Williamriggs6060

Mostly increased deposition of fat on the trunk which is considered as a marker of possible development of metabolic syndrome was apparent already in preschool age, indicating the importance of early intervention concerning also physical activity and availability for exercise since early life.Cancer progression may be affected by metabolism. In this study, we aimed to analyze the effect of glucose on the proliferation and/or survival of human hepatocellular carcinoma (HCC) cells. Human gene datasets regulated by glucose were compared to gene datasets either dysregulated in HCC or regulated by other signaling pathways. Significant numbers of common genes suggested putative involvement in transcriptional regulations by glucose. Real-time proliferation assays using high (4.5 g/L) versus low (1 g/L) glucose on two human HCC cell lines and specific inhibitors of selected pathways were used for experimental validations. High glucose promoted HuH7 cell proliferation but not that of HepG2 cell line. Gene network analyses suggest that gene transcription by glucose could be mediated at 92% through ChREBP in HepG2 cells, compared to 40% in either other human cells or rodent healthy liver, with alteration of LKB1 (serine/threonine kinase 11) and NOX (NADPH oxidases) signaling pathways and loss of transcriptional regulation of PPARGC1A (peroxisome-proliferator activated receptors gamma coactivator 1) target genes by high glucose. Both PPARA and PPARGC1A regulate transcription of genes commonly regulated by glycolysis, by the antidiabetic agent metformin and by NOX, suggesting their major interplay in the control of HCC progression.Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Long-term unemployment is associated with poorer mental health. The aim of this study was to evaluate the effectiveness of a health promotion program using the train-the-trainer approach on health-related quality of life (HRQoL) and mental health of long-term unemployed persons.

A prospective parallel-group study was conducted among 365 long-term unemployed persons. 287 participants (179 members of the intervention group IG and 108 members of the control group) were reassessed after three months. The intervention comprised both individual sessions based on Motivational Interviewing and participatory group sessions; no health promotion program was administered in the control group. The endpoints were HRQoL (SF-12), depression, and anxiety. The effect size of the change across time in the IG and CG was measured by Cohen's d. To assess the significance of group differences in the change across time, a random effects model was used.

Within three months HRQoL improved and anxiety and depression decreased significantly in the IG. A significant intervention effect was observed for anxiety (p = 0.012). Effect sizes in the IG were small to moderate in terms of Cohen's d (anxiety d = -0.33; SF-12 mental d = 0.31; depression d = -0.25; SF-12 physical d = 0.19).

The health promotion program, based on a train-the-trainer approach, showed positive effects on HRQoL and mental health, especially anxiety, of long-term unemployed persons, a highly burdened target group where an improvement in mental health is a crucial prerequisite to social participation and successful reintegration into the job market.

The health promotion program, based on a train-the-trainer approach, showed positive effects on HRQoL and mental health, especially anxiety, of long-term unemployed persons, a highly burdened target group where an improvement in mental health is a crucial prerequisite to social participation and successful reintegration into the job market.

Severe sepsis and septic shock are associated with substantial mortality. However, few studies have assessed the risk of septic shock among patients who suffered from urinary tract infection (UTI).

This retrospective study recruited UTI cases from an acute care hospital between January 2006 and October 2012 with prospective data collection.

Of the 710 participants admitted for UTI, 80 patients (11.3%) had septic shock. The rate of bacteremia is 27.9%; acute kidney injury is 12.7%, and the mortality rate is 0.28%. Multivariable logistic regression analyses indicated that coronary artery disease (CAD) (OR 2.521, 95% CI 1.129-5.628, P = 0.024), congestive heart failure (CHF) (OR 4.638, 95% CI 1.908-11.273, P = 0.001), and acute kidney injury (AKI) (OR 2.992, 95% CI 1.610-5.561, P = 0.001) were independently associated with septic shock in patients admitted with UTI. In addition, congestive heart failure (female, OR 4.076, 95% CI 1.355-12.262, P = 0.012; male, OR 5.676, 95% CI 1.103-29.220, P = 0.038, resp.) and AKI (female, OR 2.995, 95% CI 1.355-6.621, P = 0.007; male, OR 3.359, 95% CI 1.158-9.747, P = 0.026, resp.) were significantly associated with risk of septic shock in both gender groups.

This study showed that patients with a medical history of CAD or CHF have a higher risk of shock when admitted for UTI treatment. AKI, a complication of UTI, was also associated with septic shock. Crenolanib in vivo Therefore, prompt and aggressive management is recommended for those with higher risks to prevent subsequent treatment failure in UTI patients.

This study showed that patients with a medical history of CAD or CHF have a higher risk of shock when admitted for UTI treatment. AKI, a complication of UTI, was also associated with septic shock. Therefore, prompt and aggressive management is recommended for those with higher risks to prevent subsequent treatment failure in UTI patients.Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature. This approach splits the traditional processing of hypothesis generation with classic ABC model into AB model and BC model which are constructed with supervised learning method. Compared with the concept cooccurrence and grammar engineering-based approaches like SemRep, machine learning based models usually can achieve better performance in information extraction (IE) from texts. Then through combining the two models, the approach reconstructs the ABC model and generates biomedical hypotheses from literature. The experimental results on the three classic Swanson hypotheses show that our approach outperforms SemRep system.Heart disease is the leading cause of death worldwide. Therefore, assessing the risk of its occurrence is a crucial step in predicting serious cardiac events. Identifying heart disease risk factors and tracking their progression is a preliminary step in heart disease risk assessment. A large number of studies have reported the use of risk factor data collected prospectively. Electronic health record systems are a great resource of the required risk factor data. Unfortunately, most of the valuable information on risk factor data is buried in the form of unstructured clinical notes in electronic health records. In this study, we present an information extraction system to extract related information on heart disease risk factors from unstructured clinical notes using a hybrid approach. The hybrid approach employs both machine learning and rule-based clinical text mining techniques. The developed system achieved an overall microaveraged F-score of 0.8302.In skeletal muscle, dystroglycan (DG) is the central component of the dystrophin-glycoprotein complex (DGC), a multimeric protein complex that ensures a strong mechanical link between the extracellular matrix and the cytoskeleton. Several muscular dystrophies arise from mutations hitting most of the components of the DGC. Mutations within the DG gene (DAG1) have been recently associated with two forms of muscular dystrophy, one displaying a milder and one a more severe phenotype. This review focuses specifically on the animal (murine and others) model systems that have been developed with the aim of directly engineering DAG1 in order to study the DG function in skeletal muscle as well as in other tissues. In the last years, conditional animal models overcoming the embryonic lethality of the DG knock-out in mouse have been generated and helped clarifying the crucial role of DG in skeletal muscle, while an increasing number of studies on knock-in mice are aimed at understanding the contribution of single amino acids to the stability of DG and to the possible development of muscular dystrophy.

Catha edulis Forsk. (Khat) is used for its psychoactive effects among people in Africa and the Arabian Peninsula, although its utilization is illegal in some countries such as Saudi Arabia. This study examined the pattern of Khat use and assessed the applicability of the Drug Abuse Screening Test-10 (DAST-10) to measure Khat dependence.

A pretested questionnaire was used to gather data from 603 respondents. Variables included demographic characteristics, pattern of use, reasons for Khat chewing, and DAST-10. Stepwise-logistic regression was used to explore predictors of Khat dependence.

The majority of the respondents were married, had a secondary school level of education, were employed, were younger than 35 years old, and were living in rural areas. Many chewers gave more than one reason for using Khat. It was mainly used to increase mental capacity, physical strength, and social entertainment, as well as enhance cheerfulness and orgasms. Statistical modeling of Khat dependence suggested that the most significant predictors were residence (OR = 1.67, P < 0.02), frequency of Khat chewing (OR = 4.8, P < 0.01), age of starting Khat chewing (OR = 1.15, P < 0.01), and time of Khat effect (OR = 1.15, P < 0.04).

Our study provides important information on the pattern of Khat use and its potential to cause dependence.

Our study provides important information on the pattern of Khat use and its potential to cause dependence.Micro-RNAs (miRNAs) are regulators of gene expression that control various biological processes. The role of many identified miRNAs is not yet resolved. Recent evidence suggests that miRNA mutations and/or misexpression may contribute to genetic disorders. Point mutations in the seed region of MIR184 have been recently identified in Keratoconus (KC) patients with or without other corneal and lens abnormalities. We investigated mutations within MIR184 in KC patients from Saudi Arabia and examined the relative expression of miR-184 and miR-205 in human cornea. Ethnically matched KC cases (n = 134) were recruited and sequencing was performed using PCR-based Sanger sequencing and analyzed using the Sequencher 5.2 software. Expression of miR-184 and miR-205 was profiled in postmortem unaffected ocular tissues obtained from donors with no history of ocular diseases. miR-184 expression was 15-fold higher than that of miR-205 in cornea samples. No mutation(s) within the screened genomic region of MIR184 in KC cases was detected.