Neuroprotective effects of G9a inhibition through modulation of peroxisome-proliferator activator receptor gamma-dependent pathways by miR-128

Dysregulation of G9a,a histone-lysine N-methyltransferase,has been observed in Alzheimer’s disease and has been correlated with increased levels of chronic inflammation and oxidative stress.Likewise,microRNAs are involved in many biological processes and diseases playing a key role in pathogenesis,especially in multifactorial diseases such as Alzheimer’s disease.Therefore,our aim has been to provide partial insights into the interconnection between G9a,microRNAs,oxidative stress,and neuroinflammation.To better understand the biology of G9a,we compared the global microRNA expression between senescence-accelerated mouse-prone 8(SAMP8)control mice and SAMP8 treated with G9a inhibitor UNC0642.We found a downregulation of miR-128 after a G9a inhibition treatment,which interestingly binds to the 3′untranslated region(3′-UTR)of peroxisome-proliferator activator receptor γ(PPARG)mRNA.Accordingly,Pparg gene expression levels were higher in the SAMP8 group treated with G9a inhibitor than in the SAMP8 control group.We also observed modulation of oxidative stress responses might be mainly driven Pparg after G9a inhibitor.To confirm these antioxidant effects,we treated primary neuron cell cultures with hydrogen peroxide as an oxidative insult.In this setting,treatment with G9a inhibitor increases both cell survival and antioxidant enzymes.Moreover,up-regulation of PPARγby G9a inhibitor could also increase the expression of genes involved in DNA damage responses and apoptosis.In addition,we also described that the PPARγ/AMPK axis partially explains the regulation of autophagy markers expression.Finally,PPARγ/GADD45αpotentially contributes to enhancing synaptic plasticity and neurogenesis after G9a inhibition.Altogether,we propose that pharmacological inhibition of G9a leads to a neuroprotective effect that could be due,at least in part,by the modulation of PPARγ-dependent pathways by miR-128.

The Magnaporthe oryzae effector Avr-PikD suppresses rice immunity by inhibiting an LSD1-like transcriptional activator

Avirulence effectors(Avrs),encoded by plant pathogens,can be recognized by plants harboring the corresponding resistance proteins,thereby initiating effector-triggered immunity(ETI).In susceptible plants,however,Avrs can function as effectors,facilitating infection via effector-triggered susceptibility(ETS).Mechanisms of Avr-mediated ETS remain largely unexplored.Here we report that the Magnaporthe oryzae effector Avr-PikD enters rice cells via the canonical cytoplasmic secretion pathway and suppresses rice basal defense.Avr-PikD interacts with an LSD1-like transcriptional activator AKIP30 of rice,and AKIP30 is also a positive regulator of rice immunity,whereas Avr-PikD impedes its nuclear localization and suppresses its transcriptional activity.In summary,M.oryzae delivers Avr-PikD into rice cells to facilitate ETS by inhibiting AKIP30-mediated transcriptional regulation of immune response against M.oryzae.

The anti-inflammatory effects of exercise on autoimmune diseases:A 20-year systematic review

Background:The anti-inflammatory effect of exercise may be an underlying factor in improving several autoimmune diseases.The aim of this systematic review was to examine the evidence on the role of exercise training in mitigating inflammation in adolescents and adults with autoimmune disease.Methods:PubMed,Web of Science,and Embase databases were systematically reviewed for related studies published between January 1,2003,and August 31,2023.All randomized and non-randomized controlled trials of exercise interventions with autoimmune disease study participants that evaluated inflammation-related biomarkers were included.The quality of evidence was assessed using the Tool for the assEssment of Study qualiTy and reporting in EXercise scale and Cochrane bias risk tool.Results:A total of 14,565 records were identified.After screening the titles,abstracts,and full texts,87 were eligible for the systematic review.These studies were conducted in 25 different countries and included a total of 2779 participants(patients with autoimmune disease,in exercise or control groups).Overall,the evidence suggests that inflammation-related markers such as C-reactive protein,interleukin 6,and tumor necrosis factor a were reduced by regular exercise interventions.Regular exercise interventions combined with multiple exercise modes were associated with greater benefits.Conclusion:Regular exercise training by patients with autoimmune disease exerts an anti-inflammatory influence.This systematic review provides support for the promotion and development of clinical exercise intervention programs for patients with autoimmune disease.Most patients with autoimmune disease can safely adopt moderate exercise training protocols,but changes in inflammation biomarkers will be modest at best.Acute exercise interventions are ineffective or even modestly but transiently pro-inflammatory.

Alexa,let's train now!——A systematic review and classification approach to digital and home-based physical training interventions aiming to support healthy cognitive aging

Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.

ATSSC:An Attack Tolerant System in Serverless Computing

Serverless computing is a promising paradigm in cloud computing that greatly simplifies cloud programming.With serverless computing,developers only provide function code to serverless platform,and these functions are invoked by its driven events.Nonetheless,security threats in serverless computing such as vulnerability-based security threats have become the pain point hindering its wide adoption.The ideas in proactive defense such as redundancy,diversity and dynamic provide promising approaches to protect against cyberattacks.However,these security technologies are mostly applied to serverless platform based on“stacked”mode,as they are designed independent with serverless computing.The lack of security consideration in the initial design makes it especially challenging to achieve the all life cycle protection for serverless application with limited cost.In this paper,we present ATSSC,a proactive defense enabled attack tolerant serverless platform.ATSSC integrates the characteristic of redundancy,diversity and dynamic into serverless seamless to achieve high-level security and efficiency.Specifically,ATSSC constructs multiple diverse function replicas to process the driven events and performs cross-validation to verify the results.In order to create diverse function replicas,both software diversity and environment diversity are adopted.Furthermore,a dynamic function refresh strategy is proposed to keep the clean state of serverless functions.We implement ATSSC based on Kubernetes and Knative.Analysis and experimental results demonstrate that ATSSC can effectively protect serverless computing against cyberattacks with acceptable costs.

Description of martensitic transformation kinetics in Fe-C-X(X = Ni,Cr,Mn,Si) system by a modified model

Controlling the content of athermal martensite and retained austenite is important to improving the mechanical properties of high-strength steels,but a mechanism for the accurate description of martensitic transformation during the cooling process must be addressed.At present,frequently used semi-empirical kinetics models suffer from huge errors at the beginning of transformation,and most of them fail to exhibit the sigmoidal shape characteristic of transformation curves.To describe the martensitic transformation process accurately,based on the Magee model,we introduced the changes in the nucleation activation energy of martensite with temperature,which led to the varying nucleation rates of this model during martensitic transformation.According to the calculation results,the relative error of the modified model for the martensitic transformation kinetics curves of Fe-C-X(X = Ni,Cr,Mn,Si) alloys reached 9.5% compared with those measured via the thermal expansion method.The relative error was approximately reduced by two-thirds compared with that of the Magee model.The incorporation of nucleation activation energy into the kinetics model contributes to the improvement of its precision.

Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.

Method for rapid warning and activity concentration estimates in online waterγ-spectrometry systems

Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are distributed relatively uniformly and enter into a steady-state diffusion regime in the measurement chamber.To protect residents’health and ensure the safety of the living environment,better timeliness is required for this measurement method.To address this issue,this study established a mathematical model of the online waterγ-spectrometry system so that rapid warning and activity estimates can be obtained for water under non-steady-state(NSS)conditions.In addition,the detection efficiency of the detector for radionuclides during the NSS diffusion process was determined by applying the computational fluid dynamics technique in conjunction with Monte Carlo simulations.On this basis,a method was developed that allowed the online waterγ-spectrometry system to provide rapid warning and activity concentration estimates for radionuclides in water.Subsequent analysis of the NSS-mode measurements of^(40)K radioactive solutions with different activity concentrations determined the optimum warning threshold and measurement time for producing accurate activity concentration estimates for radionuclides.The experimental results show that the proposed NSS measurement method is able to give warning and yield accurate activity concentration estimates for radionuclides 55.42 and 69.42 min after the entry of a 10 Bq/L^(40)K radioactive solution into the measurement chamber,respectively.These times are much shorter than the 90 min required by the conventional measurement method.Furthermore,the NSS measurement method allows the measurement system to give rapid(within approximately 15 min)warning when the activity concentrations of some radionuclides reach their respective limits stipulated in the Guidelines for Drinking-water Quality of the WHO,suggesting that this method considerably enhances the warning capacity of in situ online waterγ-spectrometry systems.

Advances in Active Suspension Systems for Road Vehicles

Active suspension systems(ASSs)have been proposed and developed for a few decades,and have now once again become a thriving topic in both academia and industry,due to the high demand for driving comfort and safety and the compatibility of ASSs with vehicle electrification and autonomy.Existing review papers on ASSs mainly cover dynamics modeling and robust control;however,the gap between academic research outcomes and industrial application requirements has not yet been bridged,hindering most ASS research knowledge from being transferred to vehicle companies.This paper comprehensively reviews advances in ASSs for road vehicles,with a focus on hardware structures and control strategies.In particular,state-of-the-art ASSs that have been recently adopted in production cars are discussed in detail,including the representative solutions of Mercedes active body control(ABC)and Audi predictive active suspension;novel concepts that could become alternative candidates are also introduced,including series active variable geometry suspension,and the active wheel-alignment system.ASSs with compact structure,small mass increment,low power consumption,high-frequency response,acceptable economic costs,and high reliability are more likely to be adopted by car manufacturers.In terms of control strategies,the development of future ASSs aims not only to stabilize the chassis attitude and attenuate the chassis vibration,but also to enable ASSs to cooperate with other modules(e.g.,steering and braking)and sensors(e.g.,cameras)within a car,and even with high-level decision-making(e.g.,reference driving speed)in the overall transportation system-strategies that will be compatible with the rapidly developing electric and autonomous vehicles.

Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

Inpatient falls from beds in hospitals are a common problem.Such falls may result in severe injuries.This problem can be addressed by continuous monitoring of patients using cameras.Recent advancements in deep learning-based video analytics have made this task of fall detection more effective and efficient.Along with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their health.High computation-intensive models are required to monitor every action of the patient precisely.This requirement limits the applicability of such networks.Hence,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall detection.Motivated by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their poses.The whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a Residual Network(ResNet)Mixer block-based activity recognition network.The compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human poses.Finally,the activity recognition network classifies the patients’activities based on their poses.The proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.

Effects of interleukin-10 treated macrophages on bone marrow mesenchymal stem cells via signal transducer and activator of transcription 3 pathway

BACKGROUND Alveolar bone defects caused by inflammation are an urgent issue in oral implant surgery that must be solved.Regulating the various phenotypes of macrophages to enhance the inflammatory environment can significantly affect the progression of diseases and tissue engineering repair process.AIM To assess the influence of interleukin-10(IL-10)on the osteogenic differentiation of bone marrow mesenchymal stem cells(BMSCs)following their interaction with macrophages in an inflammatory environment.METHODS IL-10 modulates the differentiation of peritoneal macrophages in Wistar rats in an inflammatory environment.In this study,we investigated its impact on the proliferation,migration,and osteogenesis of BMSCs.The expression levels of signal transducer and activator of transcription 3(STAT3)and its activated form,phos-phorylated-STAT3,were examined in IL-10-stimulated macrophages.Subsequently,a specific STAT3 signaling inhibitor was used to impede STAT3 signal activation to further investigate the role of STAT3 signaling.RESULTS IL-10-stimulated macrophages underwent polarization to the M2 type through substitution,and these M2 macrophages actively facilitated the osteogenic differentiation of BMSCs.Mechanistically,STAT3 signaling plays a crucial role in the process by which IL-10 influences macrophages.Specifically,IL-10 stimulated the activation of the STAT3 signaling pathway and reduced the macrophage inflammatory response,as evidenced by its diminished impact on the osteogenic differentiation of BMSCs.CONCLUSION Stimulating macrophages with IL-10 proved effective in improving the inflammatory environment and promoting the osteogenic differentiation of BMSCs.The IL-10/STAT3 signaling pathway has emerged as a key regulator in the macrophage-mediated control of BMSCs’osteogenic differentiation.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor(PMSM)speed control systems with conventional linear active disturbance rejection control(CLADRC)strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances.In order to address these issues,this paper proposes an improved two-degree-of-freedom LADRC(TDOF-LADRC)strategy,which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning.PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately.Moreover,to evaluate the control performance of the TDOF-LADRC strategy,its stability is proven,and the influence of each controller parameter on the system control performance is analyzed.Based on it,a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances.Finally,experiments are performed on a 750 W PMSM experimental platform,and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Electroacupuncture targeting the immune system to alleviate sepsis

Sepsis is a life-threatening inflammatory syndrome with high morbidity and mortality rates.However,options for sepsis are still limited to general treatment in intensive care units(ICUs),and effective therapies that improve sepsis survival are required.Immune disturbances play a vital role in the pathology of sepsis and are associated with protracted inflammation,susceptibility to infections,and death.Therefore,many investigators have focused on the potential benefits of immunomodulation therapy for sepsis.Electroacupuncture(EA)has been practiced in clinics for many years and has shown advantages in treating infectious diseases.Over the last few decades,our understanding of the efficacy and mechanisms of EA in sepsis has undergone considerable developments.We searched the literature regarding“CNKI,Wan Fang Data,VIP Database,PubMed,and Ingenta Connect”from 2010 to 2023,using the keywords“sepsis”“septic”and“electroacupuncture”and 336 sources were searched.Finally,we included 82 studies that targeted the immune system to determine EA’s anti-inflammatory and immunomodulatory effects on sepsis.In this review,we found that EA has clinical benefits in relieving septic inflammation,improving immune function,and attenuating related multi-organ injury through several mechanisms,such as activation of the cholinergic anti-inflammatory pathway(CAP),vagaladrenal axis,inhibition of the nuclear factor Kappa-B(NF-κB)signaling pathway,signal transducers and activators of transcription(STAT)signaling pathway,and improvement of immune cell function.Therefore,EA may be a promising complementary therapy for sepsis treatment.We also expect these data will contribute to further studies on EA in sepsis.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Macrophage Activation Syndrome as the Primary Presentation of Pediatric Systemic Lupus Erythematosus: A Case Report and Review of the Literature

Macrophage activation syndrome (MAS), in its secondary form, often complicates rheumatic diseases but rarely constitutes a mode of revelation. Systemic lupus erythematosus (SLE) is a systemic autoimmune disease of unknown etiology that primarily affects women in adulthood. MAS is a serious condition that may be the first presentation of SLE. Here, we report the case of a 4-year-old female with MAS as the primary manifestation of Systemic Lupus Erythematosus (SLE). In this case, we outline the characteristics of a complex case of SLE that was initially accompanied with MAS, and also review the literature to discuss the clinical, biological, and therapeutic aspects of this condition.

Efficacy of activating blood and resolving stasis therapy for IgA nephropathy:a systematic review and meta-analysis

Background:To systematically evaluate the efficacy and safety of activating blood and resolving stasis in patients with IgA nephropathy.Methods:From inception to May 2022,databases including PubMed,Embase,the Cochrane Library,Web of Science,WanFang database,Chinese Biomedical Database,VIP,and China National Knowledge Infrastructure were searched for randomized controlled trials about enhancing blood circulation and removing stasis for IgA nephropathy.For the articles that satisfied the requirements,quality assessment and meta-analysis were done.Results:Seventeen randomized controlled trials with a total of 1653 patients were included.Meta-analysis showed that activating blood and resolving stasis could increase therapeutic effectiveness(risk ratio(RR)=-0.47,95%confidence interval(CI)(-0.37,-0.2),P=0.0006)and decrease levels of serum creatinine(RR=-0.47,95%CI(-0.37,-0.2),P=0.0006),urea nitrogen(RR=0.85,95%CI(1.44,0.26),P=0.005),24-hour urinary protein quantification(RR=1.6,95%CI(2.44,0.95).P=0.00001),and urine red blood cell count(RR=1.7,95%CI(2.57,0.82),P=0.0001).There was no significant difference between the two groups in terms of security(RR=0.6,95%CI(0.36,1.01),P=0.05).Conclusion:Western medicine combined activating blood and resolving stasis is more efficient than Western medicine therapy alone in treating IgA nephropathy,but it still needs to be supported by additional large-scale,multi-center randomized controlled clinical trials due to the poor quality of the included trials.

Urokinase-type plasminogen activator receptor as a predictor of poor outcome in patients with systemic inflammatory response syndrome

BACKGROUND:Urokinase-type plasminogen activator(uPA) and urokinase-type plasminogen activator receptor(uPAR) are known as important factors,which mediate a variety of functions in terms of vascular homeostasis,inflammation and tissue repair.However,their role in systemic inflammatory response syndrome(SIRS) has been less well studied.This study aimed to test the hypothesis that the abnormalities of fibrinolysis and degradation of extracellular matrix mediated by uPA and uPAR are directly related to the patients with SIRS.We therefore analyzed their role and clinicopathological significance in patients with SIRS.METHODS:A case-control study was conducted with 85 patients who were divided into two groups according to the diagnostic criteria of SIRS:SIRS group(n=50) and non-SIRS group(/7=35).The SIRS group was divided into MODS group(n=26) and non-MODS group(n=24) by their severity,and survival group(n=35) and non-survival group(n=15) by their prognosis.Another 30 healthy adults served as normal controls.uPA and uPAR in plasma were detected by commercial enzyme-linked immunosorbent assay(ELISA) kits.RESULTS:The plasma level of uPA was lower in the SIRS group than in the non-SIRS group and controls(P<0.001 and P<0.001).It was lower in sepsis patients and the MODS group than in the non-sepsis patients and the non-MODS patients(all P<0.05).However,there was no difference in uPA level between survivors and non-survivors(P>0.05).The plasma level of uPAR increased in the SIRS group compared with the non-SIRS group and controls(P<0.001 and P<0.001).There was a significant elevation of uPAR in sepsis patients,MODS patients and non-survivors as compared with non-sepsis patients,non-MODS patients and survivors respectively(all P<0.05).Plasma uPAR levels were positively correlated with APACHE Ⅱ score(r=0.575,P<0.001) and SOFA score(r=0.349,P=0.013).AUCs for the prediction of SIRS mortality were 0.67 and 0.51,respectively,for uPA and uPAR.CONCLUSION:uPAR could be a predictor of poor outcome in patients with SIRS.

Tissue-type plasminogen activator is a homeostatic regulator of synaptic function in the central nervous system

Membrane depolarization induces the release of the serine proteinase tissue-type plasminogen activator（t PA） from the presynaptic terminal of cerebral cortical neurons.Once in the synaptic cleft this t PA promotes the exocytosis and subsequent endocytic retrieval of glutamate-containing synaptic vesicles,and regulates the postsynaptic response to the presynaptic release of glutamate.Indeed,t PA has a bidirectional effect on the composition of the postsynaptic density（PSD） that does not require plasmin generation or the presynaptic release of glutamate,but varies according to the baseline level of neuronal activity.Hence,in inactive neurons t PA induces phosphorylation and accumulation in the PSD of the Ca^（2＋）/calmodulin-dependent protein kinase IIα（pCa MKIIα）,followed by pCa MKIIα-induced phosphorylation and synaptic recruitment of Glu R1-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid（AMPA） receptors.In contrast,in active neurons with increased levels of pCa MKIIα in the PSD t PA induces pCa MKIIα and p Glu R1 dephosphorylation and their subsequent removal from the PSD.These effects require active synaptic N-methyl-D-aspartate（NMDA） receptors and cyclin-dependent kinase 5（Cdk5）-induced phosphorylation of the protein phosphatase 1（PP1） at T320.These data indicate that t PA is a homeostatic regulator of the postsynaptic response of cerebral cortical neurons to the presynaptic release of glutamate via bidirectional regulation of the pCa MKIIα/PP1 switch in the PSD.

Screening of immune cell activators from Astragali Radix using a comprehensive two-dimensional NK-92MI cell membrane chromatography/C18 column/time-of-flight mass spectrometry system

Astragali Radix(AR)is a clinically used herbal medicine with multiple immunomodulatory activities that can strengthen the activity and cytotoxicity of natural killer(NK)cells.However,owing to the complexity of its composition,the specific active ingredients in AR that act on NK cells are not clear yet.Cell membrane chromatography(CMC)is mainly used to screen the active ingredients in a complex system of herbal medicines.In this study,a new comprehensive two-dimensional(2D)NK-92MI CMC/C18 column/time-of-flight mass spectrometry(TOFMS)system was established to screen for potential NK cell activators.To obtain a higher column efficiency,3-mercaptopropyltrimethoxysilane-modified silica was synthesized to prepare the NK-92MI CMC column.In total,nine components in AR were screened from this system,which could be washed out from the NK-92MI/CMC column after 10 min,and they showed good affinity for NK-92MI/CMC column.Two representative active compounds of AR,isoastragaloside Ⅰ and astragaloside IV,promoted the killing effect of NK cells on K562 cells in a dose-dependent manner.It can thus suggest that isoastragaloside Ⅰ and astragaloside Ⅳ are the main immunomodulatory components of AR.This comprehensive 2D NK-92MI CMC analytical system is a practical method for screening immune cell activators from other herbal medicines with immunomodulatory effects.