1.Detection and Assessment of Timeliness of Electronic Medical Tag System
Ping LIAN ; Gejun ZHANG ; Yufeng JI ; Songjun LIU ; Fengxun LV ; Ying LUAN
Chinese Medical Equipment Journal 2004;0(08):-
Objective To test the timeliness of newly developed electronic medical tag system.Methods According to a standardized logistical process of medical tag in battlefield,timeliness tests of electronic medical tag and paper-based medical tag in two different echelons: battalion-company and medical battalion were completed,and the data of two groups were compared.Results It showed that the consumed time in the electronic medical tag system was 3/10 and 1/11 of the consumed time in paper-based medical tag respectively.Conclusion The timeliness of the electronic medical tag system is much better than that of the paper-based medical tag and meets the timeliness requirements of treatment in battlefield.
2.Construction of an Escherichia coli strain for sensitive detection of arsenite ion in water.
Wu WANG ; Songjun JI ; Zhaozhu HUANG ; Binbin LU ; Jianxin LV
Chinese Journal of Biotechnology 2016;32(8):1081-1092
In order to construct an Escherichia coli strain with high sensitivity and specificity to detect arsenic ion using fluorescence as reporter, a sensitive strain to arsenic ion was obtained by knocking out the gene arsB that acts as an arsenic efflux pump. The pET28b vector containing arsenite detecting cassette Pars-arsR-egfp was constructed and then transformed into arsB deleted mutant. Measuring conditions of this constructed whole-cell biosensor were optimized and its linear concentration range, limit of detection and specificity were determined. This modified biosensor was much more sensitive than that using wild-type strain as host. The optimal detection range of As³⁺ concentration was 0.013 to 42.71 μmol/L, and the limit concentration of detection was as low as 5.13 nmol/L. Thus we successfully improved the sensitivity of arsenite detecting biosensor by modification of E. coli genome, which may provide useful strategies for development and optimization of microbial sensors to detect heavy metals.
Arsenites
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analysis
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Biosensing Techniques
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Escherichia coli
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genetics
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Gene Knockout Techniques
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Metals, Heavy
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Microorganisms, Genetically-Modified
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Water
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chemistry