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Liver X receptors (LXRs) have recently been reported to be novel and potential targets for the reversal of depressive-like behaviors, but the mechanism remains unclear. Hippocampal neuroinflammation and impairment of the normal structure and function of microglia are closely associated with depression. To investigate the effects of LXRs agonist (GW3965) on neuroinflammation and microglia in the hippocampal formation of mice with chronic unpredictable stress (CUS)-induced depression, depressive-like behaviors were evaluated by behavioral tests, hippocampal LXRs gene expression were evaluated by qRT-PCR, the protein expression levels of interleukin-1β, tumor necrosis factor-α, inducible nitric oxide synthase, nuclear factor kappa B, and cluster of differentiation 206 were estimated by western blotting, modern stereological methods were used to precisely quantify the total number of microglia in each hippocampal subregion, and immunofluorescence was used to detect the density of activated microglia and the morphology of microglia. We found that GW3965 alleviated the depressive-like behavior induced by CUS, reversed the decrease in hippocampal LXRα and LXRβ induced by CUS, increased the protein expression of pro-inflammatory factors, and decreased the protein expression of antiinflammatory factors induced by CUS. Moreover, CUS intervention significantly increased the number of microglia in the CA1 region, CA2/3 region, and dentate gyrus and the density of activated microglia in the CA2/3 region and dentate gyrus and significantly decreased the endpoints of microglial branches and process length of microglia in the dentate gyrus, while 4 weeks of injections with GW3965 reversed these changes. These findings suggest that regulating the number, activated state, and morphology of microglia in hippocampal subregions might be an important basis for the antidepressant effects of LXRs.

Many neuroimaging studies have reported that stroke induces abnormal brain activities. Yet, little is known about resting-state networks (RSNs) and the corresponding white matter changes in stroke patients with hemiplegia. Here, we utilized functional magnetic resonance imaging (fMRI) to measure the neural activity and related fiber tracks in 14 ischemic stroke patients with hemiplegia and 12 healthy controls. The fractional amplitude of low-frequency fluctuations (fALFF) calculation and correlation analyses were used to assess the relationship between the regional neural activity and movement scores. Tractography was performed using the diffusion tensor imaging (DTI) data to analyze the fibers passing the regions of interest. Compared with controls, stroke patients showed abnormal functional connectivity (FC) in some brain regions of the RSNs. The fALFF was increased in the contralesional parietal lobe, with the regional fALFF being correlated to behavioral scores in stroke patients. And the tracked fibers across regions with reduced FC in the RSNs were increased in stroke patients. The study suggested that structural remodeling of functionally-relevant white matter tracts probably be an adaptive response that compensates for injury to the brain.

Cognitive impairment can seriously affect the quality of life of Parkinson's disease (PD) patients. Although numerous studies showed that N200, P300 latency and amplitude are correlated with cognitive functions, there is a sufficient amount of controversial results. Therefore, it is necessary to conduct a meta-analysis of N200, P300 latency and amplitude data of event-related potential (ERP) in PD.We systematically searched on PubMed and Web of Science for PD-related ERP studies published before December 2021. Standard mean difference (SMD) and 95% confidence interval (CI) estimates of N200 and P300 components were compared among PD patients, PD dementia (PDD) patients, PD non-dementia (PDND) patient, and healthy control (HC).Our meta-analysis showed prolonged N200 latency at the Fz, Cz electrode sites, prolonged P300 latency at the Fz sites in PD patients, compared to HC; prolonged N200 latency at the Cz, Pz electrode sites in PDND patients, compared to HC; prolonged P300 latency at the Cz site in PDD patients, compared to PDND patients; and reduced P300 amplitude at the Fz electrode site in PDND patients, compared to HC.N200 and P300 component may be potential electrophysiological biomarkers of early cognitive impairment in PD patients. Future studies are needed to confirm this conclusion. Estimates of N200 and P300 component can be a valuable support for clinicians in diagnosis of early cognitive impairment in PD patients due to the simplicity and non-invasiveness of the procedure.

We aimed to identify the active ingredients and elucidate the underlying mechanism of action of Atractylodes lancea (Thunb.) DC (namely, Cangzhu) for the treatment of gouty arthritis (GA) based on network pharmacology methods. These findings are expected to provide a theoretical basis for the clinical treatment of GA.We used monosodium urate (MSU)-induced GA rats as a model to test the overall efficacy of Cangzhu in vivo. Then, the components of the Cangzhu decoction were analyzed and identified, and we screened the active ingredients and their targets. The GA disease targets were predicted by GeneCards and Disgenet databases and found to overlap in both databases. The STRING database was used to construct a protein-protein interaction network, followed by identification of the hub genes using Network Analyzer. Thereafter, Cytoscape software (version 3.8.2) was applied to construct a network for drug-active ingredient-key targets. Next, we applied cluego, a plug-in of Cytoscape, to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment analyses. Additionally, molecular docking was used to verify the characteristics of the key candidate components interacting with the hub therapeutic targets. Finally, we established an inflammatory injury model of LPS using RAW264.7 macrophages and used it to experimentally validate the critical active ingredients.Cangzhu effectively protected against gouty arthritis in vivo, and network pharmacology results revealed various active ingredients in Cangzhu, such as wogonin, atractylenolide I and atractylenolide II. These compounds were found to act on 16 hub targets, including tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), interleukin-1β (IL-1β), prostaglandin-endoperoxide synthase 2 (PTGS2), recombinant mitogen-activated protein kinase 14 (MAPK14) and transcription factor p65 (RELA), which have significant effects on regulating inflammatory factors and apoptosis-related pathways to improve the proinflammatory or anti-inflammatory imbalance in the body, and this may be one of the underlying mechanisms of Cangzhu in anti-GA.Our findings revealed that Cangzhu comprises multiple active components that exert various targeted effects during GA treatment. These findings provide relevant insights to illuminate the mechanism of Cangzhu in the treatment of GA and provide a reference for further experimental research.

Policy synergy is necessary to promote technological innovation and sustainable industrial development. A radial basis function (RBF) neural network model with an automatic coding machine and fractional momentum was proposed for the prediction of technological innovation. Policy keywords for China’s new energy vehicle policies issued over the years were quantified by the use of an Latent Dirichlet Allocation (LDA) model. The training of the neural network model was completed by using policy keywords, synergy was measured as the input layer, and the number of synchronous patent applications was measured as the output layer. The predictive efficacies of the traditional neural network model and the improved neural network model were compared again to verify the applicability and accuracy of the improved neural network. Finally, the influence of the degree of synergy on technological innovation was revealed by changing the intensity of policy measures. This study provides a basis for the relevant departments to formulate industrial policies and improve innovation performance by enterprises.