A tract-based spatial statistics study of white matter integrity in epilepsy.

OBJECTIVE: To explore the changes of cerebral white matter diffusion tensor in epilepsy. METHODS: This study was a retrospective study based on diffusion tensor imaging (DTI). Twenty-six epileptic patients and 42 normal controls matched for sex, age and handedness were enrolled in our research. Based on the method of tract-based spatial statistics (TBSS), we analyzed the changes of each relevant parameter index of DTI in white matter of the brain in all subjects, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). RESULTS: In comparison with the control group, epileptic patients had decreased FA and elevated MD, AD, and RD in the anterior thalamic radiation, corticospinal tract, forceps major, forceps minor, cingulum, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus and uncinate fasciculus (P < 0.05). CONCLUSION: Widespread white matter integrity was observed in epileptic patients, which may be the structural basis for the development of affective disorders, impaired cognition, and motor abnormalities.

Development of a prognostic model of glioma based on immune-related genes.

Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma, and particularly that of patients with glioblastoma, is poor. Tumor immunity serves an important role in the development of glioma. However, immunotherapy for glioma has not been completely successful, and thus, comprehensive examination of the immune-related genes (IRGs) of glioma is required. In the present study, differentially expressed genes (DEGs) and differentially expressed IRGs (DEIRGs) were identified using the edgeR package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used for functional enrichment analysis of DEIRGs. Survival-associated IRGs were selected via univariate Cox regression analysis. A The Cancer Genome Atlas prognostic model and GSE43378 validation model were established using lasso-penalized Cox regression analysis. Based on the median risk score value, patients were divided into high-risk and low-risk groups for clinical analysis. Receiver operating characteristic curve and nomogram analyses were used to assess the accuracy of the models. Reverse transcription-quantitative PCR was performed to measure the expression levels of relevant genes, such as cyclin-dependent kinase 4 (CDK4), interleukin 24 (IL24), NADPH oxidase 4 (NOX4), bone morphogenetic protein 2 (BMP2) and baculoviral IAP repeat containing 5 (BIRC5). A total of 3,238 DEGs, including 1,950 upregulated and 1,288 downregulated DEGs, and 97 DEIRGs, including 60 upregulated and 37 downregulated DEIRGs, were identified. 'Neuroactive ligand-receptor interaction' and 'Cytokine-cytokine receptor interaction' were the most significantly enriched pathways according to KEGG pathway analysis. A prognostic model and a validation prognostic model were created for glioma, including 15 survival-associated IRGs (FCER1G, NOX4, TRIM5, SOCS1, APOBEC3C, BIRC5, VIM, TNC, BMP2, CMTM3, IL24, JAG1, CALCRL, HNF4G and CDK4). Furthermore, multivariate Cox regression analysis results suggested that age, high WHO Grade by histopathology, wild type isocitrate dehydrogenase 1 and high risk score were independently associated with poor overall survival. The infiltration of B cells, CD8+ T cells, dendritic cells, macrophages and neutrophils was positively associated with the prognostic risk score. In the present study, several clinically significant survival-associated IRGs were identified, and a prognosis evaluation model of glioma was established.

Comprehensive analysis of a long non-coding RNA-associated competing endogenous RNA network in glioma.

Long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs), interacting with microRNAs (miRNAs) and playing an important role in tumor progression. However, the role of lncRNA-mediated ceRNAs in glioma remains largely unknown. The present study aimed to identify novel lncRNAs and their associated function in glioma. RNA sequencing and corresponding clinical data from patients with glioma were obtained from The Cancer Genome Atlas. A total of 598 glioma tissues and 5 normal brain tissues were analyzed in the present study. The differentially expressed (DE) lncRNAs, mRNAs and miRNAs were identified using R packages and were used to construct a ceRNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate the biological functions of the DEmRNAs. Kaplan-Meier curve analysis was performed to investigate the association between DElncRNA expression and patient outcome. A total of 752 DElncRNAs, 2,079 DEmRNAs and 113 DEmiRNAs were identified between glioma and normal tissues. A lncRNA-miRNA-mRNA ceRNA network consisting of 61 lncRNAs, 12 miRNAs and 92 mRNAs was constructed. Survival analysis indicated that 36 DElncRNAs, 72 DEmRNAs and 3 DEmiRNAs were associated with overall survival in patients with glioma. The present study identified novel lncRNAs associated with survival prognosis and may facilitate further investigation of lncRNA-mediated ceRNA regulatory mechanisms in glioma.

Prognostic value of immune related genes in lung adenocarcinoma.

Lung cancer has the highest incidence and mortality rates of all cancers in China. Immune-related genes and immune infiltrating lymphocytes are involved in tumor growth, and in the past decade, immunotherapy has become increasingly important in the treatment of lung cancer. Using the edgeR package, differentially expressed genes and immune-related genes (DEIRGs) were identified in patients with lung adenocarcinoma (LUAD). Functional enrichment analysis of DEIRGs was performed using Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Survival-associated immune-related genes (IRGs) were selected using univariate Cox regression analysis and the prognostic model was assessed using multivariate Cox regression analysis. Overall, 273 DEIRGs were identified in LUAD, and KEGG pathway analysis of IRGs showed that 'cytokine-cytokine receptor interaction' was the most significantly enriched pathway. Furthermore, six survival associated IRGs were screened to establish a prognostic model; patients in the high risk score group had less favorable survival times, and the prognostic model was negatively associated with B cell infiltration. The present study established a prognostic model using analysis of survival-related immune-related genes, which were associated with B cell infiltration.

Establishment of a Prognostic Model Using Immune-Related Genes in Patients With Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most prevalent neoplasms worldwide, particularly in China. Immune-related genes (IRGs) and immune infiltrating lymphocytes play specific roles in tumor growth. Considering how important immunotherapy has become for HCC treatment in the past decade, our objective was to establish a prognostic model by screening survival-related IRGs in patients with HCC. Using edgeR, we identified differentially expressed IRGs (DEIRGs), DEmiRNAs, and DElncRNAs. Functional enrichment analysis of DEIRGs was performed to investigate the biological functions of IRGs via gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Protein-protein interaction and competing endogenous RNA networks were established using Cytoscape. Survival-associated IRGs were selected via univariate COX regression analysis, a The Cancer Genome Atlas (TCGA) prognostic model and GSE76427 validation model were developed using multivariate COX regression analysis test by AIC (Akaike Information Criterion). We identified 116 DEIRGs in patients with HCC; the "cytokine-cytokine receptor interaction" pathway was found to be the most enriched pathway. Via the prognostic model helped us classify patients into high- and low-risk score groups based on overall survival (OS); high risk score was associated with worse OS, and a positive correlation was observed between the prognostic model and immune cell infiltration. To summarize, we established a prognostic model using survival-related IRGs that provides sufficient information for prognosis prediction and immunotherapy of patients with HCC.

Neurocutaneous Melanosis in an Adult Patient with Intracranial Primary Malignant Melanoma: Case Report and Review of the Literature.

BACKGROUND: To explore the clinical characteristics of neurocutaneous melanosis (NCM) in adult patients to help improve diagnosis and treatment of this disease, we present a rare case of an adult patient suffering from NCM with malignant melanoma, as well as a review of the relevant Chinese and English literature. CASE DESCRIPTION: The patient reported here plus the patients identified in our literature review total 30 adults with NCM (20 males [66.7%] and 10 females [33.3%]), age 19-65 years (average, 27.9 years). These include 24 cases of malignant melanoma (80.0%), 3 cases of melanocytoma (10.0%), 2 cases of diffuse melanocytosis (6.7%), and 1 case of unknown pathology (3.3%). Satellite nevi were reported in 25 cases (83.3%) and in 5 cases their presence was unknown (16.7%). Intracranial lesions were present in 28 cases (93.3%), and intraspinal lesions were present in 2 cases (6.7%). There are 4 cases of combined hydrocephalus (13.3%), and 2 cases of combined Dandy-Walker deformity (6.7%). CONCLUSIONS: NCM is a rare disease, especially in adults. With the onset of symptoms, the diagnosis is generally confirmed. In children with congenital giant nevus, regular periodic surveys of the central nervous system (brain and spinal cord) with magnetic resonance imaging or cerebrospinal fluid analysis should be performed to diagnose NCM. Active treatment should be undertaken to improve the prognosis.

17ß-Oestradiol promotes differentiation of human embryonic stem cells into dopamine neurons via cross-talk between insulin-like growth factors-1 and oestrogen receptor ß.

Human embryonic stem cells (hESCs) can self-renew and differentiate into all cell lineages. E2 is known to exhibit positive effects on embryo development. Although the importance of E2 in many physiological processes has been reported, to date few researchers have investigated the effects of E2 on hESCs differentiation. We studied the effects of E2 on dopamine (DA) neuron induction of hESCs and its related signalling pathways using the three-stage protocol. In our study, 0.1 µM E2 were applied to hESCs-derived human embryoid bodies (hEBs) and effects of E2 on neural cells differentiation were investigated. Protein and mRNA level assay indicated that E2 up-regulated the expression of insulin-like growth factors (IGF)-1, ectoderm, neural precursor cells (NPC) and DA neuron markers, respectively. The population of hESC-derived NPCs and DA neurons was increased to 92% and 93% to that of DMSO group, respectively. Furthermore, yield of DA neuron-secreted tyrosine hydroxylase (TH) and dopamine was also increased. E2-caused promotion was relieved in single inhibitor (ICI or JB1) group partly, and E2 effects were repressed more stronger in inhibitors combination (ICI plus JB1) group than in single inhibitor group at hEBs, hNPCs and hDA neurons stages. Owing to oestrogen receptors regulate multiple brain functions, when single or two inhibitors were used to treat neural differentiation stage, we found that oestrogen receptor (ER)ß but not ERα is strongly repressed at the hNPCs and hDA neurons stage. These findings, for the first time, demonstrate the molecular cascade and related cell biology events involved in E2-improved hNPC and hDA neuron differentiation through cross-talk between IGF-1 and ERß in vitro.