Inhibiting Caveolin-1-Related Akt/mTOR Signaling Pathway Protects Against N-methyl-D-Aspartate Receptor Activation-Mediated Dysfunction of Blood-Brain Barrier in vitro.

BACKGROUND: The aim of this study was to further explore the role of caveolin-1 (Cav-1) related Akt/mTOR signaling pathway in blood brain barrier (BBB) dysfunction caused by NMDAR activation. METHODS: The cell localization of NMDAR GluN1 subunit and Cav-1 was observed on human brain microvascular HBEC-5i cells after immunofluorescence double staining. The transendothelial resistance (TEER) of BBB in vitro was measured by Millicell-ERS cell resistance meter. Sodium fluorescein (SF) was used to measure the permeability of BBB in vitro. A stable Cav-1-silenced HBEC-5i cell line was established by infecting the cells with a lentivirus encoding Cav-1 shRNA. The changes of the protein and mRNA of MMP9 and Occludin induced by NMDA were detected by Western blot (WB) and real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), respectively. The phosphorylated proteins of Cav-1, Akt, and mTOR were detected by WB. RESULTS: NMDAR GluN1 was expressed in the cytoplasm and part of the cell membrane of the HBEC-5i cell line. NMDAR activation decreased TEER and increased the SF of BBB in vitro. HBEC-5i cells incubated with NMDA enhanced the phosphorylation of Cav-1, Akt, and mTOR, also promoting the expression of MMP9 along with the degradation of Occludin. These effects could be reversed by pretreatment with NMDAR antagonist (MK801) or Cav-1 antagonist (Daidzein), or Akt antagonist (LY294002), respectively. Further silencing Cav-1 with LV-Cav-1-RNAi also played a similar protective effect. CONCLUSION: Caveolin-1 (Cav-1) related Akt/mTOR signaling probably contributes to BBB dysfunction by activating NMDAR on human brain microvascular cells.

Exploring the bidirectional causal link between household income status and genetic susceptibility to neurological diseases: findings from a Mendelian randomization study.

Objectives: Observational studies have revealed that socioeconomic status is associated with neurological disorders and aging. However, the potential causal effect between the two remains unclear. We therefore aimed to investigate the causal relationship between household income status and genetic susceptibility to neurological diseases using a bidirectional Mendelian randomization (MR) study. Methods: An MR study was conducted on a large-sample cohort of the European population pulled from a publicly available genome-wide association study dataset, using a random-effects inverse-variance weighting model as the main standard. MR-Egger regression, weighted median, and maximum likelihood estimation were also performed concurrently as supplements. A sensitivity analysis, consisting of a heterogeneity test and horizontal pleiotropy test, was performed using Cochran's Q, MR-Egger intercept, and MR-PRESSO tests to ensure the reliability of the conclusion. Results: The results suggested that higher household income tended to lower the risk of genetic susceptibility to Alzheimer's disease (odds ratio [OR]: 0.740, 95% confidence interval [CI] = 0.559-0.980, p-value = 0.036) and ischemic stroke (OR: 0.801, 95% CI = 0.662-0.968, p-value = 0.022). By contrast, higher household income tended to increase the risk of genetic susceptibility to Parkinson's disease (OR: 2.605, 95% CI = 1.413-4.802, p-value = 0.002). No associations were evident for intracranial hemorrhage (OR: 1.002, 95% CI = 0.607-1.653, p-value = 0.993), cerebral aneurysm (OR: 0.597, 95% CI = 0.243-1.465, p-value = 0.260), subarachnoid hemorrhage (OR: 1.474, 95% CI = 0.699-3.110, p-value = 0.308), or epilepsy (OR: 1.029, 95% CI = 0.662-1.600, p-value = 0.899). The reverse MR study suggested no reverse causal relationship between neurological disorders and household income status. A sensitivity analysis verified the reliability of the results. Conclusion: Our results revealed that the populations with a superior household income exhibit an increased predisposition of genetic susceptibility to Parkinson's Disease, while demonstrating a potential decreased genetic susceptibility to ischemic stroke and Alzheimer's disease.

DCAF12 and HSPA1A May Serve as Potential Diagnostic Biomarkers for Myasthenia Gravis.

Background: Myasthenia gravis (MG) is an autoimmune disease that severely affects the life quality of patients. This study explores the differences in immune cell types between MG and healthy control and the role of immune-related genes in the diagnosis of MG. Methods: The GSE85452 dataset was downloaded from the Gene Expression Omnibus (GEO) database and analyzed using the limma package to determine differentially expressed genes (DEGs) between patients with MG and the control group. Differentially expressed immune cells were analyzed using single-sample gene set enrichment analysis (GSEA), while immune cell-associated modules were identified by weighted gene coexpression network analysis (WGCNA). Then, the expression of the identified hub genes was confirmed by RT-PCR in peripheral blood mononuclear cells (PBMCs) of MG patients. The R package pROC was used to plot the receiver operating characteristics (ROC) curves. Results: The modules related to CD56bright natural killer cells were identified by GSEA and WGCNA. The proportion of CD56bright natural killer cells in the peripheral blood of MG patients is low. The results of RT-PCR showed that the levels of DDB1- and CUL4-associated factor 12 (DCAF12) and heat shock protein family A member 1A (HSPA1A) were significantly decreased in peripheral blood mononuclear cells of MG patients compared with healthy controls. The ROC curve results of DCAF12 and HSPA1A mRNA in MG diagnosis were 0.780 and 0.830, respectively. Conclusions: CD56bright NK cell is lower in MG patients and may affect MG occurrence. DCAF12 and HSPA1A are lowly expressed in PBMCs of MG patients and may serve as the diagnostic biomarkers of MG.

N-methyl-D-aspartic acid increases tight junction protein destruction in brain endothelial cell via caveolin-1-associated ERK1/2 signaling.

N-methyl-D-aspartic acid (NMDA), a glutamate analog, can activate N-Methyl-D-Aspartate receptor (NMDAR) to induce vascular endothelial cell injury but the mechanisms are not fully understood. The present study intended to evaluate the role of caveolin-1 (Cav-1) in NMDA-induced dysfunction of human brain microvascular endothelial cells (HBEC-5i), and verify that endothelial NMDAR activation mediates the disruption of tight junction barrier integrity via extracellular signal-regulated kinase (ERK)1/2 pathway. The expression of NMDAR NR1 were confirmed firstly in HBEC-5i and compared with that in mouse brain by Western blot. To study the role of Cav-1 in NMDA mediated reduction of tight junction protein zonula occludens- (ZO) 1 expression, HBEC-5i were transduced with Cav-1 shRNA or Control shRNA, and the Cav-1 knockdown rate tested with qRT-PCR and Western blot is 99.98% or 87.5%, respectively. NMDA exposure decreased mRNA and protein levels of tight junction protein ZO-1 and suppressed transendothelial electrical resistance (TEER) values in HBEC-5i but blocked by NMDAR antagonist MK801. In addition, NMDA induced Cav-1 and ERK1/2 sequential phosphorylation，but these effects were attenuated by silencing the Cav-1 gene with shRNA and ERK1/2 inhibitor U0126, respectively. These results show that the functional presence of NMDAR NR1 in HBEC-5i. Endothelial NMDAR NR1 activation regulate the maintenance of HBEC-5i-constructed tight junction barrier integrity via the caveolin-1-associated ERK1/2 signaling pathway.

Factors Influencing the Withdrawal of Antiepileptic Drugs in Adult Patients with Symptomatic Seizures Secondary to Neuronal Surface Antibodies-Associated Autoimmune Encephalitis.

PURPOSE: This retrospective study aimed to investigate the relationship between clinical characteristics, seizure outcomes, and the potential factors influencing the withdrawal of antiepileptic drugs (AEDs) in adult patients with symptomatic seizures secondary to neuronal surface antibody (NSAb)-associated autoimmune encephalitis (AE). PATIENTS AND METHODS: Eighty-one patients (age ≥18 years) diagnosed with NSAb-associated AE were included in this retrospective study. After at least 1 year of follow-up, clinical details, magnetic resonance imaging (MRI) findings, electroencephalography (EEG) data, cerebrospinal fluid parameters, and the therapeutic outcomes were analyzed. Patients who needed long-term AEDs to control seizures were divided into two groups (withdrawal ≤1 year and withdrawal >1 year). Multivariable logistic regression analysis was performed to identify the risk factors affecting the AEDs' withdrawal in patients with seizures secondary to NSAb-associated AE. RESULTS: During the 12-month follow-up after AEDs' withdrawal, 28 (44.4%) patients among the 63 patients who needed long-term AEDs stopped AEDs within 1 year, while 35 (55.6%) patients continued AEDs treatment. Multivariable logistic regression analysis showed that delayed immunotherapy, status epilepticus (SE), and elevated intrathecal Immunoglobulin G synthesis rate of 24 hours (24-h intrathecal IgG) were independent risk factors for delayed withdrawal in patients with seizure secondary to NSAb-associated AE (odds ratios: 1.129, 6.497, 3.415, P<0.05). The receiver operating characteristics (ROC) curve analysis showed that the area under the curve (AUC) of delayed immunotherapy, SE, and elevated 24-h intrathecal IgG was 0.816 (95% CI=0.711-0.921, P<0.001). CONCLUSION: Delayed immunotherapy, status epilepticus and elevated 24-hour intrathecal IgG synthesis rate are the factors that may influence the decision to delay AEDs' withdrawal.

NMDA mediates disruption of blood-brain barrier permeability via Rho/ROCK signaling pathway.

Glutamate can activate the N-methyl-D-aspartatic acid (NMDA) receptor (NMDAR), damage brain microvascular endothelial cells, and disturb the intercellular tight junctions (TJs). These result in changes in the permeability of the blood brain barrier (BBB). In neurons, the activation of Rho/ROCK signaling pathway is related to the activation of NMDAR，however, whether human brain vascular endothelial cells NMDAR mediates the Rho/ROCK pathway is not fully understood. The present study evaluates the effects of excessive NMDAR activation induced by NMDA (a glutamate analog) on the Rho/ROCK signaling pathway and the permeability of BBB by using a primary human brain microvascular endothelial cell (HBMEC) model. NMDAR subunit GluN1 was expressed in HBMECs and promoted by NMDA detected by Western blot and qRT-PCR. Furthermore, NMDA exposure decreased HBMEC viability, promoted HBMEC apoptosis, increased intracellular reactive oxygen species (ROS) levels, and destroyed the endothelial cytoskeleton. Additionally, NMDA exposure suppressed transendothelial electrical resistance (TEER) values and the expression of TJ proteins occludin and claudin5; it also promoted ROCK activated substrate myosin phosphatase target subunit-1 (MYPT)-1 phosphorylation and the transmittance of sodium fluorescein. In contrast, these effects were attenuated by ROCK inhibitor hydroxyfasudil (HF) and NMDAR antagonist MK801, respectively. Therefore, these results indicate that excessive endothelial NMDAR activation induced by NMDA may induce TJs and cytoskeleton damage, while HF attenuated NMDA-induced cytotoxicity in HBMECs by inhibiting the Rho/ROCK signaling pathway.

Development and validation of a model to estimate the risk of acute ischemic stroke in geriatric patients with primary hypertension.

OBJECTIVES: This study aimed to construct and validate a prediction model of acute ischemic stroke in geriatric patients with primary hypertension. METHODS: This retrospective file review collected information on 1367 geriatric patients diagnosed with primary hypertension and with and without acute ischemic stroke between October 2018 and May 2020. The study cohort was randomly divided into a training set and a testing set at a ratio of 70 to 30%. A total of 15 clinical indicators were assessed using the chi-square test and then multivariable logistic regression analysis to develop the prediction model. We employed the area under the curve (AUC) and calibration curves to assess the performance of the model and a nomogram for visualization. Internal verification by bootstrap resampling (1000 times) and external verification with the independent testing set determined the accuracy of the model. Finally, this model was compared with four machine learning algorithms to identify the most effective method for predicting the risk of stroke. RESULTS: The prediction model identified six variables (smoking, alcohol abuse, blood pressure management, stroke history, diabetes, and carotid artery stenosis). The AUC was 0.736 in the training set and 0.730 and 0.725 after resampling and in the external verification, respectively. The calibration curve illustrated a close overlap between the predicted and actual diagnosis of stroke in both the training set and testing validation. The multivariable logistic regression analysis and support vector machine with radial basis function kernel were the best models with an AUC of 0.710. CONCLUSION: The prediction model using multiple logistic regression analysis has considerable accuracy and can be visualized in a nomogram, which is convenient for its clinical application.