Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia.

The purpose of the present study was to identify a plasma protein biomarker able to predict pre-eclampsia (PE). Comprehensive quantitative proteomics using mass spectrometry with sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) was applied to plasma samples of 7 PE and 14 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE), and 11 proteins were selected as candidates potentially able to differentiate the two groups. Plasmas collected at gestational weeks 14-24 from 36 PE and 120 healthy pregnant women (for PE subjects, plasma samples were taken before onset of PE) were used to conduct selected reaction monitoring quantification analysis, optimize protein combinations and conduct internal validation, which consisted of 30 iterations of 10-fold cross-validation using multivariate logistic regression and receiver operating characteristic (ROC) analysis. The combination of afamin, fibronectin, and sex-hormone-binding globulin was selected as the best candidate. The 3-protein combination predictive model (predictive equation and cut-off value) generated using the internal validation subjects was successfully validated in another group of validation subjects (36 PE and 54 healthy (for PE subjects, plasma samples were taken before onset of PE)) and showed good predictive performance, with the area under the curve (AUC) 0.835 and odds ratio 13.43. In conclusion, we newly identified a 3-protein combination biomarker and established a predictive equation and cut-off value that can predict the onset of PE based on analysis of plasma samples collected during gestational weeks 14-24.

The experimental humanoid robot H7: a research platform for autonomous behaviour.

This paper gives an overview of the humanoid robot 'H7', which was developed over several years as an experimental platform for walking, autonomous behaviour and human interaction research at the University of Tokyo. H7 was designed to be a human-sized robot capable of operating autonomously in indoor environments designed for humans. The hardware is relatively simple to operate and conduct research on, particularly with respect to the hierarchical design of its control architecture. We describe the overall design goals and methodology, along with a summary of its online walking capabilities, autonomous vision-based behaviours and automatic motion planning. We show experimental results obtained by implementations running within a simulation environment as well as on the actual robot hardware.