Dimethyl fumarate modulates the immune environment and improves prognosis in the acute phase after ischemic stroke.

INTRODUCTION: Dimethyl fumarate (DMF) has shown potential for protection in various animal models of neurological diseases. However, the impact of DMF on changes in peripheral immune organs and the central nervous system (CNS) immune cell composition after ischemic stroke remains unclear. METHODS: Eight-week-old C57BL/6J mice with photothrombosis (PT) ischemia and patients with acute ischemic stroke (AIS) were treated with DMF. TTC staining, flow cytometry, and immunofluorescence staining were used to evaluate the infarct volume and changes in immune cells in the periphery and the CNS. RESULTS: DMF reduced the infarct volume on Day 1 after PT. DMF reduced the percentages of peripheral immune cells, such as neutrophils, dendritic cells, macrophages and monocytes, on Day 1, followed by NK cells on Day 3 and B cells on Day 7 after PT. In the CNS, DMF significantly reduced the percentage of monocytes in the brain on Day 3 after PT. In addition, DMF increased the number of microglia in the peri-infarct area and reduced the number of neurons in the peri-infarct area in the acute and subacute phases after PT. In AIS patients, B cells decreased in patients receiving alteplase in combination with DMF. CONCLUSION: DMF can change the immune environment of the periphery and the CNS, reduce infarct volume in the acute phase, promote the recruitment of microglia and preserve neurons in the peri-infarct area after ischemic stroke.

Role of ferroptosis in neuroimmunity and neurodegeneration in multiple sclerosis revealed by multi-omics data.

Previous studies have found that ferroptosis plays an important role in a variety of neurological diseases. However, the precise role of ferroptosis in the multiple sclerosis patients remains uncertain. We defined and validated a computational metric of ferroptosis levels. The ferroptosis scores were computed using the AUCell method, which reflects the enrichment scores of ferroptosis-related genes through gene ranking. The reliability of the ferroptosis score was assessed using various methods, involving cells induced to undergo ferroptosis by six different ferroptosis inducers. Through a comprehensive approach integrating snRNA-seq, spatial transcriptomics, and spatial proteomics data, we explored the role of ferroptosis in multiple sclerosis. Our findings revealed that among seven sampling regions of different white matter lesions, the edges of active lesions exhibited the highest ferroptosis score, which was associated with activation of the phagocyte system. Remyelination lesions exhibit the lowest ferroptosis score. In the cortex, ferroptosis score were elevated in neurons, relevant to a variety of neurodegenerative disease-related pathways. Spatial transcriptomics demonstrated a significant co-localization among ferroptosis score, neurodegeneration and microglia, which was verified by spatial proteomics. Furthermore, we established a diagnostic model of multiple sclerosis based on 24 ferroptosis-related genes in the peripheral blood. Ferroptosis might exhibits a dual role in the context of multiple sclerosis, relevant to both neuroimmunity and neurodegeneration, thereby presenting a promising and novel therapeutic target. Ferroptosis-related genes in the blood that could potentially serve as diagnostic and prognostic markers for multiple sclerosis.

MSGD: a manually curated database of genomic, transcriptomic, proteomic and drug information for multiple sclerosis.

Multiple sclerosis (MS) is the most common inflammatory demyelinating disease of the central nervous system. 'Omics' technologies (genomics, transcriptomics, proteomics) and associated drug information have begun reshaping our understanding of multiple sclerosis. However, these data are scattered across numerous references, making them challenging to fully utilize. We manually mined and compiled these data within the Multiple Sclerosis Gene Database (MSGD) database, intending to continue updating it in the future. We screened 5485 publications and constructed the current version of MSGD. MSGD comprises 6255 entries, including 3274 variant entries, 1175 RNA entries, 418 protein entries, 313 knockout entries, 612 drug entries and 463 high-throughput entries. Each entry contains detailed information, such as species, disease type, detailed gene descriptions (such as official gene symbols), and original references. MSGD is freely accessible and provides a user-friendly web interface. Users can easily search for genes of interest, view their expression patterns and detailed information, manage gene sets and submit new MS-gene associations through the platform. The primary principle behind MSGD's design is to provide an exploratory platform, aiming to minimize filtration and interpretation barriers while ensuring highly accessible presentation of data. This initiative is expected to significantly assist researchers in deciphering gene mechanisms and improving the prevention, diagnosis and treatment of MS. Database URL: http://bio-bigdata.hrbmu.edu.cn/MSGD.

Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients.

Background: Stroke is a disease with high morbidity, disability, and mortality. Immune factors play a crucial role in the occurrence of ischemic stroke (IS), but their exact mechanism is not clear. This study aims to identify possible immunological mechanisms by recognizing immune-related biomarkers and evaluating the infiltration pattern of immune cells. Methods: We downloaded datasets of IS patients from GEO, applied R language to discover differentially expressed genes, and elucidated their biological functions using GO, KEGG analysis, and GSEA analysis. The hub genes were then obtained using two machine learning algorithms (least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE)) and the immune cell infiltration pattern was revealed by CIBERSORT. Gene-drug target networks and mRNA-miRNA-lncRNA regulatory networks were constructed using Cytoscape. Finally, we used RT-qPCR to validate the hub genes and applied logistic regression methods to build diagnostic models validated with ROC curves. Results: We screened 188 differentially expressed genes whose functional analysis was enriched to multiple immune-related pathways. Six hub genes (ANTXR2, BAZ2B, C5AR1, PDK4, PPIH, and STK3) were identified using LASSO and SVM-RFE. ANTXR2, BAZ2B, C5AR1, PDK4, and STK3 were positively correlated with neutrophils and gamma delta T cells, and negatively correlated with T follicular helper cells and CD8, while PPIH showed the exact opposite trend. Immune infiltration indicated increased activity of monocytes, macrophages M0, neutrophils, and mast cells, and decreased infiltration of T follicular helper cells and CD8 in the IS group. The ceRNA network consisted of 306 miRNA-mRNA interacting pairs and 285 miRNA-lncRNA interacting pairs. RT-qPCR results indicated that the expression levels of BAZ2B, C5AR1, PDK4, and STK3 were significantly increased in patients with IS. Finally, we developed a diagnostic model based on these four genes. The AUC value of the model was verified to be 0.999 in the training set and 0.940 in the validation set. Conclusion: Our research explored the immune-related gene expression modules and provided a specific basis for further study of immunomodulatory therapy of IS.

Construction of ceRNA network mediated by circRNAs screening from microarray and identification of novel biomarkers for myasthenia gravis.

BACKGROUND: Recent studies have revealed that circRNA can serve as ceRNA to participate in multiple autoimmune diseases. Our study aims to explore the key circRNA as ceRNA and biomarker for MG. METHODS: We used circRNA microarray to explore differentially expressed circRNAs (DECs) from MG and compare with control. Then, we predicted the target miRNA associated with DECs and screened miRNAs by the algorithm of random walk with restart (RWR). Next, we constructed the circRNA-miRNA-mRNA ceRNA regulated network (CMMC) to identify the hub objects. Following, we detected the expression of hub-circRNAs by RT-PCR. We verify has_circ_0004183 (circFRMD4) sponging miR-145-5p regulate cells proliferation using luciferase assay and CCK-8. RESULTS: We found that the expression level of circFRMD4 and has_circ_0035381 (circPIGB) were upregulated and has_circ_0089153(circ NUP214) had the lowest expression level in MG. Finally, we proved circFRMD4 sponging miR-145-5p regulate Jurkat cells proliferation. CircFRMD4 take part in the genesis and development of MG via circFRMD4/miR145-5p axis. CONCLUSIONS: We found that circFRMD4, circPIGB and circNUP214 can be considered as valuable potential novel biomarkers for AchR + MG. CircFRMD4 participate in the development of AchR + MG via targeting binding with miR-145-5p.

Bibliometric analysis: Hot spots and frontiers in acupuncture treatment of cerebral infarction.

OBJECTIVE: CiteSpace6.1.R2 is used to analyze the research status of acupuncture in the treatment of cerebral infarction, and to find relevant hot spots and frontiers. METHODS: The researchers searched the Web of Science Core Collection database. The search date is from the establishment of the database to August 31, 2023. The search terms and expressions are: ("Cerebral Infarction" OR "Ischemic stroke") AND ("Acupuncture" OR "fire needle"). The researchers used CiteSpace software to draw a knowledge map to explore the hot spots and frontiers of acupuncture in treating cerebral infarction. RESULTS: We screened 414 articles in the Web of Science Core Collection database. China is the country with the largest number of publications, with a total of 343 papers published. China's institutions cooperate most closely, and cooperation between countries is less and more scattered. The author with the highest number of published articles is Chen L, with a total of 31 published articles. The research focus mainly revolves around the mechanism of acupuncture treatment of cerebral infarction and electroacupuncture treatment of cerebral infarction. Among them, acupuncture treatment of cerebral infarction is the most. CONCLUSION: According to CiteSpace's analysis results, China is at the forefront of this research field, while other countries have less research in this field and little cooperation among countries. At present, the mainstream aspect of research is the mechanism of acupuncture treatment of cerebral infarction electroacupuncture and acupuncture points. Therefore, in future research, we should pay more attention to the treatment of cerebral infarction mechanism of acupuncture, problems with the type of acupuncture used, and acupuncture points.

Identification of potential immune-related hub genes in Parkinson's disease based on machine learning and development and validation of a diagnostic classification model.

BACKGROUND: Parkinson's disease is the second most common neurodegenerative disease in the world. However, current diagnostic methods are still limited, and available treatments can only mitigate the symptoms of the disease, not reverse it at the root. The immune function has been identified as playing a role in PD, but the exact mechanism is unknown. This study aimed to search for potential immune-related hub genes in Parkinson's disease, find relevant immune infiltration patterns, and develop a categorical diagnostic model. METHODS: We downloaded the GSE8397 dataset from the GEO database, which contains gene expression microarray data for 15 healthy human SN samples and 24 PD patient SN samples. Screening for PD-related DEGs using WGCNA and differential expression analysis. These PD-related DEGs were analyzed for GO and KEGG enrichment. Subsequently, hub genes (dld, dlk1, iars and ttd19) were screened by LASSO and mSVM-RFE machine learning algorithms. We used the ssGSEA algorithm to calculate and evaluate the differences in nigrostriatal immune cell types in the GSE8397 dataset. The association between dld, dlk1, iars and ttc19 and 28 immune cells was investigated. Using the GSEA and GSVA algorithms, we analyzed the biological functions associated with immune-related hub genes. Establishment of a ceRNA regulatory network for immune-related hub genes. Finally, a logistic regression model was used to develop a PD classification diagnostic model, and the accuracy of the model was verified in three independent data sets. The three independent datasets are GES49036 (containing 8 healthy human nigrostriatal tissue samples and 15 PD patient nigrostriatal tissue samples), GSE20292 (containing 18 healthy human nigrostriatal tissue samples and 11 PD patient nigrostriatal tissue samples) and GSE7621 (containing 9 healthy human nigrostriatal tissue samples and 16 PD patient nigrostriatal tissue samples). RESULTS: Ultimately, we screened for four immune-related Parkinson's disease hub genes. Among them, the AUC values of dlk1, dld and ttc19 in GSE8397 and three other independent external datasets were all greater than 0.7, indicating that these three genes have a certain level of accuracy. The iars gene had an AUC value greater than 0.7 in GES8397 and one independent external data while the AUC values in the other two independent external data sets ranged between 0.5 and 0.7. These results suggest that iars also has some research value. We successfully constructed a categorical diagnostic model based on these four immune-related Parkinson's disease hub genes, and the AUC values of the joint diagnostic model were greater than 0.9 in both GSE8397 and three independent external datasets. These results indicate that the categorical diagnostic model has a good ability to distinguish between healthy individuals and Parkinson's disease patients. In addition, ceRNA networks reveal complex regulatory relationships based on immune-related hub genes. CONCLUSION: In this study, four immune-related PD hub genes (dld, dlk1, iars and ttd19) were obtained. A reliable diagnostic model for PD classification was developed. This study provides algorithmic-level support to explore the immune-related mechanisms of PD and the prediction of immune-related drug targets.

Study of molecular patterns associated with ferroptosis in Parkinson's disease and its immune signature.

Parkinson's disease is the second most common neurodegenerative disease in the world. We downloaded data on Parkinson's disease and Ferroptosis-related genes from the GEO and FerrDb databases. We used WCGAN and Random Forest algorithm to screen out five Parkinson's disease ferroptosis-related hub genes. Two genes were identified for the first time as possibly playing a role in Braak staging progression. Unsupervised clustering analysis based on hub genes yielded ferroptosis isoforms, and immune infiltration analysis indicated that these isoforms are associated with immune cells and may represent different immune patterns. FRHGs scores were obtained to quantify the level of ferroptosis modifications in each individual. In addition, differences in interleukin expression were found between the two ferroptosis subtypes. The biological functions involved in the hub gene are analyzed. The ceRNA regulatory network of hub genes was mapped. The disease classification diagnosis model and risk prediction model were also constructed by applying hub genes based on logistic regression. Multiple external datasets validated the hub gene and classification diagnostic model with some accuracy. This study explored hub genes associated with ferroptosis in Parkinson's disease and their molecular patterns and immune signatures to provide new ideas for finding new targets for intervention and predictive biomarkers.

Which institutional investors can improve the level of corporate ESG information disclosure?

The inconsistency of existing findings on the relationship between institutional investors' shareholdings and the level of corporate Environmental, Social and Governance (ESG) disclosure may lie in the insufficient consideration of the heterogeneity of institutional investors and investee firms. In this paper, from the perspective of institutional investor heterogeneity, we use a two-way fixed effects model to examine the impact of institutional investors on corporate ESG disclosure and the possible mechanism of this impact using a sample of Chinese A-share-listed firms from 2012 to 2020. We show that institutional investor shareholding can improve the level of corporate ESG information disclosure by enhancing auditor supervision and analyst attention to these external supervision. In terms of institutional investor heterogeneity, it is found that independent institutional investors and stable institutional investors play a stronger role in promoting the level of ESG information disclosure. Moreover, the positive net effect of the institutional investors on improving the level of ESG information disclosure is more pronounced in non-heavily polluting industries and state-owned enterprises. This paper enriches the impact of institutional investors' shareholding on corporate ESG disclosure from a heterogeneity perspective.

Identifying patients with acute ischemic stroke within a 6-h window for the treatment of endovascular thrombectomy using deep learning and perfusion imaging.

Introduction: It is critical to identify the stroke onset time of patients with acute ischemic stroke (AIS) for the treatment of endovascular thrombectomy (EVT). However, it is challenging to accurately ascertain this time for patients with wake-up stroke (WUS). The current study aimed to construct a deep learning approach based on computed tomography perfusion (CTP) or perfusion weighted imaging (PWI) to identify a 6-h window for patients with AIS for the treatment of EVT. Methods: We collected data from 377 patients with AIS, who were examined by CTP or PWI before making a treatment decision. Cerebral blood flow (CBF), time to maximum peak (Tmax), and a region of interest (ROI) mask were preprocessed from the CTP and PWI. We constructed the classifier based on a convolutional neural network (CNN), which was trained by CBF, Tmax, and ROI masks to identify patients with AIS within a 6-h window for the treatment of EVT. We compared the classification performance among a CNN, support vector machine (SVM), and random forest (RF) when trained by five different types of ROI masks. To assess the adaptability of the classifier of CNN for CTP and PWI, which were processed respectively from CTP and PWI groups. Results: Our results showed that the CNN classifier had a higher performance with an area under the curve (AUC) of 0.935, which was significantly higher than that of support vector machine (SVM) and random forest (RF) (p = 0.001 and p = 0.001, respectively). For the CNN classifier trained by different ROI masks, the best performance was trained by CBF, Tmax, and ROI masks of Tmax > 6 s. No significant difference was detected in the classification performance of the CNN between CTP and PWI (0.902 vs. 0.928; p = 0.557). Discussion: The CNN classifier trained by CBF, Tmax, and ROI masks of Tmax > 6 s had good performance in identifying patients with AIS within a 6-h window for the treatment of EVT. The current study indicates that the CNN model has potential to be used to accurately estimate the stroke onset time of patients with WUS.

RNA2Immune: A Database of Experimentally Supported Data Linking Non-coding RNA Regulation to The Immune System.

Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), have emerged as important regulators of the immune system and are involved in the control of immune cell biology, disease pathogenesis, as well as vaccine responses. A repository of ncRNA-immune associations will facilitate our understanding of ncRNA-dependent mechanisms in the immune system and advance the development of therapeutics and prevention for immune disorders. Here, we describe a comprehensive database, RNA2Immune, which aims to provide a high-quality resource of experimentally supported database linking ncRNA regulatory mechanisms to immune cell function, immune disease, cancer immunology, and vaccines. The current version of RNA2Immune documents 50,433 immune-ncRNA associations in 42 host species, including (1) 6690 ncRNA associations with immune functions involving 31 immune cell types; (2) 38,672 ncRNA associations with 348 immune diseases; (3) 4833 ncRNA associations with cancer immunology; and (4) 238 ncRNA associations with vaccine responses involving 26 vaccine types targeting 22 diseases. RNA2Immune provides a user-friendly interface for browsing, searching, and downloading ncRNA-immune system associations. Collectively, RNA2Immune provides important information about how ncRNAs influence immune cell function, how dysregulation of these ncRNAs leads to pathological consequences (immune diseases and cancers), and how ncRNAs affect immune responses to vaccines. RNA2Immune is available at http://bio-bigdata.hrbmu.edu.cn/rna2immune/home.jsp.

Comparison of Tongue Acupuncture and Traditional Acupuncture in the Treatment of Poststroke Dysarthria: A Meta-Analysis and Tongue Acupuncture System Classification Evaluation.

Objective: To discuss whether tongue acupuncture is more effective than traditional acupuncture in the treatment of poststroke dysarthria and explore the advantage of tongue acupuncture treatment parameters. Methods: We evaluated the efficacy of tongue acupuncture compared with traditional acupuncture through a rigorous meta-analysis process. The included studies were from eight databases in English and Chinese. The Cochrane risk of bias assessment tool was used to evaluate the quality of studies. Stata15.1 software was used for meta-analysis and sensitivity analysis. Tongue acupuncture therapeutic parameters were classified and counted based on tongue acupoint location, acupuncture manipulation, and the number of manipulations. Subgroup analysis was used to compare the differences between various treatment parameters. Outcome The meta-analysis eventually included a total of 9 studies. Tongue acupuncture is superior to traditional acupuncture in clinical efficacy [OR = 3.62, 95%Cl (2.24, 5.85), P < 0.0001], FDA score [SMD = -1.99, 95%Cl (-3.77, -0.21), P=0.028], and NIHSS score [WMD = 0.86, 95%Cl (0.15, 1.57), P=0.017, I2 = 31.7%] in the treatment of poststroke dysarthria. According to the classified statistics of tongue acupuncture treatment parameters, there are three kinds of tongue acupuncture points in 9 studies: lingual surface, sublingual, and both lingual surface and sublingual acupoints. The operation methods include the oblique stabbing of the root of the tongue, twisting after stabbing, and acupoint pricking. The number of operation methods varies from 1 to 3. Conclusion: Tongue acupuncture outperforms traditional acupuncture in terms of clinical efficacy, FDA score, and NIHSS score in the treatment of poststroke dysarthria. The curative effect of sublingual acupoints is better than that of lingual surface acupoints, the combined use of multiple manipulations is better than that of a single manipulation, and acupuncture manipulation has a cumulative effect. PROSPERO registration number: CRD42021285722.

Identification of circulating immune landscape in ischemic stroke based on bioinformatics methods.

Ischemic stroke (IS) is a high-incidence disease that seriously threatens human life and health. Neuroinflammation and immune responses are key players in the pathophysiological processes of IS. However, the underlying immune mechanisms are not fully understood. In this study, we attempted to identify several immune biomarkers associated with IS. We first retrospectively collected validated human IS immune-related genes (IS-IRGs) as seed genes. Afterward, potential IS-IRGs were discovered by applying random walk with restart on the PPI network and the permutation test as a screening strategy. Doing so, the validated and potential sets of IS-IRGs were merged together as an IS-IRG catalog. Two microarray profiles were subsequently used to explore the expression patterns of the IS-IRG catalog, and only IS-IRGs that were differentially expressed between IS patients and controls in both profiles were retained for biomarker selection by the Random Forest rankings. CLEC4D and CD163 were finally identified as immune biomarkers of IS, and a classification model was constructed and verified based on the weights of two biomarkers obtained from the Neural Network algorithm. Furthermore, the CIBERSORT algorithm helped us determine the proportions of circulating immune cells. Correlation analyses between IS immune biomarkers and immune cell proportions demonstrated that CLEC4D was strongly correlated with the proportion of neutrophils (r = 0.72). These results may provide potential targets for further studies on immuno-neuroprotection therapies against reperfusion injury.

Ultrathin porous carbon nanosheet as an efficient adsorbent for the removal of bisphenol A: The overlooked role of topological defects.

Carbon-based materials are emerging as a type of inexpensive and efficient adsorbent, although their genuine adsorption site is still debatable. Herein, we present a novel approach for designing and constructing an ultra-thin defect-rich hierarchically porous carbon nanosheet (ZG-C). The ZG-C sample demonstrated a high adsorption capacity for bisphenol A (BPA) (602.2 mg/g) along with a fast adsorption process (20 min), and stable reusability (the decline efficiency was 9.14% after five consecutive cycles). Based on comprehensive experiments and a number of characterizations, the high adsorption capacity of ZG-C for BPA was connected with the hierarchical porous structure of ZG-C and multiple intrinsic defects of ZG-C. The results of density functional theory (DFT) further demonstrated that topological defects played an indispensable role in promoting adsorption, and its adsorption energy (-0.595 eV) for BPA was much higher than that of other intrinsic defects. This study not only provides an innovative and simple strategy for preparing hierarchically porous carbon-based adsorbent with abundant intrinsic defects for the efficient removal of BPA, but also significantly contributes to the understanding of the application of carbon-based materials to remove bisphenols.

LncRNA LINC00680 Acts as a Competing Endogenous RNA and Is Associated With the Severity of Myasthennia Gravis.

Background and Purpose: Myasthenia gravis (MG) is a T cell-dependent antibody-mediated autoimmune disorder that can seriously affect patients' quality of life. However, few studies have focused on the severity of MG. Moreover, existing therapeutic efforts, including those targeting biomarkers for MG, remain unsatisfactory. Therefore, it is vital that we investigate the pathogenesis of MG and identify new biomarkers that can not only evaluate the severity of the disease but also serve as potential therapeutic targets. Long noncoding RNA LINC00680 has been found to be associated with the progression of a variety of diseases as a competing endogenous RNA (ceRNA). However, the specific role of LINC00680 in MG has yet to be clarified. Here, we aimed to investigate the association between LINC00680 and the severity of MG. Methods: Bioinformatics tools, quantitative real-time PCR, Western blotting, and luciferase assays were selected to investigate key signaling pathways and RNA expression in patients with MG. The Quantitative MG Score scale and the MG Composite scale were used to evaluate the severity of MG in the included patients. Cell viability assays and flow cytometry analysis were selected to analyze cell proliferation and apoptosis. Results: Compared with control subjects, the expression levels of LINC00680 and mitogen-activated protein kinase 1 (MAPK1) in peripheral blood mononuclear cells of patients with MG were both upregulated; the levels of miR-320a were downregulated. A positive correlation was detected between LINC00680 expression and the severity of MG. Luciferase reporter assays identified that LINC00680 acts as a target for miR-320a. The in vitro analysis confirmed that LINC00680 regulates the expression of MAPK1 by sponging miR-320a. Finally, the functional analysis indicated that LINC00680 promoted Jurkat cell proliferation and inhibited cellular apoptosis by sponging miR-320a. Conclusion: LINC00680 may be associated with the severity of MG as a ceRNA by sponging miR-320a to upregulate MAPK1. These findings suggest that LINC00680 may represent a potential biomarker which evaluates the severity of MG and may serve as a therapeutic target.

Evolution of ischemic stroke drug clinical trials in mainland China from 2005 to 2021.

BACKGROUND: To assess the temporal changes in the characteristics of ischemic stroke drug clinical trials conducted in mainland China in 2005-2021. METHODS: A statistical analysis of registered clinical trials on ischemic stroke was performed using the platform of the Center for Drug Evaluation of China National Medical Products Administration, the Chinese Clinical Trial Registry, and ClinicalTrials.gov websites. RESULTS: From January 1, 2005 to August 1, 2021, a total of 384 registered drug clinical trials on ischemic stroke were identified in mainland China. Over time, the number of trials gradually increased each year, with a significant growth in 2014, from 16 in 2013 to 42 in 2014. Phase IV trials (31.8%) accounted for the majority, followed by phase II (16.4%), phase I (10.9%), and phase III (8.6%). In terms of sponsorship, the proportion of investigator-initiated trials (IITs) (60.7%) was higher than industry-sponsored trials (ISTs) (39.3%). Additionally, trials involving traditional Chinese medicines (TCMs) (36.2%) accounted for the largest proportion, followed by trials involving antithrombotic therapy (19.5%) and cerebral protection agents (16.7%). Furthermore, over the past 17 years, the number of leading drug clinical trial units for ischemic stroke in mainland China has continuously increased. The leading principal units from Beijing, Shanghai, Guangdong, Jiangsu, and Liaoning accounted for the majority of the trials (67.4%). CONCLUSION: In the past 17 years, great progress has been made in the research and development (R&D) of drugs and clinical trials for ischemic stroke in mainland China. The most extensive progress was observed in TCMs, antithrombotic therapy, and cerebral protection agents. More clinical trials are needed to confirm whether the newly developed drugs can improve the clinical efficacy of ischemic stroke. Simultaneously, more pharmaceutical R&D efforts of innovative drugs are warranted.

LncRNA OIP5-AS1 modulates the proliferation and apoptosis of Jurkat cells by sponging miR-181c-5p to regulate IL-7 expression in myasthenia gravis.

Background: Myasthenia gravis (MG) is an antibody-mediated autoimmune disease. In recent years, accumulating evidence has indicated that long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs), contributing to the progression of various autoimmune diseases. Nevertheless, the regulatory roles of ceRNAs in MG pathogenesis remain unclear. In this study, we aimed to elucidate the role of lncRNA OIP5-AS1 as a ceRNA associated with MG progression. Methods: Real-time PCR was used to detect OIP5-AS1 levels in peripheral blood mononuclear cells (PBMCs) from patients with MG. Luciferase reporter assays were performed to validate the relationship between OIP5-AS1 and miR-181c-5p. CCK-8 and flow cytometry were performed to test the proliferation and apoptotic abilities of OIP5-AS1 in Jurkat cells. Furthermore, real-time PCR and Western blot assays were performed to explore the interactions between OIP5-AS1, miR-181c-5p, and IL-7. Results: The expression of OIP5-AS1 was up-regulated in patients with MG. Luciferase reporter assay indicated that OIP5-AS1 targeted the miR-181c-5p. Functional assays showed that OIP5-AS1 suppressed Jurkat cell apoptosis and promoted cell proliferation by sponging miR-181c-5p. Mechanistically, knockdown of OIP5-AS1 inhibited IL-7 expression at both the mRNA and protein levels in Jurkat cells, whereas the miR-181c-5p inhibitor blocked the reduction of IL-7 expression induced by OIP5-AS1 suppression. Conclusions: We confirmed that OIP5-AS1 serves as an endogenous sponge for miR-181c-5p to regulate the expression of IL-7. Our findings provide novel insights into MG processes and suggests potential therapeutic targets for patients with MG.

Dissecting and analyzing the Subclonal Mutations Associated with Poor Prognosis in Diffuse Glioma.

The prognostic and therapeutic implications in diffuse gliomas are still challenging. In this study, we first performed an integrative framework to infer the clonal status of mutations in glioblastomas (GBMs) and low-grade gliomas (LGGs) by using exome sequencing data from TCGA and observed both clonal and subclonal mutations for most mutant genes. Based on the clonal status of a given gene, we systematically investigated its prognostic value in GBM and LGG, respectively. Focusing on the subclonal mutations, our results showed that they were more likely to contribute to the poor prognosis, which could be hardly figured out without considering clonal status. These risk subclonal mutations were associated with some specific genomic features, such as genomic instability and intratumor heterogeneity, and their accumulation could enhance the prognostic value. By analyzing the regulatory mechanisms underlying the risk subclonal mutations, we found that the subclonal mutations of AHNAK and AHNAK2 in GBM and those of NF1 and PTEN in LGG could influence some important molecules and functions associated with glioma progression. Furthermore, we dissected the role of risk subclonal mutations in tumor evolution and found that advanced subclonal mutations showed poorer overall survival. Our study revealed the importance of clonal status in prognosis analysis, highlighting the role of the subclonal mutation in glioma prognosis.

Construction Immune Related Feed-Forward Loop Network Reveals Angiotensin II Receptor Blocker as Potential Neuroprotective Drug for Ischemic Stroke.

Ischemic stroke (IS) accounts for the leading cause of disability and mortality in China. Increasing researchers are studying the effects of neuroprotective agents on IS. However, the molecular mechanisms of feed-forward loops (FFLs) associated with neuroprotection in the pathogenesis of IS need to be further studied. A protein-protein interaction (PPI) network of IS immune genes was constructed to decipher the characters and excavate 3 hub genes (PI3K, IL6, and TNF) of immunity. Then, we identified two hub clusters of IS immune genes, and the cytokine-cytokine receptor interaction pathway was discovered on the pathway enrichment results of both clusters. Combined with GO enrichment analysis, the cytokines participate in the inflammatory response in the extracellular space of IS patients. Next, a transcription factor (TF)-miRNA-immune gene network (TMIGN) was established by extracting four regulatory pairs (TF-miRNA, TF-gene, miRNA-gene, and miRNA-TF). Then, we detected 3-node regulatory motif types in the TMIGN network. According to the criteria we set for defining 3-node motifs, the motif with the highest Z-score (3-node composite FFL) was picked as the statistically evident motif, which was merged to construct an immune-associated composite FFL motif-specific sub-network (IA-CFMSN), which contained 21 3-node FFLs composed of 13 miRNAs, 4 TFs, 9 immune genes, and 1 TF& immune gene, among which TP53 and VEGFA were prominent TF and immune gene, respectively. In addition, the immune genes in IA-CFMSN were used for identifying associated pathways and drugs to further clarify the immune regulation mechanism and neuroprotection after IS. As a result, 5 immune genes targeted by 20 drugs were identified and the Angiotensin II Receptor Blockers (ARBs) target AGTR1 was found to be a neuroprotective drug for IS. In the present study, the construction of IA-CFMSN provides IS immune-associated FFLs for further experimental studies, providing new prospects for the discovery of new biomarkers and potential drugs for IS.

Dedicator of Cytokinesis 2 (DOCK2) Silencing Protects Against Cerebral Ischemia/Reperfusion by Modulating Microglia Polarization via the Activation of the STAT6 Signaling Pathway.

Cerebral ischemia/reperfusion is the major pathophysiological process in stroke and could lead to severe and permanent disability. The current study aimed to investigate the effects of dedicator of cytokinesis 2 (DOCK2) on cerebral ischemia/reperfusion-induced cerebral injury. We established a mouse middle cerebral artery occlusion (MCAO) model with suture-occluded method in vivo. Then, BV-2 cells were conducted to oxygen-glucose deprivation and re-oxygenation (OGD/R) in vitro. The results showed that DOCK2 was highly expressed in ischemic brain following MCAO and in BV-2 cells induced by OGD/R. DOCK2 depletion protected against MCAO-induced brain infarcts and neuron degeneration. DOCK2 downregulation improved long-term neurological function, which was assessed by the Morris water-maze test. Moreover, silencing of DOCK2 promoted M2 polarization (anti-inflammation) and repressed M1 polarization (pro-inflammation) of microglia both in vivo and in vitro. Subsequently, we found that the loss of DOCK2 upregulated the expression of p-STAT6. DOCK2 knockdown-induced microglial cell polarization towards M2 phenotype was partly abrogated by the STAT6 inhibitor AS1517499. In conclusion, DOCK2 downregulation protected against cerebral ischemia/reperfusion by modulating microglia polarization via the activation of the STAT6 signaling pathway.