Rabbit Anti-Human SVOP (internal) Polyclonal antibody

Background. The study compared clinician-rated and patient-rated psychopathology and analysed their relationship with subjective quality of life (QoL) in a sample of patients with a wide range of psychiatric conditions attending a community-based mental health service. Methods: In the context of the South-Verona Outcome Project (SVOP), 139 patients were assessed for both clinician-rated and self-rated psychopathology (by using respectively the Brief Psychiatric Rating Scale and the revised version of the Symptom Checklist 90), and asked to report on their subjective quality of life (by using the Lancashire Quality of Life Profile). In order to explore the associations between psychopathology and subjective QoL bivariate and multivariate analyses were performed. Results: BPRS and SCL-90-R were poorly correlated, both in their total scores and in their various dimension scores. BPRS showed only a modest negative correlation with LQL, which, in contrast, was highly negatively correlated with SCL-90-R. Regression analyses showed that patient-rated psychopathology was the strongest predictor of subjective quality of life, with self-rated depressive symptoms and self-reported paranoid ideation having the highest predictive power. Conclusions: Self-reported psychological distress is more important than clinician-rated symptom severity in predicting subjective QoL. In order to improve QoL, psychiatric treatment should focus not only on simple reduction of symptoms but also on patients' subjective psychological distress. Copyright (C) 2002 S. Karger AG, Basel.

Glioblastoma (GBM) is a most aggressive primary cancer in brain with poor prognosis. This study aimed to identify novel tumor biomarkers with independent prognostic values in GBMs. The DNA methylation profiles were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database. Differential methylated genes (DMGs) were screened from recurrent GBM samples using limma package in R software. Functional enrichment analysis was performed to identify major biological processes and signaling pathways. Furthermore, critical DMGs associated with the prognosis of GBM were screened according to univariate and multivariate cox regression analysis. A risk score-based prognostic model was constructed for these DMGs and prediction ability of this model was validated in training and validation data set. In total, 495 DMGs were identified between recurrent samples and disease-free samples, including 356 significantly hypermethylated and 139 hypomethylated genes. Functional and pathway items for these DMGs were mainly related to sensory organ development, neuroactive ligand-receptor interaction, pathways in cancer, etc. Five genes with abnormal methylation level were significantly correlated with prognosis according to survival analysis, such as ALX1, KANK1, NUDT12, SNED1, and SVOP. Finally, the risk model provided an effective ability for prognosis prediction both in training and validation data set. We constructed a novel prognostic model for survival prediction of GBMs. In addition, we identified five DMGs as critical prognostic biomarkers in GBM progression.