Tao Jiang

This essay seeks to rectify the lack of scholarly attention on the connection between Mohist and fajia thoughts, using Shang Yang and Han Fei as fajia representatives. I argue that the Mohists championed the ideal of universal justice in their teachings of impartial care (jian ai 兼愛) and objective standards (fa 法) and that the fajia thinkers appropriated the impartialist element in the Mohist ideal of universal justice by adopting the idea of objective standards in their design of an impartialist and impersonal state bureaucracy. I characterize Mohism as a form of universal state consequentialism that promotes a statist approach to maximize wealth, order, and population. In this connection, it is useful to view the fajia project as a way to operationalize the Mohist project, attempting to work out in granular details how to institute the Mohist principle of impartiality through state bureaucracy and enforcement of a uniform standard, i.e., legal and administrative codes. The mHan Fei, jian ai (impartial erit and the failing of the fajia project is briefly discussed at the end of the chapter.

© 2015 Macmillan Publishers Limited All rights reserved. Genome-wide gene expression measurements have enabled comprehensive studies that integrate the changes of gene expression and phenotypic information to uncover their novel associations. Here we reported the association analysis between psychophysical phenotypes and genome-wide gene expression changes in human adaptation to one of the most extreme climates on Earth, the Antarctic Dome Argus. Dome A is the highest ice feature in Antarctica, and may be the coldest, driest and windiest location on earth. It is considered unapproachable due to its hostile environment. In 2007, a Chinese team of 17 male explorers made the expedition to Dome A for scientific investigation. Overall, 133 psychophysical phenotypes were recorded, and genome-wide gene expression profiles from the blood samples of the explorers were measured before their departure and upon their arrival at Dome A. We found that mood disturbances, including tension, depression, anger and fatigue, had a strong, positive, linear relationship with the level of a male sex hormone, testosterone, using the Pearson correlation coefficient analysis. We also demonstrated that significantly lowest-level Gene Ontology groups in changes of gene expression in blood cells with erythrocyte removal were consistent with the adaptation of the psychophysical characteristics. Interestingly, we discovered a list of genes that were strongly related to significant phenotypes using phenotype and gene expression PCC analysis. Importantly, among the 70 genes that were identified, most were significantly related to mood disturbances, where 42 genes have been reported in the literature mining, suggesting that the other 28 genes were likely novel genes involved in the mood disturbance mechanism. Taken together, our association analysis provides a reliable method to uncover novel genes and mechanisms related to phenotypes, although further studies are needed.

© 2014 The Author. Motivation: Although many gene set analysis methods have been proposed to explore associations between a phenotype and a group of genes sharing common biological functions or involved in the same biological process, the underlying biological mechanisms of identified gene sets are typically unexplained. Results: We propose a method called Differential Regulation-based enrichment Analysis for GENe sets to identify gene sets in which a significant proportion of genes have their transcriptional regulatory patterns changed in a perturbed phenotype. We conduct comprehensive simulation studies to demonstrate the capability of our method in identifying differentially regulated gene sets. We further apply our method to three human microarray expression datasets, two with hormone treated and control samples and one concerning different cell cycle phases. Results indicate that the capability of DRAGEN in identifying phenotype-associated gene sets is significantly superior to those of four existing methods for analyzing differentially expressed gene sets.We conclude that the proposed differential regulation enrichment analysis method, though exploratory in nature, complements the existing gene set analysis methods and provides a promising new direction for the interpretation of gene expression data.