐seven patients were included. The success rate of re‐biopsy was 91.89% (34/37). The total detection rate of EGFR T790M was 62.16% (23/37) and the consistency between tissue and ctDNA was 78.26% (18/23). Thirty‐four patients were analyzed retrospectively. For tissue re‐biopsy, 24 patients harbored concomitant mutations. Moreover, tissue re‐biopsy at resistance showed 21 patients (21/34, 61.76%) had the concomitant somatic mutation. The three most frequent concomitant mutations were TP53 (18/34, 52.94%), MET (4/34, 11.76%), and PIK3CA (4/34, 11.76%). Meanwhile, 21 patients (21/34, 61.76%) with EGFR T790M mutation. Progression‐free survival (PFS) and overall survival (OS) were better in patients with T790M mutation (p = 0.010 and p = 0.017) or third‐generation EGFR‐TKI treatment (p

Chronic pain remains to be a clinical challenge and is recognized as a major health problem with varying impacts on quality of life. Currently, the first-line therapy for chronic pain is opioids, which are often accompanied by unwanted psychoactive side effects. Thus, new and effective treatments for chronic pain are urgently needed and eagerly pursued. Inflammatory cytokines, especially interleukin-17 (IL-17), are reportedly potential therapeutic targets owing to their pivotal role in chronic pain from the neuroinflammation perspective. Recently, substantial evidence confirmed that IL-17 and IL-17 receptors (IL-17Rs) were increased in neuropathic, inflammatory, and cancer pain models. Notably, IL-17/IL-17R antibodies also reportedly relieve or cure inflammatory- and pain-related diseases. However, existing studies have reported controversial results regarding IL-17/IL-17Rs as potential therapeutic targets in diverse animal models of chronic pain. In this review, we present a summary of published studies and discuss the evidence, from basic to clinical to research, regarding the role and mechanism of action between IL-17 and diverse kinds of chronic pain in animal models and clinical patients. Furthermore, we evaluated IL-17-based therapy as a potential therapeutic strategy for inflammatory- and pain-related disease. Importantly, we also discussed clinical trials of IL-17/IL-17R targeting monoclonal antibodies. Overall, we found that IL-17 is a potential therapeutic target for chronic pain from the perspective of neuroinflammation.