Application of Mixed Reality Technology in Visualization of Medical Operations.

With the continuous progress of virtual simulation technology, medical surgery visualization system has been developed from two-dimensional to three-dimensional, from digital to network and intelligentization. The visualization system with mixed reality technology will also be used in all stage of medical surgery, such as case discussion, surgical planning, intraoperative guidance, post-operative evaluation, rehabilitation, so as to further promote high intelligence, high precision of medical surgery, and consequently improve effectiveness of treatment and quality of medical service. This paper discusses the composition and technical characteristics of medical operation visualization system based on mixed reality technology, and introduces some typical applications of mixed reality technology in medical operation visualization, which provides a new perspective for the application of mixed technology in medical surgery.

In Silico Prediction of Chemical Toxicity Profile Using Local Lazy Learning.

BACKGROUND: Chemical toxicity is an important reason for late-stage failure in drug R&D. However, it is time-consuming and expensive to identify the multiple toxicities of compounds using the traditional experiments. Thus, it is attractive to build an accurate prediction model for the toxicity profile of compounds. MATERIALS AND METHODS: In this study, we carried out a research on six types of toxicities: (I) Acute Toxicity; (II) Mutagenicity; (III) Tumorigenicity; (IV) Skin and Eye Irritation; (V) Reproductive Effects; (VI) Multiple Dose Effects, using local lazy learning (LLL) method for multi-label learning. 17,120 compounds were split into the training set and the test set as a ratio of 4:1 by using the Kennard-Stone algorithm. Four types of properties, including molecular fingerprints (ECFP_4 and FCFP_4), descriptors, and chemical-chemical-interactions, were adopted for model building. RESULTS: The model 'ECFP_4+LLL' yielded the best performance for the test set, while balanced accuracy (BACC) reached 0.692, 0.691, 0.666, 0.680, 0.631, 0.599 for six types of toxicities, respectively. Furthermore, some essential toxicophores for six types of toxicities were identified by using the Laplacian-modified Bayesian model. CONCLUSION: The accurate prediction model and the chemical toxicophores can provide some guidance for designing drugs with low toxicity.

[Determination of Platinum Group Elements in City Roadside Dusts by ICP-MS ].

Platinum group elements (PGEs) can be naturally found only at very low concentration in the earth crust. However, the increasing usage of PGEs in vehicle exhaust catalysts, and some other applications cause their anthropogenic emission and spread in the environment. Currently，the accumulation of PGEs in the environment has increased over the time. Catalytic converters of modern vehicles are considered to be the main sources of PGE pollution. In order to survey PGEs contamination at residential districts in the urban areas of Beijing City, roadside dust samples were collected. The roadside dust samples were digested with aqua regia and separated and purified with cation exchange resin (Dowex AG50W-X8), and then the resulting solutions were analyzed with inductively coupled plasma mass spectrometry (ICP-MS). PGEs pollution degree in dusts was analyzed using Geoaccumulation Index. The results showed that the concentrations of Pd, Pt and Rh in roadside dusts ranged from 14.20～161.80 ng·g-1 (50.76 ng·g-1), 9.39～70.80 ng·g-1(23.82 ng·g-1), 3.18～17.05 ng·g-1(7.54 ng·g-1), respectively. It indicated that concentrations of PGEs in dusts of residential areas were obviously higher than those values in Beijing soil background. The results of Geoaccumulation Index assessment indicated that the roadside dusts in residential areas were obviously polluted by the PGEs in Beijing city. The order of average pollution level of the PGEs is: Pd＞Pt＞Rh.

[Application of ICP-mS in the health risk assessment of heavy metals for drinking water sources in reservoirs].

The six heavy metal concentrations (Cr, Cr, As, Cd, Cu, Zn and Pb) in water samples collected from five reservoirs of Liao River Basin were studied. The health risk assessment for heavy metals pollution in reservoirs was conducted based on the environmental health risk assessment model recommended by U. S. Environmental Protection Agency. The results showed that the average concentrations of Cr, Cu, Zn, As, Cd and Pb in five reservoirs of Liao River Basin were 3.36, 1.03, 2. 70, 1.23, 0. 02 and 0. 03 microg L-1, respectively. In fact, these heavy metals concentrations were obviously lower than the Standard of National Drinking Water in China (GB 5749-2006). The results also showed that the metal carcinogenic risk was relatively high in this region. The order of the risk level of carcinogenic metals was Cr>As>Cd. The highest carcinogenic risk was from Cr, with the risk for adults ranging from 4. 50 X 10(-5) approximately 7. 53 X 10(-5) a-1' and the risk for children ranging from 6. 29 X 10(-5) to 1. 05 X 10(-4) a-1. The health risk levels caused by non-carcinogenic metals ranging from 10-13 to 10(-10) a-1 were lower than the acceptable range suggested by International Commission on Radiological Protection (ICRP) and the order of the risk level of non-carcinogenic metals was Cu>Zn>Pb. The total health risk of heavy metals for adults ranging from 1. 07X 10(-4) to 1. 72X 10(-4) a-1 and for children ranging from 1. 49 X 10(-4) to 2. 40 X 10(-4) a-1 exceeded the accepted level of 5 X 10(-5) a-1 as suggested by ICRP. The health risk levels of carcinogenic metals were significantly higher than those of non-carcinogenic metals in the reservoirs for Liao River Basin.