Ramulus mori (Sangzhi) alkaloids regulates gut microbiota disorder and its metabolism profiles in obese mice induced by a high-fat diet

The imbalance of gut microbiota has been confirmed to have a close pathological and physiological correlation with obesity and metabolic syndrome. Ramulus Mori (Sangzhi) Alkaloids (SZ-A) derived from twigs of mulberry was approved by the National Medical Products Administration of China in 2020 for the treatment of type 2 diabetes mellitus. In addition to its hypoglycemic effect, previous studies have confirmed that SZ-A also alleviates high-fat diet-induced obesity and non-alcoholic fatty liver disease and ameliorates obesity-linked adipose tissue metabolism and inflammation, indicating the potential of SZ-A to regulate obesity and metabolic syndrome. However, whether SZ-A can improve obesity and metabolic syndrome by regulating gut microbiota and its metabolism profiles remains unclear. The purpose of this study was to assess the effect of SZ-A on gut microbiota in obese mice and to explore the association among changes in gut microbiota, obesity, and lipid metabolism. The results showed that oral administration of SZ-A could significantly reduce body weight, fat mass, and the level of total cholesterol and low-density lipoprotein in serum in obese mice induced by a high-fat diet. Interestingly, SZ-A also regulated gut microbiota and changed the fecal metabolite composition of obese mice. Compared with the high-fat diet group, the ratio of Firmicutes to Bacteroides changed at the phylum level and the abundance of Bifidobacterium and Akkermansia muciniphila significantly increased at the genus level in the SZ-A group. The gut microbiota of the SZ-A group was reshaped and the relative abundance of microbial genes in bile acid metabolism and fatty acid metabolism were altered, which was consistent with the metabolomics results. Additionally, SZ-A greatly enriched the number of goblet cells and reduced inflammatory colon injury and pro-inflammatory macrophage infiltration induced by a high-fat diet in obese mice. In conclusion, SZ-A can alleviate obesity and metabolic syndrome by improving the gut microbiota and its metabolism profiles of obese mice induced by a high-fat diet

Not just having fun: Experiential‐learning–based school field trips improved local children's mental models of the mangrove nature reserve in Shenzhen, China

Abstract Nature‐based school field trips gained policy support from China governments. However, in a highly exam‐oriented education system, schools might be unwilling to implement such activities which they believe are merely fun journeys and useless for knowledge acquisition. We designed an experiential learning field trip to a local mangrove reserve for third graders and assessed how it changed their mental models about the mangrove ecosystem through pre‐ and post‐drawings. We analysed and scored the paired drawings through a rubric developed based on grounded theory coding procedures, used paired t‐tests to examine the changes, and qualitatively interpreted three example pairs from three groups divided by pre‐drawing scores. We deemed that participants' mental models improved, reflecting better knowledge about the mangrove ecosystem. We suggest that the notion of mental models of the environment is relevant to the needs of both formal schools and environmental organizations. By demonstrating a relatively successful nature‐based school field trip case involving pupils from China, we hope that formal schools of this country in the exam‐oriented educational context could utilize it as a justification and vicarious experience to participate in or implement such trips. Read the free Plain Language Summary for this article on the Journal blog

Multi-Parameter Performance Modeling Based on Machine Learning with Basic Block Features

Considering the increasing complexity and scale of HPC architecture and software, the performance modeling of parallel applications on large-scale HPC platforms has become increasingly important. It plays an important role in many areas, such as performance analysis, job management, and resource estimation. In this work, we propose a multi-parameter performance modeling and prediction framework called MPerfPred, which utilizes basic block frequencies as features and uses machine learning algorithms to automatically construct multi-parameter performance models with high generalization ability. To reduce the prediction overhead, we propose some feature-filtering strategies to reduce the number of features in the training stage and build a serial program called BBF collector for each target application to quickly collect feature values in the prediction stage. We demonstrate the use of MPerfPred on the TianHe-2 supercomputer with six parallel applications. Results show that MPerfPred with SVR achieves better prediction than other input parameter-based modeling methods. The average prediction error and average standard deviation of prediction errors of MPerfPred are 8.42% and 6.09%, respectively. In the prediction stage, the average prediction overhead of MPerfPred is less than 0.13% of the total execution time

DataSheet1_Ramulus mori (Sangzhi) alkaloids regulates gut microbiota disorder and its metabolism profiles in obese mice induced by a high-fat diet.PDF

The imbalance of gut microbiota has been confirmed to have a close pathological and physiological correlation with obesity and metabolic syndrome. Ramulus Mori (Sangzhi) Alkaloids (SZ-A) derived from twigs of mulberry was approved by the National Medical Products Administration of China in 2020 for the treatment of type 2 diabetes mellitus. In addition to its hypoglycemic effect, previous studies have confirmed that SZ-A also alleviates high-fat diet-induced obesity and non-alcoholic fatty liver disease and ameliorates obesity-linked adipose tissue metabolism and inflammation, indicating the potential of SZ-A to regulate obesity and metabolic syndrome. However, whether SZ-A can improve obesity and metabolic syndrome by regulating gut microbiota and its metabolism profiles remains unclear. The purpose of this study was to assess the effect of SZ-A on gut microbiota in obese mice and to explore the association among changes in gut microbiota, obesity, and lipid metabolism. The results showed that oral administration of SZ-A could significantly reduce body weight, fat mass, and the level of total cholesterol and low-density lipoprotein in serum in obese mice induced by a high-fat diet. Interestingly, SZ-A also regulated gut microbiota and changed the fecal metabolite composition of obese mice. Compared with the high-fat diet group, the ratio of Firmicutes to Bacteroides changed at the phylum level and the abundance of Bifidobacterium and Akkermansia muciniphila significantly increased at the genus level in the SZ-A group. The gut microbiota of the SZ-A group was reshaped and the relative abundance of microbial genes in bile acid metabolism and fatty acid metabolism were altered, which was consistent with the metabolomics results. Additionally, SZ-A greatly enriched the number of goblet cells and reduced inflammatory colon injury and pro-inflammatory macrophage infiltration induced by a high-fat diet in obese mice. In conclusion, SZ-A can alleviate obesity and metabolic syndrome by improving the gut microbiota and its metabolism profiles of obese mice induced by a high-fat diet.</p