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To establish a complete technical solution for the automatic radiation biological dose estimation platform for biological dose estimation and classification of the wounded in large-scale radiation accidents, the "dose-effect curve by dicentric chromosome (DIC) automatic analysis" was established and its accuracy was verified. The effects of analyzed cell number and the special treatment of the culture on dose estimation by DIC automatic analysis were studied. Besides, sample processing capabilities of the special equipments were tested. The fitted "dose-effect curve by DIC automatic analysis" was presented as follows: Y = (0.01806 ± 0.00032) D 2 + (0.01279 ± 0.00084) D + (0.0004891 ± 0.0001358) (R 2 = 0.961). Three-gradient scanning method, culture refrigeration method, and interprofessional collaboration under extreme conditions were proposed to improve the detection speed, prolong the sample processing time window, and reduce the equipment investment. In addition, the optimized device allocation ratio for the automatic biological dose estimation laboratory was proposed to eliminate the efficiency bottleneck. The complete set of technical solutions for the high-throughput automatic biological dose estimation laboratory proposed in this study can meet the requirements of early classification and rapid biological dose assessment of the wounded during the large-scale nuclear radiation events, and it is worthy of further promotion.
Pubmed ID: 30302068 RIS Download
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Ikaros is an open infrastructure for system level modeling of the brain including databases of experimental data, computational models and functional brain data. The system makes heavy use of the emerging standards for Internet based information and makes all information accessible through an open web-based interface. In addition, Ikaros can be used as a control architecture for robots which in the extension will lead to the development of a brain inspired robot architecture. The main components of the Ikaros systems are: a platform independent simulation kernel; a set of computational brain models; a set of I/O modules for interfacing with data files and peripheral such as robots or video cameras; tools for building systems of interconnected models; a plug-in architecture that allows new models to be easily added to the system; and a database with data from learning experiments that can be used for validation of the computational models.
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