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The comprehensive properties of high-entropy alloys (HEAs) are highly-dependent on their phases. Although a large number of machine learning (ML) algorithms has been successfully applied to the phase prediction of HEAs, the accuracies among different ML algorithms based on the same dataset vary significantly. Therefore, selection of an efficient ML algorithm would significantly reduce the number and cost of the experiments. In this work, phase prediction of HEAs (PPH) is proposed by integrating criterion and machine learning recommendation method (MLRM). First, a meta-knowledge table based on characteristics of HEAs and performance of candidate algorithms is established, and meta-learning based on the meta-knowledge table is adopted to recommend an algorithm with desirable accuracy. Secondly, an MLRM based on improved meta-learning is engineered to recommend a more desirable algorithm for phase prediction. Finally, considering poor interpretability and generalization of single ML algorithms, a PPH combining the advantages of MLRM and criterion is proposed to improve the accuracy of phase prediction. The PPH is validated by 902 samples from 12 datasets, including 405 quinary HEAs, 359 senary HEAs, and 138 septenary HEAs. The experimental results shows that the PPH achieves performance than the traditional meta-learning method. The average prediction accuracy of PPH in all, quinary, senary, and septenary HEAs is 91.6%, 94.3%, 93.1%, and 95.8%, respectively. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus (S. aureus) is a pathogen closely associated with foodborne diseases. We prepared a reliable colorimetric sensor to detect S. aureus using click chemical reaction and immunomagnetic separation. Aptamer-functionalized and ALP-labeled Fe3O4 NPs act as separation and signal transduction elements. Under the optimized conditions, the Cu+ generated by signal transduction triggers a click chemistry reaction, which causes the aggregation of azides and alkyne-AuNPs and a color change. The net extinction ratio of Δ(A530/A760) was linearly correlated with the S. aureus concentration from 10 to 106 cfu mL−1, and the limit detection was 2.4 cfu mL−1. The recoveries were 91.15 ~ 106.36% for the analysis of spiked food and water samples without pre-enrichment. Therefore, we believe that the detection platform can be easily and accurately used for S. aureus detection, providing a broad prospect for on-site visual detection. [ABSTRACT FROM AUTHOR]

As an active form of vitamin D (VD), 1,25-dihydroxyvitamin D (1,25(OH)2D3) is involved in the development of many metabolic diseases, such as diabetes, autoimmune diseases, and tumours. While prospective epidemiological studies have consistently implicated VD deficiency in the regulation of glucose metabolism and insulin sensitivity, the specific mechanism remains unclear. Here, we generated 1α(OH)ase-null mice (targeted ablation of the 25-hydroxyvitamin D 1α hydroxylase enzyme) and found that these mice developed hepatic glucose overproduction, glucose intolerance, and hepatic insulin resistance accompanied by reduced Sirtuin 1 (Sirt1) expression. The chromatin immunoprecipitation (ChIP) and a luciferase reporter assay revealed that 1,25(OH)2D3-activated VD receptor (VDR) directly interacted with one VD response element (VDRE) in the Sirt1 promoter to upregulate Sirt1 transcription, triggering a cascade of serine/threonine kinase (AKT) phosphorylation at S473 and FOXO1 phosphorylation at S256. This phosphorylation cascade reduced the expression of gluconeogenic genes, eventually attenuating glucose overproduction in the liver. In addition, a signaling pathway was found to modulate gluconeogenesis involving VDR, Sirt1, Rictor (a component of mTOR complex 2 [mTorc2]), AKT, and FOXO1, and Sirt1 and FOXO1 were identified as key modulators of dysregulated gluconeogenesis due to VD deficiency. [ABSTRACT FROM AUTHOR]

1,25(OH)2D3 as an active form of vitamin D is involved in the development of many metabolic-related diseases including diabetes. While prospective epidemiological studies have shown that vitamin D deficiency is implicated in the regulation of glucose metabolism, the specific mechanism still remains unclear. Here, we generated 1α(OH)ase-null mice and discovered that these mice developed hepatic glucose overproduction and hepatic insulin resistance accompanied by decreased expression of Sirt1. ChIP and Luciferase assay confirmed that 1,25(OH)2D3 activating vitamin D receptor (VDR) directly interacts with one vitamin D response element located in Sirt1 promoter to up-regulate its transcription, triggering a cascade of phosphorylation of Akt at S473 and FOXO1 at S256 and resulting in decreased transcription of the gluconeogenic genes glucose-6-phosphatase (G6pase) and phosphoenolpyruvate carboxykinase (PCK1), eventually hepatic glucose overproduction. We have identified a signaling pathway involving VDR, Sirt1, Rictor (a component of mTOR complex 2 [mTorc2]), Akt, and FoxO1 that regulates gluconeogenesis, and identified Sirt1 and FoxO1 as key modulators of increased gluconeogenesis induced by vitamin D deficiency. Our work demonstrates a novel mechanism of 1,25(OH)2D3 deficiency-induced hyperglycemia mediated through Sirt1 downregulation. Disclosure: Q. Yuan: None. J. Yang: None. M. Sun: None. S. Tang: None. M. Dong: None. L. Mao: None. Funding: National Natural Science Foundation of China (81400789) [ABSTRACT FROM AUTHOR]