Feature Selection from a Facial Image for Distinction of Sasang Constitution

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here

Genetic Effects of FTO and MC4R Polymorphisms on Body Mass in Constitutional Types

Sasang constitutional medicine (SCM), a Korean tailored medicine, categorizes human beings into four types through states of physiological imbalances and responsiveness to herbal medicine. One SCM type susceptible to obesity seems sensitive to energy intake due to an imbalance toward preserving energy. Common variants of fat mass and obesity associated (FTO) and melanocortin 4 receptor (MC4R) genes have been associated with increased body mass index (BMI) by affecting energy intake. Here, we statistically examined the association of FTO and MC4R polymorphisms with BMI in two populations with 1370 Koreans before and after SCM typing, and with the lowering of BMI in 538 individuals who underwent a 1-month lifestyle intervention. The increased BMI replicated the association with FTO haplotypes (effect size ≃ 1.1 kg/m2) and MC4R variants (effect size ≃ 0.64 kg/m2). After the lifestyle intervention, the carriers of the haplotype represented by the minor allele of rs1075440 had a tendency to lose more waist-to-hip ratio (0.76%) than non-carriers. The constitutional discrepancy for the accumulation of body mass by the effects of FTO and/or MC4R variants seemed to reflect the physique differences shown in each group of SCM constitutional types. In conclusion, FTO and MC4R polymorphisms appear to play an important role in weight gain, while only FTO variants play a role in weight loss after lifestyle intervention. Different trends were observed among individuals of SCM types, especially for weight gain. Therefore, classification of individuals based on physiological imbalance would offer a good genetic stratification system in assessing the effects of obesity genes

Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful technique which has gained increasing attention over the last two decades. The GC × GC-MS provides much increased separation capacity, chemical selectivity and sensitivity for complex sample analysis and brings more accurate information about compound retention times and mass spectra. Despite these advantages, the retention times of the resolved peaks on the two-dimensional gas chromatographic columns are always shifted due to experimental variations, introducing difficulty in the data processing for metabolomics analysis. Therefore, the retention time variation must be adjusted in order to compare multiple metabolic profiles obtained from different conditions.</p> <p>Results</p> <p>We developed novel peak alignment algorithms for both homogeneous (acquired under the identical experimental conditions) and heterogeneous (acquired under the different experimental conditions) GC × GC-MS data using modified Smith-Waterman local alignment algorithms along with mass spectral similarity. Compared with literature reported algorithms, the proposed algorithms eliminated the detection of landmark peaks and the usage of retention time transformation. Furthermore, an automated peak alignment software package was established by implementing a likelihood function for optimal peak alignment.</p> <p>Conclusions</p> <p>The proposed Smith-Waterman local alignment-based algorithms are capable of aligning both the homogeneous and heterogeneous data of multiple GC × GC-MS experiments without the transformation of retention times and the selection of landmark peaks. An optimal version of the SW-based algorithms was also established based on the associated likelihood function for the automatic peak alignment. The proposed alignment algorithms outperform the literature reported alignment method by analyzing the experiment data of a mixture of compound standards and a metabolite extract of mouse plasma with spiked-in compound standards.</p