One sided bypass for bilateral Moyamoya disease, a case report and review of the literatures

AbstractBackgroundMoyamoya disease (MMD) is a rare condition, where the most appropriate treatment for it is yet to be determined. Surgery remains an important method of choice although it is considered a form of palliative care. The outcome following surgery is very difficult to judge, and there is no standardised measurement to assess it. It is therefore important to know which approach for such patient is adequate.Clinical presentationA 21-year-old male patient presented with signs and symptoms of intracranial haemorrhage. Upon investigation, a diagnosis of bilateral MMD was made, and one sided direct bypass surgery was subsequently performed. At 3-year follow-up, there is no evidence of recurrent cerebral vascular event.ConclusionThis case provided further evidence that direct bypass surgery is beneficial for patient in terms of blood flow improvement and symptom relieve. Although there is no consensus on whether bilateral surgical intervention is mandatory for patient with bilateral MMD, unilateral bypass might be sufficient enough. Further study is required to evaluate the best approach for such group of patient

Is There a Role for Treating Inflammation in Moyamoya Disease?: A Review of Histopathology, Genetics, and Signaling Cascades

Moyamoya disease is a slowly progressing steno-occlusive condition affecting the cerebrovasculature. Affecting the terminal internal carotid arteries (ICA) and there branches, bilaterally, a resulting in a fine vascular network in the base of the brain to allow for compensation of the stenosed vessels. While there is obvious evidence of the involvement of inflammatory proteins in the condition, this has historically not been acknowledged as a causal factor. Here we describe the fundamental histopathology, genetics, and signaling cascades involved in moyamoya and debate whether these factors can be linked as causal factor for the condition or whether they are simply a secondary result of the ischemia described in the condition. A particular focus has been placed on the multitude of signaling cascades linked to the condition as these are viewed as having the greatest therapeutic potential. As such we hope to draw some novel insight into potential diagnostic and therapeutic inflammatory targets in the condition

A Novel Soybean Dirigent Gene GmDIR22 Contributes to Promotion of Lignan Biosynthesis and Enhances Resistance to Phytophthora sojae

Phytophthora root and stem rot caused by the oomycete pathogen Phytophthora sojae is a destructive disease of soybean worldwide. Plant dirigent proteins (DIR) are proposed to have roles in biosynthesis of either lignan or lignin-like molecules, and are important for defense responses, secondary metabolism, and pathogen resistance. In the present work, a novel DIR gene expressed sequence tag is identified as up-regulated in the highly resistant soybean cultivar ‘Suinong 10’ inoculated with P. sojae. The full length cDNA is isolated using rapid amplification of cDNA ends, and designated GmDIR22 (GenBank accession no. HQ_993047). The full length GmDIR22 is 789 bp and contains a 567 bp open reading frame encoding a polypeptide of 188 amino acids. The sequence analysis indicated that GmDIR22 contains a conserved dirigent domain at amino acid residues 43–187. The quantitative real-time reverse transcription PCR demonstrated that soybean GmDIR22 mRNA is expressed most highly in stems, followed by roots and leaves. The treatments with stresses demonstrated that GmDIR22 is significantly induced by P. sojae and gibberellic acid (GA3), and also responds to salicylic acid, methyl jasmonic acid, and abscisic acid. The GmDIR22 is targeted to the cytomembrane when transiently expressed in Arabidopsis protoplasts. Moreover, The GmDIR22 recombinant protein purified from Escherichia coli could effectively direct E-coniferyl alcohol coupling into lignan (+)-pinoresinol. Accordingly, the overexpression of GmDIR22 in transgenic soybean increased total lignan accumulation. Moreover, the lignan extracts from GmDIR22 transgenic plants effectively inhibits P. sojae hyphal growth. Furthermore, the transgenic overexpression of GmDIR22 in the susceptible soybean cultivar ‘Dongnong 50’ enhances its resistance to P. sojae. Collectively, these data suggested that the primary role of GmDIR22 is probably involved in the regulation of lignan biosynthesis, and which contributes to resistance to P. sojae

FSPP: A Tool for Genome-Wide Prediction of smORF-Encoded Peptides and Their Functions

smORFs are small open reading frames of less than 100 codons. Recent low throughput experiments showed a lot of smORF-encoded peptides (SEPs) played crucial rule in processes such as regulation of transcription or translation, transportation through membranes and the antimicrobial activity. In order to gather more functional SEPs, it is necessary to have access to genome-wide prediction tools to give profound directions for low throughput experiments. In this study, we put forward a functional smORF-encoded peptides predictor (FSPP) which tended to predict authentic SEPs and their functions in a high throughput method. FSPP used the overlap of detected SEPs from Ribo-seq and mass spectrometry as target objects. With the expression data on transcription and translation levels, FSPP built two co-expression networks. Combing co-location relations, FSPP constructed a compound network and then annotated SEPs with functions of adjacent nodes. Tested on 38 sequenced samples of 5 human cell lines, FSPP successfully predicted 856 out of 960 annotated proteins. Interestingly, FSPP also highlighted 568 functional SEPs from these samples. After comparison, the roles predicted by FSPP were consistent with known functions. These results suggest that FSPP is a reliable tool for the identification of functional small peptides. FSPP source code can be acquired at https://www.bioinfo.org/FSPP

DataSheet_3_Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.xlsx

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.</p

DataSheet_5_Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.xlsx

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.</p

DataSheet_2_Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.xlsx

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.</p

DataSheet_4_Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.xlsx

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.</p

DataSheet_1_Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.xlsx

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.</p