A lightweight attention deep learning method for human-vehicle recognition based on wireless sensing technology.

Wireless sensing-based human-vehicle recognition (WiHVR) methods have become a hot spot for research due to its non-invasiveness and cost-effective advantages. However, existing WiHVR methods shows limited performance and slow execution time on human-vehicle classification task. To address this issue, a lightweight wireless sensing attention-based deep learning model (LW-WADL) is proposed, which consists of a CBAM module and several depthwise separable convolution blocks in series. LW-WADL takes raw channel state information (CSI) as input, and extracts the advanced features of CSI by jointly using depthwise separable convolution and convolutional block attention mechanism (CBAM). Experimental results show that the proposed model achieves 96.26% accuracy on the constructed CSI-based dataset, and the model size is only 5.89% of the state of the art (SOTA) model. The results demonstrate that the proposed model achieves better performance on WiHVR tasks while reducing the model size compared to SOTA model.

Detection of Four Porcine Enteric Coronaviruses Using CRISPR-Cas12a Combined with Multiplex Reverse Transcriptase Loop-Mediated Isothermal Amplification Assay.

Porcine enteric coronaviruses have caused immense economic losses to the global pig industry, and pose a potential risk for cross-species transmission. The clinical symptoms of the porcine enteric coronaviruses (CoVs) are similar, making it difficult to distinguish between the specific pathogens by symptoms alone. Here, a multiplex nucleic acid detection platform based on CRISPR/Cas12a and multiplex reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) was developed for the detection of four diarrhea CoVs: porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome coronavirus (SADS-CoV). With this strategy, we realized a visual colorimetric readout visible to the naked eye without specialized instrumentation by using a ROX-labeled single-stranded DNA-fluorescence-quenched (ssDNA-FQ) reporter. Our method achieved single-copy sensitivity with no cross-reactivity in the identification and detection of the target viruses. In addition, we successfully detected these four enteric CoVs from RNA of clinical samples. Thus, we established a rapid, sensitive, and on-site multiplex molecular differential diagnosis technology for porcine enteric CoVs.

Genistein Alleviates High-Fat Diet-Induced Obesity by Inhibiting the Process of Gluconeogenesis in Mice.

Genistein is an isoflavone phytoestrogen that has been shown to improve obesity; however, the underlying molecular mechanisms involved therein have not been clearly elucidated. In this study, we administered genistein to high-fat diet-induced obese mice to investigate its effect on hepatic gluconeogenesis. The results showed that genistein treatment significantly inhibited body weight gain, hyperglycemia, and adipose and hepatic lipid deposition in high-fat diet-induced obese mice. Glucose tolerance test (GTT), insulin tolerance test (ITT) and pyruvate tolerance test (PTT) showed that genistein treatment significantly inhibited gluconeogenesis and improved insulin resistance in obese mice. In addition, this study also found that genistein could promote the expression of miR-451 in vitro and in vivo, and the dual-luciferase reporter system showed that G6pc (glucose-6-phosphatase) may be a target gene of miR-451. Both genistein treatment and in vivo injection of miR-451 agomir significantly inhibited gluconeogenesis and inhibited the expression of G6pc and Gk (glycerol kinase, a known target gene of miR-451). In conclusion, genistein may inhibit gluconeogenesis in obese mice by regulating the expression of Gk and G6pc through miR-451. These results may provide insights into the functions of miR-451 and food-derived phytoestrogens in ameliorating and preventing gluconeogenesis-related diseases.

Alanine-Scanning Mutational Analysis of Durancin GL Reveals Residues Important for Its Antimicrobial Activity.

Durancin GL is a novel class IIa bacteriocin with 43 residues produced by Enterococcus durans 41D. This bacteriocin demonstrates narrow inhibition spectrum and potent antimicrobial activity against several Listeria monocytogenes strains, including nisin-resistant L. monocytogenes NR30. A systematic alanine-scanning mutational analysis with site-directed mutagenesis was performed to analyze durancin GL residues important for antimicrobial activity and specificity. Results showed that three mutations lost their antimicrobial activity, ten mutations demonstrated a decreased effect on the activity, and seven mutations exhibited relatively high activity. With regard to inhibitory spectrum, four mutants demonstrated a narrower antimicrobial spectrum than wild-type durancin GL. Another four mutants displayed a broader target cell spectrum and increased potency relative to wild-type durancin GL. These findings broaden our understanding of durancin GL residues important for its antimicrobial activity and contribute to future rational design of variants with increased potency.