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Abstract Adult skeletal muscle stem cells, also known satellite cells (SCs), are quiescent and activate in response to injury. However, the activation mechanisms of quiescent SCs (QSCs) remain largely unknown. Here, we investigated the metabolic regulation of SC activation by identifying regulatory metabolites that promote SC activation. Using targeted metabolomics, we found that spermidine acts as a regulatory metabolite to promote SC activation and muscle regeneration in mice. Mechanistically, spermidine activates SCs via generating hypusinated eIF5A. Using SC-specific eIF5A-knockout (KO) and Myod-KO mice, we further found that eIF5A is required for spermidine-mediated SC activation by controlling MyoD translation. More significantly, depletion of eIF5A in SCs results in impaired muscle regeneration in mice. Together, the findings of our study define a novel mechanism that is essential for SC activation and acts via spermidine-eIF5A-mediated MyoD translation. Our findings suggest that the spermidine-eIF5A axis represents a promising pharmacological target in efforts to activate endogenous SCs for the treatment of muscular disease.

Emerging as a paradigmatic shift in urban development, smart cities harness the potential of advanced information and communication technologies to seamlessly integrate urban functions, optimize resource allocation, and improve the effectiveness of city management. Within the domain of smart education, the imperative application of Visual Question Answering (VQA) technology encounters significant limitations at the prevailing stage, particularly the absence of a robust Internet of Things (IoT) framework and the inadequate incorporation of large pre-trained language models (LLMs) within contemporary smart education paradigms, especially in addressing zero-shot VQA scenarios, which pose considerable challenges. In response to these constraints, this paper introduces an IoT-based smart city framework that is designed to refine the functionality and efficacy of educational systems. This framework is delineated into four cardinal layers: the data collection layer, data transmission layer, data management layer, and application layer. Furthermore, we introduce the innovative TeachVQA methodology at the application layer, synergizing VQA technology with extensive pre-trained language models, thereby considerably enhancing the dissemination and assimilation of educational content. Evaluative metrics in the VQAv2 and OKVQA datasets substantiate that the TeachVQA methodology not only outperforms existing VQA approaches, but also underscores its profound potential and practical relevance in the educational sector.

Abstract Alkaline hydrogen evolution reaction (HER) for scalable hydrogen production largely hinges on addressing the sluggish bubble‐involved kinetics on the traditional Ni‐based electrode, especially for ampere‐level current densities and beyond. Herein, 3D‐printed Ni‐based sulfide (3DPNS) electrodes with varying scaffolds are designed and fabricated. In situ observations at microscopic levels demonstrate that the bubble escape velocity increases with the number of hole sides (HS) in the scaffolds. Subsequently, we conduct multiphysics field simulations to illustrate that as the hole shapes transition from square, pentagon, and hexagon to circle, where a noticeable reduction in the bubble‐attached HS length and the pressure balance time around the bubbles results in a decrease in bubble size and an acceleration in the rate of bubble escape. Ultimately, the 3DPNS electrode with circular hole configurations exhibits the most favorable HER performance with an overpotential of 297 mV at the current density of up to 1000 mA cm−2 for 120 h. The present study highlights a scalable and effective electrode scaffold design that promotes low‐cost and low‐energy green hydrogen production through the ampere‐level alkaline HER.

Magnesium phosphate bone cements (MPC) have been recognized as a viable alternative for bone defect repair due to their high mechanical strength and biodegradability. However, their poor porosity and permeability limit osteogenic cell ingrowth and vascularization, which is critical for bone regeneration. In the current study, we constructed a novel hierarchically-porous magnesium phosphate bone cement by incorporating extracellular matrix (ECM)-mimicking electrospun silk fibroin (SF) nanofibers. The SF-embedded MPC (SM) exhibited a heterogeneous and hierarchical structure, which effectively facilitated the rapid infiltration of oxygen and nutrients as well as cell ingrowth. Besides, the SF fibers improved the mechanical properties of MPC and neutralized the highly alkaline environment caused by excess magnesium oxide. Bone marrow stem cells (BMSCs) adhered excellently on SM, as illustrated by formation of more pseudopodia. CCK8 assay showed that SM promoted early proliferation of BMSCs. Our study also verified that SM increased the expression of OPN, RUNX2 and BMP2, suggesting enhanced osteogenic differentiation of BMSCs. We screened for osteogenesis-related pathways, including FAK signaing, Wnt signaling and Notch signaling, and found that SM aided in the process of bone regeneration by suppressing the Notch signaling pathway, proved by the downregulation of NICD1, Hes1 and Hey2. In addition, using a bone defect model of rat calvaria, the study revealed that SM exhibited enhanced osteogenesis, bone ingrowth and vascularization compared with MPC alone. No adverse effect was found after implantation of SM in vivo. Overall, our novel SM exhibited promising prospects for the treatment of critical-sized bone defects.

Species of Micropsalliota generally grow in the tropics and are characterised by small, slender basidiomes, brown basidiospores, and cheilocystidia that vary in shape with capitate or subcapitate apex, and pigmented pileipellis. Based on morphological characters and molecular evidence, here we describe seven new species from southern China, viz. Micropsalliota ferruginea, M. fimbriata, M. gigaspora, M. longicystis, M. nana, M. squarrosa, and M. umbonata. Micropsalliota appendiculata, a species recently described from Vietnam, was first recorded in China. The Maximum likelihood and Bayesian analyses based on multi-locus sequence datasets (the nuc rDNA internal transcribed spacer region ITS1-5.8S-ITS2, nrITS; the D1–D2 domains of nuc 28S rDNA, LSU; partial sequences of the most variable region of the second-largest subunit of RNA polymerase II, rpb2, and a portion of the translation-elongation factor 1-α, tef1) shows that the genus is separated into 11 major clades and subclades. To aid in diagnosis, a key to 32 species of Micropsalliota in China is provided.

Study Design A retrospective analysis. Purpose To investigate the occurrence of central sensitization (CS) in patients with osteoporotic vertebral compression fractures (OVCFs) and identify the association between CS and residual back pain (RBP). Overview of Literature RBP is a vexing complication that affects 6.3%–17.0% of patients with OVCFs who underwent percutaneous vertebroplasty (PVP). Given the negative effect of RBP on patients’ psychological and physiological statuses, efforts to preoperatively select patients who are at risk for RBP development have a high priority to offer additional treatment and minimize this complication. Methods Preoperatively, all 160 patients with OVCFs underwent pressure-pain threshold (PPT), temporal summation (TS), conditioned pain modulation (CPM), and imaging assessments. Pain intensity and pain-related disability were evaluated before and after PVP. Results Preoperatively, patients with OVCFs had lower PPTs in both local pain and pain-free areas and lower CPM and higher TS in pain-free areas than healthy participants (p

Abstract Background Multiple genetic and epigenetic regulatory mechanisms are crucial in the development and tumorigenesis process. Transcriptional regulation often involves intricate relationships and networks with post-transcriptional regulatory molecules, impacting the spatial and temporal expression of genes. However, the synergistic relationship between transcription factors and N6-methyladenosine (m6A) modification in regulating gene expression, as well as their influence on the mechanisms underlying the occurrence and progression of non-small cell lung cancer (NSCLC), requires further investigation. The present study aimed to investigate the synergistic relationship between transcription factors and m6A modification on NSCLC. Methods The transcription factor NFIC and its potential genes was screened by analyzing publicly available datasets (ATAC-seq, DNase-seq, and RNA-seq). The association of NFIC and its potential target genes were validated through ChIP-qPCR and dual-luciferase reporter assays. Additionally, the roles of NFIC and its potential genes in NSCLC were detected in vitro and in vivo through silencing and overexpression assays. Results Based on multi-omics data, the transcription factor NFIC was identified as a potential tumor suppressor of NSCLC. NFIC was significantly downregulated in both NSCLC tissues and cells, and when NFIC was overexpressed, the malignant phenotype and total m6A content of NSCLC cells was suppressed, while the PI3K/AKT pathway was inactivated. Additionally, we discovered that NFIC inhibits the expression of METTL3 by directly binding to its promoter region, and METTL3 regulates the expression of KAT2A, a histone acetyltransferase, by methylating the m6A site in the 3’UTR of KAT2A mRNA in NSCLC cells. Intriguingly, NFIC was also found to negatively regulate the expression of KAT2A by directly binding to its promoter region. Conclusions Our findings demonstrated that NFIC suppresses the malignant phenotype of NSCLC cells by regulating gene expression at both the transcriptional and post-transcriptional levels. A deeper comprehension of the genetic and epigenetic regulatory mechanisms in tumorigenesis would be beneficial for the development of personalized treatment strategies.

Abstract Background Dose-response and nonlinear relationships of cigarette exposure with sleep disturbances and depression are warranted, and the potential mechanism of sex hormones in such associations remains unclear. Methods Cigarette exposure, trouble sleeping, and depression were assessed by standard questionnaires, and the levels of cotinine and sex steroid hormones were determined among 9900 adults from the National Health and Nutrition Examination Survey (NHANES). Multiple linear regression, logistic regression, and mediation models were conducted to evaluate the associations between smoking, sex steroid hormones, trouble sleeping, and depression. Results With never smokers as a reference, current smokers had a higher prevalence of trouble sleeping (OR = 1.931, 95% CI: 1.680, 2.219) and depression (OR = 2.525, 95% CI: 1.936, 3.293) as well as testosterone level (β = 0.083, 95% CI: 0.028, 0.140). Pack-years of smoking and cigarettes per day were positively associated with the prevalence of trouble sleeping and depression as well as testosterone level (P trend 0.05). Conclusion Smoking may induce sex hormone disturbance and increase the risk of sleep problems and depression symptoms, and ceasing smoking may reduce the risk of such complications.

The basic leucine zipper (bZIP) family consists of conserved transcription factors which are widely present in eukaryotes and play important regulatory roles in plant growth, development, and stress responses. Neopyropia yezoensis is a red marine macroalga of significant economic importance; however, their bZIP family members and functions have not been systematically identified and analyzed. In the present study, the bZIP gene family in Ny. yezoensis was characterized by investigating gene structures, conserved motifs, phylogenetic relationships, chromosomal localizations, gene duplication events, cis-regulatory elements, and expression profiles. Twenty-three Ny. yezoensis bZIP (NyybZIP) genes were identified and sorted into 13 out of 30 groups, which were classified based on the bZIPs of Ny. yezoensis and 15 other red algae species. Phylogenetic analysis revealed that bZIP genes may have a complex evolutionary pattern in red algae. Cross-species collinearity analysis indicated that the bZIP genes in Ny. yezoensis, Neoporphyra haitanensis, and Porphyra umbilicalis are highly evolutionarily conserved. In addition, we identified four main categories of cis-elements, including development-related, light-responsive, phytohormone-responsive and stress-responsive promoter sequences in NyybZIP genes. Finally, RNA sequencing data and quantitative real-time PCR (qRT-PCR) showed that NyybZIP genes exhibited different expression patterns depending on the life stage. NyybZIP genes were also found to be involved in the nitrogen stress response. We thought that bZIP genes may be involved in Ny. yezoensis growth and development, and play a significant role in nitrogen deficiency response. Taken together, our findings provide new insights into the roles of the bZIP gene family and provide a basis for additional research into its evolutionary history and biological functions.

Osteosarcoma (OS) has strong invasiveness, early metastasis, high drug resistance, and poor prognosis. At present, OS still lacks reliable biomarkers, which makes early diagnosis of OS more difficult. AOC3 is highly expressed in OS and highly correlated with lung metastasis. qRT-PCR could identify mRNA levels of genes. Immunohistochemistry and Western blot assays could detect protein levels. Immunofluorescence and ELISA assays were applied to evaluate the activation of neutrophils. Additionally, transwell and wound healing assays evaluated cell migration and invasion abilities. Tube formation and sphere-forming assays were applied to detect the angiogenesis. C57BL/6 mice were injected with OS cells to establish a xenograft tumor model to observe the lung metastasis of OS. Flow cytometry is used to evaluate the ability of tumor cells to recruit neutrophils. AOC3 was significantly overexpressed in OS, and down-regulation of AOC3 could inhibit OS migration, invasion, and angiogenesis. AOC3 could increase tumor development and lung metastasis of OS in vivo experiments. The promoting effect of AOC3 on tumor lung metastasis was achieved by recruiting tumor neutrophils. Activated NETs could up-regulate the metastatic ability of OS cells. Tumor neovascularization also played a role in metastasis, and AOC3 supported tumor neovascularization. AOC3 accelerates lung metastasis of OS by recruiting tumor-related neutrophils and utilizing NETs and tumor vascularization formation.

Abstract Background Understanding of the ratio of photosynthetic photon flux density (Q p ) to global solar radiation (R s ) (Q p /R s ) is crucial for applying R s to ecology-related studies. Previous studies reported Q p /R s and its variations based on measurements from a single observatory tower, instead of multi-site-based measurements over complex terrains. This may neglect spatial heterogeneity in the terrain, creating a gap in an understanding of how terrain affects Q p /R s and how this effect interacts with meteorological factors. Methods Here the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Q p and R s over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVFs) divided from the field of view of tower’s pyranometer was calculated as a topographic factor to explain the variations of Q p /R s . Results The results identified significant differences in Q p /R s of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Q p /R s was positively correlated with SVFs of T1 and T3, while this correlation was negative with that of T2. The effect of SVFs on Q p /R s interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation (R 2) on Q p /R s was improved when SVFs was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Q p /R s . The improvement in the R 2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Q p /R s depended on sky conditions. Conclusions All findings suggested that Q p /R s is affected by terrain, and integrating terrain information into existing Q p /R s models is a feasible solution to improve Q p /R s estimates in mountainous areas.

Objective Conventional ATO (automatic train operation) systems lack a direct, real-time, and bidirectional data exchange with the vehicle traction/braking systems. In the vehicle control process, information on the vehicle traction/braking status and capabilities is not available, which can lead to issues such as control commands from the ATO system not aligning with actual vehicle capabilities, long control cycles, and low parking precision, calling for a need to achieve deep integration between ATO and vehicle systems. Method The working principle and limitations of conventional ATO systems are discussed. The ATO system based on deep vehicle integration (hereinafter referred to as Integrated ATO) is introduced. The integration optimization measures of the Integrated ATO system in terms of system architecture, information transfer, vehicle interfaces, and system functionality are elucidated. A comparative analysis is conducted between conventional and Integrated ATO systems to highlight the advantages of the latter. Result & Conclusion The Integrated ATO system cancels the interlink between ATO and vehicle traction/braking systems, reduces communication links to enhance richness and transparency of information transfer between them. The Integrated ATO system leverages the characteristics and advantages of both the vehicle and signaling systems, enhancing the coordination between ATO system and traction/braking systems, thereby improving overall control effectiveness.

Aim: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics. Methods: Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. Subsequently, the cases were randomly divided into a training cohort of 165 cases and a validation cohort of 69 cases. Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves. Additionally, the correlation between the Pathomics score (PS) and immune genes was examined. Results: In the multivariate analysis, heightened infiltration of activated CD4 memory T cells was strongly associated with improved overall survival (HR = 0.505, 95 % CI = 0.342–0.745, P

Deep-learning based approaches have been proven effective for Digital Elevation Model (DEM) super-resolution (SR) tasks. Previous networks typically treat DEM elevation values as single-channel image for input. However, DEM images alone cannot fully capture spatial and terrain features. Shaded relief images (SRIs), derived from DEMs, serve as crucial visual cues that intuitively convey terrain characteristics, addressing the limitations of DEM images and providing synergistic benefits for training DL models. The primary challenge in utilizing SRIs for guiding DEM SR lies in accurately selecting a consistent structure to extract and effectively integrate features from SRIs and DEMs. In this study, we propose an Attention-based Hierarchical Terrain Fusion (AHTF) framework for guided DEM SR. Specifically, an Attention-based Feature Fusion Module (AFFM) is designed to efficiently fuse relevant information from LR DEM and SRI, which includes a feature enhancement block to select valuable features and a feature recalibration block to fuse diverse terrain features. Additionally, we optimize the loss function from the perspectives of terrain analysis and visual effects. We validate AHTF on our newly constructed real-world Shade-DEM SR dataset and two open-source DEM SR datasets. Compared to the current state-of-the-art methods, our AHTF achieves the best results in terms of root mean square error (RMSE) for elevation, slope, and aspect. Furthermore, the extracted stream networks are closer to real-world conditions. This study offers new insights and methods for further research and application in the field of DEM super-resolution. Our dataset can be obtained at https://doi.org/10.6084/m9.figshare.25590945.

Numerous innovative low-carbon ironmaking technologies rely on the use of a high-temperature, highly reducing gas, with examples including the gas-based direct reduction approach, hydrogen-enriched blast furnace fuel injection, and hydrogen-rich carbon circulation oxygen blast furnaces. However, the process of obtaining high-temperature and highly reducing gases inevitably leads to carbon deposition, and effective methods for controlling carbon deposition have yet to be developed for practical applications. Thus, within the context of metallurgical process conditions, this article provides a comprehensive review of the advancements in carbon deposition research by integrating findings from the fields of fuel chemistry and carbon material synthesis. Initially, the thermodynamic fundamentals of the carbon deposition reactions are examined, and subsequently, the influences of temperature, H2, and catalysis on the carbon deposition reactions are discussed. In addition, the growth and erosion mechanisms of carbon on the surface of the medium are analyzed. Finally, this review consolidates the methods available for controlling carbon deposition, encompassing changes in the process conditions, the development of anti-carbon materials, and research into special processes. This article also identifies gaps in the literature and outlines future directions in related fields, notably proposing the application prospects of the sulfur passivation and thermal plasma reforming technologies in the reforming and heating of highly reducing gases.

IntroductionReward and punishment modulate behavior. In real-world motor skill learning, reward and punishment have been found to have dissociable effects on optimizing motor skill learning, but the scientific basis for these effects is largely unknown.MethodsIn the present study, we investigated the effects of reward and punishment on the performance of real-world motor skill learning. Specifically, three groups of participants were trained and tested on a ping-pong ball bouncing task for three consecutive days. The training and testing sessions were identical across the three days: participants were trained with their right (dominant) hand each day under conditions of either reward, punishment, or a neutral control condition (neither). Before and after the training session, all participants were tested with their right and left hands without any feedback.ResultsWe found that punishment promoted early learning, while reward promoted late learning. Reward facilitated short-term memory, while punishment impaired long-term memory. Both reward and punishment interfered with long-term memory gains. Interestingly, the effects of reward and punishment transferred to the left hand.DiscussionThe results show that reward and punishment have different effects on real-world motor skill learning. The effects change with training and transfer readily to novel contexts. The results suggest that reward and punishment may act on different learning processes and engage different neural mechanisms during real-world motor skill learning. In addition, high-level metacognitive processes may be enabled by the additional reinforcement feedback during real-world motor skill learning. Our findings provide new insights into the mechanisms underlying motor learning, and may have important implications for practical applications such as sports training and motor rehabilitation.

In this study, the effects on the structures and emulsion gels of carrageenan (CA) and gum arabic (GA) with soybean protein isolate (SPI) were investigated. The results showed that CA and GA exposed hydrophobic groups to SPI, and formed complexes through non-covalent interactions to improve the stability of the complexes. Furthermore, the emulsion gels based on the emulsions exhibited that CA formed emulsion-filled gels with higher elasticity, stronger gel strength, and thermal reversibility, whereas GA formed emulsion-aggregated gels with higher viscosity, and a weak-gel network. The results of digestion showed that, CA was more helpful to slow down the release of free fatty acids and protect vitamin E during digestion. Compared with SPI-GA emulsion gel, SPI-CA emulsion gel had better physicochemical properties and stronger network structure. The results of this study may be useful in the development of anionic polysaccharides that interact with SPI, and they may provide new insights on the preparation of emulsion gels that slowly release fat-soluble nutrients.

Urban green space serves as an important restorative environment for alleviating the physiological and psychological stress of residents, results which are primarily achieved through visual perception. However, air pollution results in decreased visibility, affects visual perception, and thus redues the positive effects of the experience of using the green space environment.There is a limited number of related studies. Therefore, based on the Stress Reduction Theory (SRT), this study constructed 12 groups of green space environments with different degrees of visibility and compared the physiological (SCL, α-EEG / β-EEG) and psychological (TMD) restorative effects of the participants in different environments by using photo elicitation. Combined with the perception and preference of green space, the impact of air pollution on the restoration received from the environment was explored. The results show that: (1) Visibility and green space type can affect the level of green space recovery. When the visibility is poor, the semi-open and semi-closed green spaces resulted in the best recovery; (2) When the visibility is reduced, the participants' perception of the eight types of Perceived Sensory Dimensions (PSDs) is generally reduced, and the type of green space is related to the perception of air quality; (3) As visibility decreased, participants' preference for green spaces significantly decreased; and (4) Visibility will affect green space perception and preference, thus affecting its recovery. This study provides a basis and reference for the design and construction of a higher quality restorative green space environment to effectively account for air pollution problems.

Abstract Gene therapies provide treatment options for many diseases, but the safe and long-term control of therapeutic transgene expression remains a primary issue for clinical applications. Here, we develop a muscone-induced transgene system packaged into adeno-associated virus (AAV) vectors (AAVMUSE) based on a G protein-coupled murine olfactory receptor (MOR215-1) and a synthetic cAMP-responsive promoter (PCRE). Upon exposure to the trigger, muscone binds to MOR215-1 and activates the cAMP signaling pathway to initiate transgene expression. AAVMUSE enables remote, muscone dose- and exposure-time-dependent control of luciferase expression in the livers or lungs of mice for at least 20 weeks. Moreover, we apply this AAVMUSE to treat two chronic inflammatory diseases: nonalcoholic fatty liver disease (NAFLD) and allergic asthma, showing that inhalation of muscone—after only one injection of AAVMUSE—can achieve long-term controllable expression of therapeutic proteins (ΔhFGF21 or ΔmIL-4). Our odorant-molecule-controlled system can advance gene-based precision therapies for human diseases.

Abstract Purpose The status of hormone receptors (HR) is an independent factor affecting survival and chemotherapy sensitivity in breast cancer (BC) patients, with estrogen receptor (ER) and progesterone receptor (PR) having the most significant effects. The ER-/PR + phenotype has been controversial in BC, and experts will face many challenges in determining treatment strategies. Herein, we systematically analyzed the clinicopathological characteristics of the ER-/PR + phenotype in BC patients and the response to chemotherapy. Patients and methods We included two cohorts. The first cohort counted the relationship between clinicopathologic data and survival outcomes for 72,666 female patients in the Surveillance, Epidemiology, and End Results (SEER) database. The second cohort analyzed the relationship between clinicopathological data and pathologic complete response (pCR) rate in 879 patients at the Harbin Medical University Cancer Hospital. The classification data were compared by the chi-square test and Fister's exact test of the Logistic regression model, and predictor variables with P

Abstract Current guidelines give priority to surgical treatment of carotid artery stenosis (CAS) before coronary artery bypass grafting (CABG), especially in symptomatic patients. Carotid artery stenting is an alternative treatment for narrowing of the carotid arteries. This study sought to demonstrate the role of severe CAS in predicting stroke after CABG and assess the efficacy of carotid artery stenting in preventing postoperative stroke in a Chinese cohort. From 2015 to 2021, 1799 consecutive patients undergoing isolated CABG surgery were retrospectively recruited in a Chinese cohort. The predictive value of severe CAS in postoperative stroke and carotid stenting in preventing postoperative stroke was statistically analyzed. The incidence of postoperative stroke was 1.67%. The incidence of CAS with stenosis ≥ 50% and ≥ 70% was 19.2% and 6.9%. After propensity matching, the incidence of stroke was 8.0% in the severe CAS group and 0% in the non-severe CAS group. We successfully established an optimal predictive nomogram for predicting severe CAS in patients undergoing CABG. Carotid artery stenting was found ineffective in preventing postoperative stroke. The present study provides the incidence of CAS and postoperative stroke in a Chinese cohort, identifies severe CAS as an independent risk factor for postoperative stroke after CABG, constructs a nomogram predicting the incidence of severe CAS, and evaluates the effectiveness of carotid artery stenting in preventing postoperative stroke after CABG.

Defining the structure and evolution of multi-trend faults is critical for analyzing the accumulation of hydrocarbons in buried hills. Based on high-resolution seismic and drilling data, the structural characteristics and evolutionary mechanism of multi-trend faults were investigated in detail through the structural analysis theory and quantitative calculations of fault activity, allowing us to determine the implication that fault evolution exerts on hydrocarbon accumulation in the BZ19-6 buried hill. There are four kinds of strike faults developed on the buried hill: SN-, NNE-, NE–ENE-, and nearly EW-trending, which experienced the Mesozoic Indosinian, Yanshan, and Cenozoic Himalayan tectonic movements. During the Indosinian, the BZ19-6 was in a SN-oriented compressional setting, with active faults composed of SN-trending strike-slip faults (west branch of the Tanlu fault zone) and near EW-trending thrust faults (Zhang-peng fault zone). During the Yanshanian, the NNE-trending normal faults were formed under the WNW–ESE tensile stress field. Since the Himalayan period, the BZ19-6 buried hill has evolved into the rifting stage. In rifting stage Ⅰ, all of the multi-trend pre-existing faults were reactivated, and the EW-trending thrust faults became normal faults due to negative inversion. In rifting stage II, a large number of NE–ENE-trending normal faults were newly formed in the NW–SE-oriented extensional setting, which made the structure pattern more complicated. In rifting stage III, the buried hill entered the post-rift stage, with only part of the NNE- and NE–ENE-trending faults continuously active. Multi-trend faults are the result of the combination of various multi-phase stress fields and pre-existing structures, which have great influence on the formation of tectonic fractures and then control the distribution of high-quality reservoirs in buried hills. The fractures controlled by the NNE- and EW-trending faults have higher density and scale, and fractures controlled by NE–ENE trending faults have stronger connectivity and effectiveness. The superposition of multi-trend faults is the favorable distribution of high-quality reservoirs and the favorable accumulation area of hydrocarbon.

In 2015, the Japanese public broadcaster NHK aired an educational series that re-examined traditional fairy tales by putting their characters on trial for their immoral behavior, such as revenge, violence, and dishonesty. These tales, rooted in premodern Japanese folklore, were widely available in various book formats by the late nineteenth century and, unlike modern adaptations, they did not sanitize violence or evil. This study analyzes four miniature picture books from the late nineteenth century that recount the story, Kachikachi yama (The Crackling Mountain). This analysis focuses on both verbal and visual representations of good and evil, with attention to themes of loyalty, filial piety, and virtuous revenge. The findings reveal that these picture books presented young readers with complex moral lessons, where the boundaries between good and evil were blurred. Additionally, they illuminate the prevailing image of children during that era, depicting them as “little adults” expected to be educated and prepared for the practical realities of the adult world.

The safety of chemical processes is of critical importance. However, traditional fault monitoring methods have insufficiently studied the monitoring accuracy of multi-channel data and have not adequately considered the impact of noise on industrial processes. To address this issue, this paper proposes a neural network-based model, DSCBAM-DenseNet, which integrates depthwise separable convolution and attention modules to fuse multi-channel data features and enhance the model’s noise resistance. We simulated a real environment by adding Gaussian noise with different signal-to-noise ratios to the Tennessee Eastman process dataset and trained the model using multi-channel data. The experimental results show that this model outperforms traditional models in both fault diagnosis accuracy and noise resistance. Further research on a compressor unit engineering instance validated the superiority of the model.

Periprosthetic osteolysis (PPO) is the most common cause of joint arthroplasty failure. Its progression involves both biological and mechanical factors. Osteoclastogenesis induced by wear from debris-cell interactions, ultimately leading to excessive bone erosion, is considered the primary cause of PPO; therefore, targeting osteoclasts is a promising treatment approach. Currently available drugs have various side effects and limitations. Artemisinic acid (ArA) is a sesquiterpene isolated from the traditional herb Artemisia annua L. that has various pharmacological effects, such as antimalarial, anti-inflammatory, and antioxidant activities. Therefore, this study was aimed at investigating the effect of ArA on osteoclast formation and bone resorption function in vitro, as well as wear particle-induced osteolysis in vivo, and to explore its molecular mechanism of action. Here, we report that ArA inhibits RANKL-stimulated osteoclast formation and function. Mechanistically, ArA suppresses intracellular reactive oxygen species levels by activating the antioxidant response via nuclear factor erythroid-2-related factor 2 (Nrf2) pathway upregulation. It also inhibits the mitogen-activated kinases (MAPK) and nuclear factor-κB (NF-κB) pathways, as well as the transcription and expression of NFATc1 and c-Fos. In vivo experiments demonstrated that ArA reduces osteoclast formation and alleviates titanium particle-induced calvarial osteolysis. Collectively, our study highlights that ArA, with its osteoprotective and antioxidant effects, is a promising therapeutic agent for preventing and treating PPO and other osteoclast-mediated osteolytic diseases.

Deformable registration plays a fundamental and crucial role in scenarios such as surgical navigation and image-assisted analysis. While deformable registration methods based on unsupervised learning have shown remarkable success in predicting displacement fields with high accuracy, many existing registration networks are limited by the lack of multi-scale analysis, restricting comprehensive utilization of global and local features in the images. To address this limitation, we propose a novel registration network called multi-scale feature extraction-integration network (MF-Net). First, we propose a multiscale analysis strategy that enables the model to capture global and local semantic information in the image, thus facilitating accurate texture and detail registration. Additionally, we introduce grouped gated inception block (GI-Block) as the basic unit of the feature extractor, enabling the feature extractor to selectively extract quantitative features from images at various resolutions. Comparative experiments demonstrate the superior accuracy of our approach over existing methods.

As ferroelectric materials, lithium tantalate and lithium niobate share similar material characteristics, such as a high Pockels effect and nonlinear optical coefficients. When compared to lithium niobate, lithium tantalate offers a higher optical damage threshold, a broader transparent window, and lower birefringence, making it a promising candidate for high-performance electro-optical photonic integrated devices. In this study, we design and successfully fabricate micro-ring resonators on an acoustic-grade lithium-tantalate-on-insulator wafer, demonstrating their tunability and dynamic modulation capabilities. Experimental results indicate that the achieved thin-film lithium tantalate based micro-ring resonator exhibits an intrinsic Q-factor of 8.4 × 105, corresponding to a waveguide propagation loss of 0.47 dB/cm and a tuning efficiency of 1.94 pm/V. More importantly, as compared to those based on thin-film lithium niobate, a much weaker photorefractive effect and drift phenomenon around the 1550 nm wavelength under a direct-current drive are observed in the present fabricated thin-film lithium tantalate micro-rings with a silicon oxide over-cladding and a tuning electrode on top.

BackgroundBladder cancer stands as the predominant malignant tumor in the urological system, presenting a significant challenge to public health and garnering extensive attention. Recently, with the deepening research into tumor molecular mechanisms, non-coding RNAs (ncRNAs) have emerged as potential biomarkers offering guidance for the diagnosis and prognosis of bladder cancer. However, the definitive role of ncRNAs in bladder cancer remains unclear. Hence, this study aims to elucidate the relevance and significance of ncRNAs through a Meta-analysis.MethodsA systematic meta-analysis was executed, including studies evaluating the diagnostic performance of ncRNAs and their associations with overall survival (OS) and disease-free survival (DFS). Key metrics such as hazard ratios, sensitivity, specificity, and diagnostic odds ratios were extracted and pooled from these studies. Potential publication bias was assessed using Deeks’ funnel plot, and the robustness of the results was ascertained through a sensitivity analysis.ResultsElevated ncRNA expression showed a positive correlation with improved OS, evidenced by a hazard ratio (HR) of 0.82 (95% CI: 0.66-0.96, P

Neutrophil infiltration has been linked to worse clinical outcomes after ischemic stroke. Microglia, a key type of immune-competent cell, engage in cross-talk with the infiltrating immune cells in the inflamed brain area, yet the molecular mechanisms involved remain largely unexplored. In this study, we investigated the mechanisms of how canonical transient receptor potential 1 (TRPC1) modulated neutrophil infiltration in male mouse cerebral ischemia and reperfusion injury (CIRI) models. Our findings revealed a notable upregulation of TRPC1 in microglia within both middle cerebral artery occlusion reperfusion (MCAO/R) and in vitro oxygen-glucose deprivation/regeneration (OGD/R) model. Conditional Trpc1 knockdown in microglia markedly reduced infarct volumes and alleviated neurological deficits. Microglia conditional Trpc1 knockdown mice displayed less neutrophil infiltration in peri-infarct area. Trpc1 knockdown microglia exhibited a reduced primed proinflammatory phenotype with less secretion of CC-Chemokines ligand (CCL) 5 and CCL2 after MCAO/R. Blocking CCL5/2 significantly mitigated neutrophil infiltration in microglia/neutrophil transwell co-culture system upon OGD/R condition. Trpc1 knockdown markedly reduced store-operated calcium entry and nuclear factor of activated T-cells c1 (NFATc1) level in OGD/R treated microglia. Overexpression of Nfatc1 reversed the CCL5/2 reducing effect of Trpc1 knockdown, which is mediated by small interfering RNA in BV2 cells upon OGD/R. Our data indicate that upregulation of TRPC1 in microglia stimulates the production of CCL5/2 through the Ca2+/NFATc1 pathway. Upregulated CCL5/2 leads to an increase in neutrophil infiltration into the brain, thereby aggravating reperfusion injury. Our results demonstrate the importance of TRPC1 in microglia-mediated neuroinflammation and suggest a potential means for reducing CIRI induced neurological injury.

The trade-off between strength and ductility is a prevalent issue in strengthening commercially pure titanium (CP–Ti). This study presents a method to prepare ultra-high strength Ti–N alloys with adequate ductility using ball-milling (BM) and spark plasma sintering (SPS) techniques, based on nitrogen solid solution and grain refinement strengthening. The effect of ball milling time of mixed powders on mechanical properties of Ti–N alloys was studied systematically. Quantitative analysis reveals that solid solution strengthening and grain refinement strengthening worked synergistically to enhance yield strength of alloys. The Ti–N alloys with the most favorable mechanical properties demonstrated a yield strength of 1606 MPa and a compressive plastic strain of 14.44 %. The development of novel Ti–N alloys provides a viable strategy for the advancement of high-performance titanium alloys using ubiquitous elements.

Abstract The combined effect of obesity and metabolic abnormalities on liver injury is unclear. Aiming to address this knowledge gap, this cross-sectional study was conducted among 16,201 US adults. Multiple linear regression and logistic regression analyses were conducted to assess the associations of obesity profiles, metabolic health status, and weight change with the levels of liver enzymes. The analysis revealed that general obesity and abdominal obesity were positively associated with the levels of liver enzymes and the prevalence of abnormal liver enzymes (P and P trend

The rapid development of the mariculture industry has been hindered by limited coastal aquaculture space. To utilize the abundant inland saline–alkaline water, we studied the physiological effects of high carbonate alkalinity stress and high pH stress on Fenneropenaeus chinensis. The study employed quantitative proteomics by tandem mass tag (TMT) and non-targeted metabolomics analysis using a liquid chromatograph mass spectrometer (LC-MS) to understand the physiological and biochemical adaptive mechanisms of the hepatopancreas of F. chinensis in response to saline–alkaline stress at the molecular level. We designed two stress groups as follows: a high carbonate alkalinity (CA) group and a combined high carbonate alkalinity and high pH (CP) group. The study found that the protein and metabolic profiles of the two stress groups were changed, and the CP group, which was exposed to dual stresses, incurred more severe damage to the hepatopancreas compared to that of the CA group. After exposure to CA and CP, the hepatopancreas of F. chinensis showed significant alterations in 455 proteins and 50 metabolites, and 1988 proteins and 272 metabolites, respectively. In addition, F. chinensis upregulated the level of energy metabolism in the hepatopancreas to defend against osmotic imbalance caused by CA or CP stress, which was demonstrated by the significant upregulation of important proteins and metabolites in glycolysis, pyruvate metabolism, TCA cycle, and fatty acid oxidation. Additionally, pattern recognition receptors, the phenol oxidase system, and various immune-related metabolic enzymes and metabolites were also affected. The immune homeostasis of F. chinensis was affected by the alteration of the antioxidant system following exposure to CA or CP. These findings provide valuable information for F. chinensis saline–alkaline water cultivation practices.

Metabolomics has been used extensively to identify crucial molecules and biochemical effects induced by environmental factors. To understand the effects of acute low-salinity stress on Fenneropenaeus chinensis, intestinal histological examination and untargeted metabonomic analysis of F. chinensis were performed after exposure to a salinity of 15 ppt for 3, 7, and 14 d. The histological examination revealed that acute stress resulted in most epithelial cells rupturing, leading to the dispersion of nuclei in the intestinal lumen after 14 days. Metabolomics analysis identified numerous differentially expressed metabolites (DEMs) at different time points after exposure to low-salinity stress, in which some DEMs were steadily downregulated at the early stage of stress and then gradually upregulated. We further screened 14 overlapping DEMs, in which other DEMs decreased significantly during low-salinity stress, apart from L-palmitoylcarnitine and vitamin A, with enrichments in phenylalanine, tyrosine and tryptophan biosynthesis, fatty acid and retinol metabolism, and ABC transporters. ABC transporters exhibit significant abnormalities and play a vital role in low-salinity stress. This study provides valuable insights into the molecular mechanisms underlying the responses of F. chinensis to acute salinity stress.

The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.

Hydrozoans are numerically dominant taxa in gelatinous zooplankton communities of the worldwide oceans and play an energy transfer role connecting primary producers and higher trophic level organisms. In the western subarctic Pacific, St. K2 has been established as a long-term time-series monitoring station. Various studies on zooplankton have been conducted, while hydrozoans have not been treated. This study presents the abundance, vertical distribution, and population structure of the dominant hydrozoan species (Aglantha digitale) at St. K2. Samples collected by vertical stratification samplings from eight layers of 0–1000 m both day and night during four seasons in one year. Hydrozoans occur throughout the year. The annual mean abundance of A. digitale was 198.4 ind. m−2 and composed of 91.9% of hydrozoans. The vertical distribution of A. digitale was concentrated for the epipelagic layer (0–200 m), both day and night of the most season. The bell height (BH) of A. digitale ranged between 2.4–18.9 mm. Most of the mature individuals, with gonad length larger than 10% of BH, occurred only in July. The BH of mature individuals ranged from 4.7 to 17.6 mm, with the BH of most mature individuals were larger than >10 mm. Through observation on BH at each sampling layer, small individuals with BH < 6 mm were distributed below 300 m depths throughout the seasons, expanding their vertical distribution to the deeper layers. Inter-region comparison of abundance, maturation body size, and generation length of A. digitale revealed that these parameters are varied with the region and depend on the marine ecosystem structures.

Abstract Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.

In clinical practice and research, the classification and diagnosis of neurological diseases such as Parkinson’s Disease (PD) and Multiple System Atrophy (MSA) have long posed a significant challenge. Currently, deep learning, as a cutting-edge technology, has demonstrated immense potential in computer-aided diagnosis of PD and MSA. However, existing methods rely heavily on manually selecting key feature slices and segmenting regions of interest. This not only increases subjectivity and complexity in the classification process but also limits the model’s comprehensive analysis of global data features. To address this issue, this paper proposes a novel 3D context-aware modeling framework, named 3D-CAM. It considers 3D contextual information based on an attention mechanism. The framework, utilizing a 2D slicing-based strategy, innovatively integrates a Contextual Information Module and a Location Filtering Module. The Contextual Information Module can be applied to feature maps at any layer, effectively combining features from adjacent slices and utilizing an attention mechanism to focus on crucial features. The Location Filtering Module, on the other hand, is employed in the post-processing phase to filter significant slice segments of classification features. By employing this method in the fully automated classification of PD and MSA, an accuracy of 85.71%, a recall rate of 86.36%, and a precision of 90.48% were achieved. These results not only demonstrates potential for clinical applications, but also provides a novel perspective for medical image diagnosis, thereby offering robust support for accurate diagnosis of neurological diseases.

ABSTRACT The tea green leafhopper, Matsumurasca onukii Matsuda, is the most destructive insect pest of tea plantations in East Asia. While several microbes in M. onukii have been characterized, the microbial community compositions in wild M. onukii populations and the environmental factors that shape them are mostly unknown. In this study, M. onukii populations were collected from major tea growing regions in China. Following high-throughput sequencing of 16S rRNA gene fragments for bacteria and the internal transcribed spacer region for fungi, association analyses were performed within the microbial communities associated with M. onukii and their environmental drivers. We found that the bacterial community structures differed in various regions, and the abundance of dominant bacteria such as Wolbachia, Pseudomonas, Acinetobacter, Pantoea, Enterobacter, and Methylobacterium varied widely. Moreover, wild populations of M. onukii can be infected with facultative symbionts from six genera (Wolbachia, Rickettsia, Asaia, Serratia, Arsenophonus, and Cardinium) with divergent relative abundances. Correlation analysis indicated that altitude was a key environmental factor that shaped bacterial communities of M. onukii. Furthermore, longitude, temperature, and rainfall are also significantly correlated with the bacterial communities. The fungal communities of M. onukii populations were dominated by Ascomycota and Basidiomycota, of which most genera are considered to be plant endophytes or plant pathogens, such as Cladosporium, Fusarium, Alternaria, and Gibberella. We demonstrated that M. onukii carry a complex and variable microbial community, which is influenced by altitude as well as climate-related factors. Our results provide novel insights into the bacteria and fungi of M. onukii. IMPORTANCE Host-associated microbial communities play an important role in the fitness of insect hosts. However, the factors shaping microbial communities in wild populations, including environmental factors and interactions among microbial species, remain largely unknown. The tea green leafhopper has a wide geographical distribution and is highly adaptable, providing a suitable model for studying the effect of ecological drivers on microbiomes. This is the first large-scale culture-independent study investigating the microbial communities of M. onukii sampled from different locations. Altitude as a key environmental factor may have shaped microbial communities of M. onukii by affecting the relative abundance of endosymbionts, especially Wolbachia. The results of this study, therefore, offer not only an in-depth view of the microbial diversity of this species but also an insight into the influence of environmental factors.

Pain interventional therapy, known as the most promising medical technology in the 21st century, refers to clinical treatment technology based on neuroanatomy, neuroimaging, and nerve block technology to treat pain diseases. Compared with traditional destructive surgery, interventional pain therapy is considered a better and more economical choice of treatment. In recent years, a variety of minimally invasive pain interventional therapy techniques, such as neuroregulation, spinal cord electrical stimulation, intervertebral disc ablation, and intrasheath drug infusion systems, have provided effective solutions for the treatment of patients with post-herpetic neuralgia, complex regional pain syndrome, cervical/lumbar disc herniation, and refractory cancer pain.

To overcome the challenges of inadequate representation and ineffective information exchange stemming from feature homogenization in underwater acoustic target recognition, we introduce a hybrid network named Mobile_ViT, which synergizes MobileNet and Transformer architectures. The network begins with a convolutional backbone incorporating an embedded coordinate attention mechanism to enhance the local details of inputs. This mechanism captures the long-term temporal dependencies and precise frequency–domain relationships of signals, focusing the features on the time–frequency positions. Subsequently, the Transformer’s Encoder is integrated at the end of the backbone to facilitate global characterization, thus effectively overcoming the convolutional neural network’s shortcomings in capturing long-range feature dependencies. Evaluation on the Shipsear and DeepShip datasets yields accuracies of 98.50% and 94.57%, respectively, marking a substantial improvement over the baseline. Notably, the proposed method also demonstrates obvious separation coefficients, signifying enhanced clustering effectiveness, and is lighter than other Transformers.

It is well known that the hippocampus is a vital brain region playing a key role in both episodic and spatial memory. Insulin receptors (InsRs) are densely distributed in the hippocampus and are important for its function. However, the effects of InsRs on the function of the specific hippocampal cell types remain elusive. In this study, hippocampal InsRs knockout mice had impaired episodic and spatial memory. GABAergic neurons and glutamatergic neurons in the hippocampus are involved in the balance between excitatory and inhibitory (E/I) states and participate in the processes of episodic and spatial memory. InsRs are located mainly at excitatory neurons in the hippocampus, whereas 8.5% of InsRs are glutamic acid decarboxylase 2 (GAD2)::Ai9-positive (GABAergic) neurons. Next, we constructed a transgenic mouse system in which InsR expression was deleted from GABAergic (glutamate decarboxylase 2::InsR fl/fl , GAD2 Cre ::InsR fl/fl ) or glutamatergic neurons (vesicular glutamate transporter 2::InsR fl/fl ,Vglut2 Cre ::InsR fl/fl ). Our results showed that in comparison to the InsR fl/fl mice, both episodic and spatial memory were lower in GAD2 Cre ::InsR fl/fl and Vglut2 Cre ::InsR fl/fl . In addition, both GAD2 Cre ::InsR fl/fl and Vglut2 Cre ::InsR fl/fl were associated with more anxiety and lower glucose tolerance. These findings reveal that hippocampal InsRs might be crucial for episodic and spatial memory through E/I balance hippocampal regulation.

Within urban green spaces, spontaneous groundcovers, as potential alternatives for traditional lawns, have garnered attention due to their ecological adaptability. However, little attention has been paid to whether spontaneous groundcovers can serve as suitable replacements for lawns in terms of the aesthetic values and human preferences for each. Based on questionnaires accompanied by photo elicitation, this study explored the perceptions of and preferences for seven kinds of lawns and six kinds of spontaneous groundcovers in China. The effects of social backgrounds on people’s perceptions of and preferences for ground covers were also analyzed. The results indicated a general equivalence in preferences for the lawn and spontaneous groundcover. The Taraxacum mongolicum – Cynodon dactylon – Conyza canadensis community was significantly preferred most among all of the selected ground covers. Spontaneous groundcovers were regarded as more natural, wild, variable, and species-richer compared to lawns, while lawns were perceived as better kept than spontaneous groundcovers. Ground covers were preferred which were perceived to have high ecological aesthetic value and low wildness. Industry and attention to herbaceous plants mostly affected human perceptions and preferences among the social background factors, and gender, age, education level, and occupation also had significant effects. The results thus provide the support for the application of spontaneous groundcovers in moderately developed cities, but such application should consider the comprehensive development of ecological aesthetic value and the applicability of different groups of residents.

Perivascular adipose tissue and the vessel wall are connected through intricate bidirectional paracrine and vascular secretory signaling pathways. The secretion of inflammatory factors and oxidative products by the vessel wall in the diseased segment has the ability to influence the phenotype of perivascular adipocytes. Additionally, the secretion of adipokines by perivascular adipose tissue exacerbates the inflammatory response in the diseased vessel wall. Therefore, quantitative and qualitative studies of perivascular adipose tissue are of great value in the context of vascular inflammation and may provide a reference for the assessment of cardiovascular ischemic disease.

There is a continuing need for artificial bone substitutes for bone repair and reconstruction, Magnesium phosphate bone cement (MPC) has exceptional degradable properties and exhibits promising biocompatibility. However, its mechanical strength needs improved and its low osteo-inductive potential limits its therapeutic application in bone regeneration. We functionally modified MPC by using a polymeric carboxymethyl chitosan-sodium alginate (CMCS/SA) gel network. This had the advantages of: improved compressive strength, ease of handling, and an optimized interface for bioactive bone in-growth. The new composites with 2% CMCS/SA showed the most favorable physicochemical properties, including mechanical strength, wash-out resistance, setting time, injectable time and heat release. Biologically, the composite promoted the attachment and proliferation of osteoblast cells. It was also found to induce osteogenic differentiation in vitro, as verified by expression of osteogenic markers. In terms of molecular mechanisms, data showed that new bone cement activated the Wnt pathway through inhibition of the phosphorylation of β-catenin, which is dependent on focal adhesion kinase. Through micro-computed tomography and histological analysis, we found that the MPC-CMCS/SA scaffolds, compared with MPC alone, showed increased bone regeneration in a rat calvarial defect model. Overall, our study suggested that the novel composite had potential to help repair critical bone defects in clinical practice.

Multimodal matching remains a difficult and pressing problem in the imaging processing community. Accurate and robust multimodal matching is important for the performance of applications, such as registration and fusion. Traditional image matching algorithms cannot effectively handle multimodal images with severe nonlinear radiometric distortion (NRD). In this article, a novel multiscale template matching algorithm for multimodal image matching is proposed to address this problem. We propose a novel frequency-domain convolutional map based on the wavelet transform and phase congruency to construct a feature description map that significantly reduces the NRD between multimodal images. The development of omnidirectional aggregated feature vectors with rotational invariance also helped to achieve robustness on rotated images. Finally, a multiscale template matching strategy improved the matching performance on multimodal images with displacement and scale variations. To improve the time efficiency of the algorithm, most of the complex computations in this article are performed in the frequency domain. According to the experimental findings on six multimodal image datasets, the method can obtain accurate and robust matching results between multimodal images. Through qualitative and quantitative evaluations, the method outperforms several mainstream multimodal image matching algorithms in terms of matching accuracy, success rate, and time consumption.

Smart agriculture utilizes a variety of advanced technologies to promote sustainable agriculture and provide solutions for intelligent, automated and unmanned agriculture. Agricultural robots and related technologies are an important part of smart agriculture, while autonomous navigation is a core function of autonomous agricultural robots, which rely on information about the distance of obstacles in a scene to support decision making. In this paper, we propose a ground point geometric ranging model, which can be used in camera height dynamic change scenarios, and the method is validated by model derivation and hypothesis testing. The model combines ranging and camera calibration, choosing to compensate for distortion and defocus phenomena caused by nonlinear imaging of the camera to the focal length, and completes the parameter calibration using a small amount of ground point real distance data. In this paper, the YOLOv8 model is used to identify and range outdoor cattle, and the experimental results show that the lowest range accuracy of this method reaches 95%, this method eliminates the dependence on camera height for focal calibration in ranging models, and in practice requires only once focal calibration for permanent use, achieving a significant reduction in the complexity of focal calibration, and the migrability of the model in scenarios where the camera height changes.

Accidents involving electric vehicle fires have increased as the number of electric vehicles has grown recently. The issue of charging safety is a key barrier to the growth of the electric vehicle sector because these accidents have resulted in large financial losses for car owners and charging facility operators. The approach for resolving the issue of electric car charging safety through an electric vehicle charging safety warning system is suggested in this research. The suggested solution uses an adaptive optimization of long short-term memory neural network (A-LSTM) to forecast voltage changes throughout the whole charging process by using the vehicle’s daily historical charging data. The warning threshold adjustment method is established by the difference between the predicted voltage data and the actual voltage data, which is dynamically adjusted as the charging process progresses. Finally, a real-time warning model for vehicle charging alert is developed. The daily charging data of electric vehicles is used in the paper to verify the precision of data prediction and the accuracy and timeliness of the model. The study’s findings demonstrate that the early warning model suggested in this paper can quickly send out early warning signals to safeguard the safety of car charging and can identify aberrant charging data.

Considering that the centralized optimization control strategy is difficult to adapt to the access of large-scale electric vehicles, a distributed collaborative control strategy based on consensus algorithm is proposed in this paper to control the operation of multiple charging stations. In order to reduce the computational cost, a charging station aggregation model is established to reduce the optimization variables of large-scale electric vehicle access. According to the dispatching instructions issued by the distribution network, this method takes the economic operation of charging stations as the goal, satisfies the global and local constraints, and realizes the power allocation among charging stations. The case analysis proves the accuracy, effectiveness and robustness of the method, and the adaptability to large-scale electric vehicle access.

Nanozyme has been one of the most promising artificial enzymes for substitute natural enzymes. The main research focus in this field is developing the nanozymes with high activity, sensitivity and stability. In this paper, prussian blue/polyacrylonitrile (PB/PAN) composite nanofiber was prepared by electrospinning which was calcined to obtain iron oxide/carbon (FeOx/C) composite nanozyme. The structure of the prepared FeOx/C nanozyme was characterized by scanning electron microscopy (SEM), X-ray diffractometer (XRD), Energy dispersive spectrometer (EDS) and X-ray photoelectron spectra (XPS). The results revealed that FeOx/C nanozyme containing the catalytic active species of γ-Fe2O3 possessed peroxidase-like catalytic activity. The catalytic activity of prepared nanozyme which was influenced by different content of PB and different calcination temperatures was investigated. The optimal PB content in the PB/PAN nanofiber and calcination temperature were 41.5% and 600 °C in this research. The prepared FeOx/C nanozyme possessed highly sensitive detection of ascorbic acid. This research provides a new approach to fabricate iron oxide/carbon composite nanozyme with highly catalytic activity and sensitive for colorimetric sensor.

Abstract Background Our understanding of the physiological responses of rice inflorescence (panicle) to environmental stresses is limited by the challenge of accurately determining panicle photosynthetic parameters and their impact on grain yield. This is primarily due to the lack of a suitable gas exchange methodology for panicles and non-destructive methods to accurately determine panicle surface area. Results To address these challenges, we have developed a custom panicle gas exchange cylinder compatible with the LiCor 6800 Infra-red Gas Analyzer. Accurate surface area measurements were determined using 3D panicle imaging to normalize the panicle-level photosynthetic measurements. We observed differential responses in both panicle and flag leaf for two temperate Japonica rice genotypes (accessions TEJ-1 and TEJ-2) exposed to heat stress during early grain filling. There was a notable divergence in the relative photosynthetic contribution of flag leaf and panicles for the heat-tolerant genotype (TEJ-2) compared to the sensitive genotype (TEJ-1). Conclusion The novelty of this method is the non-destructive and accurate determination of panicle area and photosynthetic parameters, enabling researchers to monitor temporal changes in panicle physiology during the reproductive development. The method is useful for panicle-level measurements under diverse environmental stresses and is sensitive enough to evaluate genotypic variation for panicle physiology and architecture in cereals with compact inflorescences.