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Objective@#To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students.@*Methods@#By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students.@*Results@#The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05).@*Conclusions@#Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.
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BACKGROUND@#Lung cancer is the most common cancer worldwide with the highest morbidity and mortality, in which the non-small cell lung cancer accounts for 80% of all cases. The expression of (HOX transcript antisense RNA) HOTAIR were abnormal in a variety of tumor tissues and is involved in the regulation of the occurrence and development of lung cancer. The purpose of this study is to investigate the effect and mechanism of down-regulation of HOTAIR on gefitinib resistance of lung adenocarcinoma HCC827 cells by targeting PTEN.@*METHODS@#The HOTAIR downstream target gene was predicted by bioinformatics database. The small interfering RNAs (siRNA) which is corresponding to HOTAIR was transfected using Lipofectamine™ 2000. Quantitative real-time PCR (RT-qPCR) and Western blot were used to detect the expression of HOTAIR, PTEN, PI3K and AKT in HCC827 and HCC827GR cells. MTT assay was used to detect the changes in drug resistance of HCC827GR cells. Flow cytometry analysis were used to test the cell proliferation and the rate of apoptosis.@*RESULTS@#The expression of HOTAIR increased in HCC827GR and the serum of NSCLC patients with gefitinib resistance (P<0.05). Transfection of HOTAIR siRNA decreased the expression of HOTAIR (P<0.05), and increased the expressions of PTEN (P<0.05), while the expression of PI3K and AKT were decreased (P<0.05). Compared with the blank control group, down-regulation of HOTAIR increased the sensitivity of HCC827GR cells to gefitinib. The cell proliferation ability was decreased and the apoptosis was promoted apparently (P<0.05).@*CONCLUSIONS@#Down-regulation of HOTAIR can suppress the cell growth and promote the apoptosis, and it can reverse the resistance of HCC827GR cells to gefitinib. Its potential mechanism may be related with the targeting of PTEN/PI3K/AKT pathway.
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BACKGROUND@#Lung cancer is the most common cancer worldwide with the highest morbidity and mortality, in which the non-small cell lung cancer accounts for 80% of all cases. The expression of (HOX transcript antisense RNA) HOTAIR were abnormal in a variety of tumor tissues and is involved in the regulation of the occurrence and development of lung cancer. The purpose of this study is to investigate the effect and mechanism of down-regulation of HOTAIR on gefitinib resistance of lung adenocarcinoma HCC827 cells by targeting PTEN.@*METHODS@#The HOTAIR downstream target gene was predicted by bioinformatics database. The small interfering RNAs (siRNA) which is corresponding to HOTAIR was transfected using Lipofectamine™ 2000. Quantitative real-time PCR (RT-qPCR) and Western blot were used to detect the expression of HOTAIR, PTEN, PI3K and AKT in HCC827 and HCC827GR cells. MTT assay was used to detect the changes in drug resistance of HCC827GR cells. Flow cytometry analysis were used to test the cell proliferation and the rate of apoptosis.@*RESULTS@#The expression of HOTAIR increased in HCC827GR and the serum of NSCLC patients with gefitinib resistance (P<0.05). Transfection of HOTAIR siRNA decreased the expression of HOTAIR (P<0.05), and increased the expressions of PTEN (P<0.05), while the expression of PI3K and AKT were decreased (P<0.05). Compared with the blank control group, down-regulation of HOTAIR increased the sensitivity of HCC827GR cells to gefitinib. The cell proliferation ability was decreased and the apoptosis was promoted apparently (P<0.05).@*CONCLUSIONS@#Down-regulation of HOTAIR can suppress the cell growth and promote the apoptosis, and it can reverse the resistance of HCC827GR cells to gefitinib. Its potential mechanism may be related with the targeting of PTEN/PI3K/AKT pathway.
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OBJECTIVE@#This study aimed to evaluate the stress distribution of the mandibular first molar with different thicknesses and heights of the axial wall restored by the endocrown with two marginal designs and thus provide a theoretical basis for selecting clinical preparation through the finite-element method.@*METHODS@#Two marginal endocrowns of the mandibular first molar with different axial-wall thicknesses (t=1, 2, 3 mm) and heights (h=2, 3, 4 mm) were established. Group A was the butt-joint design, whereas group B was the shoulder-surrounded design. After applying vertical and oblique loads , the size and distribution of the maximum principal stress and equivalent stress of residual tooth tissue were recorded.@*RESULTS@#The maximum principal stress and equivalent stress distribution of residual tooth tissue were similar among different models. Group A showed a lower maximum principal stress and equivalent stress than group B at the same thickness and height under vertical load. Meanwhile, under oblique load, the maximum principal stress values of groups A and B decreased with increased thickness at constant height. Group A showed lower equivalent stress than group B at the same thickness and height of 2 and 3 mm. However, when the height was 4 mm, the trend was reversed.@*CONCLUSIONS@#In mastication, when bearing the vertical force, the retention of the butt-joint marginal endocrown preferred to the shoulder-surrounded one. Given the higher axial wall of the shoulder-surrounded marginal endocrown, it showed better ability to bear the oblique force than the butt-joint one.
Subject(s)
Crowns , Dental Stress Analysis , Finite Element Analysis , Mastication , MolarABSTRACT
Fourier transform infrared spectroscopic imaging (FTIRSI) technology can simultaneously obtain microstructure information and infrared spectral information of the samples. The method of FTIRSI combined with chemometric algorithms can be used for quantitative analysis of sample spectral information and tissue discrimination research. Based on this, FTIRSI and support vector machine classification (SVC) for the first time were used in this work to discriminate healthy and degenerated articular cartilage, with high accuracies of 100％ and 95. 4％ , respectively, and sum accuracy of 97. 7％ . The support vector regression (SVR) model was used to quantitatively study the contents and distribution of two biomacromolecules, collagen and proteoglycan, in articular cartilage. The proteoglycan loss occurred in the degenerated articular cartilage, especially in the superficial area. This study indicates that the combination of FTIRSI and support vector machine (SVM) is expected to become a new diagnostic tool for osteoarthritis, which is of great significance for the early diagnosis and research of osteoarthritis.