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Background: Monocyte to high-density lipoprotein cholesterol ratio (MHR) is a novel inflammatory marker that has been used to predict various inflammation-related diseases. This study aims to explore the association between MHR and prevalent hyperuricemia in a rural Chinese population. Methods: 8163 eligible participants (mean age: 54.13 years, males: 45.71%) from northeast China were enrolled in this cross-sectional study between 2012 to 2013. MHR was determined as blood monocyte count ratio to highdensity lipoprotein cholesterol concentration. Results: The prevalence of hyperuricemia was 12.86%. After adjusting for potential confounding factors, per SD increase of MHR caused a 25.2% additional risk for hyperuricemia, and the top quartile of MHR had an 82.9% increased risk for hyperuricemia compared with the bottom quartile. Additionally, smooth curve fitting and subgroup analyses showed a linear and robust association between MHR and prevalent hyperuricemia respectively. Finally, after introducing MHR into the established model of risk factors, the AUC displayed a significant improvement (0.718 vs 0.724, p = 0.008). Furthermore, Category-free net reclassification improvement (0.160, 95% CI: 0.096-0.224, P < 0.001) and integrated discrimination improvement (0.003, 95% CI: 0.002-0.005, P < 0.001) also demonstrated significant improvements. Conclusions: The present study suggests that MHR was positively and independently correlated with prevalent hyperuricemia among rural Chinese adults. Our results also implicate an important value for MHR in optimizing the risk stratification of hyperuricemia.

Purpose Some studies have established an association between hypertension or obesity and the risk of diabetes. This study aimed to examine the interaction of hypertension and obesity on diabetes. Participants and Methods The data of 11,731 Chinese men and women were analyzed from the 2012–2013 Northeast China Rural Cardiovascular Health Study. The interaction was examined by both additive and multiplicative scales. General obesity was measured by body mass index (BMI); central obesity was defined by waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHpR). Results After controlling for potential confounders, the odds ratios for diabetes were 3.864 (3.205–4.660), 4.500 (3.673–5.514), 4.932 (3.888–6.255) and 4.701 (3.817–5.788) for the combinations of hypertension and BMI, WC, WHtR or WHpR, respectively, which had the highest risk of diabetes among the four combinations. Notwithstanding the multiplicative interactions showed statistically significant in all analyses, the results of additive interactions were not consistent, suggesting the diabetes risk from female BMI (relative excess risk due to interaction (RERI): 1.136, 95% CI: 0.127–2.146, attributable proportion due to interaction (AP): 0.267, 95% CI: 0.057–0.477, synergy index (S):1.536, 95% CI: 1.017–2.321) or female WHpR (RERI: 1.076, 95% CI: 0.150–2.002, AP:0.205, 95% CI: 0.037–0.374, S:1.340, 95% CI: 1.012–1.775) was additive to the risk from hypertension. Conclusion The findings suggest that high BMI and high WHpR have synergistic interactions with hypertension on the risk of diabetes for females. The results of this study also suggest that BMI and WHpR, rather than WC, should be used for the diagnosis of metabolic syndrome in Chinese population.

A new approach for extracting the hairiness from fabric based on the predicted fabric surface plane is presented in this paper to extract the hairiness from the depth image. The depth from focus (DFF) technique is utilized in this study to establish the depth image of the pilled fabrics by using a series of image layers captured under a microscope. A pilled fabric depth image provides information on the hairiness and the fabric surface, and the hairiness is located above the fabric surface. However, the depth value of the fabric surface covered with hairiness cannot be directly obtained. Therefore, for hairiness extraction, a predicted plane of the fabric surface is fitted by selecting several base points on the fabric surface. The target above the predicted plane will be considered as hairiness and will be extracted. The oversegmentation method based on the mean shift algorithm is used in the study to select the base points of the fabric surface. First, several seed points are marked along the Sobel edges; then, several oversegmented areas are formed after the growth of the seed points, which are called split pieces in this paper. The split pieces of the fabric surfaces are selected as the base points according to the depth value as well as the spatial direction of each split piece. Finally, the predicted plane of the fabric surface is established using these base points. The results of significance testing show that is it reasonable to assume that the fabric surface can be expressed as a plane. The results of the residual examination show that the predicted plane can correctly calculate the depth value (z) of the fabric surface at any plane position (x, y). The extracted hairiness images show that hairiness can be correctly and completely obtained through the predicted plane.

Background Hypertension and obesity are recognized as modifiable risk factors for stroke, but their combined effects are unknown. This study aimed to explore the combined effects of hypertension and general or central obesity on the risk of ischemic stroke in a middle-aged and elderly population. Methods The data of 11,731 participants (53.5 ± 10.5 years old) were analyzed from the Northeast China Rural Cardiovascular Health Study, 2012–2013. General obesity (GO) was defined by body mass index (BMI); central obesity (CO) was measured by waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHpR). Results The overall prevalence of ischemic stroke was 3.1%. After adjusting for age and sex, the odds ratios for having ischemic stroke were 4.31 (3.14–5.91) among subjects with hypertension, 1.79 (1.40–2.30) with GO, 1.94 (1.54–2.43), 1.98 (1.54–2.53), and 1.65 (1.33–2.06) with CO measured by WC, WHtR and WHpR, respectively. After full adjustment for potential confounders, the combinations of hypertension and obesity indices (including BMI, WC, WHtR and WHpR) were associated with the highest risk of ischemic stroke, especially in women, which were respectively 7.3-fold, 9.3-fold, 9.9-fold and 7.6-fold higher than that of individuals without both conditions. Conclusion Our study results suggest that women with both hypertension and obesity, no matter defined by BMI, WC, WHtR or WHpR, were more likely to have ischemic stroke. A better understanding of the combined effects of these risk factors can help promote primary prevention in susceptible subgroups.

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