Alleviation of fatigue has been emerging as a serious issue that requires urgent attention. Health professionals and sports physiologists have been looking for active natural products and synthetic compounds to overcome fatigue in humans. This study was designed to define the anti-fatigue property of Rubus parvifolius L. (RPL) by characterization of active constituents using a mouse forced swimming test model. Four RPL fractions with different polarities containing anti-fatigue activity were sequentially isolated from the n-butanol RPL extract, followed by elution of 50% ethanol-water fraction from D101 macroporous resin chromatography to obtain nigaichigoside F 1 , suavissimoside R 1 and coreanoside F 1 . Active constituents of the 50% ethanol-water eluate of RPL were total saponins. The fractions were examined based on the effect on weight-loaded swimming capacity of mice. Serum levels of urea nitrogen (SUN), triglyceride fatty acids (TG), lactate dehydrogenase (LDH), lactic acid (LA), ammonia and hepatic glycogen (HG) were also examined for potential mechanisms underlying the anti-fatigue effect of RPL extracts. During the experiment, two inflammatory markers, interleukin-6 (IL-6) and tumor necrosis factor (TNF-α) in serum, were measured. We found that total saponins from RPL possess potent capabilities to alleviate mouse fatigue induced by forced swimming and that nigaichigoside F 1 was responsible for the pharmacological effect. The underlying mechanisms include delays of SUN and LA accumulation, a decrease in TG level by increasing fat consumption, increases in HG and LDH so that lactic acid accumulation and OPEN ACCESSMolecules 2013, 18 11625 ammonia in the muscle were reduced, and suppression of increased immune activation and inflammatory cytokine production. Our findings will be helpful for functional identification of novel anti-fatigue components from natural medicinal herbs.

Rubus parvifolius L. (Rp) is a medicinal herb that possesses antibacterial activity. In this study, we extracted the volatile oil from the leaves of Rp to assess its antibacterial activity and analyze its chemical composition. A uniform distribution design was used to optimize the extraction procedure, which yielded 0.36% (w/w) of light yellowish oil from the water extract of Rp leaves. We found that the extracted oil effectively inhibited the growth of a wide range of Gram positive and negative bacteria, including Staphylococcus aureus, Staphylococcus epidermidis, Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumanii, Bacillus cloacae, and Klebsiella pneumoniae. We further analyzed the components contained in the hydro-distillated Rp volatile oil by gas chromatography-mass spectroscopy. Twenty nine compounds were identified, including 4-hydroxy-3-methoxystyrene (66%), 3,7,11,15-tetramethyl-2-hexadecen-1-ol (10%) and 4-tert-butylbenzoic acid (2%). Our results suggest that one or multiple constituents contained in Rp volatile oil may account for its antibacterial activity.

Compared with the general Visual Question Answering (VQA), Medical VQA is more challenging. Medical images contain more complex information than general images. Aiming at this point, we propose the IIF module that can improve the model's ability to obtain visual feature. In addition, we design QAM to help the model analyze the question better. On the VQA-RAD dataset, the accuracy of our model improved to 66.4% on the opened-ended questions and 80.1% on the closed-ended questions, outperforming other relevant models. The results on the VQA-MED 2019 dataset also verify the effectiveness of our model.