RESUMEN
Homochirality is an important feature in biological systems and occurs even in inorganic nanoparticles. However, the mechanism of chirality formation and the key steps during growth are not fully understood. Here we identify two distinguishable pathways from achiral to chiral morphologies in gold nanoparticles by training an artificial neural network of cellular automata according to experimental results. We find that the chirality is initially determined by the nature of the asymmetric growth along the boundaries of enantiomeric high-index planes. The deep learning-based interpretation of chiral morphogenesis provides a theoretical understanding but also allows us to predict an unprecedented crossover pathway and the resulting morphology.
RESUMEN
BACKGROUND: Metabolic syndrome is a common extrapulmonary comorbidity in patients with chronic obstructive pulmonary disease (COPD). However, the reported relationship of COPD with dyslipidemia, an important component of metabolic syndrome, is ambiguous. The aim of this meta-analysis is to investigate the association between COPD and the serum levels of high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), and triglyceride (TG). METHODS: The PubMed and Embase databases were searched to find potential studies using the search terms of ("dyslipidemia" or "HDL" or "LDL" or "cholesterol" or "triglyceride") and COPD. We also performed subgroup analysis enrolling patients who were not receiving treatment for dyslipidemia. Mean differences (MD) with 95% confidence intervals (CI) were estimated with random effects models. RESULTS: A total of 11 studies comprising 615 cases and 471 controls were included in the study. No significant differences were found in the HDL (MD = -2.55, 95% CI [-6.03, 0.93], P = 0.15), LDL (MD = -2.25, 95% CI [-13.36, 8.86], P = 0.69), TC (MD = -2.69, 95% CI [-13.30, 7.92], P = 0.62), and TG (MD = 6.90, 95% CI [-2.81, 16.60], P = 0.16) levels of the 2 groups. However, subgroup analysis enrolling patients who were not receiving treatment for dyslipidemia showed that TG levels were higher in patients with stable COPD than in healthy individuals (MD = 16.35, 95% CI [5.90, 26.80], P = 0.002). CONCLUSIONS: Excluding the impact of hypolipidemic treatment on serum lipid profile, TG levels were higher in patients with COPD than in healthy individuals. This meta-analysis suggested that physicians should screen COPD patients for elevated TG levels to reduce the risk of cardiovascular morbidity and mortality.
