Elderly depression symptoms was the only factor significantly associating with poor sleep quality after adjustment. Higher level of physical activity was associated with better sleep quality in univariate analysis but not in multivariate analysis, which considered the factor of elderly depression symptoms in the elderly. The role of physical activity in late life potentially influence sleep quality but may have less significance compared with depression. Therefore, we suggest the need for more future research to investigate the relationship between elderly people's sleep and physical activity.

BackgroundsInternet addiction (IA) has become a major public health issue worldwide and is closely linked to psychiatric disorders and suicide. The present study aimed to investigate the prevalence of IA and its associated psychosocial and psychopathological determinants among internet users across different age groups.MethodsThe study was a cross-sectional survey initiated by the Taiwan Suicide Prevention Center. The participants were recruited from the general public who responded to the online questionnaire. They completed a series of self-reported measures, including Chen Internet Addiction Scale-revised (CIAS-R), Five-item Brief Symptom Rating Scale (BSRS-5), Maudsley Personality Inventory (MPI), and questions about suicide and internet use habits.ResultsWe enrolled 1100 respondents with a preponderance of female subjects (85.8%). Based on an optimal cutoff for CIAS-R (67/68), the prevalence rate of IA was 10.6%. People with higher scores of CIAS-R were characterized as: male, single, students, high neuroticism, life impairment due to internet use, time for internet use, online gaming, presence of psychiatric morbidity, recent suicide ideation and past suicide attempts. Multiple regression on IA showed that age, gender, neuroticism, life impairment, internet use time, and BSRS-5 score accounted for 31% of variance for CIAS-R score. Further, logistic regression showed that neuroticism, life impairment and internet use time were three main predictors for IA. Compared to those without IA, the internet addicts had higher rates of psychiatric morbidity (65.0%), suicide ideation in a week (47.0%), lifetime suicide attempts (23.1%), and suicide attempt in a year (5.1%).ConclusionNeurotic personality traits, psychopathology, time for internet use and its subsequent life impairment were important predictors for IA. Individuals with IA may have higher rates of psychiatric morbidity and suicide risks. The findings provide important information for further investigation and prevention of IA.

The transcriptional network of the SRY (sex determining region Y)-box 17 (SOX17) and the prognostic impact of SOX17 protein expression in human cancers remain largely unclear. In this study, we evaluated the prognostic effect of low SOX17 protein expression and its dysregulation of transcriptional network in esophageal squamous cell carcinoma (ESCC). Low SOX17 protein expression was found in 47.4% (73 of 154) of ESCC patients with predicted poor prognosis. Re-expression of SOX17 in ESCC cells caused reduced foci formation, cell motility, decreased ESCC xenograft growth and metastasis in animals. Knockdown of SOX17 increased foci formation in ESCC and normal esophageal cells. Notably, 489 significantly differential genes involved in cell growth and motility controls were identified by expression array upon SOX17 overexpression and 47 genes contained putative SRY element in their promoters. Using quantitative chromatin immunoprecipitation-PCR and promoter activity assays, we confirmed that MACC1, MALAT1, NBN, NFAT5, CSNK1A1, FN1 and SERBP1 genes were suppressed by SOX17 via the SRY binding-mediated transcriptional regulation. Overexpression of FN1 and MACC1 abolished SOX17-mediated migration and invasion suppression. The inverse correlation between SOX17 and FN1 protein expression in ESCC clinical samples further strengthened our conclusion that FN1 is a transcriptional repression target gene of SOX17. This study provides compelling clinical evidence that low SOX17 protein expression is a prognostic biomarker and novel cell and animal data of SOX17-mediated suppression of ESCC metastasis. We establish the first transcriptional network and identify new suppressive downstream genes of SOX17 which can be potential therapeutic targets for ESCC.

BackgroundHigh smoking prevalence is a major public health concern for people with mental disorders. Improved monitoring could be facilitated through electronic health record (EHR) databases. We evaluated whether EHR information held in structured fields might be usefully supplemented by open-text information. The prevalence and correlates of EHR-derived current smoking in people with severe mental illness were also investigated.MethodsAll cases had been referred to a secondary mental health service between 2008-2011 and received a diagnosis of schizophreniform or bipolar disorder. The study focused on those aged over 15 years who had received active care from the mental health service for at least a year (N=1,555). The ‘CRIS-IE-Smoking’ application used General Architecture for Text Engineering (GATE) natural language processing software to extract smoking status information from open-text fields. A combination of CRIS-IE-Smoking with data from structured fields was evaluated for coverage and the prevalence and demographic correlates of current smoking were analysed.ResultsProportions of patients with recorded smoking status increased from 11.6% to 64.0% through supplementing structured fields with CRIS-IE-Smoking data. The prevalence of current smoking was 59.6% in these 995 cases for whom this information was available. After adjustment, younger age (below 65 years), male sex, and non-cohabiting status were associated with current smoking status.ConclusionsA natural language processing application substantially improved routine EHR data on smoking status above structured fields alone and could thus be helpful in improving monitoring of this lifestyle behaviour. However, limited information on smoking status remained a challenge.

Acute kidney injury (AKI) is associated with higher hospital mortality. However, the relationship between geriatric AKI and in-hospital complications is unclear. We prospectively enrolled elderly patients (≥65 years) from general medical wards of National Taiwan University Hospital, part of whom presented AKI at admission. We recorded subsequent in-hospital complications, including catastrophic events, incident gastrointestinal bleeding, hospital-associated infections, and new-onset electrolyte imbalances. Regression analyses were utilized to assess the associations between in-hospital complications and the initial AKI severity. A total of 163 elderly were recruited, with 39% presenting AKI (stage 1: 52%, stage 2: 23%, stage 3: 25%). The incidence of any in-hospital complication was significantly higher in the AKI group than in the non-AKI group (91% vs. 68%, p < 0.01). Multiple regression analyses indicated that elderly patients presenting with AKI had significantly higher risk of developing any complication (Odds ratio [OR] = 3.51, p = 0.01) and new-onset electrolyte imbalance (OR = 7.1, p < 0.01), and a trend toward more hospital-associated infections (OR = 1.99, p = 0.08). The risk of developing complications increased with higher AKI stage. In summary, our results indicate that initial AKI at admission in geriatric patients significantly increased the risk of in-hospital complications.