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Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments. [ABSTRACT FROM AUTHOR]

A potential use of small extracellular vesicles (sEVs) for diagnostic and therapeutic purposes has recently generated a great interest. sEVs, when purified directly from various tissues with proper procedures, can reflect the physiological and pathological state of the organism. However, the quality of sEV is affected by many factors during isolation, including separation of sEV from cell and tissues debris, the use of enzymes for tissue digestion, and the storage state of tissues. In the present study, we established an assay for the isolation and purification of liver cancer tissues-derived sEVs (tdsEVs) and cultured explants-derived sEVs (cedsEVs) by comparing the quality of sEVs derived from different concentration of digestion enzyme and incubation time. The nano-flow cytometry (NanoFCM) showed that the isolated tdsEVs by our method are purer than those obtained from differential ultracentrifugation. Our study thus establishes a simple and effective approach for isolation of high-quality sEVs that can be used for analysis of their constituents. [ABSTRACT FROM AUTHOR]

Tuberculosis caused by Mycobacterium tuberculosis (M. tuberculosis) is the leading cause of death among infectious diseases in the worldwide. Lack of more sensitive and effective diagnostic reagents has increased the awareness of rapid diagnosis for tuberculosis. In this study, T7 phage displayed genomic DNA library of M. tuberculosis was constructed to screen the antigens that specially bind with TB-positive serum from the whole genome of M. tuberculosis and to improve the sensitivity and specificity of tuberculosis serological diagnosis. After three rounds of biopanning, results of DNA sequencing and BLAST analysis showed that 19 positive phages displayed four different proteins and the occurrence frequency of the phage which displayed ribokinase was the highest. The results of indirect ELISA and dot immunoblotting indicated that representative phages could specifically bind to tuberculosis-positive serum. The prokaryotic expression vector containing the DNA sequence of ribokinase gene was then constructed and the recombinant protein was expressed and purified to evaluate the serodiagnosis value of ribokinase. The reactivity of the recombinant ribokinase with different clinical serum was detected and the sensitivities and specificities in tuberculosis serodiagnosis were 90% and 86%, respectively by screening serum from tuberculosis patients (n = 90) and uninfected individuals (n = 90) based on ELISA. Therefore, this study demonstrated that ribokinase had good potential for the serodiagnosis of tuberculosis. [ABSTRACT FROM AUTHOR]