Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis.

BACKGROUND: Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease. MATERIAL AND METHODS: Firstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs (differentially expressed mRNAs). Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR (real-time polymerase chain reaction) verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers. RESULTS: A total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers (such as RAB13, KIF1B, CLEC5A, FCER1A, CACNA2D3, DUSP3, HMGN3, MGST1 and ARHGEF18) for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock. CONCLUSION: Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.

IL4-driven microglia modulate stress resilience through BDNF-dependent neurogenesis.

Adult neurogenesis in the dentate gyrus of the hippocampus is regulated by specific microglia groups and functionally implicated in behavioral responses to stress. However, the role of microglia in hippocampal neurogenesis and stress resilience remains unclear. We identified interleukin 4 (IL4)-driven microglia characterized by high expression of Arg1, which is critical in maintaining hippocampal neurogenesis and stress resistance. Decreasing Arg1+ microglia in the hippocampus by knocking down the microglial IL4R suppressed hippocampal neurogenesis and enhanced stress vulnerability. Increasing Arg1+ microglia in the hippocampus by enhancing IL4 signaling restored hippocampal neurogenesis and the resilience to stress-induced depression. Brain-derived neurotrophic factor (BDNF) was found necessary for the proneurogenesis effects of IL4-driven microglia. Together, our findings suggest that IL4-driven microglia in the hippocampus trigger BDNF-dependent neurogenesis responding to chronic stress, helping protect against depressive-like symptoms. These findings identify the modulation of a specific microglial phenotype as a treatment strategy for mood disorders.

Universal Adaptive Neural Network Predictive Algorithm for Remotely Piloted Unmanned Combat Aerial Vehicle in Wireless Sensor Network.

Remotely piloted unmanned combat aerial vehicle (UCAV) will be a prospective mode of air fight in the future, which can remove the physical restraint of the pilot, maximize the performance of the fighter and effectively reduce casualties. However, it has two difficulties in this mode: (1) There is greater time delay in the network of pilot-wireless sensor-UCAV, which can degrade the piloting performance. (2) Designing of a universal predictive method is very important to pilot different UCAVs remotely, even if the model of the control augmentation system of the UCAV is totally unknown. Considering these two issues, this paper proposes a novel universal modeling method, and establishes a universal nonlinear uncertain model which uses the pilot's remotely piloted command as input and the states of the UCAV with a control augmentation system as output. To deal with the nonlinear uncertainty of the model, a neural network observer is proposed to identify the nonlinear dynamics model online. Meanwhile, to guarantee the stability of the overall observer system, an adaptive law is designed to adjust the neural network weights. To solve the greater transmission time delay existing in the pilot-wireless sensor-UCAV closed-loop system, a time-varying delay state predictor is designed based on the identified nonlinear dynamics model to predict the time delay states. Moreover, the overall observer-predictor system is proved to be uniformly ultimately bounded (UUB). Finally, two simulations verify the effectiveness and universality of the proposed method. The results indicate that the proposed method has desirable performance of accurately compensating the time delay and has universality of remotely piloting two different UCAVs.

Sliding Mode Fault Tolerant Control for Unmanned Aerial Vehicle with Sensor and Actuator Faults.

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.

The antidepressant-like effects of pioglitazone in a chronic mild stress mouse model are associated with PPARγ-mediated alteration of microglial activation phenotypes.

BACKGROUND: Discoveries that microglia-mediated neuroinflammation is involved in the pathological process of depression provided a new strategy for novel antidepressant therapy. Peroxisome proliferator-activated receptor γ (PPARγ) is a nuclear receptor regulating inflammation and microglial polarization and, therefore, a potential target for resolving depressive disorders. Our hypothesis was that antidepressant effects could be achieved through anti-inflammatory and neuroprotective activities by PPARγ-dependent microglia-modulating agents. METHODS: Chronic mild stress (CMS) treatment was performed on C57BL/6 mice for 6 weeks. After 3 weeks with the CMS procedure, depressive-like behaviors were evaluated by sucrose preference (SP), tail suspension test (TST), forced swimming test (FST), and locomotor activity. Pioglitazone was administered intragastrically once per day for 3 weeks at different doses. Neuroinflammatory cytokines were determined by real time-PCR (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and western blot. The activated microglial state was confirmed by immunohistochemistry. N9 microglial cells were subjected to lipopolysaccharide, pioglitazone, and GW9662 to discuss the phenotype of activated microglia by RT-PCR, ELISA, and western blot. RESULTS: It was demonstrated that the PPARγ agonist pioglitazone (2.5 mg/kg) ameliorated depression-like behaviors in CMS-treated mice, as indicated by body weight (BW), the SP test, the FST, and the TST. The amelioration of the depression was blocked by the PPARγ antagonist GW9662. The expression of M1 markers (IL-1ß, IL-6, TNFα, iNOS, and CCL2) increased, and the gene expression of M2 markers (Ym1, Arg1, IL-4, IL-10, and TGFß) decreased in the hippocampus of the stress-treated mice. Pioglitazone significantly inhibited the increased numbers and morphological alterations of microglia in the hippocampus, reduced the elevated expression of microglial M1 markers, and increased the downgraded expression of microglial M2 markers in C57BL/6 mice exposed to CMS. In an in vitro experiment, pioglitazone reversed the imbalance of M1 and M2 inflammatory cytokines, which is correlated with the inhibition of nuclear factor kB activation and is expressed in LPS-stimulated N9 microglial cells. CONCLUSIONS: We showed that pioglitazone administration induce the neuroprotective phenotype of microglia and ameliorate depression-like behaviors in CMS-treated C57BL/6 mice. These data suggested that the microglia-modulating agent pioglitazone present a beneficial choice for depression.

Salvianolic acid B ameliorates depressive-like behaviors in chronic mild stress-treated mice: involvement of the neuroinflammatory pathway.

AIM: Major depressive disorder (MDD) is a debilitating mental disorder associated with dysfunction of the neurotransmitter-neuroendocrine system and neuroinflammatory responses. Salvianolic acid B (SalB) has shown a variety of pharmacological activities, including anti-inflammatory, antioxidant and neuroprotective effects. In this study, we examined whether SalB produced antidepressant-like actions in a chronic mild stress (CMS) mouse model, and explored the mechanisms underlying the antidepressant-like actions of SalB. METHODS: Mice were subjected to a CMS paradigm for 6 weeks. In the last 3 weeks the mice were daily administered SalB (20 mg·kg(-1)·d(-1), ip) or a positive control drug imipramine (20 mg·kg(-1)·d(-1), ip). The depressant-like behaviors were evaluated using the sucrose preference test, the forced swimming test (FST), and the tail suspension test (TST). The gene expression of cytokines in the hippocampus and cortex was analyzed with RT-PCR. Plasma corticosterone (CORT) and cerebral cytokines levels were assayed with an ELISA kit. Neural apoptosis and microglial activation in brain tissues were detected using immunofluorescence staining. RESULTS: Administration of SalB or imipramine reversed the reduced sucrose preference ratio of CMS-treated mice, and significantly decreased their immobility time in the FST and TST. Administration of SalB significantly decreased the expression of pro-inflammatory cytokines IL-1ß and TNF-α, and markedly increased the expression of anti-inflammatory cytokines IL-10 and TGF-ß in the hippocampus and cortex of CMS-treated mice, and normalized their elevated plasma CORT levels, whereas administration of imipramine did not significantly affect the imbalance between pro- and anti-inflammatory cytokines in the hippocampus and cortex of CMS-treated mice. Finally, administration of SalB significantly decreased CMS-induced apoptosis and microglia activation in the hippocampus and cortex, whereas administration of imipramine had no significant effect on CMS-induced apoptosis and microglia activation in the hippocampus and cortex. CONCLUSION: SalB exerts potent antidepressant-like effects in CMS-induced mouse model of depression, which is associated with the inhibiting microglia-related apoptosis in the hippocampus and the cortex.

Phenotypic dysregulation of microglial activation in young offspring rats with maternal sleep deprivation-induced cognitive impairment.

Despite the potential adverse effects of maternal sleep deprivation (MSD) on physiological and behavioral aspects of offspring, the mechanisms remain poorly understood. The present study was intended to investigate the roles of microglia on neurodevelopment and cognition in young offspring rats with prenatal sleep deprivation. Pregnant Wistar rats received 72 h sleep deprivation in the last trimester of gestation, and their prepuberty male offspring were given the intraperitoneal injection with or without minocycline. The results showed the number of Iba1(+) microglia increased, that of hippocampal neurogenesis decreased, and the hippocampus-dependent spatial learning and memory were impaired in MSD offspring. The classical microglial activation markers (M1 phenotype) IL-1ß, IL-6, TNF-α, CD68 and iNOS were increased, while the alternative microglial activation markers (M2 phenotype) Arg1, Ym1, IL-4, IL-10 and CD206 were reduced in hippocampus of MSD offspring. After minocycline administration, the MSD offspring showed improvement in MWM behaviors and increase in BrdU(+)/DCX(+) cells. Minocycline reduced Iba1(+) cells, suppressed the production of pro-inflammatory molecules, and reversed the reduction of M2 microglial markers in the MSD prepuberty offspring. These results indicate that dysregulation in microglial pro- and anti-inflammatory activation is involved in MSD-induced inhibition of neurogenesis and impairment of spatial learning and memory.