To identify pathways associated with survival phenotypes using gene expression data, we recently proposed the hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE) method. The HisCoM-PAGE software can consider hierarchical structural relationships between genes and pathways and analyze multiple pathways simultaneously. It can be applied to various types of gene expression data, such as microarray data or RNA sequencing data. We expect that the HisCoM-PAGE software will make our method more easily accessible to researchers who want to perform pathway analysis for survival times.
Gene Expression ; Methods ; Phenotype ; Sequence Analysis, RNA

To identify pathways associated with survival phenotypes using gene expression data, we recently proposed the hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE) method. The HisCoM-PAGE software can consider hierarchical structural relationships between genes and pathways and analyze multiple pathways simultaneously. It can be applied to various types of gene expression data, such as microarray data or RNA sequencing data. We expect that the HisCoM-PAGE software will make our method more easily accessible to researchers who want to perform pathway analysis for survival times.

In patients with myasthenia gravis, it is difficult to manufacture and maintain dentures because the muscles and nervous system in the oral cavity are not properly adjusted. In addition, excessively extended or thick dentures may cause muscle weakness by stimulating the muscles, so dentures should be manufactured in consideration of this. In this case, a denture was fabricated using the closed mouth technique in a patient with myasthenia gravis with mouth opening limitation. Using the closed mouth technique, the patient’s masticatory pressure and muscle movements were reproduced and denture with good retention were manufactured.

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecological malignancies. Over 70% of ovarian cancer cases are high-grade serous ovarian cancers and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good, and making an accurate prediction of the prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve the patient's prognosis through proper treatment, we present a prognostic prediction model by integrating high-dimensional RNA sequencing data with their clinical data through the following steps: gene filtration, pre-screening, gene marker selection, integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.
Drug Therapy ; Filtration ; Mortality ; Ovarian Neoplasms ; Prognosis ; RNA ; Sequence Analysis, RNA ; Survival Rate

INTRODUCTION: Several studies on the effectiveness of exercise in improving sleep quality in the elderly have been done but have conficting results. This meta-analysis aimed to determine the effect of low- to moderate-intensity aerobic exercise in improving sleep quality among the elderly. METHODS: EBSCO, ClinicalKey, PubMed, Wiley Online Library, and Cochrane Library were searched for articles using the terms “exercise AND sleep quality AND elderly”. The risk of bias assessment was done using the Cochrane Collaboration tool and encoded using RevMan 5.4. Data on outcome measures were subjected to meta-analysis using inverse variance methods. RESULTS: Seven articles with a total of 225 participants were included. There was a statistically signifcant improvement in sleep quality with low to moderate intensity aerobic exercise (MD = -3.87 points; 95% CI -5.56, -2.19 points; p < 0.001). There was a statistically signifcant decrease in total sleep time after intervention (MD = -8.86; 95% CI -16.31, -1.41 points; p = 0.02). There was no improvement in sleep effciency. CONCLUSION Low and moderate intensity exercise improves sleep quality in the elderly and may be used as a non-pharmacologic intervention to enhance sleep quality.

Background/Aims: Several prediction models for evaluating the prognosis of nonmetastatic resected pancreatic ductal adenocarcinoma (PDAC) have been developed, and their performances were reported to be superior to that of the 8th edition of the American Joint Committee on Cancer (AJCC) staging system. We developed a prediction model to evaluate the prognosis of resected PDAC and externally validated it with data from a nationwide Korean database. Methods: Data from the Surveillance, Epidemiology and End Results (SEER) database were utilized for model development, and data from the Korea Tumor Registry System-Biliary Pancreas (KOTUS-BP) database were used for external validation. Potential candidate variables for model development were age, sex, histologic differentiation, tumor location, adjuvant chemotherapy, and the AJCC 8th staging system T and N stages. For external validation, the concordance index (C-index) and time-dependent area under the receiver operating characteristic curve (AUC) were evaluated. Results: Between 2004 and 2016, data from 9,624 patients were utilized for model development, and data from 3,282 patients were used for external validation. In the multivariate Cox proportional hazard model, age, sex, tumor location, T and N stages, histologic differentiation, and adjuvant chemotherapy were independent prognostic factors for resected PDAC. After an exhaustive search and 10-fold cross validation, the best model was finally developed, which included all prognostic variables. The C-index, 1-year, 2-year, 3-year, and 5-year time-dependent AUCs were 0.628, 0.650, 0.665, 0.675, and 0.686, respectively. Conclusions The survival prediction model for resected PDAC could provide quantitative survival probabilities with reliable performance. External validation studies with other nationwide databases are needed to evaluate the performance of this model.