Exploring the XIST axis as oxidative stress-related signatures in systemic lupus erythematosus.

OBJECTIVES: In the pathogenesis of systemic lupus erythematosus (SLE), oxidative stress (OS) plays an complex role; nevertheless, few investigations have indicated a ceRNA-based mechanism involved. The aim of this study was to explore the ceRNA regulation mechanism of oxidative stress in SLE and provide new therapeutic targets for SLE. METHODS: Three datasets from the Gene Expression Omnibus (GEO) database were used to obtain differentially expressed lncRNAs, miRNAs, and mRNAs (DElncRNAs, DEmiRNAs, and DEmRNAs). Functional analysis was explored and a triple ceRNA network was built. Least absolute shrinkage and selection operator regression was used to find optimal signatures. The sensitivity and specificity of the signatures were examined and validated using receiver operating characteristic (ROC) analysis. The CIBERSORT algorithm was used to investigate immune infiltration features. Moreover, the hub mRNAs were validated by quantitative real-time PCR. RESULTS: 42 DEmRNAs were identified. Enrichment analysis showed that the DEmRNAs were primarily concentrated in neutrophil-associated biological processes. The ROC curve found FOS and MME provided potential biomarkers for identifying SLE patients. And the XIST/FOS and XIST/MME axes were identified the possible OS-related regulatory pathway in SLE. Immune infiltration showed that resting memory CD4 T cells presented a lower level. CONCLUSIONS: This study constructed the ceRNA-based XIST/FOS and XIST/MME axes as prospective OS-related signatures for SLE. Our findings provide new insights into the pathogenesis of SLE and shed a novel light on therapeutic strategies.

Combination of machine learning-based bulk and single-cell genomics reveals necroptosis-related molecular subtypes and immunological features in autism spectrum disorder.

Background: Necroptosis is a novel form of controlled cell death that contributes to the progression of various illnesses. Nonetheless, the function and significance of necroptosis in autism spectrum disorders (ASD) remain unknown and require further investigation. Methods: We utilized single-nucleus RNA sequencing (snRNA-seq) data to assess the expression patterns of necroptosis in children with autism spectrum disorder (ASD) based on 159 necroptosis-related genes. We identified differentially expressed NRGs and used an unsupervised clustering approach to divide ASD children into distinct molecular subgroups. We also evaluated immunological infiltrations and immune checkpoints using the CIBERSORT algorithm. Characteristic NRGs, identified by the LASSO, RF, and SVM-RFE algorithms, were utilized to construct a risk model. Moreover, functional enrichment, immune infiltration, and CMap analysis were further explored. Additionally, external validation was performed using RT-PCR analysis. Results: Both snRNA-seq and bulk transcriptome data demonstrated a greater necroptosis score in ASD children. Among these cell subtypes, excitatory neurons, inhibitory neurons, and endothelials displayed the highest activity of necroptosis. Children with ASD were categorized into two subtypes of necroptosis, and subtype2 exhibited higher immune activity. Four characteristic NRGs (TICAM1, CASP1, CAPN1, and CHMP4A) identified using three machine learning algorithms could predict the onset of ASD. Nomograms, calibration curves, and decision curve analysis (DCA) based on 3-NRG have been shown to have clinical benefit in children with ASD. Furthermore, necroptosis-based riskScore was found to be positively associated with immune activation. Finally, RT-PCR demonstrated differentially expressed of these four NRGs in human peripheral blood samples. Conclusion: A comprehensive identification of necroptosis may shed light on the underlying pathogenic process driving ASD onset. The classification of necroptosis subtypes and construction of a necroptosis-related risk model may yield significant insights for the individualized treatment of children with ASD.

Neuropilin-1 promotes mitochondrial structural repair and functional recovery in rats with cerebral ischemia.

OBJECTIVES: Available literature documents that ischemic stroke can disrupt the morphology and function of mitochondria and that the latter in other disease models can be preserved by neuropilin-1 (NRP-1) via oxidative stress suppression. However, whether NRP-1 can repair mitochondrial structure and promote functional recovery after cerebral ischemia is still unknown. This study tackled this very issue and explored the underlying mechanism. METHODS: Adeno-associated viral (AAV)-NRP-1 was stereotaxically inoculated into the cortex and ipsilateral striatum posterior of adult male Sprague-Dawley (SD) rats before a 90-min transient middle cerebral artery occlusion (tMCAO) and subsequent reperfusion. Lentivirus (LV)-NRP-1 was transfected into rat primary cortical neuronal cultures before a 2-h oxygen-glucose deprivation and reoxygenation (OGD/R) injury to neurons. The expression and function of NRP-1 and its specific protective mechanism were investigated by Western Blot, immunofluorescence staining, flow cytometry, magnetic resonance imaging, transmission electron microscopy, etc. The binding was detected by molecular docking and molecular dynamics simulation. RESULTS: Both in vitro and in vivo models of cerebral ischemia/reperfusion (I/R) injury presented a sharp increase in NRP-1 expression. The expression of AAV-NRP-1 markedly ameliorated the cerebral I/R-induced damage to the motor function and restored the mitochondrial morphology. The expression of LV-NRP-1 alleviated mitochondrial oxidative stress and bioenergetic deficits. AAV-NRP-1 and LV-NRP-1 treatments increased the wingless integration (Wnt)-associated signals and ß-catenin nuclear localization. The protective effects of NRP-1 were reversed by the administration of XAV-939. CONCLUSIONS: NRP-1 can produce neuroprotective effects against I/R injury to the brain by activating the Wnt/ß-catenin signaling pathway and promoting mitochondrial structural repair and functional recovery, which may serve as a promising candidate target in treating ischemic stroke.

Integration of bulk RNA sequencing and single-cell analysis reveals a global landscape of DNA damage response in the immune environment of Alzheimer's disease.

Background: We developed a novel system for quantifying DNA damage response (DDR) to help diagnose and predict the risk of Alzheimer's disease (AD). Methods: We thoroughly estimated the DDR patterns in AD patients Using 179 DDR regulators. Single-cell techniques were conducted to validate the DDR levels and intercellular communications in cognitively impaired patients. The consensus clustering algorithm was utilized to group 167 AD patients into diverse subgroups after a WGCNA approach was employed to discover DDR-related lncRNAs. The distinctions between the categories in terms of clinical characteristics, DDR levels, biological behaviors, and immunological characteristics were evaluated. For the purpose of choosing distinctive lncRNAs associated with DDR, four machine learning algorithms, including LASSO, SVM-RFE, RF, and XGBoost, were utilized. A risk model was established based on the characteristic lncRNAs. Results: The progression of AD was highly correlated with DDR levels. Single-cell studies confirmed that DDR activity was lower in cognitively impaired patients and was mainly enriched in T cells and B cells. DDR-related lncRNAs were discovered based on gene expression, and two different heterogeneous subtypes (C1 and C2) were identified. DDR C1 belonged to the non-immune phenotype, while DDR C2 was regarded as the immune phenotype. Based on various machine learning techniques, four distinctive lncRNAs associated with DDR, including FBXO30-DT, TBX2-AS1, ADAMTS9-AS2, and MEG3 were discovered. The 4-lncRNA based riskScore demonstrated acceptable efficacy in the diagnosis of AD and offered significant clinical advantages to AD patients. The riskScore ultimately divided AD patients into low- and high-risk categories. In comparison to the low-risk group, high-risk patients showed lower DDR activity, accompanied by higher levels of immune infiltration and immunological score. The prospective medications for the treatment of AD patients with low and high risk also included arachidonyltrifluoromethane and TTNPB, respectively. Conclusions: In conclusion, immunological microenvironment and disease progression in AD patients were significantly predicted by DDR-associated genes and lncRNAs. A theoretical underpinning for the individualized treatment of AD patients was provided by the suggested genetic subtypes and risk model based on DDR.

Identification of immune microenvironment subtypes and signature genes for Alzheimer's disease diagnosis and risk prediction based on explainable machine learning.

Background: Using interpretable machine learning, we sought to define the immune microenvironment subtypes and distinctive genes in AD. Methods: ssGSEA, LASSO regression, and WGCNA algorithms were used to evaluate immune state in AD patients. To predict the fate of AD and identify distinctive genes, six machine learning algorithms were developed. The output of machine learning models was interpreted using the SHAP and LIME algorithms. For external validation, four separate GEO databases were used. We estimated the subgroups of the immunological microenvironment using unsupervised clustering. Further research was done on the variations in immunological microenvironment, enhanced functions and pathways, and therapeutic medicines between these subtypes. Finally, the expression of characteristic genes was verified using the AlzData and pan-cancer databases and RT-PCR analysis. Results: It was determined that AD is connected to changes in the immunological microenvironment. WGCNA revealed 31 potential immune genes, of which the greenyellow and blue modules were shown to be most associated with infiltrated immune cells. In the testing set, the XGBoost algorithm had the best performance with an AUC of 0.86 and a P-R value of 0.83. Following the screening of the testing set by machine learning algorithms and the verification of independent datasets, five genes (CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12) that were closely associated with AD pathological biomarkers and allowed for the accurate prediction of AD progression were found to be immune microenvironment-related genes. The feature gene-based nomogram may provide clinical advantages to patients. Two immune microenvironment subgroups for AD patients were identified, subtype2 was linked to a metabolic phenotype, subtype1 belonged to the immune-active kind. MK-866 and arachidonyltrifluoromethane were identified as the top treatment agents for subtypes 1 and 2, respectively. These five distinguishing genes were found to be intimately linked to the development of the disease, according to the Alzdata database, pan-cancer research, and RT-PCR analysis. Conclusion: The hub genes associated with the immune microenvironment that are most strongly associated with the progression of pathology in AD are CXCR4, PPP3R1, HSP90AB1, CXCL10, and S100A12. The hypothesized molecular subgroups might offer novel perceptions for individualized AD treatment.

Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning.

Introduction: Alzheimer's disease (AD) is a severe dementia with clinical and pathological heterogeneity. Our study was aim to explore the roles of endoplasmic reticulum (ER) stress-related genes in AD patients based on interpretable machine learning. Methods: Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. We performed nine machine learning algorithms including AdaBoost, Logistic Regression, Light Gradient Boosting (LightGBM), Decision Tree (DT), eXtreme Gradient Boosting (XGBoost), Random Forest, K-nearest neighbors (KNN), Naïve Bayes, and support vector machines (SVM) to screen ER stress-related feature genes and estimate their efficiency of these genes for early diagnosis of AD. ROC curves were performed to evaluate model performance. Shapley additive explanation (SHAP) was applied for interpreting the results of these models. AD patients were classified using a consensus clustering algorithm. Immune infiltration and functional enrichment analysis were performed via CIBERSORT and GSVA, respectively. CMap analysis was utilized to identify subtype-specific small-molecule compounds. Results: Higher levels of immune infiltration were found in AD individuals and were markedly linked to deregulated ER stress-related genes. The SVM model exhibited the highest AUC (0.879), accuracy (0.808), recall (0.773), and precision (0.809). Six characteristic genes (RNF5, UBAC2, DNAJC10, RNF103, DDX3X, and NGLY1) were determined, which enable to precisely predict AD progression. The SHAP plots illustrated how a feature gene influence the output of the SVM prediction model. Patients with AD could obtain clinical benefits from the feature gene-based nomogram. Two ER stress-related subtypes were defined in AD, subtype2 exhibited elevated immune infiltration levels and immune score, as well as higher expression of immune checkpoint. We finally identified several subtype-specific small-molecule compounds. Conclusion: Our study provides new insights into the role of ER stress in AD heterogeneity and the development of novel targets for individualized treatment in patients with AD.

Identification and immunological characterization of cuproptosis-related molecular clusters in Alzheimer's disease.

Introduction: Alzheimer's disease is the most common dementia with clinical and pathological heterogeneity. Cuproptosis is a recently reported form of cell death, which appears to result in the progression of various diseases. Therefore, our study aimed to explore cuproptosis-related molecular clusters in Alzheimer's disease and construct a prediction model. Methods: Based on the GSE33000 dataset, we analyzed the expression profiles of cuproptosis regulators and immune characteristics in Alzheimer's disease. Using 310 Alzheimer's disease samples, we explored the molecular clusters based on cuproptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were identified using the WGCNA algorithm. Subsequently, the optimal machine model was chosen by comparing the performance of the random forest model, support vector machine model, generalized linear model, and eXtreme Gradient Boosting. Nomogram, calibration curve, decision curve analysis, and three external datasets were applied for validating the predictive efficiency. Results: The dysregulated cuproptosis-related genes and activated immune responses were determined between Alzheimer's disease and non-Alzheimer's disease controls. Two cuproptosis-related molecular clusters were defined in Alzheimer's disease. Analysis of immune infiltration suggested the significant heterogeneity of immunity between distinct clusters. Cluster2 was characterized by elevated immune scores and relatively higher levels of immune infiltration. Functional analysis showed that cluster-specific differentially expressed genes in Cluster2 were closely related to various immune responses. The Random forest machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.9829). A final 5-gene-based random forest model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.8529 and 0.8333). The nomogram, calibration curve, and decision curve analysis also demonstrated the accuracy to predict Alzheimer's disease subtypes. Further analysis revealed that these five model-related genes were significantly associated with the Aß-42 levels and ß-secretase activity. Conclusion: Our study systematically illustrated the complicated relationship between cuproptosis and Alzheimer's disease, and developed a promising prediction model to evaluate the risk of cuproptosis subtypes and the pathological outcome of Alzheimer's disease patients.

Identification of Ferroptosis-Related Molecular Clusters and Immune Characterization in Autism Spectrum Disorder.

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with clinical presentation and prognostic heterogeneity. Ferroptosis is a regulated non-apoptotic cell death program implicated in the occurrence and progression of various diseases. Therefore, we aimed to explore ferroptosis-related molecular subtypes in ASD and further illustrate the potential mechanism. Methods: A total of 201 normal samples and 293 ASD samples were obtained from the Gene Expression Omnibus (GEO) database. We used the unsupervised clustering analysis to identify the molecular subtypes based on ferroptosis-related genes (FRGs) and evaluate the immune characteristics between ferroptosis subtypes. Ferroptosis signatures were identified using the least absolute shrinkage and selection operator regression (LASSO) and recursive feature elimination for support vector machines (SVM-RFE) machine learning algorithms. The ferroptosis scores based on seven selected genes were constructed to evaluate the ferroptosis characteristics of ASD. Results: We identified 16 differentially expressed FRGs in ASD children compared with controls. Two distinct molecular clusters associated with ferroptosis were identified in ASD. Analysis of immune infiltration revealed immune heterogeneity between the two clusters. Cluster2, characterized by a higher immune score and a larger number of infiltrated immune cells, exhibited a stronger immune response and was markedly enriched in immune response-related signaling pathways. Additionally, the ferroptosis scores model was capable of predicting ASD subtypes and immunity. Higher levels of ferroptosis scores were associated with immune activation, as seen in Cluster2. Lower ferroptosis scores were accompanied by relative immune downregulation, as seen in Cluster1. Conclusion: Our study systematically elucidated the intricate correlation between ferroptosis and ASD and provided a promising ferroptosis score model to predict the molecular clusters and immune infiltration cell profiles of children with ASD.

Comprehensive Analysis of Molecular Subtypes and Hub Genes of Sepsis by Gene Expression Profiles.

Background: Sepsis is a systemic inflammatory response syndrome (SIRS) with heterogeneity of clinical symptoms. Studies further exploring the molecular subtypes of sepsis and elucidating its probable mechanisms are urgently needed. Methods: Microarray datasets of peripheral blood in sepsis were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) analysis was conducted to screen key module genes. Consensus clustering analysis was carried out to identify distinct sepsis molecular subtypes. Subtype-specific pathways were explored using gene set variation analysis (GSVA). Afterward, we intersected subtype-related, dramatically expressed and module-specific genes to screen consensus DEGs (co-DEGs). Enrichment analysis was carried out to identify key pathways. The least absolute shrinkage and selection operator (LASSO) regression analysis was used for screen potential diagnostic biomarkers. Results: Patients with sepsis were classified into three clusters. GSVA showed these DEGs among different clusters in sepsis were assigned to metabolism, oxidative phosphorylation, autophagy regulation, and VEGF pathways, etc. In addition, we identified 40 co-DEGs and several dysregulated pathways. A diagnostic model with 25-gene signature was proven to be of high value for the diagnosis of sepsis. Genes in the diagnostic model with AUC values more than 0.95 in external datasets were screened as key genes for the diagnosis of sepsis. Finally, ANKRD22, GPR84, GYG1, BLOC1S1, CARD11, NOG, and LRG1 were recognized as critical genes associated with sepsis molecular subtypes. Conclusion: There are remarkable differences in and enriched pathways among different molecular subgroups of sepsis, which may be the key factors leading to heterogeneity of clinical symptoms and prognosis in patients with sepsis. Our current study provides novel diagnostic and therapeutic biomarkers for sepsis molecular subtypes.

Bone marrow-derived mesenchymal stem cells improve post-ischemia neurological function in rats via the PI3K/AKT/GSK-3ß/CRMP-2 pathway.

BACKGROUND: Transplantation of bone marrow-derived mesenchymal stem cells (BMSCs) is a potential therapy for cerebral ischemia. However, the underlying protective mechanism remains undetermined. Here, we tested the hypothesis that transplantation of BMSCs via intravenous injection can alleviate neurological functional deficits through activating PI3K/AKT signaling pathway after cerebral ischemia in rats. METHODS: A cerebral ischemic rat model was established by the 2 h middle cerebral artery occlusion (MCAO). Twenty-four hours later, BMSCs (1 × 106 in 1 ml PBS) from SD rats were injected into the tail vein. Neurological function was evaluated by modified neurological severity score (mNSS) and modified adhesive removal test before and on d1, d3, d7, d10 and d14 after MCAO. Protein expressions of AKT, GSK-3ß, CRMP-2 and GAP-43 were detected by Western-bolt. NF-200 was detected by immunofluorescence. RESULTS: BMSCs transplantation did not only significantly improve the mNSS score and the adhesive-removal somatosensory test after MCAO, but also increase the density of NF-200 and the expression of p-AKT, pGSK-3ß and GAP-43, while decrease the expression of pCRMP-2. Meanwhile, these effects can be suppressed by LY294002, a specific inhibitor of PI3K/AKT. CONCLUSION: These data suggest that transplantation of BMSCs could promote axon growth and neurological deficit recovery after MCAO, which was associated with activation of PI3K/AKT /GSK-3ß/CRMP-2 signaling pathway.

Downregulation of Three Immune-Specific Core Genes and the Regulatory Pathways in Children and Adult Friedreich's Ataxia: A Comprehensive Analysis Based on Microarray.

BACKGROUND: Friedreich's ataxia (FRDA) is a familial hereditary disorder that lacks available therapy. Therefore, the identification of novel biomarkers and key mechanisms related to FRDA progression is urgently required. METHODS: We identified the up-regulated and down-regulated differentially expressed genes (DEGs) in children and adult FRDA from the GSE11204 dataset and intersected them to determine the co-expressed DEGs (co-DEGs). Enrichment analysis was conducted and a protein-protein interaction (PPI) network was constructed to identify key pathways and hub genes. The potential diagnostic biomarkers were validated using the GSE30933 dataset. Cytoscape was applied to construct interaction and competitive endogenous RNA (ceRNA) networks. RESULTS: Gene Set Enrichment Analysis (GSEA) indicated that the genes in both the child and adult samples were primarily enriched in their immune-related functions. We identified 88 co-DEGs between child and adult FRDA samples. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome enrichment analysis suggested that these co-DEGs were primarily enriched in immune response, inflammatory reaction, and necroptosis. Immune infiltration analysis showed remarkable differences in the proportions of immune cell subtype between FRDA and healthy samples. In addition, ten core genes and one gene cluster module were screened out based on the PPI network. We verified eight immune-specific core genes using a validation dataset and found CD28, FAS, and ITIF5 have high diagnostic significance in FRDA. Finally, NEAT1-hsa-miR-24-3p-CD28 was identified as a key regulatory pathway of child and adult FRDA. CONCLUSIONS: Downregulation of three immune-specific hub genes, CD28, FAS, and IFIT5, may be associated with the progression of child and adult FRDA. Furthermore, NEAT1-hsa-miR-24-3p-CD28 may be the potential RNA regulatory pathway related to the pathogenesis of child and adult FRDA.

Effect of Functionalized Carbon Microspheres Combined with Ammonium Polyphosphate on Fire Safety Performance of Thermoplastic Polyurethane.

In this article, carbon microspheres (CMSs) synthesized by the hydrothermal method and CMSs-Fe (with Fe3+ adsorbed on the surface of CMSs) were combined with ammonium polyphosphate (APP) to achieve the fire safety improvement of thermoplastic polyurethane (TPU). The fire safety performance of TPU composites was investigated by the cone calorimeter test, microscale combustion calorimeter test, thermogravimetric analysis/infrared spectrometry, Raman spectrometry, X-ray photoelectron spectroscopy, and scanning electron microscopy. The results showed that CMSs and CMSs-Fe can improve the fire safety performance of TPU/APP composites and the effect of CMSs-Fe was better than that of CMSs. The peak heat release rate of the sample containing 0.25 wt % CMSs and 7.75 wt % APP was 16.7% lower than that of the sample containing 8.00 wt % APP, and the content of toxic gases was also reduced in the fire smoke. Also, total heat release and total smoke release of the sample containing CMSs-Fe were 54.7% and 11.6%, respectively, lower than those of the sample containing 0.25% CMSs. It confirmed the contribution of CMSs to the flame retardant system, and the performance of CMSs is improved by adsorbing Fe3+.

Restoration of L-OPA1 alleviates acute ischemic stroke injury in rats via inhibiting neuronal apoptosis and preserving mitochondrial function.

BACKGROUND: Ischemic stroke can induce changes in mitochondrial morphology and function. As a regulatory gene in mitochondria, optic atrophy 1 (OPA1) plays a pivotal role in the regulation of mitochondrial dynamics and other related functions. However, its roles in cerebral ischemia-related conditions are barely understood. METHODS: Cultured rat primary cortical neurons were respectively transfected with OPA1-v1ΔS1-encoding and OPA1-v1-encoding lentivirus before exposure to 2-h oxygen-glucose deprivation (OGD) and subsequent reoxygenation (OGD/R). Adult male SD rats received an intracranial injection of AAV-OPA1-v1ΔS1 and were subjected to 90 min of transient middle cerebral artery occlusion (tMCAO) followed by reperfusion. OPA1 expression and function were detected by in vitro and in vivo assays. RESULTS: OPA1 was excessively cleaved after cerebral ischemia/reperfusion injury, both in vitro and in vivo. Under OGD/R condition, compared with that of the LV-OPA1-v1-treated group, the expression of OPA1-v1ΔS1 efficiently restored L-OPA1 level and alleviated neuronal death and mitochondrial morphological damage. Meanwhile, the expression of OPA1-v1ΔS1 markedly improved cerebral ischemia/reperfusion-induced motor function damage, attenuated brain infarct volume, neuronal apoptosis, mitochondrial bioenergetics deficits, oxidative stress, and restored the morphology of mitochondrial cristae and mitochondrial length. It also preserved the mitochondrial integrity and reinforced the mtDNA content and expression of mitochondrial biogenesis factors in ischemic rats. INTERPRETATION: Our results demonstrate that the stabilization of L-OPA1 protects ischemic brains by reducing neuronal apoptosis and preserving mitochondrial function, suggesting its significance as a promising therapeutic target for stroke prevention and treatment.

IL-10 produces a dual effect on OGD-induced neuronal apoptosis of cultured cortical neurons via the NF-κB pathway.

As a classic immunoregulatory cytokine, interleukin-10 (IL-10) can provide in vivo and in vitro neuroprotection respectively during cerebral ischemia and after the oxygen-glucose deprivation (OGD)-induced injury. However, its role in cortical neuronal survival at different post-ischemic phases remains unclear. The current study found that IL-10 had distinct effects on the neuronal apoptosis at different OGD stages: at an early stage after OGD, IL-10 promoted the OGD-induced neuronal apoptosis in the cultured primary cortical neurons by activating p65 subunit, which up-regulated Bax expression and down-regulated Bcl-xL expression; at a late OGD stage, however, it attenuated the OGD-induced neuronal apoptosis by activating c-Rel, which up-regulated Bcl-xL expression and down-regulated Bax expression. The early-stage pro-apoptosis and late-stage anti-apoptosis were both partly abolished by PDTC, an NF-κB inhibitor, and promoted by PMA, an NF-κB activator. The optimal anti-apoptotic effect appeared when the cultured neurons were treated with IL-10 at 9-24 h after OGD. Taken together, our findings suggest that IL-10 exerts a dual effect on the survival of the cultured neurons by activating the NF-κB pathway at different stages after OGD injury and that PMA treatment at a late stage can facilitate the IL-10-conferred neuroprotection against OGD-induced neuronal injury.

Netrin-1 Promotes Synaptic Formation and Axonal Regeneration via JNK1/c-Jun Pathway after the Middle Cerebral Artery Occlusion.

As a secreted axon guidance molecule, Netrin-1 has been documented to be a neuroprotective factor, which can reduce infarct volume, promote angiogenesis and anti-apoptosis after stroke in rodents. However, its role in axonal regeneration and synaptic formation after cerebral ischemic injury, and the related underlying mechanisms remain blurred. In this study, we used Adeno-associated vectors carrying Netrin-1 gene (AAV-NT-1) to up-regulate the expression level of Netrin-1 in rats' brain after middle cerebral artery occlusion (MCAO). We found that the up-regulated level of Netrin-1 and its receptor DCC promoted axonal regeneration and synaptic formation; the overexpression of Netrin-1 activated the JNK1 signaling pathway; these effects were partially reduced when JNK1 signaling pathway was inhibited by SP600125 (JNK specific inhibitor). Taken together, these findings suggest that Netrin-1 can facilitate the synaptic formation and axonal regeneration via the JNK1 signaling pathway after cerebral ischemia, thus promoting the recovery of neural functions.

Netrin-1 Prevents Rat Primary Cortical Neurons from Apoptosis via the DCC/ERK Pathway.

In the nervous system, Netrin-1 serves as a neural guide, mediating the neuronal development. However, it remains blurred whether Netrin-1 can protect neurons from apoptosis induced by cerebral stroke. In the current study, the cultured rat primary cortical neurons were transfected with Netrin-1-encoding lentivirus before the oxygen-glucose-deprivation (OGD) treatment. Cell death and apoptosis were evaluated by lactate dehydrogenase (LDH) release and flow cytometry. We found that Netrin-1 attenuated OGD-induced cell death and neuronal apoptosis at 24 h after OGD treatment, and that the overexpression of Netrin-1 activated the ERK signaling pathway. These effects were partly abolished by blocking its receptor deleted in colorectal cancer (DCC) or U0126, an inhibitor of the ERK signaling pathway. Netrin-1 overexpression in neurons elevated the expression of DCC, on mRNA level and protein level. Netrin-1 also reduced DNA damage. Taken together, our findings suggest that Netrin-1 attenuates cell death and neuronal apoptosis via the DCC/ERK signaling pathway in the cultured primary cortical neurons after OGD injury, which may involve the mediation of DNA damage in the neurons.