RESUMEN
Objective: Accumulating experimental evidence has identified the beneficial effects of the anti-aging protein, serum soluble α-Klotho, on longevity, and the cardiovascular system. Although a previous study has revealed the predictive value of α-Klotho on total cardiovascular disease (CVD), the associations between α-Klotho and specific CVDs, including congestive heart failure (CHF), coronary heart disease (CHD), myocardial infarction (MI), and stroke, remains to be fully elucidated in humans. Methods: For 8,615 adults in the 2007 to 2016 National Health and Nutrition Examination Survey, stratified multivariable logistic regression models, restricted cubic spline curves, and subgroup analyses were used to evaluate the associations between α-Klotho and the four specific CVDs. Results: In the quartile analyses, compared to those in the highest quartile, participants in the lowest level of α-Klotho were significantly associated with CHF [odds ratio (OR) = 1.46, 95% CI: 1.09-1.97] and MI (1.33, 1.02-1.74), which was not the case for CHD (1.12, 0.91-1.38) or stroke (0.96, 0.73-1.25). Each unit increment in the ln-transformed α-Klotho concentrations was only positively associated with a 38 and 24% reduction in the prevalence of CHF and MI, respectively. Restricted cubic spline curves indicated that the α-Klotho was correlated with CHF and MI in linear-inverse relationships. Conclusion: The present findings suggested that the serum soluble α-Klotho is significantly associated with the prevalence of CHF and MI. To better determine whether α-Klotho is a specific biomarker of CVD, particularly for CHD and stroke, further research in humans is needed.
RESUMEN
Heavy metals pollution in foodstuffs is more and more serious. It is impossible to satisfy the modern agricultural development by conventional chemical analysis. Laser induced breakdown spectroscopy (LIBS) is an emerging technology with the characteristic of rapid and nondestructive detection. But LIBS' s repeatability, sensitivity and accuracy has much room to improve. In this work, heavy metal Cu in Gannan Navel Orange which is the Jiangxi specialty fruit will be predicted by LIBS. Firstly, the navel orange samples were contaminated in our lab. The spectra of samples were collected by irradiating the peel by optimized LIBS parameters. The laser energy was set as 20 mJ, delay time of Spectral Data Gathering was set as 1.2 micros, the integration time of Spectral data gathering was set as 2 ms. The real concentration in samples was obtained by AAS (atom absorption spectroscopy). The characteristic variables Cu I 324.7 and Cu I 327.4 were extracted. And the calibration model was constructed between LIBS spectra and real concentration about Cu. The results show that relative error of the predicted concentrations of three relational model were 7.01% or less, reached a minimum of 0.02%, 0.01% and 0.02% respectively. The average relative errors were 2.33%, 3.10% and 26.3%. Tests showed that different characteristic variables decided different accuracy. It is very important to choose suitable characteristic variable. At the same time, this work is helpful to explore the distribution of heavy metals between pulp and peel.
