Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease.

BACKGROUND: Machine learning (ML) employs algorithms that learn from data, building models with the potential to predict events by aggregating a large number of variables and assessing their complex interactions. The aim of this study is to assess ML potential in identifying patients with ischemic heart disease (IHD) at high risk of cardiac death (CD). METHODS: 3987 (mean age 68 ± 11) hospitalized IHD patients were enrolled. We implemented and compared various ML models and their combination into ensembles. Model output constitutes a new ML indicator to be employed for stratification. Primary variable importance was assessed with ablation tests. RESULTS: An ensemble classifier combining three ML models achieved the best performance to predict CD (AUROC of 0.830, F1-macro of 0.726). ML indicator use through Cox survival analysis outperformed the 18 variables individually, producing a better stratification compared to standard multivariate analysis (improvement of ∼20%). Patients in the low risk group defined through ML indicator had a significantly higher survival (88.8% versus 29.1%). The main variables identified were Dyslipidemia, LVEF, Previous CABG, Diabetes, Previous Myocardial Infarction, Smoke, Documented resting or exertional ischemia, with an AUROC of 0.791 and an F1-score of 0.674, lower than that of 18 variables. Both code and clinical data are freely available with this article. CONCLUSION: ML may allow a faster, low-cost and reliable evaluation of IHD patient prognosis by inclusion of more predictors and identification of those more significant, improving outcome prediction towards the development of precision medicine in this clinical field.

Effects of supplemental fulvic acid on survival, growth performance, digestive ability and immunity of large yellow croaker (Larimichthys crocea) larvae.

A 30-day feeding trial was designed to evaluate the effect of supplemental fulvic acid (FA) on survival, growth performance, digestive ability and immunity of large yellow croaker (Larimichthys crocea) larvae (initial body weight 11.33 ± 0.57 mg). Four isonitrogenous and isolipids diets containing 0.00%, 0.01%, 0.02% and 0.04% FA were formulated, respectively. Results showed that the supplementation of 0.04% FA significantly improved survival rate of large yellow croaker larvae. Meanwhile, supplemental FA significantly increased final body weight and specific growth rate. Based on the specific growth rate, the optimal supplementation was 0.0135% FA. Larvae fed the diet with 0.01% FA had significantly higher villus height than the control. The supplementation of 0.01%-0.02% FA significantly increased the muscular thickness of intestine. Moreover, supplementation of FA significantly increased mRNA expression of intestinal epithelial proliferation and barrier genes (pcna, zo-1 and zo-2). Diets supplemented with 0.02%-0.04% FA significantly increased the activity of trypsin in the intestinal segment, while 0.01%-0.02% FA significantly increased the activity of trypsin in the pancreatic segment. Compared with the control, supplementation of FA remarkably increased activities of alkaline phosphatase and leucine aminopeptidase in the brush border membrane of intestine. Larvae fed the diet with 0.01% FA significantly increased activities of lysozyme and total nitric oxide synthase. Furthermore, the supplementation of 0.01% to 0.02% FA significantly decreased the mRNA expression of pro-inflammatory cytokines (tnf-α and il-6). Concurrently, supplemental FA significantly increased anti-inflammatory cytokine (il-10) mRNA expression level. In conclusion, this study indicated that the supplementation of FA could improve the survival rate and growth performance of larvae by promoting intestinal development, digestive enzymes activities and innate immunity.

Growth responses and physiological and biochemical changes in five ornamental plants grown in urban lead-contaminated soils.

An increasing concentration of lead (Pb) in urban contaminated soil due to anthropogenic activities has been a global issue threatening human health. The use of urban ornamental plants as phytoremediation of Pb-contaminated soil is a new choice. In the present experiment, the physiological and biochemical response of five ornamental plants to increase in concentrations of C4H6O4Pb·H2O in the soil were measured to investigate these plans' Pb tolerance strategies and abilities. Our results showed that Pb stress significantly inhibited the growth and the biomass of all the plants. The root activity (RA), net photosynthetic rate (P n), and chlorophyll (Chl) content in Pb-stressed leaves were significantly decreased, whereas the leaf proline (Pro), soluble sugar (SS), and membrane stability index (MSI) were remarkable increased compared with those in the control group. By application of all-subsets regression and linear regression, the reduction in photosynthetic capacity in the five plants is mainly due to the decrease in the leaf Chl content caused by Pb stress. The bioconcentration factor (BCF) in Canna generalis was greater than 1, while in the other plants were lower than 1, suggesting that Canna generalis had the highest Pb accumulation ability. The translocation factor (TF) in all the plants were lower than 1, suggesting that Pb preferentially accumulated in the external part of roots. By calculating the comprehensive evaluation value (CEV), Iris germanica L. was found to be the most sensitive species, and Canna generalis was the most tolerant species, to Pb stress among the five ornamental plants.