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As an education model that focuses on the cultivation of students' creativity and practical ability, the integration of maker education and the development of artificial intelligence is of great significance. In order to analyze and study the application effect of artificial intelligence in maker education, based on this, this study adopts the method of questionnaire and case analysis to investigate and analyze students from three dimensions: learning experience, learning attitude and learning emotion, learning effect and transfer. The survey results show that, on the whole, the integration of artificial intelligence technology into maker education can significantly improve students' learning feelings and attitudes, and enhance the enthusiasm of learning emotions. The research also finds that it has a positive impact on students' learning effect and transfer ability. Learning experience, learning attitude and learning emotion, learning effect and learning transfer are related to gender, teaching time, teaching subjects or majors. Therefore, the article will suggest creating a maker cultural atmosphere, creating a maker resource space, and improving the maker education system. This provides a valuable reference for further promoting the development of maker education courses in the field of artificial intelligence. [ABSTRACT FROM AUTHOR]

Developing mechanical metamaterials through topology optimization attracts high attention in both computational design and engineering applications. However, most of the studies in the literature are of quite limited applicability and poor extensibility. Hence, this work originally established an adaptable metamaterial topology optimization framework through integrating a commercial finite element analysis (FEA) platform. Particularly, the sensitivity analysis was derived and simplified to avoid the complex extraction of internal FEA information according to the strain-energy-based homogenization method. A series of two- and three-dimensional metamaterials with different properties, i.e., bulk and shear moduli, negative Poisson's ratio, were subsequently devised. These optimized metamaterials were fabricated and experimentally tested based on the additive manufacturing, firmly demonstrating the effectiveness of the developed design framework. This well-structured design framework can be conveniently extended to the systematic design of metamaterials with various other exclusive performances, fulfilling the urgent need for metamaterial design methods. [ABSTRACT FROM AUTHOR]

Extensive research indicates that tumor stemness promotes tumor progression. Nonetheless, the underlying roles of stemness-related genes in renal clear cell carcinoma (ccRCC) are unclear. Data used in bioinformatics analysis were downloaded from The Cancer Genome Atlas (TCGA) database. Moreover, the R software, SPSS, and GraphPad Prism 8 were used for mapping and statistical analysis. First, the stemness index of each patient was quantified using a machine learning algorithm. Subsequently, the differentially expressed genes between high and low stemness index were identified as stemness-related genes. Based on these genes, a stable and effective prognostic model was identified to predict the overall survival of patients using a random forest algorithm (Training cohort; 1-year AUC: 0.67; 3-year AUC: 0.79; 5-year AUC: 0.73; Validation cohort; 1-year AUC: 0.66; 3-year AUC: 0.71; 5-year AUC: 0.7). The model genes comprised AC010973.2, RNU6-125P, AP001209.2, Z98885.1, KDM5C-IT1, and AL021368.3. Due to its highest importance evaluated by randomforst analysis, the AC010973.2 gene was selected for further research. In vitro experiments demonstrated that AC010973.2 is highly expressed in ccRCC tissue and cell lines. Meanwhile, its knockdown could significantly inhibit the proliferation of ccRCC cells based on colony formation and CCK8 assays. In summary, our findings reveal that the stemness-related gene AC01097.3 is closely associated with the survival of patients. Besides, it remarkably promotes cell proliferation in ccRCC, hence a novel potential therapeutic target. [ABSTRACT FROM AUTHOR]

The focus of this study was to explore the association between the non-HDL-cholesterol to HDL-cholesterol (non-HDLc/HDLc) ratio and mortality in septic patients. This was a retrospective cohort study of patients with sepsis in the eICU Collaborative Research Database (eICU-CRD) from 208 distinct ICUs across the United States between 2014 and 2015 that explored. All-cause mortality within 28 days after ICU admission. A multivariable logistic regression model was used to estimate the risk of death. Of the 724 patients with a median age of 68 years, 43 (5.94%) died within 28 days after ICU admission. When the non-HDLc/HDLc ratio was < 3.3, the mortality rate decreased with an adjusted odds ratio (OR) of 0.60 (95% CI 0.37–0.99, P = 0.043) for every 1 increment in the non-HDLc/HDLc ratio. When the non-HDLc/HDLc ratio was ≥ 3.3, the mortality rate increased with an adjusted OR of 1.28 (95% CI 1.01–1.62, P = 0.039) for every one increment in the non-HDLc/HDLc ratio. For patients with sepsis, the association between the non-HDLc/HDLc ratio and the 28-day mortality risk was a U-shaped curve. A higher or lower non-HDLc/HDLc ratio was associated with an increased risk of 28-day mortality. [ABSTRACT FROM AUTHOR]

With the rapid industrial development and urbanisation in China, nitrogen dioxide (NO 2) pollution has become a severe environmental problem that threatens public health. Based on hourly concentration monitoring data of the six main air pollutants in mainland China, a space–time Bayesian hierarchy model was employed to analyse the spatiotemporal trends of the absolute and relative NO 2 concentrations (i.e., the proportion of NO 2 in the six main air pollutants: CO , NO 2 , PM 2.5 , PM 10 , O 3 , and SO 2 ). Both the absolute and relative NO 2 concentrations were higher in the autumn and winter of each year during the study period. Four regions in particular—the North China Plain, the Yangtze River Delta, the Sichuan Basin, and the Pearl River Delta—experience the largest amounts of NO 2 pollution, with a high local magnitude of more than 1.0 relative to the overall absolute and relative NO 2 concentrations; this affects an area with a human population of 571.85 million, which is 42.47% of the total population. Central China (i.e., the Shaanxi–Shanxi–Henan region) and the Tarim Basin (northwest of Xinjiang) were heavily polluted by NO 2 and other pollutants throughout the year, with a high local magnitude of more than 1.0 relative to the overall absolute NO 2 concentration. The NO 2 pollution in most of the cities in western and southern China is less serious, along with cities in the northeast. Local trends reveal that in general, cities with high NO 2 pollution are accompanied by upward trends. Specifically, except for in the summer, there were about 86 cities showing the increasing trend, of which 66 cities are located in areas with higher absolute and relative NO 2 concentrations. Taiyuan, for example, represents the maximal local trend, with an average annual increase of 4.39 (95% CI 1.61–7.43) μ g / m 3 and 0.43 (95% CI 0.16–0.73) %, respectively, which will lead to further increases in the population exposure-risk in heavily polluted areas. [ABSTRACT FROM AUTHOR]

Background: Changes in platelet count are common in COVID-19 patients. The platelet count reflects the thrombocyte turnover, acting as a sensitive indicator of illness severity that is of great clinical utility to monitor a quickly changing health condition of patients affected by aggressive viral infections. This study aims to investigate the significance of platelet count during the progression of the disease in COVID-19 patients. Methods: A total of 532 COVID-19 patients were involved in the cohort study from the First People's Hospital of Jiangxia District in Wuhan from January 7, 2020, to February 28, 2020. We collected the clinical characteristics and laboratory data of patients. Patients still hospitalized before February 29, 2020, died on admission, with malignant tumors, previous gastrointestinal surgery, missing baseline platelet count, or platelet count detected only once, were excluded. We used a generalized additive model and generalized additive mixed model to compare trends in platelet count over time among survivors and non-survivors, with an adjustment for potential confounders. Results: During the follow-up, twenty-nine subjects died (mortality rate, 5.45%). The platelets among non-survivors decreased and among survivors increased gradually within 1 week after admission. In addition, the difference between the two groups showed an increasing trend during 1 week after admission. This difference increased by an average of 5.3 × 10^9/L daily. Conclusions: In the early stage, platelet count can dynamically reflect the pathophysiological changes in COVID-19 patients. Early decrease in platelet count was associated with mortality in patients with COVID-19. Causality, however, cannot be deduced from our data. [ABSTRACT FROM AUTHOR]

Agarases are hydrolytic enzymes that act on the hydrolysis of agar and have a broad range of applications in food, cosmetics and pharmaceutical industries. In this study, a glycerol feeding strategy based on induction mode optimization for high cell density and β-agarase production was established, which could effectively control acetate yield. First, exponential feeding strategy of glycerol with different overall specific growth rates ( μ) was applied in the pre-induction phase. The results showed that the low μ ( μ=0.2) was suggested to be the optimal for cell growth and β-agarase production. Second, the effects of induction temperature and the inducer concentration on cell growth and β-agarase production were investigated in the post-induction phase. When induced by isopropyl-β-d-thiogalactoside (IPTG), the strategy of 0.8 mmol/L IPTG induction at 20°C was found to be optimal for β-agarase production. When cultivation was induced by continuous lactose feeding strategy of 1.0 g/(L·h), the β-agarase activity reached 112.5 U/mL, which represented the highest β-agarase production to date. Furthermore, the β-agarase was capable of degrading G. lemaneiformis powder directly to produce neoagarooligosaccharide, and the hydrolysates were neoagarotetraose (NA4) and neoagarohexaose (NA6). The overall research may be useful for the industrial production and application of β-agarase. [ABSTRACT FROM AUTHOR]

The diversity of modular polyketide synthase (PKS) genes in sediments of Ardley Island in Antarctica, was studied by restriction fragment length polymorphism (RFLP) analysis. Phylogenetic analysis of 14 amino acid (AA) sequences indicates that the identified ketosynthase (KS) domains were clustered with those from diverse bacterial groups, including Cyanobacteria, γ-Proteobacteria, Actinobacteria, Firmicutes, and some unidentified microorganisms from marine sponge, bryozoan and other environmental samples. The obtained KS domains showed 43%-81% similarity at the AA level to reference sequences in GenBank. Six identified KS domains showed diverse sequences of the motif (VQTACSTS) that was used to identify the hybrid PKS/nonribosomal peptide synthetase (NRPS) enzyme complex, and formed a new branch. These results reveal a high diversity and novelty of PKS genes in antarctic sediments. [ABSTRACT FROM AUTHOR]