Scope: Published data support that gut microbiota play an important role in the pathological process of obesity and related metabolic disorders. In the current study, it is investigated whether a standardized extract from Jamun (Eugenia jambolana), a widely consumed tropical fruit, could alleviate obesity and alter gut microbial community in high-fat diet (HFD)-fed mice. Methods and results: C57BL/6 mice are fed either a standard diet (SD) or HFD with or without Jamun fruit extract (JFE; 100 mg kg −1 day −1 ) by oral gavage for 8 weeks. JFE supplementation significantly alleviated diet-induced obesity, insulin resistance, and liver steatosis. JFE supplementation also improved HFD-induced gut dysbiosis by restoring the ratio of Firmicutes to Bacteroidetes as revealed by 16S rDNA analyses. The relative abundance of certain genera, as well as levels and proportion of intestinal-derived short-chain fatty acids are improved in JFE-treated mice in comparison to the HFD-fed control group. Conclusion: These promising data show the potential association between gut microbiota modulation and metabolism improvement of the JFE administration, and support the utilization and further investigation of Jamun fruit as a dietary intervention strategy for the prevention of obesity and related metabolic disorders.
In this paper, we propose a cloud-based benchmark for robotic grasping and manipulation, called the OCR-TOC benchmark. The benchmark focuses on the object rearrangement problem, specifically table organization tasks. We provide a set of identical real robot setups and facilitate remote experiments of standardized table organization scenarios in varying difficulties. In this workflow, users upload their solutions to our remote server and their code is executed on the real robot setups and scored automatically. After each execution, the OCRTOC team resets the experimental setup manually. We also provide a simulation environment that researchers can use to develop and test their solutions. With the OCR-TOC benchmark, we aim to lower the barrier of conducting reproducible research on robotic grasping and manipulation and accelerate progress in this field. Executing standardized scenarios on identical real robot setups allows us to quantify algorithm performances and achieve fair comparisons. Using this benchmark we held a competition in the 2020 International Conference on Intelligence Robots and Systems (IROS 2020). In total, 59 teams took part in this competition worldwide. We present the results and our observations of the 2020 competition, and discuss our adjustments and improvements for the upcoming OCRTOC 2021 competition. The homepage of the OCRTOC competition is www.ocrtoc.org, and the OCRTOC software package is available at https://github. com/OCRTOC/OCRTOC_software_package.
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