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This article established a rapid detection method for 34 pesticides in vegetables by combining QuEChERS purification method with high-performance liquid chromatography triple quadrupole linear ion trap tandem mass spectrometry. The samples were extracted with acetonitrile (containing 1% acetic acid), 1.5 g sodium acetate, 4 g anhydrous magnesium sulfate, and 1 g sodium chloride. The extract was further purified using 20 mg graphitized carbon black (GCB), 300 mg primary secondary amine (PSA), 200 mg octadecylsilane chemically bonded silica (C18), and 1000 mg MgSO4. Acetonitrile-water was chosen as mobile phase. The samples were analyzed using MRM-IDA-EPI mode, and an EPI database was established. Qualitative analysis was performed based on retention time, ion pair peak ratio, and EPI database, and quantification was carried out using matrix-matched external standard method. The study results indicated that using eggplant, garlic chives, cowpea, and spinach as representative matrices, the 34 pesticides showed good linear correlation with R2≥0.99011. The detection limits ranged from 0.16 to 1.81 μg/kg, and the quantification limits ranged from 0.52 to 6.02 μg/kg. The spiked recoveries of the samples were between 73.51% and 118.77%, and the precision was in the range of 0.01% to 14.27%. Vegetable samples were tested, with a detection rate of 58.23% for thiamethoxam. This method was characterized by its rapid and effective detection, simple operation, accurate data, and high sensitivity, making it suitable for the detection of 34 pesticides in vegetables.

Abstract Background Increasing evidence shows the pivotal significance of miRNAs in the pathogenesis of osteoporosis. miR-381-3p has been identified as an inhibitor of osteogenesis. This study explored the role and mechanism of miR-381-3p in postmenopausal osteoporosis (PMOP), the most common type of osteoporosis. Methods Bilateral ovariectomy (OVX) rat model was established and miR-381-3p antagomir was administrated through the tail vein in vivo. The pathological changes in rats were assessed through the evaluation of serum bone turnover markers (BALP, PINP, and CTX-1), hematoxylin and eosin (H&E) staining, as well as the expression of osteoblast differentiation biomarkers. Moreover, isolated bone marrow mesenchymal stem cells from OVX-induced rats (OVX-BMMSCs) were utilized to explore the impact of miR-381-3p on osteoblast differentiation. In addition, the target gene and downstream pathway of miR-381-3p were further investigated both in vivo and in vitro. Results miR-381-3p expression was elevated, whereas KLF5 was suppressed in OVX rats. miR-381-3p antagomir decreased serum levels of bone turnover markers, improved trabecular separation, promoted osteoblast differentiation biomarker expression in OVX rats. ALP activity and mineralization were suppressed, and levels of osteoblast differentiation biomarkers were impeded after miR-381-3p overexpression during osteoblast differentiation of OVX-BMMSCs. While contrasting results were found after inhibition of miR-381-3p. miR-381-3p targets KLF5, negatively affecting its expression as well as its downstream Wnt/β-catenin pathway, both in vivo and in vitro. Silencing of KLF5 restored Wnt/β-catenin activation induced by miR-381-3p antagomir. Conclusion miR-381-3p aggravates PMOP by inhibiting osteogenic differentiation through targeting KLF5/Wnt/β-catenin pathway. miR-381-3p appears to be a promising candidate for therapeutic intervention in PMOP.

Abstract Background The minimally invasive approach for the treatment of displaced scapular neck or body fractures has the advantages of less trauma and minimal muscle dissection. In clinical practice, the minimally invasive approach combined with an anatomical locking plate has been used to treat scapular body fractures. In addition, we have made minor modifications to the minimally invasive approach. However, the biomechanical study about the approach combined with an anatomical locking plate in treating scapular body fractures was limited. Methods Finite element analysis (FEA) was used to conduct the biomechanical comparison between the anatomical locking plate (AP model) and reconstructive plate (RP model) in the treatment of scapular body fractures through the modified minimally invasive approach. A healthy male volunteer with no history of scapula or systemic diseases was recruited. High-resolution computed tomography images of his right scapula were obtained. Two scapula models were constructed and analyzed by the software of Mimics 21.0, Geomagic Wrap 2021, SolidWorks 2021, and ANSYS Workbench 2022, respectively. Results Through static structural analysis, in terms of equivalent von Mises stress, equivalent elastic strain, and total deformation, the AP model exhibited superior safety characteristics, enhanced flexibility, and anticipated stability compared with the RP model. This was evidenced by lower maximum stress, lower maximum strain and displacement. Conclusion The minimally invasive approach combined with an anatomical locking plate for scapular body fractures had better biomechanical stability. The study provided a biomechanical basis to guide the clinical treatment of scapular body fractures.

Abstract Spinal cord injury (SCI) is a serious traumatic disease of the central nervous system and leads to incomplete or complete loss of the body’s autonomous motor and sensory functions, seriously endangering human health. Recently, exosomes have been proposed as important substances in cell-to-cell interactions. Mesenchymal stem cell (MSC)-derived exosomes exert good therapeutic effects and play a crucial role in neurological damage repair. However, the detailed mechanisms underlying their effects remain unknown. Herein, we found that compared to SCI rats, those subjected to umbilical cord MSC (UC-MSC)-derived exosomes injection showed an improved motor ability. Nevertheless, the transcriptome of BV2 microglia in different treatment groups indicated that the action pathway of exosomes might be the NF-κB/MAPK pathway. Additionally, exosomes from UC-MSCs could inhibit P38, JNK, ERK, and P65 phosphorylation in BV2 microglia and SCI rat tissues. Moreover, exosomes could inhibit apoptosis and inflammatory reaction and reactive oxygen species (ROS) production of BV2 microglia in vitro and in vivo. In conclusion, UC-MSCs-derived exosomes might protect SCI in rats by inhibiting inflammatory response via the NF-κB/MAPK signaling pathway, representing novel treatment targets or approaches for SCI.

With the rapid development of the automotive finance market in China, fraudulent behaviors present new characteristics such as intellectualization and high concealment. Graph neural networks and memory networks have strong capabilities for processing the textual data containing massive complex associations, providing a new perspective for fraud detection. During the operation of an automotive finance company, a large amount of credit review texts with recording the customers’ multidimensional data are accumulated. These texts contain information that is helpful for risk management, but have not been well explored. In order to effectively identify fraud risks, we propose a fraud detection method based on credit review texts with dual-channel memory network, which combines graph and text memory networks. By utilizing pre-trained language models, the text data for credit review text is encoded into semantic vectors. The graph memory network module and the text memory network module are then employed to extract graph features and text features corresponding to the credit review text. Finally, the generated results from the three modules are fused and input into a classification network to obtain the final determination of financial fraud risk. Comparative experiments with baseline models demonstrate the validity of our model in fraud detection.

The brain topology highly reflects the complex cognitive functions of the biological brain after million-years of evolution. Learning from these biological topologies is a smarter and easier way to achieve brain-like intelligence with features of efficiency, robustness, and flexibility. Here we proposed a brain topology-improved spiking neural network (BT-SNN) for efficient reinforcement learning. First, hundreds of biological topologies are generated and selected as subsets of the Allen mouse brain topology with the help of the Tanimoto hierarchical clustering algorithm, which has been widely used in analyzing key features of the brain connectome. Second, a few biological constraints are used to filter out three key topology candidates, including but not limited to the proportion of node functions (e.g., sensation, memory, and motor types) and network sparsity. Third, the network topology is integrated with the hybrid numerical solver-improved leaky-integrated and fire neurons. Fourth, the algorithm is then tuned with an evolutionary algorithm named adaptive random search instead of backpropagation to guide synaptic modifications without affecting raw key features of the topology. Fifth, under the test of four animal-survival-like RL tasks (i.e., dynamic controlling in Mujoco), the BT-SNN can achieve higher scores than not only counterpart SNN using random topology but also some classical ANNs (i.e., long-short-term memory and multi-layer perception). This result indicates that the research effort of incorporating biological topology and evolutionary learning rules has much in store for the future.

INTRODUCTION: The development of integrated energy systems (IES) is of paramount significance in addressing climate change and other challenges. Ensuring the rapid and accurate calculation of energy flow states is crucial for their efficient operation. However, the difference in response time of various heterogeneous energy flows in IES will lead to the inaccuracy of the steady-state model. OBJECTIVES: This paper proposes a model for multi-stage multi-energy flow IES of electricity, gas, and heat based on heterogeneous energy flow characteristics. Methods: IES was divided into fast variable networks and slow variable networks, and a multi-energy flow multi-stage model was established. Suitable models were matched for different subnets at different stages to improve the calculation accuracy. RESULTS: Selected a practical Electrical-Gas-Heat IES as a case study for simulation. Through case studies, the effectiveness and accuracy of the proposed method are demonstrated. CONCLUSION: The multi-stage model proposed in this paper can improve the accuracy of multi-energy flow in IES.

Abstract In recent years, China's automobile industry has undergone rapid development, creating new opportunities for the auto loan industry. Currently, auto financing companies are actively seeking to expand their cooperation with banks. Therefore, improving the approval rate and scale of joint loan business is of significant practical importance. In this paper, we propose a Stacking‐based financial institution risk approval model and select the optimal stacking model by comparing its performance with other models. Additionally, we construct a bank approval model using deep learning techniques on a biased data set, with feature extraction performed using convolution neural networks (CNN) and feature‐based counterfactual augmentation used for balanced sampling. Finally, we optimize the model of the prediction of auto finance companies by selecting the optimal coefficients of loss function based on the features and results of the bank approval model. The proposed approach leads to an approximately 6% increase in the joint loan approval rate on the actual data set, as demonstrated by experimental results.

Abstract Background N6-methyl adenosine (m6A) is the most common reversible mRNA modification in eukaryotes implicated in key roles in various biological processes. The purpose of our analysis was to examine the association of ankylosing spondylitis (AS) with m6A methylation. Method We obtained 72 samples from the data set GSE73754, including 52 AS patients and 20 healthy people. We divided the samples into two groups: the experimental group and the control group, and then observed the differences of 26 m6A related genes in the two groups. We also analyzed the correlation between different m6A genes. We used a random forest tree model to screen seven m6A signature genes associated with AS to evaluate its prevalence. Next, the samples were classified according to the m6a content and differential genes. Immune analysis, gene ontology, and KEGG enrichment analyses were performed. Finally, we scored each sample with m6a and analyzed the relationship between different samples and inflammation-related factors. Results and conclusion In conclusion, we screened out AS-related genes and the nomogram showed that they were negatively correlated with the incidence of AS. And we found that AS may have some relationship with immunity. Our analysis results could provide further insights into the treatment of AS.

IntroductionSpinal cord injury (SCI) is a profoundly disabling and devastating neurological condition, significantly impacting patients’ quality of life. It imposes unbearable psychological and economic pressure on both patients and their families, as well as placing a heavy burden on society.MethodsIn this study, we integrated datasets GSE5296 and GSE47681 as training groups, analyzed gene variances between sham group and SCI group mice, and conducted Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis based on the differentially expressed genes. Subsequently, we performed Weighted Gene Correlation Network Analysis (WGCNA) and Lasso regression analyses.ResultsWe identified four characteristic disease genes: Icam1, Ch25h, Plaur and Tm4sf1. We examined the relationship between SCI and immune cells, and validated the expression of the identified disease-related genes in SCI rats using PCR and immunohistochemistry experiments.DiscussionIn conclusion, we have identified and verified four genes related to SCI: Icam1, Ch25h, Plaur and Tm4sf1, which could offer insights for SCI treatment.

Abstract Background The harlequin ladybird Harmonia axyridis (Coleoptera: Coccinellidae), native to Asia, has been introduced to other major continents where it has caused serious negative impacts on local biodiversity. Though notable advances to understand its invasion success have been made during the past decade, especially with then newer molecular tools, the conclusions reached remain to be confirmed with more advanced genomic analyses and especially using more samples from larger geographical regions across the native range. Furthermore, although H. axyridis is one of the best studied invasive insect species with respect to life history traits (often comparing invasive and native populations), the traits responsible for its colonization success in non-native areas warrant more research. Results Our analyses of genome-wide nuclear population structure indicated that an eastern Chinese population could be the source of all non-native populations and revealed several putatively adaptive candidate genomic loci involved in body color variation, visual perception, and hemolymph synthesis. Our estimates of evolutionary history indicate (1) asymmetric migration with varying population sizes across its native and non-native range, (2) a recent admixture between eastern Chinese and American populations in Europe, (3) signatures of a large progressive, historical bottleneck in the common ancestors of both populations and smaller effective sizes of the non-native population, and (4) the southwest origin and subsequent dispersal routes within its native range in China. In addition, we found that while two mitochondrial haplotypes-Hap1 and Hap2 were dominant in the native range, Hap1 was the only dominant haplotype in the non-native range. Our laboratory observations in both China and USA found statistical yet slight differences between Hap1 and Hap2 in some of life history traits. Conclusions Our study on H. axyridis provides new insights into its invasion processes into other major continents from its native Asian range, reconstructs a geographic range evolution across its native region China, and tentatively suggests that its invasiveness may differ between mitochondrial haplotypes.

Abstract Background Titanium (Ti) is now widely used as implant material due to its excellent mechanical properties and superior biocompatibilities, while its inert bioactivities might lead to insufficient osseointegration, and limit its performance in dental applications. Methods We introduced a robust and simple approach of modifying titanium surfaces with polysaccharide complexes. Titanium samples were subjected to hydrothermal treatment to create a uniform porous structure on the surface, followed by coating with a bioinspired and self-assembly polydopamine layer. Strontium Eucommia Ulmoides Polysaccharide (EUP-Sr) complexes are then introduced to the polydopamine-coated porous titanium. Multiple morphological and physiochemical characterizations are employed for material evaluation, while cell proliferation and gene expression tests using macrophages, primary alveolar bone osteoblasts, and vascular endothelial cells are used to provide an overall insight into the functions of the product. The significances of statistical differences were analyzed using student’s t-test. Results Microscopic and spectrometric characterizations confirmed that the Ti surface formed a porous structure with an adequate amount of EUP-Sr loading. The attachment was attributed to hydrogen bonding between the ubiquitous glycosidic linkage of the polysaccharide complex and the ring structure of polydopamine, yet the loaded EUP-Sr complex can be gradually released, consequently benefiting the neighboring microenvironment. Cell experiments showed no cytotoxicity of the material, and the product showed promising anti-inflammation, osseointegration, and angiogenesis properties, which were further confirmed by in vivo evaluations. Conclusion We believe the EUP-Sr modified titanium implant is a promising candidate to be used in dental applications with notable osteoimmunomodulation and angiogenesis functions. And the novel technique proposed in this study would benefit the modification of metal/inorganic surfaces with polysaccharides for future research.

Abstract Background Due to the lack of postoperative reporting outcomes and bio-mechanical studies, an optimal management of scapular fractures has not been well-established in clinical treatment, even though there are many options available. This study aimed to compare the stability of the new titanium anatomic and traditional titanium reconstructive plates for extra-articular scapular fractures through finite element analysis. Methods Two models of scapular assembly were constructed, including one anatomic plate (AP model) and one reconstructive plate (RP model). After meshing, material parameter, and boundary condition settings, we applied four loading conditions to simulate forces acting on the scapula and osteosynthesis material. To evaluate the bio-mechanical properties, the equivalent von Mises stress, equivalent elastic strain, and total deformation were investigated. Result The stress and strain distribution of model AP has better performance than model RP, with more uniform and lower values. The maximum stress value of the scapula in model AP is smaller than that of the scapula in model RP (102.83 MPa vs. 166.71 MPa). The maximum stress of the anatomic plate is half that of the reconstructive plate (218.34 MPa vs. 416.01 MPa). The maximum strain of the scapula in model AP is smaller than that of the scapula in model RP (0.0071 vs. 0.0106). The maximum strain of the anatomic plate is half that of the reconstructive plate (0.0019 vs. 0.0037). The maximum displacement of each model is all at the acromion, with a similar value (2.2947 mm vs. 1.8308 mm). Conclusions With sufficient bio-mechanical stability, the anatomic plate to support scapular fracture fragments was superior to that of the reconstructive plate.

Structural vibration has always been a major concern in the engineering field. A dynamic vibration absorber in the form of contacts with adjustable stiffness (CDVA) offers effective vibration suppression and can improve conventional dynamic vibration absorbers with high sensitivity to frequency deviation and difficulty in adjusting the frequency. In this research, first, based on the theoretical model of the contact between a rubber ball and an inner cone, the feasibility of changing the axial contact state to change the structure’s natural frequency was verified using an ANSYS simulation. A theoretical model of the static contact stiffness between the ball and the inner cone was constructed using Hertzian contact theory and Hooke’s law, and a theoretical model of the cubic nonlinear elastic restoring force was used to characterize the stiffness properties of the rubber ball during compressive rebound. The steady-state frequency response equations of the main vibration structure were derived using the averaging method in conjunction with the two-degree-of-freedom dynamics model, and the stability of the solutions to the frequency response equations was obtained in conjunction with the stability determination criterion. Then, the impact of the CDVA’s design parameters on the nonlinear dynamic response of the primary vibration structure was simulated and analyzed. The resulting findings can serve as guidance for designing dynamic vibration absorber parameters. Based on the principles of ball-inner cone contact, a dynamic vibration absorber structure was proposed. A design test was conducted to verify the correctness of the contact stiffness model, and an experimental study was carried out to investigate the law of change in the dynamic stiffness and damping of the principle structure of CDVA under dynamic excitation conditions. Finally, the vibration test platform of the solidly supported beam structure was constructed, and vibration suppression tests of the CDVA in different compression states were conducted to investigate the tunability and feasibility of CDVA vibration suppression. The results showed that the dynamic vibration absorber had good vibration absorption characteristics and could be used for single-mode vibration suppression of multimodal main structures.

A computational spectrometer is a novel form of spectrometer powerful for portable in situ applications. In the encoding part of the computational spectrometer, filters with highly non-correlated properties are requisite for compressed sensing, which poses severe challenges for optical design and fabrication. In the reconstruction part of the computational spectrometer, conventional iterative reconstruction algorithms are featured with limited efficiency and accuracy, which hinders their application for real-time in situ measurements. This study proposes a neural network computational spectrometer trained by a small dataset with high-correlation optical filters. We aim to change the paradigm by which the accuracy of neural network computational spectrometers depends heavily on the amount of training data and the non-correlation property of optical filters. First, we propose a presumption about a distribution law for the common large training dataset, in which a unique widespread distribution law is shown when calculating the spectrum correlation. Based on that, we extract the original dataset according to the distribution probability and form a small training dataset. Then a fully connected neural network architecture is constructed to perform the reconstruction. After that, a group of thin film filters are introduced to work as the encoding layer. Then the neural network is trained by a small dataset under high-correlation filters and applied in simulation. Finally, the experiment is carried out and the result indicates that the neural network enabled by a small training dataset has performed very well with the thin film filters. This study may provide a reference for computational spectrometers based on high-correlation optical filters.

The intelligent identification of coal gangue on industrial conveyor belts is a crucial technology for the precise sorting of coal gangue. To address the issues in coal gangue detection algorithms, such as high false negative rates, complex network structures, and substantial model weights, an optimized coal gangue detection algorithm based on YOLOv5s is proposed. In the backbone network, a feature refinement module is employed for feature extraction, enhancing the capability to extract features for coal and gangue. The improved BIFPN structure is employed as the feature pyramid, augmenting the model’s capability for cross-scale feature fusion. In the prediction layer, the ESIOU is utilized as the bounding box regression loss function to rectify the misalignment issue between predicted and actual box angles. This approach expedites the convergence speed of the network while concurrently enhancing the accuracy of coal gangue detection. Channel pruning is implemented on the network to diminish model computational complexity and weight, consequently augmenting detection speed. The experimental results demonstrate that the refined YOLOv5s coal gangue detection algorithm outperforms the original YOLOv5s algorithm, achieving a notable accuracy enhancement of 2.2% to reach 93.8%. Concurrently, a substantial reduction in model weight by 38.8% is observed, resulting in a notable 56.2% increase in inference speed. These advancements meet the detection requirements for scenarios involving mixed coal gangue.

The original purpose of resilience design for traditional architectures is to be coordinated with and adapted to the natural environment. The natural environmental resilience of traditional dwellings refers to the ability of the dwellings to maintain the residents’ comfort, safety, and health in the face of natural environmental challenges including various disasters. In the process of designing traditional dwellings, the wisdom contributed to improving living environment conditions is of significant reference value. Therefore, this paper reviews the main literature on the resilience of traditional dwellings to the natural environment in Fujian of China. A topical review framework is proposed to cover the resilience performance of traditional dwellings in Fujian under various natural environmental conditions. Specifically, it is divided into two aspects: internal comfort resilience and external disaster-resistance resilience, based on which researchers in related fields can establish a clearer classification of resilience research in their future studies. In terms of internal comfort resilience, this paper focuses on relevant perspectives such as humidity, temperature, brightness, noise, etc. In terms of external disaster-resistance resilience, this paper summarizes the adaptability of traditional dwellings in the face of disasters triggered by natural hazards such as fires, floods, earthquakes, and typhoons. Based on this framework, this paper reviews the current research status, discusses the limitations and shortcomings in this research area, and proposes corresponding prospects for future research.

The spaceborne solar observation system is crucial for the study of space phenomena such as solar flares, which requires high tracking accuracy. This study presents a coupling model that integrates mechanical, electrical, and control models to investigate the structural flexibility effect on the micro-vibration response. We established a rigid–flexible model using mechanical parts. We considered the influence of flexible features while studying the dynamic responses in its operation. The state-space equations of the system showed that modal frequency, damping, and modal participation factors played significant roles. We derived transfer functions using the Laplace transform of the coupling models to better understand this mechanism, and Simulink models were thereby established. We simulated the acceleration responses of the rigid–flexible and rigid models under angle tracking modes, and the results showed significant differences. We also simulated the acceleration responses of the models under various control frequencies, and the optimal control frequency was thus obtained. Finally, we performed experiments, and the results indicated that the rigid–flexible model could better predict the motion and acceleration responses for the spaceborne solar observation system. This study provides valuable information for understanding the role of flexible features in space performance high-tracking accuracy instruments and for micro-vibration suppression research.

VEGF165 and its isoform VEGF165b have the same length but opposite functions in cancer. Some studies have indicated the important role of VEGF165 in osteosarcoma (OS); however, VEGF165b has not been taken into consideration. This study aims to clarify the roles of the two isoforms in OS and the mechanism controlling their formation from an alternative splicing perspective. By in vivo and in vitro experiments, we assessed the expression and function of VEGF165 and VEGF165b, screened the underlying splicing factors, and verified the regulatory function of splicing factor YBX1 on the two isoforms and its role in OS. The results showed that in OS, VEGF165 was upregulated but VEGF165b was downregulated. VEGF165 promoted the proliferation, migration and invasion of OS cells and induced angiogenesis in OS tumours; however, VEGF165b showed the opposite function. Of the four screened splicing factors, YBX1 was upregulated in OS tissues. It was positively correlated with VEGF165 but negatively correlated with VEGF165b. Further study indicated that YBX1 could upregulate VEGF165 but downregulate VEGF165b. Moreover, YBX1 promoted the proliferation, migration and invasion of OS cells and induced angiogenesis in OS tumours. OS patients with higher YBX1 had a poor prognosis within five years, but this difference disappeared in a longer follow-up. In conclusion, VEGF165b was antineoplastic and downregulated in OS, in contrast to VEGF165. YBX1 was found to be an important splicing factor that increased VEGF165 but decreased VEGF165b. Targeting YBX1 could endogenously alter the levels of VEGF165 and VEGF165b simultaneously.

With the development of smart grids and the popularization of smart meters, grid companies have obtained a large amount of fine-grained user electricity consumption data, making it possible to forecast individual users’ electricity load. Traditional deterministic forecasting cannot measure the uncertainty of users’ future electricity consumption behavior. This paper aims to establish a short-term load probability forecasting model for individual users, which can output the probability prediction interval and the probability density curve. Firstly, historical data is applied to train a deterministic prediction model based on random forest. Then, when predicting the user load at a future time, the output of each tree in the forest is formed into a prediction set, and the kernel density estimation method is used to obtain the probability prediction result of the user load. The proposed RF-KDE method obtains promising results on a public dataset. It also shows the advantages of easy parameters adjustment and fast training speed. Besides, tests conducted on the public dataset confirm that the proposed method can be applied to users with different electricity consumption behaviors.

For high ground-stress soft-rock tunnels surrounding rock with large deformation, rapid deformation rate, a long creep time, and a high likelihood of to causing initial and secondary lining damage, the yielding and relief-pressure support technology of a lining filled with a granular material is proposed. A layer of granular material is placed at the reserved deformation layer of the tunnel to provide the surrounding rock with a certain amount of deformation space. Confined compression tests were undertaken to study the laws of compressive strain, load reduction law, and horizontal force variation of different granular materials under different rock stresses. The research showed that the compressibility and load reduction performance of 8 mm soil was optimal. Its maximum compressive strain reached 47.6%, and the total load reduction rate reached 71%. The yielding- and relief-pressure effects of the granular sand-filled lining support were analyzed from the angles of deflection, pressure, and energy. The results show that the highest reduction rate of deflection was 36.7%, and the greatest load reduction rate of pressure was 78%. The grainy filling material can remove part of the load imposed by the surrounding rock on the support structure of the secondary lining through yielding pressure and relief pressure, which dramatically reduces the damage to the secondary lining from the surrounding rock. The research results have specific reference significance for designing and constructing tunnel support structures.

Binary ethosome vesicles have been developed as flexible lipid vesicles for the enhanced physicochemical stability and skin delivery of drugs. This work aimed to prepare phloretin-loaded propylene glycol ethosomes (PHL-PGEs) to improve their stability, skin permeability and antioxidant activity. PHL-PGEs were prepared via the ethanol injection method and optimized using different weight ratios of ethanol to propylene glycol (PG). When the ethanol/PG mass ratio changed from 10:0 to 0:10, the encapsulation efficiency and stability of ethosomes increased. At a PHL concentration of 1mg/mL, the EE% was 89.42 ± 2.42 and the DL% was 4.21 ± 0.04, which exhibited their highest values. The encapsulation of the PHL in the PHL-PGEs was strengthened via XRD analysis and FTIR analysis. The results of the in vitro percutaneous permeability test demonstrated that the combined use of ethanol and PG exhibited a notable enhancement in skin permeability, and the skin retention of PHL-PGEs was 1.06 times that of PHL-ethosomes (PHL-Es) and 2.24 times that of the PHL solution. An in vitro antioxidant activity study indicated that solubility and antioxidant activity was potentiated via the nanoencapsulation of phloretin. Therefore, these results confirm the potential of this nanocarrier to enhance physicochemical stability, skin permeability and antioxidant activity.

Abstract Combining 3D printing with precursor-derived ceramic for fabricating electromagnetic (EM) wave-absorbing metamaterials has attracted great attention. This study presents a novel ultraviolet-curable polysiloxane precursor for digital light processing (DLP) 3D printing to fabricate ceramic parts with complex geometry, no cracks and linear shrinkage. Guiding with the principles of impedance matching, attenuation, and effective-medium theory, we design a cross-helix-array metamaterial model based on the complex permittivity constant of precursor-derived ceramics. The corresponding ceramic metamaterials can be successfully prepared by DLP printing and subsequent pyrolysis process, achieving a low reflection coefficient and a wide effective absorption bandwidth in the X-band even under high temperature. This is a general method that can be extended to other bands, which can be realized by merely adjusting the unit structure of metamaterials. This strategy provides a novel and effective avenue to achieve “target-design-fabricating” ceramic metamaterials, and it exposes the downstream applications of highly efficient and broad EM wave-absorbing materials and structures with great potential applications.

A place name is a textual identification of a specific spatial location by people and is an important carrier of geographical information. The recognition of Chinese place names is of great importance in information retrieval and event extraction. The traditional approach is to transform the recognition of Chinese place names into a sequential annotation problem, with commonly used classification models such as support vector machines and conditional random fields. In this paper, Chinese address recognition is converted into a sequential annotation task, and a multi-feature fusion approach to Chinese address recognition is proposed. A deep learning network architecture model based on the fusion of character, word, and address features is constructed to convert characters, words, and their features into vector representations; finally, the sequential annotation of sentences is performed by CRF to achieve the recognition and extraction of address information. On the autonomously constructed dataset, the proposed method MFBL (Multi-Feature-BiLSTM) improves in accuracy by 4 to 10 percentage points compared to other methods, demonstrating that the MFBL model has better performance in the address recognition task.

The reliability of the aircraft engine duct system is of paramount importance as it directly affects the safety of the aircraft, particularly under high-temperature and high-pressure cycles. In this study, ANSYS Workbench was used for finite element analysis, and a sleeve-type tie rod structure was proposed to address the critical problem of tie rod tearing during the operation of the duct system, thereby optimizing thermal stress compensation for the duct system. The research results show the following: (1) The anchor of the traditional tie rod imposes displacement constraints on the thermal deformation of the duct system, leading to stress concentration and even structural failure in the connection area between a duct and a tie rod. (2) The improved sleeve-type tie rod provides greater axial displacement freedom for the duct, effectively mitigating stress concentration phenomena. (3) Taking a worst-case scenario of 537.78 °C and 2 MPa as an example, the sleeve-type tie rod proposed in this paper can reduce the stress at the tie rod connection from 757.61 MPa to less than 25 MPa, a reduction of more than 96%. The original tie rod tearing problem is solved, and the maximum stress of the whole duct system is reduced to 459.25 MPa, which is below the yield strength.

Abstract Backgrounds Osteosarcomas are one of the most common primary malignant tumors of bone. It primarily occurs in children and adolescents, with the second highest incidence among people over 50 years old. Although there were immense improvements in the survival of patients with osteosarcoma in the past 30 years, targetable mutations and agents of osteosarcomas still have been generally not satisfactory. Therefore, it is of great importance to further explore the highly specialized immune environment of bone, genes related to macrophage infiltration and potential therapeutic biomarkers and targets. Methods The 11 expression data sets of OS tissues and the 11 data sets of adjacent non-tumorous tissues available in the GEO database GSE126209 were used to conduct immune infiltration analysis. Then, through WGCNA analysis, we acquired the co-expression modules related to Mast cells activated and performed the GO and KEGG enrichment analysis. Next, we did the survival prognosis analysis and plotted a survival curve. Finally, we analyzed the COX multivariate regression of gene expression on clinical parameters and drew forest maps for visualization by the forest plot package. Results OS disease-related immune cell populations, mainly Mast cells activated, have higher cell content (p = 0.006) than the normal group. Then, we identified co-expression modules related to Mast cells activated. In sum, a total of 822 genes from the top three strongest positive correlation module MEbrown4, MEdarkslateblue and MEnavajowhite2 and the strongest negative correlation module MEdarkturquoise. From that, we identified nine genes with different levels in immune cell infiltration related to osteosarcoma, eight of which including SORBS2, BAIAP2L2, ATAD2, CYGB, PAMR1, PSIP1, SNAPC3 and ZDHHC21 in their low abundance have higher disease-free survival probability than the group in their high abundances. Conclusion These results could assist clinicians to select targets for immunotherapies and individualize treatment strategies for patients with OS.

Enhancers are short non-coding DNA sequences outside of the target promoter regions that can be bound by specific proteins to increase a gene's transcriptional activity, which has a crucial role in the spatiotemporal and quantitative regulation of gene expression. However, enhancers do not have a specific sequence motifs or structures, and their scattered distribution in the genome makes the identification of enhancers from human cell lines particularly challenging. Here we present a novel, stacked multivariate fusion framework called SMFM, which enables a comprehensive identification and analysis of enhancers from regulatory DNA sequences as well as their interpretation. Specifically, to characterize the hierarchical relationships of enhancer sequences, multi-source biological information and dynamic semantic information are fused to represent regulatory DNA enhancer sequences. Then, we implement a deep learning-based sequence network to learn the feature representation of the enhancer sequences comprehensively and to extract the implicit relationships in the dynamic semantic information. Ultimately, an ensemble machine learning classifier is trained based on the refined multi-source features and dynamic implicit relations obtained from the deep learning-based sequence network. Benchmarking experiments demonstrated that SMFM significantly outperforms other existing methods using several evaluation metrics. In addition, an independent test set was used to validate the generalization performance of SMFM by comparing it to other state-of-the-art enhancer identification methods. Moreover, we performed motif analysis based on the contribution scores of different bases of enhancer sequences to the final identification results. Besides, we conducted interpretability analysis of the identified enhancer sequences based on attention weights of EnhancerBERT, a fine-tuned BERT model that provides new insights into exploring the gene semantic information likely to underlie the discovered enhancers in an interpretable manner. Finally, in a human placenta study with 4,562 active distal gene regulatory enhancers, SMFM successfully exposed tissue-related placental development and the differential mechanism, demonstrating the generalizability and stability of our proposed framework.

This paper presents a numerical study on the static behavior and cyclic behavior of UHPC-filled steel tube (UHPCFST) columns. A novel fiber element model is developed based on the effective distribution width method to consider the influence of local buckling. The parameters of the descending branch of the stress–strain curve of constrained concrete have been modified and proposed according to the existing experimental results. Thereafter, the impact parameter analysis of the seismic performance of UHPCFST columns under the pseudo static load is conducted, and the strength of steel and UHPC, width–thickness ratio, length–diameter ratio and axial compression ratio are considered. The results indicate that the proposed fiber element model can accurately predict the static and cyclic nonlinear behaviors of the UHPCFST columns. The bearing capacity and the post-peak ductility of UHPCFST columns can be overestimated, such as neglecting the local buckling of the steel tube, which will lead to the insecurity of structures.

Background: The standard treatment for osteosarcoma comprises complete surgical resection and neoadjuvant chemotherapy, which may cause serious side effects and partial or total limb loss. Therefore, to avoid the disadvantages of traditional treatment, we developed self-assembling imageable silk hydrogels for osteosarcoma.Methods: We analysed whether iodine induced apoptosis in MG-63 and Saos-2 cells by using CCK-8 and flow cytometry assays and transmission electron microscopy. Western blotting was used to analyse the pathway of iodine-induced apoptosis in osteosarcoma cells. PEG400, silk fibroin solution, polyvinylpyrrolidone iodine (PVP-I), and meglumine diatrizoate (MD) were mixed to produce an imageable hydrogel. A nude mouse model of osteosarcoma was established, and the hydrogel was injected locally into the interior of the osteosarcoma with X-ray guidance. The therapeutic effect and biosafety of the hydrogel were evaluated.Results: Iodine treatment at 18 and 20 µM for 12 h resulted in cell survival rate reduced to 50 ± 2.1% and 50.5 ± 2.7% for MG-63 and Sao-2 cells, respectively (p < 0.01). The proportion of apoptotic cells was significantly higher in the iodine-treatment group than in the control group (p < 0.05), and apoptotic bodies were observed by transmission electron microscopy. Iodine could regulate the death receptor pathway and induce MG-63 and Saos-2 cell apoptosis. The hydrogels were simple to assemble, and gels could be formed within 38 min. A force of less than 50 N was required to inject the gels with a syringe. The hydrogels were readily loaded and led to sustained iodine release over 1 week. The osteosarcoma volume in the PEG-iodine-silk/MD hydrogel group was significantly smaller than that in the other three groups (p < 0.001). Caspase-3 and poly (ADP-ribose) polymerase (PARP) expression levels were significantly higher in the PEG-iodine-silk/MD hydrogel group than in the other three groups (p < 0.001). Haematoxylin and eosin (H&E) staining showed no abnormalities in the heart, liver, spleen, lung, kidney, pancreas or thyroid in any group.Conclusions: Self-assembling imageable silk hydrogels could be injected locally into osteosarcoma tissues with X-ray assistance. With the advantages of good biosafety, low systemic toxicity and minimal invasiveness, self-assembling imageable silk hydrogels provide a promising approach for improving the locoregional control of osteosarcoma.

The Upper Permian Linghao Formation marine shale and contemporaneous transitional shale are the most potential shale gas targets in the Nanpanjiang basin, which is characterized by considerable TOC content, wide distribution, and considerable shale thickness. On the basis of division in Linghao Formation, petrographic, mineralogical, and high-resolution geochemical analyses were integrated to reveal the sedimentary environment including paleoproductivity, paleoredox conditions, detrital influx, paleoclimate, and the paleosalinity. There are two organic-rich shale intervals in Linghao Formation, which are Ling 1 member and the lower Ling 3 member. The lower Ling 1 is dominated by deep-water shelf facies, which are characterized by high TOC value (0.93%–6.36%, avg. 2.43%), high detrital influx proxies (Zr, 746–1508 ppm, avg. 1093 ppm; Ti, 19278–128730 ppm, avg. 16091 ppm), relatively warm–humid paleoclimate condition (CIA*, 75.94-91.90, avg. 82.26), low paleosalinity proxies (Sr/Ba, 0.13-0.34, avg. 0.22), and high paleoproductivity (P/Al (10−2), 1.06-2.06, avg. 1.63; Mn/Ca (10−3), 27.37-291.69, avg. 128.07). Detrital influx including gravity flow plays a critical role in the enrichment of organic matter. The sedimentary environment of upper Ling 1 and lower Ling 3 is the same as that of lower Ling 1. Unlike lower Ling 1, these intervals are characterized by low detrital influx proxies, moderate weathering, and relatively high paleosalinity proxies. The volcanic ash of Emei volcanism and felsic volcanism in South China plays a critical role in the enrichment of organic matter in upper Ling 1 and lower Ling 3, respectively. The sedimentary models for Linghao Formation organic-rich shale can reveal factors controlling the enrichment of organic matter.

The word “Light” has two common meanings, one is illuminant (referred as LIGHT in this paper), and the other is something of little weight (referred as light in this paper). The “Weight of LIGHT” is an art of creating visual illusion applied in architecture design, which is a new understanding about LIGHT as well as the relationship between LIGHT and users. This study develops the concept of “the weight of LIGHT” through analyzing of the contradictions between the two concepts, and looking into several specific LIGHT designs to discuss the mediums through which LIGHT acts on buildings and occupants. The author then focuses on the library of Faculty of Architecture of Porto University (FAUP) designed by Alvaro Siza and argues that by providing a unique “Triangular Prism” inside the building, Siza conveyed “the weight of LIGHT” indirectly through the container (size, shape, material) and the relationship between the container and the surroundings (roof, wall, ceiling).

Breast cancer is one of most serious malignant tumors that affect women’s health. To carry out the early screening of breast cancer, mammography provides breast cancer images for doctors’ efficient diagnosis. However, breast cancer lumps can vary in size and shape, bringing difficulties for the accurate recognition of both humans and machines. Moreover, the annotation of such images requires expert medical knowledge, which increases the cost of collecting datasets to boost the performance of deep learning methods. To alleviate these problems, we propose an attention-based active learning framework for breast cancer segmentation in mammograms; the framework consists of a basic breast cancer segmentation model, an attention-based sampling scheme and an active learning strategy for labelling. The basic segmentation model performs multi-scale feature fusion and enhancement on the basis of UNet, thus improving the distinguishing representation capability of the extracted features for further segmentation. Afterwards, the proposed attention-based sampling scheme assigns different weights for unlabeled breast cancer images by evaluating their uncertainty with the basic segmentation model. Finally, the active learning strategy selects unlabeled images with the highest weights for manual labeling, thus boosting the performance of the basic segmentation model via retraining with new labeled samples. Testing on four datasets, experimental results show that the proposed framework could greatly improve segmentation accuracy by about 15% compared with an existing method, while largely decreasing the cost of data annotation.

Nowadays, the uncertainty of renewable energy and demand side response have become a significant issue in microgrid dispatch. To optimize the dispatching, it is usually a common way to establish the probability distribution functions of the renewables and the associated load model. Though there have been various modeling approaches, few of them consider the customer satisfaction with uncomplicated parameter solving algorithms. To settle this problem, this paper proposes an optimal dispatching strategy for a thermoelectric coupled microgrid. A parameter simplification approach is firstly presented to deal with the renewable energy uncertainty, by introducing normal distribution probability distribution function and reserve capacity allocation cost. Secondly, as for the demand side response, the effect of transferable and reducible loads on customer satisfaction has been fully considered, and the load tracking ability on renewables has also been taken account. The effectiveness of the proposed strategy and its superiority in reducing the operating cost of the microgrid have been verified by computer simulations and comparisons.

In this paper, a handheld liquor authenticity detection system is demonstrated based on the laser spectroscopy technique, which consists of a handheld laser spectrometer and a mobile phone display terminal. In this system, the semiconductor laser is integrated into the spectrometer and the laser beam is further angled to the optical axis of the spectrometer to avoid interference of the fluorescence generated by the bottle wall. During the system operation, the laser excites the tested liquor to generate fluorescence and Raman spectroscopy signals, which are digitized and wirelessly transmitted by Wi-Fi to the Android mobile terminal. After the image processing by the mobile phone APP, the tested liquor spectrum curve is obtained. At the same time, based on the standard liquor spectrum curve stored in the database, the Pearson correlation coefficient is calculated and the matching similarity is given. In addition, this paper proposes a calibration method based on pure water Raman intensity to achieve accurate measurement of fluorescence intensity and minimize the influence of fluorescence intensity saturation on the measurement results. In the experiment, we measured the similarity of 12 brands of Chinese liquor by using our self-developed handheld laser spectrometer. Their authenticity of liquor could be given accurately and effectively.

Traditional haemostatic materials generally have slow hemostasis rate and poor biocompatibility. This paper reports on the haemostatic properties and mechanism of silk fibroin (SF). SF-PEG sponge that could be solubilised and changed to gel form by blood was fabricated through mixing SF and polyethylene glycol (PEG, 1500 Da) followed by lyophilisation of the mixed solution. SF-PEG sponge, together with control samples of SF sponge (no PEG) and a commercially available haemostatic material, gelatine sponge, were subjected to the hemostasis tests using a liver trauma model of rabbit. The results showed that SF was superior to gelatine sponge in hemostasis time (136.17 ± 62.27 s and 249.83 ± 29.18 s) and blood loss (2.16 ± 1.27 g vs. 4.97 ± 1.44 g). Furthermore, in vitro experiments indicated SF-PEG sol-gel transition promoted platelet adhesion and aggregation, as well as platelet-fibrinogen interaction. Therefore, except for the physical blocking of bleeding port due to PEG-induced SF fast gelation, SF might also have an impact on blood coagulation process, a phenomenon that has not been reported before. In conclusion, SF is a new type of haemostatic material that might be able to meet the requirements of speed, efficiency and biosafety in a variety of clinical applications.

Fast power flow calculation is generally required in static security analysis and power system optimal planning. And the classical DC power flow algorithm, due to its simple mathematical model, linearized equation, and rapid solving speed, is widely utilized. However, the classical DC power flow algorithm has been found to be only suitable for high voltage transmission networks with small branch impedance ratio. To address this issue, a general fast power flow algorithm is proposed. Utilizing this method, the classical DC power flow algorithm is firstly performed to obtain the initial values of the branch active power flow. And the nodal voltage angles are then calculated by the established node-injected reactive power equations. Secondly, through the identical transformation and approximate treatment of the node power flow equation, a voltage offset calculation method for PQ nodes is proposed. Finally, the active power flow and active power loss can be calculated based on the corrected phase angles and node voltages. Simulation studies on standard IEEE power systems, such as the IEEE 33-bus and IEEE 118-bus systems, etc., were conducted by the presented algorithm, compared with those by the back/forward sweep, classical DC power flow and Newton-Raphson algorithms. It is indicated that, the proposed power flow algorithm has the superiority in satisfactory calculation speed and non-sensitivity on the network impedance ratio.

In order to solve the problem of low recognition rate and low real-time performance of vehicle detection in complex road environment, a data-driven forward vehicle detection algorithm based on improved tiny-YOLOv3 is proposed. Based on tiny-YOLOv3, the context feature information is combined to increase the two scale detections of tiny-YOLOv3 to three. The spatial pyramid pooling (SPP) module is added to increase the number of feature channels to improve the network feature extraction ability. According to the dense arrangement of vehicles on the horizontal axis in the road image ahead, we change the grid size of tiny-YOLOv3 and increase the number of candidate boxes on the horizontal axis. In addition, combined with the characteristics of the vehicle size in the road image ahead, K-means clustering method is used to select the appropriate number and size of target candidate boxes. We obtain the optimal detection model by multi-scale training of the improved network. The experimental results show that the average accuracy of the improved algorithm on the KITTI datasets is 91.03%, which is 7.12% higher than that of tiny-YOLOv3. And the detection speed of improved network is 144 frames/s, which meets the real-time requirements.

In recent years, with the rapid development of renewable energy, microgrid that behaves as a multi-energy coupling system, has attracted more and more attention. A growing trend needs to be concerned is that the relation among the electric power, thermal and gas in a microgrid system gets closer and closer, which could significantly affect the system dispatching. The existing research on microgrid dispatch mainly focuses on power and load coordination and improving the utilization rate of primary energy. However, there is some limit in the energy form independence and operation mode. Besides, some research had ignored the consumer electricity experience in load optimization. To settle such problem, a dispatching model based on a complicated electric-thermal-gas coupling microgrid is firstly proposed in this paper. Then the mathematical model of the subsystems in the microgrid is established, and the demand side response based on consumer satisfaction is employed to optimize the loads. Finally, the operation cost of the microgrid can be minimized by the proposed economic optimization strategy. Case studies were performed to verify the effectiveness of the proposed scheduling strategy.

Senile osteoporosis is closely related to the loss of function of stem cells. In this study, we tried to investigate the potential of secretome from human umbilical cord-derived mesenchymal stem cells (hUCMSCs) in recovering stem cell ability from senescence and then delaying bone loss. We first harvested bone marrow-derived mesenchymal stem cells (BMSCs) from young and old rats and then compared their cellular characteristics such as cell growth, anti-senescence and differentiation. The results showed that these abilities were negatively affected by animal aging. Subsequently, aged BMSCs were exposed to secretome from hUCMSCs, and we found that this loss of cell potential can be modified by secretome treatment. Thereafter, the secretome was loaded into silk fibroin-based hydrogels and used for an in vivo animal study. The results showed that compared to the old untreated group, the bone formation capacity of aged rats was improved by local treatment of secretome-loaded silk fibroin hydrogels. In conclusion, these findings demonstrated that secretome from hUCMSCs has the capacity to recover stem cell potential and delay local bone loss in age-related osteoporosis, which could potentially be applied in osteoporosis therapy in the future.

In order to get insight information of the band structure of acoustic metamaterials (AMMs) in condensed matter, periodic lattice structures are analyzed using Bloch’s theorem. Typical approaches of the band structure computation methods, topology optimization, and tunable abilities cannot overcome the gap between the two-dimensional (2D) AMMs theoretical and three-dimensional (3D) specimens’ experimental data yet. In this work, the variation in the results of the band structure obtained from the 2D mathematical model computed with respect to the 3D experimental models, and related cause of the variation is explored. The band structures and mode shapes of the 2D AMMs, quasi-2D models, and 3D specimen models are followed to reveal the boundary conditions and source for the observed differences in band structures. The cause for the discrepancies is verified by using the finite element method (FEM) with corresponding boundary conditions. It is found that outcomes from computational data of the 2D AMMs model are diverted significantly by means of bandgap, band structure, and stress distribution in counterparts of the 3D specimen model. This approach can provide assistance for computing the band structure of 2D AMMs for practical applications.

A bandpass filter integrated metalens based on electromagnetically induced transparency (EIT) for long-wavelength infrared (LWIR) imaging is designed in this paper. The bandwidth of the metalens, which is a diffractive optical element, decreases significantly with the increase of the aperture size to a fixed f-number, which leads to the decline of imaging performance. The same material composition and preparation process of the metalens and the EIT metasurface in the long-wavelength infrared make it feasible that the abilities of focusing imaging and filtering are integrated into a metasurface device. With the purpose of validating the feasibility of this design method, we have designed a 300-μm-diameter integrated metalens whose f-number is 0.8 and the simulation was carried out. The introduction of EIT metasurface does not affect the focusing near the diffraction limit at the target wavelength, and greatly reduces the influence of stray light caused by non-target wavelength incident light. This bandpass filter integrated metalens design method may have a great potential in the field of LWIR compact optical systems.

A novel acoustic metamaterial structure, made up of both resonator and multiple channels, is proposed to insulate low-frequency broadband noises. Three bandgaps with a total width of 658 Hz can be obtained below 900 Hz when the structure appears as a single negative characteristic within specific frequency ranges. These bandgaps are caused by the standing-wave characteristics under the coupling action of the interior and exterior cavities and the multiple channels. By changing structural parameters and materials, the low-frequency broadband sound insulation performance of the structure can be improved. Experimental results further prove the sound insulation characteristics. The results obtained herein can be used as a guide toward achieving low-frequency broadband sound insulation using a lightweight structure.

Abstract Background Increasing reports demonstrated that dysregulated expression of microRNAs (miRNAs) leads to the progression of various tumors. Previous studies revealed that miR-328-3p exhibited dysregulated expression in various types of tumors. However, its function and underlying mechanism in osteosarcoma (OS) are still unexplored. Methods The expression of miR-328-3p in the tissues and OS cell lines was detected by qRT-PCR analysis. The effects of miR-328-3p in the proliferation were analyzed by MTT assay. The proliferation and apoptosis of OS cells were examined by colony formation assay and TUNEL staining respectively. The migration and tumor formation ability of OS cells were measured by wound healing assay and xenograft in vivo mice assay. Furthermore, the regulatory roles of miR-328-3p/MMP16 were determined by western blot and luciferase reporter assay. Results The expression of miR-328-3p was significantly decreased in OS tissues and cell lines. Furthermore, overexpression of miR-328-3p inhibited the cell proliferation and migration, but promoted the apoptosis of OS cells in vitro. Moreover, the analysis in vivo showed that miR-328-3p effectively suppressed the formation of tumors. According to the results of western blot analysis and luciferase reporter assay, we identified matrix metalloproteinase-16 (MMP-16) acted as a direct target of miR-328-3p. Moreover, the expression level of MMP-16, which participates in the occurrence and development of many cancers, was negatively correlated with the miR-328-3p expression in OS cells. Conclusion miR-328-3p inhibited the proliferation, migration but accelerated the apoptosis of OS by directly inhibiting MMP-16. And miR-328-3p/MMP-16 axis may be one of the mechanisms of OS development and a novel potential method for the treatment of OS in clinic.

As for a grid-connected PWM converter with LCL filter, harmonic current can flow freely into the grid-side inductor and filter capacitor, when the connected power grid is harmonically distorted. The fact lies in that the conventional control scheme has a little ability to suppress the grid current harmonics. Though the harmonics can be suppressed by the capacitor current compensation method, it may lead to system stability issues. This paper proposes an improved harmonic suppression scheme with the partial capacitor current feedforward, which can effectively suppress the specified grid current harmonics on the premise of ensuring the system stability. Since the partial capacitor current is obtained as the differential output of a multi-second-order generalized integrator, no extra current sensors are needed. The effectiveness and feasibility of the proposed strategy are verified by detailed experimental results.

An accurate iron loss estimation is necessary before manufacturing the filter inductors of the three-phase grid-connected converters. Besides the loss characteristics of the magnetic core, obtaining an accurate current flowing through the inductor is also very important in the iron loss estimation. In three-phase grid-connected converters, there are two current ripple periods with different magnitudes in one switching period, both of which can generate the iron loss in the converter. In this paper, a dual current-ripple envelopes (DCRE) method is proposed to accurately outline the two current ripples in each switching period. A novel iron loss estimation method is further presented based on the DCRE and the existing iron loss characteristics. Adopting the DCRE method, the influence of pulse width modulation (PWM) schemes, voltage levels, and the amplitude of output current, can be easily evaluated, which provides a satisfactory guidance to the design of the inductor. The effectiveness of the proposed DCRE and iron loss estimation method is verified by the numerical simulation and the experimental test on a three-phase grid-connected converter.

With an increase in the number of international students in China, there has been a simultaneous increase in their emotional problems, such as depression, as well as the importance of their emotional well-being. This study aimed to investigate the influence of social support on depression and the mediation and moderation mechanisms of this relationship in international students. In total, 349 international students in China responded to a questionnaire survey comprising the Social Support Rating Scale, Self-rating Depression Scale, Adult Attachment Scale, and Self-Esteem Scale. The results showed that: (1) attachment closeness had a significant direct predictive effect on depression; (2) attachment closeness played a mediating role in the relationship between social support and depression; and (3) the direct effect of social support on depression and the mediating effect of attachment and closeness are regulated by self-esteem. Therefore, interventions aimed at improving the social support, attachment closeness, and self-esteem of international students in China can be effective in reducing their depressive symptoms.

Background/aims: Acute myocardial infarction (AMI) is a major clinical manifestation of ischemic heart disease and represents a significant cause of morbidity and mortality. However, key regulators in the pathogenesis of ischemic heart disease remain controversial. The present study was designed to investigate the involvement of miR-200a and its related mechanism in AMI. Methods: Left coronary artery (LCA) ligation was conducted to induce an AMI mouse model. The infarct size was measured by TTC staining. H2O2 was used to induce an AMI model in vitro. miR-200a mimics, anti-miR-200a antisense oligodeoxyribonucleotides (AMO-200a), as well as corresponding negative controls were transfected into cardiomyocytes to observe the effect of miR-200a. Flow cytometry was used to detect cell apoptosis. Real-time PCR, immunofluorescence and western blot assays were used to evaluate gene expression at RNA or protein levels, respectively. Results: Apoptosis was activated in AMI models. The expression of miR-200a was upregulated both in the peri-infarcted region of mice myocardium and H2O2-treated cardiomyocytes. The co-administration of AMO-200a decreased the number of apoptosis cells and altered the expression of apoptosis related proteins. Interestingly, bioinformatics analysis results revealed that miR-200a could bind to the 3′-untranslated regions (3’-UTR) of Fus mRNA. In addition, the expression of Fus was downregulated in the AMI mouse models and in H2O2-treated cardiomyocytes. The alteration of miR-200a negatively regulated Fus expression in cardiomyocytes. Also, the protective effect of AMO-200a was observed through its regulation of Fus. Conclusion: MiR-200a-dependent apoptosis signaling pathway plays an important role in the pathogenesis of AMI injury and could be an exciting potential therapeutic target.

Huganpian (HGP), a traditional chinese medicine composed of 6 herbs, possesses excellent therapeutic effects in clinical application. In this study, we aimed to elucidate the anti-tumor activity and the underlying mechanisms of HGP in liver cancer. The results of this study indicated that HGP effectively inhibited liver cancer growth in vitro and in vivo in a dose-dependent manner. Mechanistically, HGP exerted its anti-tumor effects by triggering autophagy with increased LC3Ⅱ and beclin1 levels and arrested the cell cycle on G0-G1 phase by downregulating the expressions of cyclin-dependent kinase 2 (CDK2), cyclin-dependent kinase 4 (CDK4) and cyclinE1 in vitro and in vivo. Meanwhile, HGP did not induce apoptosis significantly. Importantly, we also confirmed that there were fewer side effects of HGP on immune system. Taken together, our findings suggest for the first time that HGP may become a promising drug or adjuvant drug with a lower toxicity for liver cancer treatment in the future.

Abstract Background Low-intensity pulsed ultrasound (LIPUS) is a common adjunct used to promote bone healing for fresh fractures and non-unions, but its efficacy for bone distraction osteogenesis remains uncertain. This study aims to determine whether LIPUS can effectively and safely reduce the associated treatment time for patients undergoing distraction osteogenesis. Methods MEDLINE, EMBASE, and the Cochrane Library were searched until May 1, 2018, without language restriction. Studies should be randomized controlled trials (RCTs) or quasi-RCTs of LIPUS compared with sham devices or no devices in patients who undergo distraction osteogenesis. The primary outcome was the treatment time. The secondary outcome was the risk of complications. Treatment effects were assessed using mean differences, standardized mean differences, or risk ratios using a random-effects model. The Cochrane risk-of-bias tool was used to assess the risk of bias. The I 2 statistic was used to assess the heterogeneity. The GRADE system was used to evaluate the evidence quality. Results A total of 7 trials with 172 patients were included. The pooled results suggested that during the process of distraction osteogenesis, LIPUS therapy did not show a statistically significant reduction in the treatment time (mean difference, − 8.75 days/cm; 95% CI, − 20.68 to 3.18 days/cm; P = 0.15; I 2 = 72%) or in the risk of complications (risk ratio, 0.90 in favor of LIPUS; 95% CI, 0.65 to 1.24; I 2 = 0%). Also, LIPUS therapy did not show a significant effect on the radiological gap fill area (standardized mean difference, 0.48 in favor of control; 95%CI, − 1.49 to 0.52; I 2 = 0%), the histological gap fill length (standardized mean difference, 0.76 in favor of control; 95%CI, − 1.78 to 0.27; I 2 = 0%), or the bone density increase (standardized mean difference, 0.43 in favor of LIPUS; 95%CI, − 0.02 to 0.88; I 2 = 0%). Conclusions Among patients undergoing distraction osteogenesis, neither the treatment time nor the risk of complications could be reduced by LIPUS therapy. The currently available evidence is insufficient to support the routine use of this intervention in clinical practice. Trial registration CRD 42017073596