Burnout and study engagement among medical students at Sun Yat-sen University, China: A cross-sectional study.

This study aims to investigate burnout and study engagement among medical students at Sun Yat-sen University, China.A cross-sectional survey was conducted among undergraduate medical students of Sun Yat-sen University, China. A total of 453 undergraduate students completed a self-administered, structured questionnaire between January and February, 2016. Burnout and study engagement were measured using the Maslach Burnout Inventory-Student Survey (MBI-SS) and the UTRECHT Work Engagement Scale-Students (UWES-S), respectively. Subjects who scored high in emotional exhaustion subscale, high in cynicism subscale, and low in professional efficacy subscale simultaneously were graded as having high risk of burnout. Independent sample t tests and chi-square tests were used to compare the differences in burnout and work engagement between genders, majors, and grade levels.The means (standard deviations) of the MBI-SS subscales were 3.42 (1.45) for emotional exhaustion, 2.34 (1.64) for cynicism, and 3.04 (1.30) for professional efficacy. The means (standard deviations) of the UWES-S subscales were 3.13 (1.49) for vigor, 3.44 (1.47) for dedication and 3.00 (1.51) for absorption. Approximately 1 in 11 students experienced a high risk of burnout. There were no statistically significant gender differences in burnout and study engagement. There were also no statistically significant differences in burnout and study engagement subscales according to student major. Students in higher grades displayed increased burnout risk, higher mean burnout subscale score of cynicism, lower mean burnout subscale score of professional efficacy, and decreased mean study engagement subscale scores of dedication and absorption. There were strong correlations within study engagement subscales.Chinese medical students in this university experience a high level of burnout. Students at higher-grade level experience more burnout and decreased study engagement compared with students in lower level

An Transaction Cost Analysis on Products’ Adaptability to E-Commerce

Based on theories of transaction cost economics, this paper study up on the relationship between product cognitive, transaction complexity and transaction cost, and examined the impact of product cognitive, transaction complexity on the product suitable for E-commerce. Being difference from the previous point of view that the product cognitive would reduce transaction cost, and transaction complexity would increase transaction cost, that combination with previous researches, we conclude that transaction cost tends to influence product suitable for E-commerce; and with the product cognitive increasing and transaction complexity reducing, transaction cost reduced so that the product are more suitable for E-commerce

Cyclic voltammetry: A simple method for determining contents of total and free iron ions in sodium ferric gluconate complex

Sodium ferric gluconate complex (SFGC) is the third generation of iron supplement of polysaccharide iron (III) complex (PIC). For evaluation of technological level and application value of the prepared SFGC, it would be of great significance to determine the iron content in SFGC in a simple but effective way. This paper introduces the cyclic voltammetry (CV) method for determination of iron content in SFGC. Under established optimal experimental conditions, the content of free iron ions can be directly scanned and calculated, while the total iron content can also be determined by completely acidifying SFGC into Fe3+ ions. After optimizing and screening, the optimal scanning conditions are determined as pH 3 and 0.05 V/s of the scanning rate. Prior CV measurements, 0.4 V of the enrichment potential, and 3 min of the enrichment time are found optimal. It has also been verified that CO32- ions present in the solution show little interference in the system within the experimental range of investigation. The contents of free Fe3+, Fe2+ ions and the total iron determined after acid-hydrolysis of SFGC can be accurately calculated according to the corresponding linear relationships between peak currents and iron concentrations. In this paper, the repeatability and accuracy of the method are verified, and its feasibility as a convenient and effective method to determine the iron supplements is confirmed

Enhancement of recombinant myricetin on the radiosensitivity of lung cancer A549 and H1299 cells

OBJECTIVE: Myricetin, a common dietary flavonoid is widely distributed in fruits and vegetables, and is used as a health food supplement based on its immune function, anti-oxidation, anti-tumor, and anti-inflammatory properties. The aim of this study was to investigate the effects of myricetin on combination with radiotherapy enhance radiosensitivity of lung cancer A549 and H1299 cells. METHODS: A549 cells and H1299 cells were exposed to X-ray with or without myricetin treatment. Colony formation assays, CCK-8 assay, flow cytometry and Caspase-3 level detection were used to evaluate the radiosensitization activity of myricetin on cell proliferation and apoptosis in vitro. Nude mouse tumor xenograft model was built to assessed radiosensitization effect of myricetin in vivo. RESULTS: Compared with the exposed group without myricetin treatment, the groups treated with myricetin showed significantly suppressed cell surviving fraction and proliferation, increased the cell apoptosis and increased Caspase-3 protein expression after X-ray exposure in vitro. And in vivo assay, growth speed of tumor xenografts was significantly decreased in irradiated mice treated with myricetin. CONCLUSIONS: The study demonstrated both in vitro and in vivo evidence that combination of myricetin with radiotherapy can enhance tumor radiosensitivity of pulmonary carcinoma A549 and H1299 cells, and myricetin could be a potential radiosensitizer for lung cancer therapy. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/579151800121063

Quantitative regulation of FLC via coordinated transcriptional initiation and elongation

The basis of quantitative regulation of gene expression is still poorly understood. In Arabidopsis thaliana, quantitative variation in expression of FLOWERING LOCUS C (FLC) influences the timing of flowering. In ambient temperatures, FLC expression is quantitatively modulated by a chromatin silencing mechanism involving alternative polyadenylation of antisense transcripts. Investigation of this mechanism unexpectedly showed that RNA polymerase II (Pol II) occupancy changes at FLC did not reflect RNA fold changes. Mathematical modeling of these transcriptional dynamics predicted a tight coordination of transcriptional initiation and elongation. This prediction was validated by detailed measurements of total and chromatin-bound FLC intronic RNA, a methodology appropriate for analyzing elongation rate changes in a range of organisms. Transcription initiation was found to vary ∼25-fold with elongation rate varying ∼8- to 12-fold. Premature sense transcript termination contributed very little to expression differences. This quantitative variation in transcription was coincident with variation in H3K36me3 and H3K4me2 over the FLC gene body. We propose different chromatin states coordinately influence transcriptional initiation and elongation rates and that this coordination is likely to be a general feature of quantitative gene regulation in a chromatin context

Quantitative Systems Pharmacological Analysis of Drugs of Abuse Reveals the Pleiotropy of Their Targets and the Effector Role of mTORC1

Existing treatments against drug addiction are often ineffective due to the complexity of the networks of protein-drug and protein-protein interactions (PPIs) that mediate the development of drug addiction and related neurobiological disorders. There is an urgent need for understanding the molecular mechanisms that underlie drug addiction toward designing novel preventive or therapeutic strategies. The rapidly accumulating data on addictive drugs and their targets as well as advances in machine learning methods and computing technology now present an opportunity to systematically mine existing data and draw inferences on potential new strategies. To this aim, we carried out a comprehensive analysis of cellular pathways implicated in a diverse set of 50 drugs of abuse using quantitative systems pharmacology methods. The analysis of the drug/ligand-target interactions compiled in DrugBank and STITCH databases revealed 142 known and 48 newly predicted targets, which have been further analyzed to identify the KEGG pathways enriched at different stages of drug addiction cycle, as well as those implicated in cell signaling and regulation events associated with drug abuse. Apart from synaptic neurotransmission pathways detected as upstream signaling modules that “sense” the early effects of drugs of abuse, pathways involved in neuroplasticity are distinguished as determinants of neuronal morphological changes. Notably, many signaling pathways converge on important targets such as mTORC1. The latter emerges as a universal effector of the persistent restructuring of neurons in response to continued use of drugs of abuse

Evolution Feature Oriented Model Driven Product Line Engineering Approach for Synergistic and Dynamic Service Evolution in Clouds

The proposed research will focus on developing a novel approach to solve Software Service Evolution problems in Computing Clouds. The approach will support dynamic evolution of the software service in clouds via a set of discovered evolution patterns. An initial survey informed us that such an approach does not exist yet and is in urgent need. Evolution Requirement can be classified into evolution features; researchers can describe the whole requirement by using evolution feature typology, the typology will define the relation and dependency between each features. After the evolution feature typology has been constructed, evolution model will be created to make the evolution more specific. Aspect oriented approach can be used for enhance evolution feature-model modularity. Aspect template code generation technique will be used for model transformation in the end. Product Line Engineering contains all the essential components for driving the whole evolution process

Down-regulated miR-9 and miR-433 in human gastric carcinoma

<p>Abstract</p> <p>Background</p> <p>MircoRNAs(miRNAs) are short, endogenously non-coding RNAs. The abnormal expression of miRNAs may be valuable for the diagnosis and treatment of tumors.</p> <p>Methods</p> <p>To screening the special miRNAs in gastric carcinoma, expression level of miRNAs in gastric carcinoma and normal gaster samples were detected by miRNA gene chip. Then, the expressions of miR-9 and miR-433 in gastric carcinoma tissue and SGC7901 cell line were validated by qRT-PCR. GRB2 and RAB34, targets of miR-433 and miR-9 respectively, were detected by Western blot.</p> <p>Results</p> <p>We found 19 miRNAs and 7 miRNAs were down-regulated and up-regulated respectively. Compared with normal gaster samples, our data showed that miR-9 and miR-433 were down-regulated in gastric carcinoma. Meanwhile, we also found that miR-433 and miR-9 regulated the expression levels of GRB2 and RAB34 respectively.</p> <p>Conclusion</p> <p>Our data show miR-9 and miR-433 was down-regulated in gastric carcinoma. The targets of miR-433 and miR-9 were tumor-associated proteins GRB2 and RAB34 respectively. This result provided the related information of miRNAs in gastric carcinoma.</p

Chronic Alcohol Causes Alteration of Lipidome Profiling in Brain

Much efforts have been tried to clarify the molecular mechanism of alcohol-induced brain damage from the perspective of genome and protein; however, the effect of chronic alcohol exposure on global lipid profiling of brain is unclear. In the present study, by using Q-TOF/MS-based lipidomics approach, we investigated the comprehensive lipidome profiling of brain from the rats orally administrated with alcohol daily, continuously for one year. Through systematically analysis of all lipids in prefrontal cortex (PFC) and striatum region, we found that long-term alcohol exposure profoundly modified brain lipidome profiling. Notably, three kinds of lipid classes, glycerophospholipid (GP), glycerolipid (GL) and fatty acyls (FA), were significantly increased in these two brain regions. Interestingly, most of the modified lipids were involved in synthetic pathways of endoplasmic reticulum (ER), which may result in ER stress-related metabolic disruption. Moreover, alcohol-modified lipid species displayed long length of carbon chain with high degree of unsaturation. Taken together, our results firstly present that chronic alcohol exposure markedly modifies brain lipidomic profiling, which may activate ER stress and eventually result in neurotoxicity. These findings provide a new insight into the mechanism of alcohol-related brain damage.Peer reviewe