LASense: Pushing the Limits of Fine-grained Activity Sensing Using Acoustic Signals.

Acoustic signals have been widely adopted in sensing fine-grained human activities, including respiration monitoring, finger tracking, eye blink detection, etc. One major challenge for acoustic sensing is the extremely limited sensing range, which becomes even more severe when sensing fine-grained activities. Different from the prior efforts that adopt multiple microphones and/or advanced deep learning techniques for long sensing range, we propose a system called LASense, which can significantly increase the sensing range for fine-grained human activities using a single pair of speaker and microphone. To achieve this, LASense introduces a virtual transceiver idea that purely leverages delicate signal processing techniques in software. To demonstrate the effectiveness of LASense, we apply the proposed approach to three fine-grained human activities, i.e., respiration, finger tapping and eye blink. For respiration monitoring, we significantly increase the sensing range from the state-of-the-art 2 m to 6 m. For finer-grained finger tapping and eye blink detection, we increase the state-of-the-art sensing range by 150% and 80%, respectively.

lncRNA NEAT1 prompts autophagy and apoptosis in MPTP-induced Parkinson's disease by impairing miR-374c-5p.

Long non-coding RNAs (lncRNAs) play biological roles in brain disorder and neurodegenerative diseases. As the functions of lncRNA NEAT1 in Parkinson's disease (PD) remain unknown, in the present study, we aimed to explore the roles and underlying molecular mechanisms of NEAT1 in PD. A PD mouse model induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and a cell model of SH-SY5Y induced by N-methyl-4-phenylpyridinium (MPP+) were established. The ratio of tyrosine hydroxylase (TH+) cells was determined by immunofluorescence assay, and the behavioral changes in mice were observed using pole tests and rotarod tests. The cellular viability and apoptosis of SH-SY5Y were detected by MTT assay and flow cytometric analysis, respectively, and the number of autophagosomes was subsequently measured by transmission electron microscopy. High-performance liquid chromatography was performed to detect the content of dopamine, and a dual-luciferase reporter assay was used to clarify the target of NEAT1 simultaneously. The results demonstrated that the level of NEAT1 was upregulated in the MPTP-induced PD mice, dopamine neurons, and the SH-SY5Y cells treated with MPP+, whereas the level of miR-374c-5p was downregulated. NEAT1 level was positively correlated with MPP+ in a concentration-dependent manner. NEAT1 inhibition efficiently facilitated cell proliferation but inhibited apoptosis and autophagy in the MPP+-treated SH-SY5Y cells. Additionally, silencing of NEAT1 increased the TH+ rate of neurons and suppressed autophagy greatly in PD mice. As a possible target of NEAT1, miR-374c-5p could impact on the apoptosis and autophagy of the SH-SY5Y cells. NEAT1 inhibition upregulated the expression of miR-374c-5p, enhanced SH-SY5Y cell viability, and repressed autophagy and apoptosis in MPTP-induced PD mice. These findings indicated a potential therapeutic role of NEAT1 in treating PD.

[Fingerprint analysis and Q-marker prediction of processed liquorice products].

Licorice has long been regarded as one of the most popular herbs, with a very wide clinical application range. Whether being used alone or as an ingredient in prescription, it has an important role which cannot be ignored. However, the efficacy and chemical constituents of licorice will change after honey-processing. Therefore, it is necessary to find quality markers before and after honey-processing to lay the foundation for a comprehensive evaluation of the differences between raw and processed licorice pieces. HPLC-DAD was employed to establish fingerprints of raw and processed licorice. Multivariate statistical analysis methods including principal component analysis(PCA) and orthogonal partial least squares discrimination analysis(OPLS-DA) were applied to screen out the differential components before and after processing of licorice. Based on network pharmacology, the targets and pathways corresponding to the differential components were analyzed with databases such as Swiss Target Prediction and Metascape, and the "component-target-pathway" diagram was constructed with Cytoscape 3.6.0 software to predict the potential quality markers. A total of 17 common peaks were successfully identified in the established fingerprint, and seven differential components were selected as potential quality markers(licoricesaponin G2, glycyrrhizic acid, liquiritigenin, liquiritin, isoliquiritin, liquiritin apioside and isoliquiritigenin). The HPLC fingerprint method proposed in this study was efficient and feasible. The above seven differential chemical components screened out as potential quality markers of licorice can help to improve and promote the overall quality. These researches offer more sufficient theoretical basis for scientific application of licorice and its corresponding products.