A Cox-based Model for Predicting the Risk of Cardiovascular Disease

This research is aimed to develop a 10-year risk prediction model and identify key contributing Cardiovascular Disease (CVD) risk factors. A Cox proportional hazard regression method was adopted to design and develop the risk model. We used Framingham Original Cohort dataset of 5079 men and women aged 30 - 62 years, who had no overt symptoms of CVD at the baseline. Out of them, 3189 (62.78%) had an actual CVD event. A 10-year CVD risk model based on multiple risk factors (such as age, sex, body mass index (BMI), hypertension, systolic blood pressure, cigarettes per day, pulse rate, and diabetes) was developed in which heart rate was identified as one of the novel contributing risk factors. We validated the model via statistical and empirical validation methods. The proposed model achieved an acceptable discrimination and calibration with C-index (receiver operating characteristic (ROC)) being 0.71 from the validation dataset

Identification and characterization of gonadotropin-releasing hormone (GnRH) in Zhikong scallop Chlamys farreri during gonadal development

Gonadotropin-releasing hormone (GnRH) controls synthesis of sex steroid hormones through hypothalamic-pituitary-gonadal (HPG) axis in vertebrates. But in mollusks, research on neuroendocrine control of gonadal function, such as the function of GnRH during gonadal development is limited. In this study, we investigated the morphology and structure of the nerve ganglia of Zhikong scallop Chlamys farreri by physiological and histological observations. We also cloned the ORF and studied the expression patterns of GnRH in the scallop. Tissue expression analysis showed that GnRH was highly expressed in parietovisceral ganglion (PVG). The in situ hybridization result further confirmed that GnRH mRNA only distributed in some good-sized neurons in the posterior lobe (PL) and some pint-sized neurons in the lateral lobe (LL). In addition, by examining the expression of GnRH during gonadal development in ganglia, we found GnRH displayed higher expression in the female scallops, and showed significant high expression at the growing stage of female scallops in PVG. This study would contribute to gaining insight into the mechanism underlying reproduction regulation by GnRH in the scallop and help to provide a better understanding of reproductive neuroendocrine in mollusks

Update of TTD: Therapeutic Target Database

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp

A Cox-based Risk Prediction Model for Early Detection of Cardiovascular Disease

Cardiovascular disease (CVD) is the number one cause of mortality around the world. A fair proportion of health care resource is consumed for managing CVD, which imposes a heavy health burden on the community. To prevent the prevalence of CVD, an effective approach is to create prediction models to assess the CVD risk and then enable early lifestyle adjustments or clinical treatments. A great amount of research has been done but challenges and issues still exist. The aim of this research is to create an effective risk prediction model for early assessment and detection of CVD. The Framingham Original Cohort Study data set of 5079 subjects aged from 30 to 74 years old who had not previous symptoms of CVD at the baseline was enclosed. The Cox regression method was used for the data analysis. A complete process of creating risk models was conducted according to statistical regression strategies. Lastly, a risk prediction model for general CVDs was generated based on risk predictors, including age, sex, body mass index, hypertension, pulse rate, systolic blood pressure, cigarettes per day, and diabetes. We obtained a good predictive ability of discrimination and calibration with ROC of 0.71 indicating a good accuracy for the risk estimate of CVD. In our new Cox-based risk model, a novel predictor heart rate was incorporated to predict CVD risk, which expands the predictive ability of existing CVD risk models. Moreover, this risk prediction model was developed based on office risk factors, i.e. the measure of risk factors does not require clinical tests, which would be beneficial to both health care providers and patients to assess CVD event rates at any time and any place

Characteristic Evaluation of Recombinant MiSp/Poly(lactic-<i>co</i>-glycolic) Acid (PLGA) Nanofiber Scaffolds as Potential Scaffolds for Bone Tissue Engineering

Biomaterial-based nanofibrous scaffolds are the most effective alternative to bone transplantation therapy. Here, two recombinant minor ampullate spidroins (spider silk proteins), R1SR2 and NR1SR2C, were blended with Poly(lactic-co-glycolic) Acid (PLGA), respectively, to generate nanofiber scaffolds by electrospinning. The N-terminal (N), C-terminal (C), repeating (R1 and R2) and spacer (S) modules were all derived from the minor ampullate spidroins (MiSp). The physical properties and structures of the blended scaffolds were measured by scanning electron microscopy (SEM), water contact angle measurement, Fourier transform infrared spectroscopy (FTIR), Differential scanning calorimetry (DSC), and Tensile mechanical testing. The results showed that blending of MiSp (R1SR2 and NR1SR2C) reduced the diameter of nanofibers, increased the porosity and glass transition temperatures of nanofibrous scaffolds, and effectively improved the hydrophilicity and ultimate strain of scaffolds. It is worth noting that the above changes were more significant in the presence of the N- and C-termini of MiSp. In cell culture assays, human bone mesenchymal stem cells (HBMSCs) grown on NR1SR2C/PLGA (20/80) scaffolds displayed markedly enhanced proliferative and adhesive abilities compared with counterparts grown on pure PLGA scaffolds. Jointly, these findings indicated recombinant MiSp/PLGA, particularly NR1SR2C/PLGA (20/80) blend nanofibrous scaffolds, is promising for bone tissue engineering