Objective: The objective was to assess the waist circumference (WC) cut‐off point that best identifies a level of 10‐year cardiovascular disease (CVD) risk with optimal balance of sensitivity and specificity in Chinese subjects according to their predicted 10‐year CVD risk. Research Methods and Procedures: A community‐based cross‐sectional observational study involving 14,919 Hong Kong Chinese subjects. The 10‐year CVD risk based on various prediction models was calculated. The projected WC cut‐off points were then determined. Results: There were 4837 (32.4%) men and 10,082 (67.6%) women (mean age ± standard deviation, 47.3 ± 13.5 years; age range, 18 to 93 years; median age, 45.0 years). The mean optimal WC or BMI predicting a 15% to 30% 10‐year CVD risk were 83 to 88 cm and 25 kg/m2 for men, and 76 cm and 23 kg/m2 for women, respectively. With WC ≥90 cm in men and ≥80 cm in women, the likelihood ratio at various WC cut‐off points to develop a ≥20% 10‐year CVD risk is 1.5 to 2.0 in men and 3.0 in women. The likelihood ratio was 1.5 in men with WC at 84 cm and in women at 70 cm. Discussion: Our results agree with the present guidelines on the definition of general and central obesity in Asia‐Pacific regions. We propose the creation of an intermediate state of high WC, the “central pre‐obesity” for Chinese men with WC ≥84 to 90 cm (≥33 to 36 inches) and women with WC ≥74 to 80 cm (≥29 to 32 inches). People with central pre‐obesity, similar to those with overweight (BMI ≥23 to 25 kg/m2), already have an increased risk of co‐morbidities. 相似文献
Using information from sequence alignments significantly improves protein secondary structure prediction. Typically, more divergent profiles yield better predictions. Recently, various groups have shown that accuracy can be improved significantly by using PSI-BLAST profiles to develop new prediction methods. Here, we focused on the influences of various alignment strategies on two 8-year-old PHD methods. The following results stood out. (i) PHD using pairwise alignments predicts about 72% of all residues correctly in one of the three states: helix, strand, and other. Using larger databases and PSI-BLAST raised accuracy to 75%. (ii) More than 60% of the improvement originated from the growth of current sequence databases; about 20% resulted from detailed changes in the alignment procedure (substitution matrix, thresholds, and gap penalties). Another 20% of the improvement resulted from carefully using iterated PSI-BLAST searches. (iii) It is of interest that we failed to improve prediction accuracy further when attempting to refine the alignment by dynamic programming (MaxHom and ClustalW). (iv) Improvement through family growth appears to saturate at some point. However, most families have not reached this saturation. Hence, we anticipate that prediction accuracy will continue to rise with database growth. 相似文献
The pathway which proteins take to fold can be influenced from the earliest events of structure formation. In this light, it was both predicted and confirmed that increasing the stiffness of a beta hairpin turn decreased the size of the transition state ensemble (TSE), while increasing the folding rate. Thus, there appears to be a relationship between conformationally restricting the TSE and increasing the folding rate, at least for beta hairpin turns. In this study, we hypothesize that the enormous sampling necessary to fold even two-state folding proteins in silico could be reduced if local structure constraints were used to restrict structural heterogeneity by polarizing folding pathways or forcing folding into preferred routes. Using a Gō model, we fold Chymotrypsin Inhibitor 2 (CI-2) and the src SH3 domain after constraining local sequence windows to their native structure by rigid body dynamics (RBD). Trajectories were monitored for any changes to the folding pathway and differences in the kinetics compared with unconstrained simulations. Constraining local structure decreases folding time two-fold for 41% of src SH3 windows and 45% of CI-2 windows. For both proteins, folding times are never significantly increased after constraining any window. Structural polarization of the folding pathway appears to explain these rate increases. Folding rate enhancements are consistent with the goal to reduce sampling time necessary to reach native structures during folding simulations. As anticipated, not all constrained windows showed an equal decrease in folding time. We conclude by analyzing these differences and explain why RBD may be the preferred way to constrain structure. 相似文献
Objective: Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3).
Methods: We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage.
Results: We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC.
Conclusions: Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage. 相似文献
Agriculture has a key role in food production worldwide and it is a major component of the gross domestic product of several countries. Livestock production is essential for the generation of high quality protein foods and the delivery of foods in regions where animal products are the main food source. Environmental impacts of livestock production have been examined for decades, but recently emission of methane from enteric fermentation has been targeted as a substantial greenhouse gas source. The quantification of methane emissions from livestock on a global scale relies on prediction models because measurements require specialized equipment and may be expensive. The predictive ability of current methane emission models remains poor. Moreover, the availability of information on livestock production systems has increased substantially over the years enabling the development of more detailed methane prediction models. In this study, we have developed and evaluated prediction models based on a large database of enteric methane emissions from North American dairy and beef cattle. Most probable models of various complexity levels were identified using a Bayesian model selection procedure and were fitted under a hierarchical setting. Energy intake, dietary fiber and lipid proportions, animal body weight and milk fat proportion were identified as key explanatory variables for predicting emissions. Models here developed substantially outperformed models currently used in national greenhouse gas inventories. Additionally, estimates of repeatability of methane emissions were lower than the ones from the literature and multicollinearity diagnostics suggested that prediction models are stable. In this context, we propose various enteric methane prediction models which require different levels of information availability and can be readily implemented in national greenhouse gas inventories of different complexity levels. The utilization of such models may reduce errors associated with prediction of methane and allow a better examination and representation of policies regulating emissions from cattle. 相似文献