GPR30 agonist G1 combined with hypothermia alleviates cognitive impairment and anxiety-like behavior after subarachnoid hemorrhage in rats.

INTRODUCTION: This study aimed to investigate the treatment effect of G protein-coupled receptor 30 (GPR30) agonist G1 combined with hypothermia (HT) on cognitive impairment and anxiety-like behavior after subarachnoid hemorrhage (SAH) in rats. METHODS: Fifty male rats were randomly assigned to one of five groups: Sham group, SAH group, SAH + G1 group, SAH + HT group, and SAH + G1 + HT group. The SAH rat model was established by modified endovascular puncture in all groups except the Sham group. Neurological function after the operation was assessed by Garcia scoring. The degree of rat cerebral edema was determined using dry-wet weighing method on the 28th day after operation. Moreover, the behavioral test was performed on rats on the 4th and 28th days after operation. RESULTS: Compared with Sham group, the Garcia score of each SAH rat model group decreased significantly on the first day and thereafter increased gradually. However, the recovery rate of each treatment group was higher than the SAH group (no treatment), and the Garcia score of SAH + G1 + HT group was much higher than the SAH group on the seventh day after operation. In addition, each treatment group could obviously reduce the cerebral edema degree of SAH rats, among which rats in SAH + G1 + HT group had lower cerebral edema degree than SAH + G1 group and SAH + HT group. Behavioral test results showed that the combination of GPR30 agonist G1 and HT markedly improved the learning and memory ability of SAH rats, alleviated their anxiety- and emotion-related behavior, and enhanced their social interaction. CONCLUSION: GPR30 agonist G1 combined with HT reduces cognitive impairment and anxiety-like behavior in rats with SAH.

LncRNA XIST Exacerbates Oxygen-Glucose Deprivation/Reoxygenation-Induced Cerebral Injury Through the miR-25-3p/TRAF3 Axis.

Ischemic stroke causes lethal damage to the brain. Identifying key regulators of OGD/R-induced cerebral injury is important for developing novel therapies for ischemic stroke. HMC3 and SH-SY5Y cells were treated with OGD/R as an in vitro ischemic stroke model. Cell viability and apoptosis were determined via CCK-8 assay and flow cytometry. Inflammatory cytokines were examined by ELISA. Luciferase activity was measured for evaluating the interaction of XIST, miR-25-3p, and TRAF3. Bcl-2, Bax, Bad, cleaved-caspase 3, total caspase 3, and TRAF3 were detected via western blotting. HMC3 and SH-SY5Y cells showed increased XIST expression and decreased miR-25-3p expression following OGD/R. Importantly, silencing of XIST and overexpression of miR-25-3p reduced apoptosis and inflammatory response following OGD/R. Furthermore, XIST worked as a miR-25-3p sponge, and miR-25-3p targeted TRAF3 to suppress its expression. Moreover, the knockdown of TRAF3 ameliorated OGD/R-induced injury. Loss of XIST-mediated protective effects was reversed by overexpression of TRAF3. LncRNA XIST exacerbates OGD/R-induced cerebral damage via sponging miR-25-3p and enhancing TRAF3 expression.

Bone Marrow Mesenchymal Stem Cell-Derived Exosomal KLF4 Alleviated Ischemic Stroke Through Inhibiting N6-Methyladenosine Modification Level of Drp1 by Targeting lncRNA-ZFAS1.

Ischemic stroke has become a serious public health problem that causes high rates of death and disability. Bone marrow mesenchymal stem cell (BMSC)-derived exosomes have shown promising therapeutic results in IS, while the underlying mechanisms need further investigation. Cell and mice models were established through oxygen-glucose deprivation/reoxygenation (OGD/R) treatment and middle cerebral artery occlusion (MCAO)/reperfusion. Exosomes were isolated from BMSCs. Related gene and protein expression was measured by qRT-PCR, Western blotting, and immunofluorescence analysis. The biological functions of treated cells and tissues were analyzed by MTT, ELISA, JC-1, flow cytometry, TTC staining, or TUNEL staining. The interaction of KLF4/lncRNA-ZFAS1 promoter and lncRNA-ZFAS1/FTO was measured by ChIP, dual-luciferase reporter, or RIP assays. The m6A levels of Drp1 were measured by MeRIP-PCR. Mitochondrial staining and transmission electron microscopy (TEM) were used to evaluate the mitochondrial morphology in N2a cells and brain tissues. BMSC-derived exosomes increased the viability of neuronal cells treated with OGD/R while decreasing LDH release, oxidative stress, mitochondrial injury, and apoptosis. Furthermore, these effects were abolished by knockdown of exosomal KLF4. KLF4 increased lncRNA-ZFAS1 through binding to its promoter. LncRNA-ZFAS1 overexpression suppressed the m6A levels of Drp1 and reversed the promoting effect of exosomal KLF4 silencing on mitochondrial injury and the imbalance of mitochondrial dynamics by targeting FTO. Exosomal KLF4 alleviated the infarct area, neuronal injury, and apoptosis in MCAO mice through lncRNA-ZFAS1/FTO/Drp1 axis. BMSC-derived exosomal KLF4 promoted lncRNA-ZFAS1 expression to repress Drp1 m6A modification by targeting FTO, thus reducing mitochondrial dysfunction and alleviating neuronal injury in ischemic stroke.

OIP5-AS1 Inhibits Oxidative Stress and Inflammation in Ischemic Stroke Through miR-155-5p/IRF2BP2 Axis.

BACKGROUND: Ischemic stroke is a very dangerous disease with high incidence, fatality and disability rate in human beings. Massive evidence has indicated that oxidative stress and inflammation are intimately correlated with progression of ischemic stroke. Additionally, LncRNAs were reported to be involved in ischemic stroke. Here, we aim to explore the effects and molecular mechanism of lncRNA OIP5-AS1 on oxidative stress and inflammation in ischemic stroke. METHODS: HMC3 and SH-SY5Y cells were under the condition of oxygen-glucose deprivation/reoxygenation (OGD/R) treatment to establish cell models of ischemic stroke. Commercial kits were employed to detect the indicators of oxidative stress including ROS, MDA and SOD. The expression of OIP5-AS1, miR-155-5p and IRF2BP2 mRNA was determined using RT-qPCR. The protein levels of inflammatory factors including TNF-α, IL-1ß and IL-6 and IRF2BP2 were assessed by western blot and/or ELISA. Luciferase activity assay was employed to validate their correlations among OIP5-AS1, miR-155-5p and IRF2BP2. RESULTS: In OGD/R-induced HMC3 and SH-SY5Y cells, the expression of OIP5-AS1 and IRF2BP2 was reduced while miR-155-5p was elevated. OGD/R induction promoted oxidative stress and inflammatory response in HMC3 and SH-SY5Y cells, while OIP5-AS1 or IRF2BP2 sufficiency as well as miR-155-5p inhibitor attenuated OGD/R-induced these influences. In addition, IRF2BP2 knockdown abolished the suppressive impacts of OIP5-AS1 overexpression on oxidative stress and inflammatory response in OGD/R-induced HMC3 and SH-SY5Y cells. Mechanistically, OIP5-AS1 enhanced IRF2BP2 expression via sponging miR-155-5p. CONCLUSION: OIP5-AS1 suppressed oxidative stress and inflammatory response to alleviate cell injury caused by OGD/R induction in HMC3 and SH-SY5Y cells through regulating miR-155-5p/IRF2BP2 axis, which might offer novel targeted molecules for ischemic stroke therapy.

CircUCK2 regulates HECTD1-mediated endothelial-mesenchymal transition inhibition by interacting with FUS and protects the blood-brain barrier in ischemic stroke.

Ischemic stroke (IS) has become a cerebrovascular disease of widespread concern. Overexpression of circUCK2 alleviates neuronal damage in IS. However, the specific regulatory mechanisms of circUCK2 are not fully understood. In this study, we found that circUCK2 and HECT domain E3 ubiquitin ligase 1 (HECTD1) were downregulated in IS models in vitro and in vivo. Overexpression of circUCK2 or HECTD1 inhibited endothelial-mesenchymal transition (EndoMT) and protected the blood-brain barrier (BBB) in transient middle cerebral artery occlusion mice from damage. It was further discovered that circUCK2 regulated HECTD1 expressions by interacting with fused in sarcoma (FUS). Moreover, FUS overexpression partially restored the effect of circUCK2 on EndoMT, and overexpression of HECTD1 weakened the effect of FUS on EndoMT. Collectively, circUCK2 upregulates the expression of HECTD1 by combining with FUS and inhibits EndoMT to alleviate BBB damage in IS both in vivo and in vitro.

LncRNA CEBPA-AS1 knockdown prevents neuronal apoptosis against oxygen glucose deprivation/reoxygenation by regulating the miR-455/GPER1 axis.

Ischemic stroke (IS) is a common nervous system disease, which is a major cause of disability and death in the world. In present study, we demonstrated a regulatory mechanism of CCAAT/enhancer binding protein-alpha antisense 1 (CEBPA-AS1) in oxygen glucose deprivation/reoxygenation (OGD/R)-induced SH-SY5Y cells, with a focus on neuronal apoptosis. CEBPA-AS1, miR-455, and GPER1 expressions were evaluated by using qRT-PCR and Western blotting. The binding relationship among CEBPA-AS1, miR-455, and GPER1 was determined by a dual luciferase reporter assay. Neuronal viability and apoptosis were examined using MTT and flow cytometry assays, followed by determination of apoptosis-related factors (caspase 3, caspase 8, caspase 9, Bax, and Bcl-2). CEBPA-AS1 and GPER1 levels were upregulated, and miR-455 level was downregulated in the cell model of OGD/R induced. CEBPA-AS1 knockdown increased SH-SY5Y viability and reduced OGD/R-induced apoptosis. CEBPA-AS1 could act as a sponge of miR-455, and CEBPA-AS1 knockdown was found to elevate miR-455 expression. miR-455 overexpression also promoted SH-SY5Y cell viability and rescued them from OGD/R-induced apoptosis by binding to GPER1. GPER1 overexpression or miR-455 inhibition reversed the anti-apoptotic effect of CEBPA-AS1 knockdown. These findings suggest a regulatory network of CEBPA-AS1/miR-455/GPER1 that mediates neuronal cell apoptosis in the OGD model, providing a better understanding of pathogenic mechanisms after IS.

[Terahertz Spectrum Features Extraction Based on Kernel Optimization Relevance Vector Machine].

Terahertz spectrum is sensitive to the change of the nonlocal molecular vibration mode. Accordingly, the spectral waveform is susceptible to variety of physical and chemical factors, which will lead to peak changes, frequency shifts, and even deformation of the overall waveform. Component analysis and material identification from the correspondence between the fixed peak features and materials will prone to cause errors or mistakes. Therefore, to solve this problem, we proposed a method based on Kernel Optimization Relevance Vector Machine (KO-RVM), which extracts global graphic features to distinct from the local features extraction method. And we use Support Vector Regression (SVR) algorithm as comparison. The result shows that, when basis functions' parameters of RVM are optimized with expectation-maximization algorithm, it will be suitable for feature extraction of terahertz transmission spectrum. The spectrum can be sparsely represented, and the amount of extracted graphic features is substantially reduced. Reconstruction models based on these features are capable of retaining the overall spectral characteristics, and fitting results for each band are more consistent, while the extracted spectrum features can be used as basis of similarity measurement and the common characteristics investigation between different materials.

[Classification of THz Transmission Spectrum Based on Kevnel Function of Convex Combination].

In the present paper, support vector machine (SVM) based on convex combination kernel function will be used for classification of THz pulse transmission spectra. Wavelet transform is used in data pre-processing. Peaks and valleys are regarded as location features of THz pulse transmission spectra, which are injected into maximum interval features of term frequency-inverse document frequency (TF-IDF). We can conclude weight of each sampling point from the information theory. The weight represents the possibility that sampling point becomes feature. According to the situation that different terahertz-transmission spectra are lack of obvious features, we composed a SVM classification model based on convex combination kernel function. Evaluation function should be used as an evaluation method for obtaining the parameters of optimal convex combination to achieve a better accuracy. When the optimal parameter of kenal founction was determined, we should compose the model for process of classification and prediction. Compared with the single kernel function, the method can be combined with transmission spectroscopic features with classification model iteratively. Thanks to the dimensional mapping process, outstanding margin of features can be gained for the samples of different terahertz transmission spectrum. We carried out experiments using different samples The results demonstrated that the new approach is on par or superior in terms of accuracy and much better in feature fusion than SVM with single kernel function.

[Terahertz Spectroscopic Identification with Deep Belief Network].

Feature extraction and classification are the key issues of terahertz spectroscopy identification. Because many materials have no apparent absorption peaks in the terahertz band, it is difficult to extract theirs terahertz spectroscopy feature and identify. To this end, a novel of identify terahertz spectroscopy approach with Deep Belief Network (DBN) was studied in this paper, which combines the advantages of DBN and K-Nearest Neighbors (KNN) classifier. Firstly, cubic spline interpolation and S-G filter were used to normalize the eight kinds of substances (ATP, Acetylcholine Bromide, Bifenthrin, Buprofezin, Carbazole, Bleomycin, Buckminster and Cylotriphosphazene) terahertz transmission spectra in the range of 0.9-6 THz. Secondly, the DBN model was built by two restricted Boltzmann machine (RBM) and then trained layer by layer using unsupervised approach. Instead of using handmade features, the DBN was employed to learn suitable features automatically with raw input data. Finally, a KNN classifier was applied to identify the terahertz spectrum. Experimental results show that using the feature learned by DBN can identify the terahertz spectrum of different substances with the recognition rate of over 90%, which demonstrates that the proposed method can automatically extract the effective features of terahertz spectrum. Furthermore, this KNN classifier was compared with others (BP neural network, SOM neural network and RBF neural network). Comparisons showed that the recognition rate of KNN classifier is better than the other three classifiers. Using the approach that automatic extract terahertz spectrum features by DBN can greatly reduce the workload of feature extraction. This proposed method shows a promising future in the application of identifying the mass terahertz spectroscopy.