Relationship of Body Mass Index to Alcohol Consumption in College Freshmen

Objective. Assess the relationship between body mass index (BMI) and drinking in college freshman. Method. College freshman (N = 199) at a university completed the drinking questionnaires. Drinking amount and the alcohol problem index (RAPI) served as outcomes, and BMI was the independent variable. Results. RAPI scores were associated with gender, amount of drinking, and BMI (P < 0.001, F = 13.44). Increase of RAPI with drinking amount was larger for females (slope = 0.06) than for males (slope = 0.03). Conclusion. This information can be helpful when providing health promotion strategies to college students regarding nutrition modifications that would be most beneficial for their health

Nonparametric pricing kernel models

The capital asset pricing model (CAPM) and the arbitrage asset pricing theory (APT) have been the cornerstone in theoretical and empirical finance for the recent few decades. The classical CAPM usually assumes a simple and stable linear relationship between an asset’s systematic risk and its expected return. However, this simple relationship assumption has been challenged and rejected by several recent studies based on empirical evidences of time variation in betas and expected returns. It is well documented that large pricing errors could be due to the linear ap- proach used in a nonlinear model and treating a non-linear relationship as a linear could lead to serious prediction problems in estimation. To overcome these problems, in the first part of this dissertation I would like to investigate a general nonpara- metric asset pricing model to avoid functional form misspecification of betas, risk premia, and the stochastic discount factor by considering estimating unknown func- tional involved in the nonparametric pricing kernel. To estimate the nonparametric functionals, I propose a new nonparametric estimation procedure, termed as non- parametric generalized estimation equations (NPGEE), which combines the local linear fitting and the generalized estimation equations. I establish the asymptotic properties of the resulting estimator. Also, as a rule of thumb, I propose a data- driven method to select the bandwidth and provide a consistent estimate of the asymptotic variance. The nonparametric method may provide a useful insight for further parametric fitting, while parametric models for time-varying betas can be most efficient if the underlying betas are specified. However, a misspecification may cause serious bias and model constraints may distort the betas in local area. Hence, to test whether the pricing kernel model has some specific parametric form becomes essentially impor- tant. In the second part of this dissertation, I propose a consistent nonparametric testing procedure to test whether the model is correctly specified and I establish the asymptotic properties of the test statistic using a U-statistic technique. Finite sample results are investigated using Monte Carlo simulation studies in order to show the usefulness of the estimation method and the test statistics. The empirical applications using CRSP monthly returns are also implemented to illustrate our proposed models and methods

Preventive effect and mechanism of Tibetan tea extract on thrombosis in arachidonic acid-induced zebrafish determined via RNA-seq transcriptome profiles.

Thrombosis is a key pathological event in cardiovascular diseases and is also the most important targeting process for their clinical management. In this study, arachidonic acid (AA) was used to induce thrombus formation in zebrafish larvae. Blood flow, red blood cell (RBCs) aggregation and cellular oxidative stress were measured to evaluate the antithrombotic effect of Tibetan tea (TT). Meanwhile, the potential molecular mechanism was further explored by transcriptome sequencing (RNA-seq). The results indicated that TT could significantly restore heart RBCs intensity of thrombotic zebrafish, whilst decreasing RBCs accumulation in the caudal vein. The transcriptome analysis revealed that the preventive effect of TT on thrombosis could be mostly attributed to changes in lipid metabolism related signaling pathways, such as fatty acid metabolism, glycerollipid metabolism, ECM-receptor interaction and steroid biosynthesis signaling pathway. This study demonstrated that Tibetan tea could alleviate thrombosis by reducing oxidative stress levels and regulating lipid metabolism

Advances in nanoplasmonic biosensors for clinical applications

Biomarkers are unquestionable biological indicators for diagnosis and therapeutic interventions providing appropriate classification of a wide range of health disorders and risk factors. Nonetheless, the detection and quantification of biomarkers need to be tested with sufficient reliability by robust analytical methods in order to assure clinical performance in health care settings. Since the analytical performance is determined by the sensitivity and specificity of the method employed, techniques have been intensively refined in order to avoid the misinterpretation of results and undesirable bias. Although biomarkers can be detected with the existing analytical techniques, to reproducibly quantify them in decentralized settings or remote locations with the required accuracy is still a challenge. Currently, only a few point-of-care devices for biomarker evaluation are commercially available. Thus, more focused research efforts are needed to overcome these limitations in order to provide universal patient-centered care platforms. To this end, plasmonic biosensors can be conveniently used as portable diagnostic devices for attaining timely and cost-effective clinical outcomes. The development of enhanced performance based on nanoplasmonics technology opens the way for sensor miniaturization, multiplexing and point of care testing. This review covers recent advances and applications of plasmonic and nanoplasmonic biosensors intended for biomarker diagnosis in clinical practice, including cancer, cardiovascular and neurodegenerative diseases. The review specially focuses on: (i) recent progress in plasmonics development including the design of singular nanostructured surfaces, (ii) novel chemical functionalization strategies for the appropriate incorporation of bioreceptors and (iii) plasmonic applications as real operative devices in the clinical field. Future prospects in the use of nanoplasmonic sensor platforms for personalised quantification and management of biomarkers directly in body fluids will also be discussed