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Summary: Our work aimed to investigate the interactive roles of transforming growth factor β1 (TGF-β1), ubiquitin-specific-processing protease 7 (USP7), and Yes-associated protein (YAP) in ferroptosis during sepsis-secondary acute lung injury (ALI). Our study demonstrated that ferroptosis was aggravated by TGF-β1 in both cellular and animal models of acute lung injury. Additionally, YAP upregulated glutathione peroxidase 4 (GPX4) and SLC7A11 by regulating the binding of TEAD4 to GPX4/SLC7A11 promoters. Furthermore, large tumor suppressor kinase 1 (LATS1) knockdown resulted in YAP expression stimulation, while USP7 downregulated YAP via deubiquitinating and stabilizing LATS1/2. YAP overexpression or USP7/LATS1 silencing reduced ferroptosis process, which regulated YAP through a feedback loop. However, TGF-β1 annulled the repression of ferroptosis by YAP overexpression or LATS1/USP7 knockdown. By elucidating the molecular interactions between TGF-β1, USP7, LATS1/2, and YAP, we identified a new regulatory axis of ferroptosis in sepsis-secondary ALI. Our study sheds light on the pathophysiology of ferroptosis and proposes a potential therapeutic approach for sepsis-induced ALI.

IntroductionPathological changes in the articular cartilage (AC) and synovium are major manifestations of osteoarthritis (OA) and are strongly associated with pain and functional limitations. Exosome-derived microRNAs (miRNAs) are crucial regulatory factors in intercellular communication and can influence the progression of OA by participating in the degradation of chondrocytes and the phenotypic transformation in the polarization of synovial macrophages. However, the specific relationships and pathways of action of exosomal miRNAs in the pathological progression of OA in both cartilage and synovium remain unclear.MethodsThis study evaluates the effects of fibroblast-like synoviocyte (FLS)-derived exosomes (FLS-Exos), influenced by miR-146a, on AC degradation and synovial macrophage polarization. We investigated the targeted relationship between miR-146a and TRAF6, both in vivo and in vitro, along with the involvement of the NF-κB signaling pathway.ResultsThe expression of miR-146a in the synovial exosomes of OA rats was significantly higher than in healthy rats. In vitro, the upregulation of miR-146a reduced chondrocyte apoptosis, whereas its downregulation had the opposite effect. In vivo, exosomes derived from miR-146a-overexpressing FLSs (miR-146a-FLS-Exos) reduced AC injury and chondrocyte apoptosis in OA. Furthermore, synovial proliferation was reduced, and the polarization of synovial macrophages shifted from M1 to M2. Mechanistically, the expression of TRAF6 was inhibited by targeting miR-146a, thereby modulating the Toll-like receptor 4/TRAF6/NF-κB pathway in the innate immune response.DiscussionThese findings suggest that miR-146a, mediated through FLS-Exos, may alleviate OA progression by modulating cartilage degradation and macrophage polarization, implicating the NF-κB pathway in the innate immune response. These insights highlight the therapeutic potential of miR-146a as a protective agent in OA, underscoring the importance of exosomal miRNAs in the pathogenesis and potential treatment of the disease.

This study designs and proposes a method for evaluating the configuration of energy storage for integrated renewable generation plants in the power spot market, which adopts a two-level optimization model of “system simulation + plant optimization”. The first step is “system simulation” which is using the power market simulation model to obtain the initial nodal marginal price and curtailment of the integrated renewable generation plant. The second step is “plant optimization” which is using the operation optimization model of the integrated renewable generation plant to optimize the charge-discharge operation of energy storage. In the third step, “system simulation” is conducted again, and the combined power of renewable and energy storage inside the plant is brought into the system model and simulated again for 8,760 h of power market year-round to quantify and compare the power generation and revenue of the integrated renewable generation plant after applying energy storage. In the case analysis of the provincial power spot market, an empirical analysis of a 1 GW wind-solar-storage integrated generation plant was conducted. The results show that the economic benefit of energy storage is approximately proportional to its capacity and that there is a slowdown in the growth of economic benefits when the capacity is too large. In the case that the investment benefit of energy storage only considers the income of electric energy-related incomes and does not consider the income of capacity mechanism and auxiliary services, the income of energy storage cannot fulfill the economic requirements of energy storage investment.

Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of various artificial intelligence models for long-term water demand forecasting across different water use sectors. We utilized the Tuojiang River basin in Sichuan Province as our case study, comparing the performance of five artificial intelligence models: Genetic Algorithm optimized Back Propagation Neural Network (GA-BP), Extreme Learning Machine (ELM), Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Random Forest (RF). These models were employed to predict water demand in the agricultural, industrial, domestic, and ecological sectors using actual water demand data and relevant influential factors from 2005 to 2020. Model performance was evaluated based on the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with the most effective model used for 2025 water demand projections for each sector within the study area. Our findings reveal that the GPR model demonstrated superior results in predicting water demand for the agricultural, domestic, and ecological sectors, attaining R2 values of 0.9811, 0.9338, and 0.9142 for the respective test sets. Also, the GA-BP model performed optimally in predicting industrial water demand, with an R2 of 0.8580. The identified optimal prediction model provides a useful tool for future long-term water demand forecasting, promoting sustainable water resource management.

ABSTRACT Zika virus (ZIKV) is an important pathogen that causes Guillain-Barre syndrome in adults and congenital Zika syndrome in newborns. Interferon (IFN) triggers intracellular antiviral signaling through two essential mediators STAT1 and STAT2, which are critical for host innate antiviral immunity. ZIKV has been reported to antagonize host IFN signaling by diverse mechanisms, including NS5-dependent and -independent ablation of STAT2. Whether flaviviruses target STAT1 remains controversial. In this study, we used infectious clones of ZIKV MR766 as tools and found that ZIKV infection triggered caspase-dependent cleavage of STAT1 during late infection. Further studies identified that the cleavage site is the aspartic acid 694, and the D694A mutation rendered STAT1 resistant to ZIKV infection-induced cleavage. Murine STAT1 (mSTAT1) was resistant to cleavage in ZIKV-infected cells. Ectopically expressed STAT1.D694A and mSTAT1 exerted comparable anti-ZIKV activity upon IFN treatment, challenging the role of STAT1 cleavage in IFN antagonism. We further knocked out STAT1 in the mouse embryonic fibroblast NIH3T3 cells, and STAT1 knockout dramatically augmented ZIKV infection, suggesting a STAT1-mediated viral restriction. Intriguingly, in the STAT1-knockout NIH3T3 cells, complementation of mSTAT1.D695G, a cleavage-sensitive variant, and the wild-type mSTAT1 both restored comparable anti-viral activities. These data suggest that caspase-mediated STAT1 cleavage is dispensable for IFN antagonism in ZIKV-infected cells. IMPORTANCE Zika virus (ZIKV) is a re-emerging flavivirus. Similar to other flaviviruses, ZIKV antagonizes the host interferon (IFN) signaling pathway to establish infection. Understanding the molecular mechanism by which ZIKV antagonizes IFN-induced antiviral signaling may lead to a new antiviral strategy by cracking the IFN antagonism. Flaviviruses have been reported to employ NS5-dependent and -independent mechanisms to block STAT2-mediated signaling, whereas whether flaviviruses target STAT1 remains controversial. Herein, we found that ZIKV infection triggered caspase-dependent cleavage of STAT1 at the aspartic acid 694 during late infection, whereas murine STAT1 (mSTAT1) was resistant to cleavage. Intriguingly, ectopically expressed cleavage-resistant human STAT1.D694A or complementation of cleavable mSTAT1.D695G exerted comparable anti-ZIKV activity with their counterparts, challenging the role of caspase-mediated STAT1 cleavage in the IFN antagonism in ZIKV-infected cells. These data may also imply a dominant role of the antagonism of STAT2 but not STAT1 in ZIKV-infected cells.

BackgroundAdult degenerative scoliosis (ADS) is forecast to be a prevalent disabling condition in an aging society. Universally, its pathogenesis is perceived as intervertebral disc degeneration (IDD), however, a thought-provoking issue is why precisely a subset of patients with disc degeneration develop ADS. Exploring the diversities between common IDD and ADS would contribute to unraveling the etiological mechanisms of ADS. Therefore, we aimed to integrate the circRNA, lncRNA, miRNA, and mRNA expression profiles from normal adults (Normal), patients with lumbar disc herniation (LDH), and ADS by whole transcriptome sequencing, which identifies critical functional ncRNA and ceRNA networks and crosstalk between the various transcripts.MethodsThe fresh whole blood samples (n = 3/group) were collected from ADS patients, LDH patients, and healthy volunteers (Normal group), which were examined for mRNA, miRNA, lncRNA, and circRNA expression and screened for differentially expressed (DE) ncRNAs. Then, Gene Ontology (GO) and KEGG analyses were performed for gene annotation and enrichment pathways on the DE RNAs, which were constructed as a lncRNA-miRNA-mRNA network. Eventually, DE RNAs were validated by qRT-PCR targeting disc nucleus pulposus (NP) tissue in ADS and LDH group (n = 10/group).ResultsCompared to the LDH group, we identified 3322 DE mRNAs, 221 DE lncRNAs, 20 DE miRNAs, and 15 DE circRNAs in the ADS. In contrast to Normal, 21 miRNAs and 19 circRNAs were differentially expressed in the ADS. The expression of multiple differentially expressed ncRNAs was confirmed by qRT-PCR analysis to be consistent with the sequencing results. In addition, GO, and KEGG analysis demonstrated that most DE mRNAs and ncRNAs target genes are involved in various biological processes, including Endocytosis, Apoptosis, Rap1 signaling pathway, Notch signaling pathway, and others. The constructed lncRNA-miRNA-mRNA co-expression network was primarily related to angiogenesis and regulation.ConclusionBy focusing on comparing asymmetric and symmetric disc degeneration, whole-transcriptome sequencing and bioinformatics analysis systematically screened for key ncRNAs in the development of ADS, which provided an abundance of valuable candidates for the elucidation of regulatory mechanisms. The DE ncRNAs and the lncRNA-miRNA-mRNA network are intrinsically involved in the regulation of mediator and angiogenesis, which may contribute to the insight into the pathogenesis of ADS.

The peak detect and sample hold (PDSH) circuit is an important component of the light detection and ranging (LiDAR) system, because the PDSH circuit can correct the walk error of the time discriminator, and distinguish different objects at the same location. However, due to the requirement for high-precision measurement of nanosecond-scale pulse signals, the design of the PDSH circuit presents significant challenges. This paper accomplishes the modeling of the PDSH circuit, including the modeling of the PDSH measurement speed and the voltage step, quantifies various factors that affect the PDSH circuit measurement results, and makes predictions based on the model. Through the derivation and simplification of the rise process in the PDSH circuit, this study establishes a mathematical model to predict the performance of the PDSH circuit. Furthermore, this study also investigates the effect of circuit delay time on the measurement speed of the PDSH circuit. Meanwhile, this study analyzes the voltage step process, and an equivalent circuit model is derived through theoretical analysis. By utilizing a fitting method, the equivalent capacitance value of the diode is obtained. The simulation and experiment results show that the errors between the measurement speed model of the PDSH circuit and the actual circuit are no more than 1.98 ns and 2.03 ns, respectively. Thus, the measurement speed model can accurately predict whether the PDSH circuit meets the requirements. Moreover, the maximum absolute error of the equivalent circuit model is 19.87 mV, which can significantly reduce the error caused by the voltage step.

Abstract. Background:. Systemic lupus erythematosus (SLE) is a complex autoimmune disease, and the mechanism of SLE is yet to be fully elucidated. The aim of this study was to explore the role of two-pore segment channel 2 (TPCN2) in SLE pathogenesis. Methods:. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of TPCN2 in SLE. We performed a loss-of-function assay by lentiviral construct in Jurkat and THP-1 cell. Knockdown of TPCN2 were confirmed at the RNA level by qRT-PCR and protein level by Western blotting. Cell Count Kit-8 and flow cytometry were used to analyze the cell proliferation, apoptosis, and cell cycle of TPCN2-deficient cells. In addition, gene expression profile of TPCN2-deficient cells was analyzed by RNA sequencing (RNA-seq). Results:. TPCN2 knockdown with short hairpin RNA (shRNA)-mediated lentiviruses inhibited cell proliferation, and induced apoptosis and cell-cycle arrest of G2/M phase in both Jurkat and THP-1 cells. We analyzed the transcriptome of knockdown-TPCN2-Jurkat cells, and screened the differential genes, which were enriched for the G2/M checkpoint, complement, and interleukin-6-Janus kinase-signal transducer and activator of transcription pathways, as well as changes in levels of forkhead box O, phosphatidylinositol 3-kinase/protein kinase B/mechanistic target of rapamycin, and T cell receptor pathways; moreover, TPCN2 significantly influenced cellular processes and biological regulation. Conclusion:. TPCN2 might be a potential protective factor against SLE.

Abstract A novel liquid crystal beam‐steerable antenna is presented. It is a conventional liquid crystal microstrip patch antenna with a bending slot in the middle of the H‐plane. Owing to the introduction of the bending slot, this antenna can work at even mode and odd mode within a frequency band. To obtain the resonant frequencies and radiation characteristics of the two modes, the method of characteristic mode analysis is utilised. It indicates that the resonant frequency of even mode is lower than that of odd mode. Therefore, by choosing liquid crystal as its substrate, this antenna can alter its operating modes by varying the permittivity of liquid crystal. Furthermore, beam steering can be realised since the radiation patterns of the two modes are divergent. An antenna prototype at Ka‐band has been designed, fabricated and measured. The measured results show that the maximum radiation direction can scan from −30° to −2° continuously at 26.5 GHz in the H‐plane.

Tendinopathy refers to a type of tendon disease with a multifactorial spectrum. Recent research has begun to reveal the effects of inflammation on the tendinopathic process, especially in the first stage of tendinopathy. Radial extracorporeal shock wave therapy (rESWT) has been successfully used to treat orthopedic diseases. However, the molecular mechanisms underlying the anti-inflammatory effects of rESWT on tumor necrosis factor-α treated tenocytes have not been fully elucidated. In this study, we applied total protein tandem mass tag-labeled quantitative proteomics with liquid chromatography-mass spectrometer/mass spectrometer technology to identify differentially expressed proteins (DEPs) among inflammatory tenocytes, rESWT inflammatory tenocytes, and controls using three biological replicates. Human tenocytes were used and they were cultured in vitro. In total, 1028 and 40 DEPs were detected for control versus inflammatory tenocytes and for inflammatory tenocytes versus rESWT inflammatory tenocytes, respectively. Further, we identified integrin α2, selenoprotein S, and NLR family CARD domain-containing protein 4 as pivotal molecular targets of the anti-inflammatory effects of rESWT. This is the first study to provide a reference proteomic map for inflammatory tenocytes and rESWT inflammatory tenocytes. Our findings provide crucial insight into the molecular mechanisms underscoring the anti-inflammatory effects of rESWT in tendinopathy.

Abstract Background Reduced exercise tolerance is an important clinical feature of chronic obstructive pulmonary disease (COPD) and is associated with poor prognosis. The 6-min walk test (6MWT) is widely used to assess exercise capacity; however, it is not commonly administered in primary medical institutions because it requires a suitable site and professional training. Ultrasound has great potential for evaluating skeletal muscle dimensions in COPD. However, whether skeletal muscle ultrasound can predict impaired exercise tolerance is unclear. Methods The study included 154 stable patients with COPD, who were randomly divided into a development set and a validation set. The thickness (RFthick) and cross-sectional area (RFcsa) of the rectus femoris were measured using ultrasound. Standardized RFthick (STD- RFthick) and Standardized RFcsa (STD-RFcsa) were obtained via standardization of RFthick and RFcsa by patients' height. Results Strong correlations were observed between the 6MWD and RFthick (r = 0.84, p

BackgroundVascular dementia (VaD) and carotid atherosclerotic plaques are common in the elderly population, conferring a heavy burden on families and society. Accumulating evidence indicates carotid atherosclerotic plaques to be a risk factor for VaD. However, the underlying mechanisms for this association are mainly unknown.Materials and methodsWe analyzed temporal cortex gene expression data of the GSE122063 dataset and gene expression data of the GSE163154 dataset to identify commonly differentially expressed genes (DEGs). Then we performed functional enrichment analysis, immune cell infiltration and evaluation, correlation analysis between differentially expressed immune-related genes (DEIRGs) and immune cells, receiver operating characteristic (ROC) analysis, and drug-gene analysis.ResultsWe identified 41 overlapped DEGs between the VaD and carotid atherosclerosis plaque datasets. Functional enrichment analyses revealed that these overlapped DEGs were mainly enriched in inflammatory and immune-related processes. Immunocyte infiltration and evaluation results showed that M0 macrophages, M2 macrophages, and T cells gamma delta had a dominant abundance in carotid atherosclerosis plaque samples, and M0 macrophages showed a significantly different infiltration percentage between the early and advanced stage plaques group. Resting CD4 memory T cells, M2 macrophages, and naive B cells were the top three highest infiltrating fractions in VaD. Furthermore, B cells and NK cells showed a different infiltration percentage between VaD and matched controls. We identified 12 DEIRGs, and the result of correlation analysis revealed that these DEIRGs were closely related to differentially expressed immune cells. We identified five key DEIRGs based on ROC analysis. The drug-gene interaction analysis showed that four drugs (avacopan, CCX354, BMS-817399, and ASK-8007) could be potential drugs for VaD and carotid atherosclerotic plaques treatment.ConclusionCollectively, these findings indicated that inflammatory and immune-related processes be a crucial common pathophysiological mechanism shared by VaD and carotid plaques. This study might provide new insights into common molecular mechanisms between VaD and carotid plaques and potential targets for the treatment.

The intelligent diagnosis of premium threaded connections (PTCs) is vital for ensuring the robust and leak-proof performance of tubing under high-temperature, high-pressure, acidic gas conditions. However, achieving accurate diagnostic results necessitates a substantial number of PTCs curves under diverse make-up conditions, presenting considerable challenges in practical industrial detection. In this study, we introduce an end-to-end classification model, which combines an asynchronously optimized two-dimensional deep convolutional generative adversarial network (AoT-DCGAN) and a two-dimensional convolutional neural network (T-CNN), designed to enhance the classification performance under small sample size. Our proposed method first leverages AoT-DCGAN to identify the distribution patterns of the original samples and generate synthetic counterparts. Concurrently, we implement a novel weight optimization strategy, termed asynchronous optimization (AO), to alleviate the issue of gradient vanishing during the generator’s optimization phase. Following this, a novel T-CNN model is devised and trained on the enlarged dataset to automate the classification of PTCs curves. The performance evaluation of our method, based on recall, specificity, F1-score, precision values, and confusion matrices at varying data augmentation ratios, demonstrates that the model’s classification capabilities are enhanced as the dataset size escalates, peaking at a dataset size of 1200. Moreover, given the same training set, the T-CNN model outperforms traditional machine learning and deep learning models, achieving classification accuracies of up to 95.9%, 95.5%, and 96.7% for the AC, ATI, and NDT curves, respectively. Lastly, it was confirmed that applying asynchronous optimization in the DCGAN training process results in a more consistent decline in the loss function.

Background: Numerous studies have suggested that programmed cell death (PCD) pathways play vital roles in cerebral ischemia/reperfusion (I/R) injury. However, the specific mechanisms underlying cell death during cerebral I/R injury have yet to be completely clarified. There is thus a need to identify the PCD-related gene signatures and the associated regulatory axes in cerebral I/R injury, which should provide novel therapeutic targets against cerebral I/R injury.Methods: We analyzed transcriptome signatures of brain tissue samples from mice subjected to middle cerebral artery occlusion/reperfusion (MCAO/R) and matched controls, and identified differentially expressed genes related to the three types of PCD(apoptosis, pyroptosis, and necroptosis). We next performed functional enrichment analysis and constructed PCD-related competing endogenous RNA (ceRNA) regulatory networks. We also conducted hub gene analysis to identify hub nodes and key regulatory axes.Results: Fifteen PCD-related genes were identified. Functional enrichment analysis showed that they were particularly associated with corresponding PCD-related biological processes, inflammatory response, and reactive oxygen species metabolic processes. The apoptosis-related ceRNA regulatory network was constructed, which included 24 long noncoding RNAs (lncRNAs), 41 microRNAs (miRNAs), and 4 messenger RNAs (mRNAs); the necroptosis-related ceRNA regulatory network included 16 lncRNAs, 20 miRNAs, and 6 mRNAs; and the pyroptosis-related ceRNA regulatory network included 15 lncRNAs, 18 miRNAs, and 6 mRNAs. Hub gene analysis identified hub nodes in each PCD-related ceRNA regulatory network and seven key regulatory axes in total, namely, lncRNA Malat1/miR-181a-5p/Mapt, lncRNA Malat1/miR-181b-5p/Mapt, lncRNA Neat1/miR-181a-5p/Mapt, and lncRNA Neat1/miR-181b-5p/Mapt for the apoptosis-related ceRNA regulatory network; lncRNA Neat1/miR-181a-5p/Tnf for the necroptosis-related ceRNA regulatory network; lncRNA Malat1/miR-181c-5p/Tnf for the pyroptosis-related ceRNA regulatory network; and lncRNAMalat1/miR-181a-5p for both necroptosis-related and pyroptosis-related ceRNA regulatory networks.Conclusion: The results of this study supported the hypothesis that these PCD pathways (apoptosis, necroptosis, pyroptosis, and PANoptosis) and crosstalk among them might be involved in ischemic stroke and that the key nodes and regulatory axes identified in this study might play vital roles in regulating the above processes. This may offer new insights into the potential mechanisms underlying cell death during cerebral I/R injury and provide new therapeutic targets for neuroprotection.

Objective: Owing to the intensification of the aging process worldwide, the prevalence of adult degenerative scoliosis (ADS) is increasing at an alarming rate. However, genomic research related to the etiology of ADS is rarely reported worldwide. Since long noncoding RNAs (lncRNAs) play a pivotal role in the progression of human diseases, this study aimed to investigate ADS-associated messenger RNAs (mRNAs) and lncRNAs by RNA sequencing (RNA-seq), as well as performed comprehensive bioinformatics analysis based on the lncRNA–mRNA coexpression network and protein–protein interaction (PPI) network.Methods: Initially, six whole blood (WB) samples were obtained from three ADS and three nondegenerative lumbar trauma patients who underwent surgical operation for RNA-seq exploration to construct differential mRNA and lncRNA expression profiles. Subsequently, quantitative RT-PCR (qRT-PCR) was performed to validate three randomly selected differentially expressed mRNAs and lncRNAs derived from the nucleus pulposus (NP) tissue of 14 other subjects (seven ADS patients and seven nondegenerative lumbar trauma patients), respectively.Results: A total of 1,651 upregulated and 1,524 downregulated mRNAs and 147 upregulated and 83 downregulated lncRNAs were screened out from the RNA-Seq data, which constructed coexpression networks to investigate their regulatory interactions further. GO gene function prediction revealed that lncRNA-targeted genes might play a vital role in ADS via participation in multiple biological processes such as the AMPK signaling pathway, lysosomes, and ubiquitin-mediated proteolysis, as well as cellular metabolic processes. Moreover, the expression levels of three selected lncRNAs and mRNAs were validated by qRT-PCR, respectively, demonstrating that the relative expression levels were consistent with the RNA-seq data. Notably, the dysregulated RNAs, AKT1, UBA52, PTPN12, and CLEC16A, were significantly differentially expressed in ADS WB samples and might serve as potentially regulated genes for research in the future.Conclusions: This study provides the first insight into the altered transcriptome profile of long-stranded noncoding RNAs associated with ADS, which paves the way for further exploration of the clinical biomarkers and molecular regulatory mechanisms for this poorly understood degenerative disease. However, the detailed biological mechanisms underlying these candidate lncRNAs in ADS necessitate further elucidation in future studies.

The liver is essential for metabolic and immune functions and has been linked to systemic inflammatory diseases. However, the role of the liver is still elusive during the development of rheumatoid arthritis (RA), although there have been indeed some reports. We used label-free quantitative proteomics and experimental verification in this study to reveal the hepatic lipid metabolism and immune function during collagen-induced arthritis (CIA) development. The proteomics results revealed that the role of the liver differs in different phases of CIA rats. In terms of specific performance, hepatic lipid metabolism, which is primarily concerned with cholesterol, triacylglycerol, and phospholipid, was significantly influenced in the CIA induction phase, whereas the immune function, which includes binding of granulocytes, adhesion of immune cells, etc., was affected considerably at the peak phase of CIA rats compared to normal rats. Finally, the hepatic dynamic changes in CIA rats were further confirmed using targeted metabolomics and ELISA. We found that most fatty acids of the liver in the CIA induction phase were significantly decreased, and proteins related to complement activation and migration or adhesion of immune cells including C3, MMP-8, CTSZ, and S100A9 were significantly increased in the liver of CIA rats in the peak phase. Our findings indicated that the lipid metabolism and immune function of the liver were influenced in CIA rats. Thus, the conditions of the liver during RA development should be considered in therapeutic and nutritional interventions.

Electroencephalogram (EEG) authentication has become a research hotspot in the field of information security due to its advantages of living, internal, and anti-stress. However, the performance of identity authentication system is limited by the inherent attributes of EEG, such as low SNR, low stability, and strong randomness. Researchers generally believe that the in-depth fusion of features can improve the performance of identity authentication and have explored among various feature domains. This experiment invited 70 subjects to participate in the EEG identity authentication task, and the experimental materials were visual stimuli of the self and non-self-names. This paper proposes an innovative EEG authentication framework, including efficient three-dimensional representation of EEG signals, multi-scale convolution structure, and the combination of multiple authentication strategies. In this work, individual EEG signals are converted into spatial–temporal–frequency domain three-dimensional forms to provide multi-angle mixed feature representation. Then, the individual identity features are extracted by the various convolution kernel of multi-scale vision, and the strategy of combining multiple convolution kernels is explored. The results show that the small-size and long-shape convolution kernel is suitable for ERP tasks, which can obtain better convergence and accuracy. The experimental results show that the classification performance of the proposed framework is excellent, and the multi-scale convolution method is effective to extract high-quality identity characteristics across feature domains. The results show that the branch number matches the EEG component number can obtain the excellent cost performance. In addition, this paper explores the network training performance for multi-scale module combination strategy and provides reference for deep network construction strategy of EEG signal processing.

Wound repair is a key step in the treatment of skin injury caused by burn, surgery, and trauma. Various stem cells have been proven to promote wound healing and skin regeneration as candidate seed cells. Therefore, exosomes derived from stem cells are emerging as a promising method for wound repair. However, the mechanism by which exosomes promote wound repair is still unclear. In this study, we reported that exosomes derived from umbilical cord mesenchymal stem cells (UC-MSCs) promote wound healing and skin regeneration by treating cutaneous nerve damage. The results revealed that UC-MSCs exosomes (UC-MSC-Exo) promote the growth and migration of dermal fibroblast cells. In in vitro culture, dermal fibroblasts could promote to nerve cells and secrete nerve growth factors when stimulated by exosomes. During the repair process UC-MSC-Exo accelerated the recruitment of fibroblasts at the site of trauma and significantly enhanced cutaneous nerve regeneration in vivo. Interestingly, it was found that UC-MSC-Exo could promote wound healing and skin regeneration by recruiting fibroblasts, stimulating them to secrete nerve growth factors (NGFs) and promoting skin nerve regeneration. Therefore, we concluded that UC-MSC-Exo promote cutaneous nerve repair, which may play an important role in wound repair and skin regeneration.

Abstract Solid-state electrolyte (SSE) of the sodium-ion battery have attracted tremendous attention in the next generation energy storage materials on account of their wide electrochemical window and thermal stability. However, the high interfacial impedance, low ion transference number and complex preparation process restrict the application of SSE. Herein, inspired by the excellent sieving function and high specific surface area of red blood cells, we obtained a solid-like electrolyte (SLE) based on the combination of the pancake-like metal–organic framework (MOF) with liquid electrolyte, possessing a high ionic conductivity of 6.60 × 10–4 S cm−1, and excellent sodium metal compatibility. In addition, we investigated the ion restriction effect of MOF’s apertures size and special functional groups, and the ion transference number increased from 0.16 to 0.33. Finally, the assembled Na0.44MnO2//SLE//Na full batteries showed no obvious capacity decrease after 160 cycles. This material design of SLE in our work is an important key to obtain fast ion migration SLE for high-performance sodium-ion batteries.

Different jadeites have different characteristics. In this paper, the La-ICP-MS test is used to compare and analyze the elemental characteristics of jadeite in Guatemala and the Qing dynasty. The test results show that the highest value of Guatemalan jadeite Ca can reach 2.5 apfu, while the highest value of Qing dynasty jadeite is 0.73 apfu. The highest value of Na is the same for both. The concentration distribution range and highest value of Guatemalan jadeite and Qing dynasty jadeite Mg/(Mg + Fe) are the same. Guatemalan jadeite and Qing dynasty jadeite have a very wide content of trace elements. Qing dynasty Ca/(Mg + Fe) distribution is wider. Concentrations of Guatemalan and Qing dynasty jadeite Sr/Ba, which is a marine sediment, are greater than 1. The Ba in the Qing dynasty jadeite sediments contains a large amount of clay, resulting in higher levels than the average amount in Guatemalan jadeite Ba. The standard distribution map is similar, showing a “horn” shape. The Sr distribution is uneven. Guatemalan jadeite is heavily enriched in rare earths. Eu shows positive and negative abnormalities. The total rare earth value is 8.15 ppm. Qing Dynasty jadeite shows light rare earth enrichment, and Eu is a positive anomaly. The total rare earth value is 7.07 ppm. The characteristics of the two elements are somewhat similar, but different, which does not rule out the possibility that Qing dynasty jadeite came from Guatemala.

Flavivirus genus includes numerous arthropod-borne human pathogens that are clinically important. Flaviviruses are notorious for their ability to antagonize host interferon (IFN) induced anti-viral signalling. It has been documented that NS5s of flaviviruses mediate proteasome degradation of STAT2 to evade IFN signalling. Deciphering the molecular mechanism of the IFN antagonism by the viruses and reversing this antagonism may dictate anti-viral responses and provide novel antiviral approaches. In this report, by using Zika virus (ZIKV) as a model, we first demonstrated that ZIKV antagonized interferon signalling in an infectious dose-dependent manner; in other words, the virus antagonized interferon signalling at a high multiple of infection (MOI) and was sensitive to interferon signalling at a low MOI. Mechanistically, we found that ZIKV infection triggered degradation of ubiquitinated STAT2 and host short-lived proteins while didn't affect the proteasome activity per se. ZIKV infection resulted in suppression of host de novo protein synthesis. Overexpression of NS5 alone only marginally reduced STAT2 and had no effect on the host de novo protein synthesis. Ectopically expressed murine STAT2 that was resistant to NS5- and ZIKV-induced ablation exaggerated the IFN-induced anti-viral signalling. These data favour a new model of the innate immune evasion of ZIKV in which the viral infection triggers suppression of host de novo protein synthesis to accelerate the degradation of short-lived, ubiquitinated STAT2. As flaviviruses share a very conserved replication strategy, the mechanisms of IFN antagonism elucidated here might also be employed by other flaviviruses.

The accumulation of abnormal aggregation of amyloid-β plaques is one of the most distinguishing pathologies of Alzheimer’s disease (AD) and is highly toxic to neurons. Exosomes have demonstrated great potential for AD therapy. However, the impact and underlying mechanism of M2 microglia-derived exosomes (M2-EXOs) in AD progression and outcome are seldom explored. Therefore, we employed an Aβ1-42 oligomer (Aβ)-induced AD model in neuronal HT-22 cells and 7-month-old APP/PS1 mice to investigate the effects of M2-EXOs on AD. We revealed that the AD cell model established by Aβ was accompanied by the upregulation of Aβ1-42, neuronal death, alternation of mitochondrial function and autophagy. M2-EXOs can be internalized by HT-22 cells and MAP2-positive neuronal cells in APP/PS1 mice, and exert neuroprotective functions. Specifically, the administration of M2-EXOs in the AD cell model partially increased cell viability, restored the destruction of mitochondrial membrane potential, and reduced the accumulation of reactive oxygen species inside the mitochondria and cells in a dose-dependent manner. Moreover, we demonstrated that PINK1/Parkin mediated mitophagy was enhanced, while incubation with M2-EXOs decreased beclin1, LC3II, PINK1, and Parkin expression levels. Finally, we observed that compared with APP/PS1 mice treated with PBS, the application of M2-EXOs could decrease Aβ plaque deposition and minus Aβ oligomer expression along with improved PINK1/Parkin pathway-mediated autophagy. Overall, our results imply that M2-EXOs play a protective role in the pathogenesis of AD by ameliorating PINK1/Parkin-mediated mitophagy, indicating that it may provide a novel therapeutic strategy to treat AD.

Abstract Background Rheumatoid arthritis (RA) is an autoimmune disease characterized by synovitis. Pien Tze Huang (PZH) is a Chinese patent medicine with anti-inflammatory and immunomodulatory effects. However, whether PZH could be used in RA therapy is still unknown. Therefore, this study aimed to explore the therapeutic effect and the potential mechanism of PZH on collagen-induced arthritis (CIA) mice. Methods Male DBA/1J mice were used to establish an animal model of CIA and then treated with different doses of PZH for 4 weeks. The therapeutic effect of PZH on CIA mice was evaluated by arthritis score, pathological staining, and detecting the levels of inflammatory factors in serum and joints. To investigate its possible mechanism, the activity of NF-κB signaling pathway, NLRP3 inflammasome and the level of A20 were detected. Results The results showed that PZH could alleviate the erythema and swelling of hind paws of CIA mice, improve the pathological conditions of joint and decrease the production of IL-1β, IL-6 and IL-17 in serum and joints. Furthermore, PZH could significantly inhibit the activity of NF-κB signaling pathway and NLRP3 inflammasome in the ankle joint of CIA mice compared with the model group. It also increased the level of A20 in the ankle joint of CIA mice. Conclusion This study indicated that PZH could alleviate the joint inflammation of CIA mice, and the mechanism might be related to the regulation of NF-κB signaling pathway and NLRP3 inflammasome.

A novel beam steerable antenna employing tunable high impedance surface with liquid crystal is proposed. This antenna utilizes three microstrip patches as the radiators and a tunable high impedance surface based on liquid crystal as the ground plane. In this design, liquid crystal is deliberately disposed under the two parasitic microstrip patches to reduce the effect of relatively large dielectric loss and to improve the gain and radiation efficiency of the antenna. More importantly, this work explores a tunable high impedance surface based on liquid crystal, which has advantages of simple structure and biasing scheme as compared with other tunable high impedance surfaces based on solid-state devices. It is shown that by tuning the permittivity of liquid crystal, the high impedance surface becomes to support the propagation of TE surface waves to strengthen the mutual coupling between main and parasitic microstrip patches. Consequently, the main lobe can be steered to the desired direction and the scanning range of the antenna is enlarged. To prove this novel concept, a Ka-band prototype is fabricated and tested. Measured results show that the antenna not only has acceptable gain, but also keeps a satisfactory scanning range. In addition, this antenna consumes negligible DC power and thus is a strong antenna competitor for 5G access point applications.

Vascular dementia (VaD) is considered to be the second most common form of dementia after Alzheimer’s disease, and no specific drugs have been approved for VaD treatment. We aimed to identify shared transcriptomic signatures between the frontal cortex and temporal cortex in VaD by bioinformatics analyses. Gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) and hub gene identification, hub gene–transcription factor interaction, hub gene–microRNA interaction, and hub gene–drug interaction analyses were performed. We identified 159 overlapping differentially expressed genes (DEGs) between the frontal cortex and temporal cortex that were enriched mainly in inflammation and innate immunity, synapse pruning, regeneration, positive regulation of angiogenesis, response to nutrient levels, and positive regulation of the digestive system process. We identified 10 hub genes in the PPI network (GNG13, CD163, C1QA, TLR2, SST, C1QB, ITGB2, CCR5, CRH, and TAC1), four central regulatory transcription factors (FOXC1, CREB1, GATA2, and HINFP), and four microRNAs (miR-27a-3p, miR-146a-5p, miR-335-5p, and miR-129-2-3p). Hub gene–drug interaction analysis found four drugs (maraviroc, cenicriviroc, PF-04634817, and efalizumab) that could be potential drugs for VaD treatment. Together, our results may contribute to understanding the underlying mechanisms in VaD and provide potential targets and drugs for therapeutic intervention.

Electroencephalography (EEG)-based emotion computing has become one of the research hotspots of human-computer interaction (HCI). However, it is difficult to effectively learn the interactions between brain regions in emotional states by using traditional convolutional neural networks because there is information transmission between neurons, which constitutes the brain network structure. In this paper, we proposed a novel model combining graph convolutional network and convolutional neural network, namely MDGCN-SRCNN, aiming to fully extract features of channel connectivity in different receptive fields and deep layer abstract features to distinguish different emotions. Particularly, we add style-based recalibration module to CNN to extract deep layer features, which can better select features that are highly related to emotion. We conducted two individual experiments on SEED data set and SEED-IV data set, respectively, and the experiments proved the effectiveness of MDGCN-SRCNN model. The recognition accuracy on SEED and SEED-IV is 95.08 and 85.52%, respectively. Our model has better performance than other state-of-art methods. In addition, by visualizing the distribution of different layers features, we prove that the combination of shallow layer and deep layer features can effectively improve the recognition performance. Finally, we verified the important brain regions and the connection relationships between channels for emotion generation by analyzing the connection weights between channels after model learning.

One of the greatest limitations in the field of EEG-based emotion recognition is the lack of training samples, which makes it difficult to establish effective models for emotion recognition. Inspired by the excellent achievements of generative models in image processing, we propose a data augmentation model named VAE-D2GAN for EEG-based emotion recognition using a generative adversarial network. EEG features representing different emotions are extracted as topological maps of differential entropy (DE) under five classical frequency bands. The proposed model is designed to learn the distributions of these features for real EEG signals and generate artificial samples for training. The variational auto-encoder (VAE) architecture can learn the spatial distribution of the actual data through a latent vector, and is introduced into the dual discriminator GAN to improve the diversity of the generated artificial samples. To evaluate the performance of this model, we conduct a systematic test on two public emotion EEG datasets, the SEED and the SEED-IV. The obtained recognition accuracy of the method using data augmentation shows as 92.5 and 82.3%, respectively, on the SEED and SEED-IV datasets, which is 1.5 and 3.5% higher than that of methods without using data augmentation. The experimental results show that the artificial samples generated by our model can effectively enhance the performance of the EEG-based emotion recognition.

Mild behavioral impairment (MBI), characterized by the late-life onset of sustained and meaningful neuropsychiatric symptoms, is increasingly recognized as a prodromal stage of dementia. However, the underlying neural mechanisms of MBI remain unclear. Here, we examined alterations in the topological organization of the structural covariance networks of patients with MBI (N = 32) compared with normal controls (N = 38). We found that the gray matter structural covariance networks of both the patients with MBI and controls exhibited a small-world topology evidenced by sigma value larger than one. The patients with MBI had significantly decreased clustering coefficients at several network densities and local efficiency at densities ranging from 0.05 to 0.26, indicating decreased local segregation. No significant differences in the characteristic path length, gamma value, sigma value, or global efficiency were detected. Locally, the patients with MBI showed significantly decreased nodal betweenness centrality in the left middle frontal gyrus, right inferior frontal gyrus (opercular part), and left Heschl gyrus and increased betweenness centrality in the left gyrus rectus, right insula, bilateral precuneus, and left thalamus. Moreover, the difference in the bilateral precuneus survived after correcting for multiple comparisons. In addition, a different number and distribution of hubs was identified in patients with MBI, showing more paralimbic hubs than observed in the normal controls. In conclusion, we revealed abnormal topological patterns of the structural covariance networks in patients with MBI and offer new insights into the network dysfunctional mechanisms of MBI.

Background: The disruption of joint homeostasis is a critical event during the process of joint injury in osteoarthritis (OA). As regulatory molecules, microRNAs (miRNAs) can be released from secretory cells and delivered to recipient cells through extracellular vesicles (EVs), thereby playing an important role in regulating joint homeostasis. We hypothesized that the fibroblast-like synoviocytes (FLSs) in healthy joints could release EVs enriched in miRNAs that can maintain joint homeostasis by regulating the signal transduction pathways in the joints, whereby the articular cartilage (AC) is protected from degeneration, and OA progression is delayed. Methods: Via high-throughput sequencing and qPCR, we found that miR-150-3p was enriched in the circulating EVs in healthy rats. Next, we established an in vitro cell model in which chondrocytes were cultured with (i) FLSs transfected with miR-150-3p mimics or (ii) EVs released by FLSs (FLS–EVs) inside the healthy synovial membrane (SM). The transportation mechanism from FLSs to chondrocytes was studied using the EV inhibitor GW4869, and the FLSs were transfected with a miR-150-3p mimic or inhibitor. To assess the therapeutic effect of miR-150-3p-carrying EVs (EVs-150) in vivo, healthy FLS-derived EVs (H-FLS–EVs) were injected into the tail vein of rats with OA at various stages of the pathogenesis and evaluated for the progression of OA. Results: The chondrocytes could uptake fluorescent-labeled miR-150-3p mimics and FLS–EVs, and GW4869 suppressed this uptake. The overexpression of miR-150-3p could significantly reduce the concentrations of pro-inflammatory cytokines in the cell culture medium and the expression of the miR-150-3p target T cell receptor-interacting molecule 14 (Trim14), as well as the innate immune-related factors, including nuclear factor kappa B (NF-κB) and interferon-β (IFN-β). Similarly to the in vitro findings, the miR-150-3p level in the serum EVs was significantly upregulated among the EV-treated rats. In the AC of the OA rat model injected with H-FLS–EVs, the joint degeneration was suppressed, and Type II collagen (COLII) and aggrecan (ACAN) were significantly upregulated, whereas the innate immune-related factors Trim14, NF-κB, and IFN-β were downregulated compared with the levels in the untreated OA rats. Notably, the suppression of joint degeneration was more significant when H-FLS–EVs were administered at the early stages of OA rather than the late stages. Conclusion: H-FLS–EVs protect chondrocyte function and maintain joint homeostasis by modulating the innate immune response by suppressing the Trim14/NF-κB/IFNβ axis. These effects are achieved through the EV-mediated transport of miR-150-3p from the FLSs to the chondrocytes. Our findings show that EV-mediated miR-150-3p can be used to suppress OA, thus providing a novel therapeutic strategy. Additionally, the EV-mediated miR-150-3p transport may also serve as a potential biomarker in the diagnosis, treatment, and prognosis of OA.

Single-trial electroencephalogram detection has been widely applied in brain-computer interface (BCI) systems. Moreover, an individual generalized model is significant for applying the dynamic visual target detection BCI system in real life because of the time jitter of the detection latency, the dynamics and complexity of visual background. Hence, we developed an unsupervised multi-source domain adaptation network (P3-MSDA) for dynamic visual target detection. In this network, a P3 map-clustering method was proposed for source domain selection. The adversarial domain adaptation was conducted for domain alignment to eliminate individual differences, and prediction probabilities were ranked and returned to guide the input of target samples for imbalanced data classification. The results showed that individuals with a strong P3 map selected by the proposed P3 map-clustering method perform best on the source domain. Compared with existing schemes, the proposed P3-MSDA network achieved the highest classification accuracy and F1 score using five labeled individuals with a strong P3 map as the source domain. These findings can have a significant meaning in building an individual generalized model for dynamic visual target detection.

Radiomic features extracted from segmented tumor regions have shown great power in gene mutation prediction, while deep learning–based (DL-based) segmentation helps to address the inherent limitations of manual segmentation. We therefore investigated whether deep learning–based segmentation is feasible in predicting KRAS/NRAS/BRAF mutations of rectal cancer using MR-based radiomics. In this study, we proposed DL-based segmentation models with 3D V-net architecture. One hundred and eight patients’ images (T2WI and DWI) were collected for training, and another 94 patients’ images were collected for validation. We evaluated the DL-based segmentation manner and compared it with the manual-based segmentation manner through comparing the gene prediction performance of six radiomics-based models on the test set. The performance of the DL-based segmentation was evaluated by Dice coefficients, which are 0.878 ± 0.214 and 0.955 ± 0.055 for T2WI and DWI, respectively. The performance of the radiomics-based model in gene prediction based on DL-segmented VOI was evaluated by AUCs (0.714 for T2WI, 0.816 for DWI, and 0.887 for T2WI+DWI), which were comparable to that of corresponding manual-based VOI (0.637 for T2WI, P=0.188; 0.872 for DWI, P=0.181; and 0.906 for T2WI+DWI, P=0.676). The results showed that 3D V-Net architecture could conduct reliable rectal cancer segmentation on T2WI and DWI images. All-relevant radiomics-based models presented similar performances in KRAS/NRAS/BRAF prediction between the two segmentation manners.

Biometric identity authentication technology is widely used in the field of information security. As a new biological method, electroencephalography (EEG) is gradually applied in biometric recognition, because scientists believe that practicability and portability are the development direction of EEG identity authentication. This work investigates the feasibility of using resting state EEG signals recorded by single-channel portable device for identity authentication. Single-channel EEG classification are effectively improved by using mixed-method in three feature domains (i.e., time, frequency, and time-frequency), feature selection (Rayleigh quotient) and classifier design (ensemble classifier). We invited 46 subjects to participate in the EEG identity authentication experiment. Experimental results show that the open-eyed resting state is an ideal authentication method, and the average classification accuracy of the authentication algorithm can reach 95.48% in 2 seconds, validating that the new method of processing single-channel EEG signals is especially useful in extrapolating EEG identity authentication to realistic field contexts.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Emotion recognition plays an important part in human-computer interaction (HCI). Currently, the main challenge in electroencephalogram (EEG)-based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network (TDANN) to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy (MMD) to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network (DANN) to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness (84%), anger (87.04%), and fear (85.32%) on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness (83.79%), anger (84.13%), and fear (81.72%) on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition.

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High-frequency electroencephalography (EEG) signals play an important role in research on human emotions. However, the different network patterns under different emotional states in the high gamma band (50–80 Hz) remain unclear. In this paper, we investigate different emotional states using functional network analysis on various frequency bands. We constructed multiple functional networks on different frequency bands and performed functional network analysis and time–frequency analysis on these frequency bands to determine the significant features that represent different emotional states. Furthermore, we verified the effectiveness of these features by using them in emotion recognition. Our experimental results revealed that the network connections in the high gamma band with significant differences among the positive, neutral, and negative emotional states were much denser than the network connections in the other frequency bands. The connections mainly occurred in the left prefrontal, left temporal, parietal, and occipital regions. Moreover, long-distance connections with significant differences among the emotional states were observed in the high frequency bands, particularly in the high gamma band. Additionally, high gamma band fusion features derived from the global efficiency, network connections, and differential entropies achieved the highest classification accuracies for both our dataset and the public dataset. These results are consistent with literature and provide further evidence that high gamma band EEG signals are more sensitive and effective than the EEG signals in other frequency bands in studying human affective perception.

The Chinese formula Pien Tze Huang (PZH) has been used to treat hepatocellular carcinoma (HCC) and showed positive clinical effects. However, the antitumor mechanism of PZH in HCC remains unclear. In this study, HCC xenograft Balb/c mice were treated with PZH; then, proteomics detection and Ingenuity Pathway Analysis (IPA) were used to analyze the differentiated phosphorylated proteins in tumor tissues. The results indicated that PZH could inhibit tumor weight by 50.76%. Eighty-four upregulated and 11 downregulated phosphorylated proteins were identified in PZH-treated mice. Twenty signaling pathways were associated with inflammation (including the IL-6 and TNFR1/2 pathways), cancer growth (including the p53 and FAK pathways), and the cell cycle (including the G2/M and G1/S checkpoint regulation pathways). Moreover, TNF-α, IL-6, and several typical differentially expressed phosphorylated proteins (such as p-CCNB1, p-FOXO3, and p-STAT3) in tumor tissues, tumor cell viability, and cell cycle arrest assay in vitro further verify the results of IPA. These results revealed that PZH achieved antitumor activity in HCC; the underlying mechanisms of which were mainly through regulating the inflammation-associated cytokine secretion, cancer growth pathways, and induction of G2/M arrest. These data provided the potential molecular basis for PZH to act as a therapeutic drug or a supplement to chemotherapy drugs for human HCC in the future.

Abstract To explore the impact of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids in nulliparous women on subsequent pregnancy and delivery. A retrospective analysis was conducted of nulliparous women who received HIFU treatment at Chongqing Medical University, Chongqing,China, from January 1, 2010, to January 1, 2015. A total of 189 cases were enrolled, the median follow-up time was three years. Among them,there were 131 cases pregnancy with a total of 133 times,the pregnancy rate was 69.3% (131/189),and the spontaneous conception rate was 95.4% (125/131). Of 131 pregnant women, 19 were on-going pregnancy, terminated pregnancy 114 times,which include 93 times successfully delivery with a 76.3% (87/114) full-term birth rate,and the cesarean section rate was 72.0% (67/93). Of 94 newborns,the average birth weight was (3.3 ± 0.4)kg (range:1.5–4.8 kg), and a pair of them were identical twins. The incidence of complications during pregnancy and delivery were 10.8% (10/93) and 7.5% (7/93),respectively,except one woman failed on-going pregnancy and one woman suffered hysterectomy due to the complications,others all successful pregnant and delivered. Multiple-factor regression analysis found that age and infertility history were the important factors that may affect pregnancy after HIFU (P

Porous microstructure pressure sensors that are highly sensitive, reliable, low-cost, and environment-friendly have aroused wide attention in intelligent biomedical diagnostics, human–machine interactions, and soft robots. Here, an all-tissue-based piezoresistive pressure sensor with ultrahigh sensitivity and reliability based on the bottom interdigitated tissue electrode and the top bridge of a microporous tissue/carbon nanotube composite was proposed. Such pressure sensors exhibited ultrahigh sensitivity (≈1911.4 kPa−1), fast response time (

The inclusion of microRNAs (miRNAs) in extracellular microvesicles/exosomes (named cardiosomes when deriving from cardiomyocytes) allows their active transportation and ensures cell-cell communication. We hypothesize that cardiosomal miRNAs play a pivotal role in the activation of myofibroblasts following ischemic injury. Using a murine model of myocardial infarction (MI), we tested our hypothesis by measuring in isolated fibroblasts and cardiosomes the expression levels of a set of miRNAs, which are upregulated in cardiomyocytes post-MI and involved in myofibroblast phenoconversion. We found that miR-195 was significantly upregulated in cardiosomes and in fibroblasts isolated after MI compared with SHAM conditions. Moreover, primary isolated cardiac fibroblasts were activated both when incubated with cardiosomes isolated from ischemic cardiomyocytes and when cultured in conditioned medium of post-MI cardiomyocytes, whereas no significant effect was observed following incubation with cardiosomes or medium from sham cardiomyocytes. Taken together, our findings indicate for the first time that a cardiomyocyte-specific miRNA, transferred to fibroblasts in form of exosomal cargo, is crucial in the activation of myofibroblasts.

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Currently, there is still lack of curative treatment for MS. Mesenchymal stem cell- (MSC-) based therapy is recently the subject of intense interest in autoimmune diseases. Here, we investigated the therapeutic effect and potential mechanism of human amnion mesenchymal cells (hAMC) on inflammation and remyelination in experimental autoimmune encephalomyelitis (EAE) mice. C57BL/6 mice were immunized with myelin oligodendrocyte glycoprotein (MOG) 35–55 peptide. hAMC were injected intraperitoneal when EAE was successfully established. The results demonstrated that application of hAMC significantly ameliorated the disease severity and histopathological changes in EAE mice. The production of proinflammatory cytokines such as IFN-γ, TNF-α, IL-1β, and IL-17A in the spleen and CNS was dramatically inhibited. Moreover, CD4+ T cells and CD8+ T cells in the CNS were also significantly decreased in EAE mice after hAMC treatment. In addition, hAMC treatment also promoted the production of neuron-repair factors (NGF, CNTF, and BDNF) in the CNS of EAE mice. In conclusion, these results indicated that hAMC could attenuate the inflammation and promote the remyelination in EAE mice, which might be a promising cell source for the therapy of MS.

Yupingfeng San (YPFS) is a representative Traditional Chinese Medicine (TCM) formula with accepted therapeutic effect on Asthma. However, its action mechanism is still obscure. In this study, we used network pharmacology to explore potential mechanism of YPFS on asthma. Nucleotide-binding oligomerization domain (NOD)-like receptor pathway was shown to be the top one shared signaling pathway associated with both YPFS and asthma. In addition, NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome was treated as target protein in the process of YPFS regulating asthma. Further, experimental validation was done by using LPS-stimulated U937 cells and ovalbumin (OVA)-sensitized BALB/c mice model. In vitro experiments showed that YPFS significantly decreased the production of TNF-α and IL-6, as well as both mRNA and protein levels of IL-1β, NLRP3, Caspase-1 and ASC in LPS-stimulated U937 cells. In vivo experiment indicated that YPFS treatment not only attenuated the clinical symptoms, but also reduced inflammatory cell infiltration, mucus secretion and MUC5AC production in lung tissue of asthmatic mice. Moreover, YPFS treatment remarkably decreased the mRNA and protein levels of IL-1β, NLRP3, Caspase-1 and ASC in lung tissue of asthmatic mice. In conclusion, these results demonstrated that YPFS could inhibit NLRP3 inflammasome components to attenuate the inflammatory response in asthma.

Discovering a new cell transplantation approach for treating chronic renal insufficiency is a goal of many nephrologists. In vitro-cultured peripheral blood mononuclear cells (PBMCs) were reprogrammed into induced mesenchymal stem cells (iMSCs) by using natural inducing agents made in our laboratory. The stem cell phenotype of the iMSCs was then identified. Unilateral ureteral obstruction (UUO) was used to create an animal model of chronic renal insufficiency characterized by renal interstitial fibrosis. The induced and non-induced PBMCs were transplanted, and the efficacy of iMSCs in treating chronic renal insufficiency was evaluated using a variety of methods. The ultimate goal was to explore the effects of iMSC transplantation on the treatment of chronic renal insufficiency, with the aim of providing a new therapeutic modality for this disease.

Electroencephalogram (EEG) signals, which originate from neurons in the brain, have drawn considerable interests in identity authentication. In this paper, a face image-based rapid serial visual presentation (RSVP) paradigm for identity authentication is proposed. This paradigm combines two kinds of biometric trait, face and EEG, together to evoke more specific and stable traits for authentication. The event-related potential (ERP) components induced by self-face and non-self-face (including familiar and not familiar) are investigated, and significant differences are found among different situations. On the basis of this, an authentication method based on Hierarchical Discriminant Component Analysis (HDCA) and Genetic Algorithm (GA) is proposed to build subject-specific model with optimized fewer channels. The accuracy and stability over time are evaluated to demonstrate the effectiveness and robustness of our method. The averaged authentication accuracy of 94.26% within 6 s can be achieved by our proposed method. For a 30-day averaged time interval, our method can still reach the averaged accuracy of 88.88%. Experimental results show that our proposed framework for EEG-based identity authentication is effective, robust, and stable over time.

Astragalus polysaccharides (APS), one of main bioactive components in Astragalus membranaceus Bunge, has been reported to possess anti-inflammatory activities, but the molecular mechanisms behind this activity are largely unknown. This study aimed to investigate expression of inflammatory cytokines and the MAPK/NF-κB pathway in human THP-1 macrophages induced by lipopolysaccharide (LPS). The results showed that the concentrations of TNF-a and IL-1β released from LPS stimulated THP-1 cells increased significantly compared to control (p < 0.01). After treatment with APS, the TNF-a and IL-1β levels were significantly lower than those in the LPS group (p < 0.05). The mRNA expression of TNF-a and IL-1β were also inhibited. Mechanistic studies indicated that APS strongly suppressed NF-κB activation and down-regulated the phosphorylation of ERK and JNK, which are important signaling pathways involved in the production of TNF-a and IL-1β, demonstrating that APS could suppress the production of TNF-a and IL-1β by LPS stimulated macrophages by inhibiting NF-κB activation and ERK and JNK phosphorylation.

We are delighted to share with you our sixth Journal Club and highlight some of the most interesting papers published recently [...]

We report on the first growth, spectroscopy, and visible laser operation of a single-crystal fiber (SCF) of KY3F10 (KYF) grown by the micro-pulling-down (μ-PD) method, doped with Pr3+ ions. This material has a cubic lattice, which makes it appealing for use in the industry. However, KYF crystals are considered difficult to grow with high optical quality, even with well-established methods. Nevertheless, we grew a 50-mm-long SCF of Pr:KYF, which was transparent in its inner part. We studied the spectroscopic features of it in comparison with existing literature and with samples of the same crystal grown by the Czochralski method, and we did not notice any large differences. These characterizations confirmed that is indeed possible to grow high-quality crystals of Pr:KYF by the μ-PD method. Unfortunately, the crystal proved to be more brittle than typical KYF and especially difficult to polish, leading to rough and irregular facets, as evidenced by transmission measurements. Despite these issues, we obtained continuous-wave laser operation in the orange, red, and deep red regions, using a sample carved from the SCF as active medium and an InGaN-based laser diode as pump source, though with lower performances than in existing reports on this crystal.

The aim of this study is to understand the influences of the social custom of foot binding on female osteoporosis by means of comparing and analyzing the lumbar vertebrae and hip bone mass differences between the foot-binding aged women and unbound women of the same age at Qujing District of Yunnan Province. Of the examined people, 81.37% suffer from osteoporosis on the basis of lumbar vertebra (L1–L4) and femoral neck BMD, of which 82.14% for the foot-binding group and 80.44% for the unbound group. There is no statistical difference for the osteoporosis morbidity of the two groups. Compare the BMD value for various vertebrae, femoral neck, and rehabilitation of the two groups and find the BMD value for the other parts have no statistical difference except the BMD value of L1 centrum, which shows that foot binding does not significantly influence the overall bone mineral density of foot-binding women.