Sexual characteristics of male guppies Poecilia reticulata serve as effect biomarkers of estrogens

Guppies( Poecilia reticulata) are considered a candidate model species for the identification and testing of endocrine-disrupting chemicals. Male guppies may be used to address the challenge of making potential linkages between alterations of biomarkers, both at the cellular and organ level, and adverse outcomes. In the present study, a predictive relationship between sex characteristics and reproductive output was observed in male guppies that underwent a long-term toxicity test with 0.5 μg/L 17 β-estradiol administered during the juvenile period. Radioimmunoassay and western blot analyses demonstrated that 17 β-estradiol exposure caused a significant increase in testicular 17 β-estradiol levels as well as the induction of exposure biomarkers, namely hepatic vitellogenin. Exposure to 17 β-estradiol also caused a significant decrease in testosterone levels, which consequently reduced the gonadosomatic index, sperm counts, and the coloration index. These changes of male sexual characteristics further translated into adverse influences on reproduction, as measured by a decrease in offspring production and survival rate. Our results suggest that the above-mentioned sexual characteristics of male guppies may be considered potential in vivo biomarkers of estrogen effects on reproduction.

A quick and effective multivariate statistical strategy for imaging mass spectrometry

A new multivariate statistical strategy for analyzing large datasets that are produced by imaging mass spectrometry（IMS） techniques is reported.The strategy divides the whole datacube of the sample into several subsets and analyses them one by one to obtain the results.Instead of analyzing the whole datacube at one time,the strategy makes the analysis easier and decreases the computation time greatly.In this report,the IMS data are produced by the air flow-assisted ionization IMS（AFAI-IMS）.The strategy can be used in combination with most multivariate statistical analysis methods.In this paper,the strategy was combined with the principal component analysis（PCA） and partial least square analysis（PLS）.It was proven to be effective by analyzing the handwriting sample.By using the strategy,the m/z corresponding to the specific lipids in rat brain tissue were distinguished successfully.Moreover the analysis time grew linearly instead of exponentially as the size of sample increased.The strategy developed in this study has enormous potential for searching for the mjz of potential biomarkers quickly and effectively.

Chinmedomics:Newer Theory and Application

The scientific interpretation of the effectiveness of traditional Chinese medicine（TCM） is a communication channel between Chinese medicine and modern medicine. The evaluation of TCM efficacy is an important prerequisite for discovering active constituents. Therefore, there is an urgent need to establish a biological language for scientific explanation of the effectiveness of TCM, and modern scientists can further accept the significant value of TCM theory and its clinical practice. The syndrome and corresponding formulation are two important parts in TCM, and they are directly related to the effectiveness of TCM. Our team has taken syndrome and formulation as the research objects, integrated serum pharm-chemistry of TCM with metabolomics technology, developed a new platform termed Chinmedomics, which is capable of evaluating effectiveness of TCM and discovering the syndrome biomarkers as well as the effective substances. The correlation between the endogenous biomarkers of syndrome and exogenous constituents of formulation is analyzed to find the highly associated compounds as the effective substances, and further clarifying their activities, and may discover lead compounds. This effective strategy could speed the drug discovery from natural resources. This article systematically introduced the establishment and application of Chinmedomics theory, in order to provide references for studies on TCM, and some characteristic examples are presented to highlight the application of this new strategy for discovering the potential active constituents of TCM.