ObjectiveTo determine the effects of recombinant human insulin-like growth factor-1 (IGF-1) complexed with its principal binding protein, IGFBP-3, on skeletal muscle metabolism in severely burned children. Summary Background DataSevere burns are associated with a persistent hypermetabolic response characterized by hyperdynamic circulation and severe muscle catabolism and wasting. Previous studies showed that nutritional support and pharmacologic intervention with anabolic agents such as growth hormone and insulin abrogated muscle wasting and improved net protein synthesis in the severely burned. The use of these agents, however, has several adverse side effects. A new combination of IGF-1 and IGFBP-3 is now available for clinical study. MethodsTwenty-nine severely burned children were prospectively studied before and after treatment with 0.5, 1, 2, or 4 mg/kg/ day IGF-1/IGFBP-3 to determine net balance of protein across the leg, muscle protein fractional synthetic rates, and glucose metabolism. Another group was studied in a similar fashion without IGF-1/IGFBP-3 treatment as time controls. ResultsSeventeen of 29 children were catabolic before starting treatment. The infusion of 1.0 mg/kg/day IGF-1/IGFBP-3 increased serum IGF-1, which did not further increase with 2.0 and 4.0 mg/kg/day. IGF-1/IGFBP-3 treatment at 1 to 4 mg/ kg/day improved net protein balance and increased muscle protein fractional synthetic rates. This effect was more pronounced in catabolic children. IGF-1/IGFBP-3 did not affect glucose uptake across the leg or change substrate utilization. ConclusionsIGF-1/IGFBP-3 at doses of 1 to 4 mg/kg/day attenuates catabolism in catabolic burned children with negligible clinical side effects.Severe burns are associated with a persistent hypermetabolic response characterized by hyperdynamic circulation and increased circulating levels of catabolic hormones such as catecholamines, glucagon, and cortisol.

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In traffic accident, an accurate and timely severity prediction method is necessary for the successful deployment of an intelligent transportation system to provide corresponding levels of medical aid and transportation in a timely manner. The existing traffic accident's severity prediction methods mainly use shallow severity prediction models and statistical models. To promote the prediction accuracy, a novel traffic accident's severity prediction-convolutional neural network (TASP-CNN) model for traffic accident's severity prediction is proposed that considers combination relationships among traffic accident's features. Based on the weights of traffic accident's features, the feature matrix to gray image (FM2GI) algorithm is proposed to convert a single feature relationship of traffic accident's data into gray images containing combination relationships in parallel as the input variables for the model. Moreover, experiments demonstrated that the proposed model for traffic accident's severity prediction has a better performance.

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Being the necessary data of the city-scale seismic damage simulations, structural types of buildings of a city need to be collected. To this end, a prediction method of structural types of buildings based on machine learning (ML) is proposed herein. Specifically, using the training data of 230,683 buildings in Tangshan city, China, a supervised ML solution based on a decision forest model was designed for the prediction. The scale sensitivity and regional applicability of the designed solution are discussed, respectively, and the results show that the supervised ML solution can maintain high accuracy for different scales; however, it is only suitable for cities similar to the sample city. For wide applicability for various cities, a semi-supervised ML solution was designed based on sampling investigation and self-training procedures. The downtowns of Daxing and Tongzhou districts in Beijing were selected as a case study for the designed semi-supervised ML solution. The overall prediction accuracies of structural types for Daxing and Tongzhou downtowns can reach 94.8% and 99.5%, respectively, which are acceptable for seismic damage simulations. Based on the predicted results, the distributions of seismic damage in Daxing and Tongzhou downtown were output. This study provides a smart and efficient method for obtaining structural types for a city-scale seismic damage simulation.

Habitat directly affects the population size and geographical distribution of wildlife species, including the Mangshan pit viper (Protobothrops mangshanensis), a critically endangered snake species endemic to China. We searched for Mangshan pit viper using randomly arranged transects in their area of distribution and assessed their habitat association using plots, with the goals of gaining a better understanding of the habitat features associated with P. mangshanensis detection and determining if the association with these features varies across season. We conducted transect surveys, found 48 individual snakes, and measured 11 habitat variables seasonally in used and random plots in Hunan Mangshan National Nature Reserve over a period of 5 years (2012–2016). The important habitat variables for predicting Mangshan pit viper detection were fallen log density, shrub density, leaf litter cover, herb cover and distance to water. In spring, summer and autumn, Mangshan pit viper detection was always positively associated with fallen log density. In summer, Mangshan pit viper detection was related to such habitats with high canopy cover, high shrub density and high herb cover. In autumn, snakes generally occurred in habitats near water in areas with high fallen log density and tall shrubs height. Our study is the first to demonstrate the relationship between Mangshan pit viper detection and specific habitat components. Mangshan pit viper detection was associated with habitat features such as with a relatively high fallen log density and shrub density, moderately high leaf litter cover, sites near stream, and with lower herb cover. The pattern of the relationship between snakes and habitats was not consistent across the seasons. Identifying the habitat features associated with Mangshan pit viper detection can better inform the forestry department on managing natural reserves to meet the habitat requirements for this critically endangered snake species.