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Musk is a secretion of the forest musk deer (Moschus berezovskii). Normal musk is a brown solid secretion with a light fragrance. In this study, abnormal types of musk, namely, white and black musks, were discovered during the musk collection process. Researchers have long been concerned with the components of musk. Herein, GC-MS, headspace solid-phase microextraction (HS-SPME), and nonmetric multidimensional scaling (NMDS) were used to analyze the nonpolar organic components, volatile organic components, and sample similarities among different musks, respectively. Abundant steroid hormones and proteins were also found in the musk. The steroid hormone concentrations were detected using a radioimmunoassay (RIA). Proteins in the samples were hydrolyzed and the amino acids concentrations were detected. The steroid hormone and amino acid concentrations in white musk were significantly lower than in normal and black musks (p

Abstract Background Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Results Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. Conclusions The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

The musk gland in an adult male forest musk deer is an organ that synthesizes, stores, and secretes musk, a cream-colored liquid upon initial secretion that gradually transforms into a blackish-brown solid substance upon full maturation. In this study, four healthy adult male forest musk deer were selected and a total of 12 musk samples were collected for analysis. The samples were in three different states depending on the different seasonal collection dates, which were in June, August, and October. High-throughput 16S-rRNA gene sequencing technology was used to detect microbiota changes in the gland. The results indicate that microbial richness gradually declined during the musk maturation process. The microbiota composition between the initial liquid and final solid musk samples was varied significantly (P < 0.05). The dominant bacterial phyla were similar at all three stages included Firmicutes, Proteobacteria, Actinobacteria, and Bacteroidetes. However, the abundances were differences in terms of the dominant bacterial genera. PICRUSt analysis showed the highest represented category was “Amino acid transport and metabolism” (24.8%), followed by “Transcription” (22.04%), and “Carbohydrate transport and metabolism” (20.74%). Our findings indicate that the microbiota in the musk gland plays an important role in the maturation process of musk.

Micro-expressions, as fleeting facial expressions, are very important for judging people’s true emotions, thus can provide an essential behavioral clue for lie and dangerous demeanor detection. From embodied accounts of cognition, we derived a novel hypothesis that facial feedback from upper and lower facial regions has differential effects on micro-expression recognition. This hypothesis was tested and supported across three studies. Specifically, the results of Study 1 showed that people became better judges of intense micro-expressions with a duration of 450 ms when the facial feedback from upper face was enhanced via a restricting gel. Additional results of Study 2 showed that the recognition accuracy of subtle micro-expressions was significantly impaired under all duration conditions (50, 150, 333, and 450 ms) when facial feedback from lower face was enhanced. In addition, the results of Study 3 also revealed that blocking the facial feedback of lower face, significantly boosted the recognition accuracy of subtle and intense micro-expressions under all duration conditions (150 and 450 ms). Together, these results highlight the role of facial feedback in judging the subtle movements of micro-expressions.

This study used 16S rRNA high-throughput sequencing technology to examine the differences in gut microbiota between the Père David's deer populations in the Beijing and Shishou areas of China in order to understand the effects of ex situ conservation on the intestinal microflora in the Père David's deer.Results: On the phylum level, the main bacteria found in the Père David's deer populations from both areas were similar: Firmicutes and Bacteroidetes. However, the relative abundances of the two groups were significantly different. Alpha diversity results indicated that there was a difference in the evenness of the microflora between the two groups, and the beta diversity results further indicated that there was a significant difference in the microflora structure between the two groups.Conclusions: During the ex situ conservation process of the Père David's deer, their food sources may change, resulting in differences in the gut microbiota. The intestinal microflora in the Père David's deer from the same area are clustered. Therefore, the impact of changes in food on the gut microbiota of the Père David's deer should be taken into consideration during ex situ conservation.

Diarrhea constitutes one of the most common diseases affecting the survival of captive musk deer and is usually caused by an imbalance in intestinal microbiota. Currently, research regarding the structure and function of intestinal microbiota in diarrheic musk deer is lacking. Therefore, in the present study, high-throughput 16S-rRNA gene sequencing was used to analyze the intestinal microbiota in feces of healthy captive musk deer (HMD) (n = 8) and musk deer with mild (MMD) (n = 8), and severe (n = 5) (SMD) diarrhea to compare the difference in intestinal microbiota of musk deer under various physiological conditions. The results showed that the diversity of HMD fecal microbiota was significantly higher than that of the two diarrhea samples. β Diversity results indicated that there were extremely significant differences in bacterial communities between the HMD sample and the MMD and SMD samples. However, no significant difference was found between the two diarrhea samples. LefSe analysis showed that the degree of intestinal physiological dysfunction in musk deer was correlated with the types of major pathogens. The main pathogen in the MMD group is Escherichia–Shigella, whereas Fusobacterium is the main pathogen in the SMD group. PICRUSt functional profile prediction indicated that the intestinal microbiota disorder could also lead to changes in the abundance of genes in metabolic pathways of the immune system. Altogether, this study provides a theoretical basis for the exploration of treatments for diarrhea in captive musk deer, which is of considerable significance to the implementation of the musk deer release into the wild program.

The large and complex gut microbiota in animals has profound effects on feed utilization and metabolism. Currently, gastrointestinal diseases due to dysregulated gut microbiota are considered important factors that limit growth of the captive forest musk deer population. Compared with captive forest musk deer, wild forest musk deer have a wider feeding range with no dietary limitations, and their gut microbiota are in a relatively natural state. However, no reports have compared the gut microbiota between wild and captive forest musk deer. To gain insight into the composition of gut microbiota in forest musk deer under different food-source conditions, we employed high-throughput 16S rRNA sequencing technology to investigate differences in the gut microbiota occurring between captive and wild forest musk deer. Both captive and wild forest musk deer showed similar microbiota at the phylum level, which consisted mainly of Firmicutes and Bacteroidetes, although significant differences were found in their relative abundances between both groups. α-Diversity results showed that no significant differences occurred in the microbiota between both groups, while β-diversity results showed that significant differences did occur in their microbiota compositions. In summary, our results provide important information for improving feed preparation for captive forest musk deer and implementing projects where captive forest musk deer are released into the wild.

The scented gland, a musk-secreting organ of male muskrats, shows clear seasonal changes. When entering the secreting season in March, scented glands gradually increase in size and active secretion starts. In September, scented glands become gradually smaller and secretion decreases. By November, scented glands are gradually replaced by adipose tissue. In this study, six healthy adult male muskrats were analysed: three from the secreting season (March) and three from the non-secreting season (November). Using RNA-Seq analysis, gene expression profiles of scented glands from both seasons were determined. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we found that genes involved in calcium and TGF-beta signalling pathways were significantly more expressed in the non-secreting than in the secreting season. These changes in gene expression correlated with alterations in scented gland size. Both calcium and TGF-beta signalling pathways are important regulators of cell apoptosis, which may thus be involved in muskrat scented gland degeneration.