Classification of Chinese herbs based on the cluster analysis of delayed luminescence

Traditional Chinese material medica are an important component of the Chinese pharmacopeia. According to the traditional Chinese medicinal concept, Chinese herbal medicines are classified into different categories based on their therapeutic effects, however, the bioactive principles cannot be solely explained by chemical analysis. The aim of this study is to classify different Chinese herbs based on their therapeutic effects by using delayed luminescence (DL). The DL of 56 Chinese herbs was measured using an ultra‐sensitive luminescence detection system. The different DL parameters were used to classify Chinese herbs according to a hierarchical cluster analysis. The samples were divided into two groups based on their DL kinetic parameters. Interestingly, the DL classification results were quite consistent with classification according to the Chinese medicinal concepts of ‘cold’ and ‘heat’ properties. In this paper, we show for the first time that by using DL technology, it is possible to classify Chinese herbs according to the Chinese medicinal concept and it may even be possible to predict their therapeutic properties. Copyright © 2015 John Wiley & Sons, Ltd.     

Green synthesis of fluorescence carbon nanoparticles from yum and application in sensitive and selective detection of ATP

Fluorescent carbon nanoparticles (CPs), a fascinating class of recently discovered nanocarbons, have been widely known as some of the most promising sensing probes in biological or chemical analysis. In this study, we demonstrate a green synthetic methodology for generating water‐soluble CPs with a quantum yield of approximately 24% via a simple heating process using yum mucilage as a carbon source. The prepared carbon nanoparticles with an ~10 nm size possessed excellent fluorescence properties, and the fluorescence of the CPs was strongly quenched by Fe³⁺, and recovered by adenosine triphosphate (ATP), thus, an ‘off’ and ‘on’ system can be easily established. This ‘CPs‐Fe³⁺‐ATP’ strategy was sensitive and selective at detecting ATP with the linear range of 0.5 µmol L^?1 to 50 µmol L^?1 and with a detection limit of 0.48 µmol L^?1. Copyright © 2015 John Wiley & Sons, Ltd.     

Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies

False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days.     

LncRNA NONRATT021972 involved the pathophysiologic processes mediated by P2X<Subscript>7</Subscript> receptors in stellate ganglia after myocardial ischemic injury

Adenosine triphosphate (ATP) acts on P2X receptors to initiate signal transmission. P2X₇ receptors play a role in the pathophysiological process of myocardial ischemic injury. Long noncoding RNAs (lncRNAs) participate in numerous biological functions independent of protein translation. LncRNAs are implicated in nervous system diseases. This study investigated the effects of NONRATT021972 small interference RNA (siRNA) on the pathophysiologic processes mediated by P2X₇ receptors in stellate ganglia (SG) after myocardial ischemic injury. Our results demonstrated that the expression of NONRATT021972 in SG was significantly higher in the myocardial ischemic (MI) group than in the control group. Treatment of MI rats with NONRATT021972 siRNA, the P2X₇ antagonist brilliant blue G (BBG), or P2X₇ siRNA improved the histology of injured ischemic cardiac tissues and decreased the elevated concentrations of serum myocardial enzymes, creatine kinase (CK), CK isoform MB (CK-MB), lactate dehydrogenase (LDH) and aspartate aminotransferase (AST) compared to the MI rats. NONRATT021972 siRNA, BBG, or P2X₇ siRNA treatment in MI rats decreased the expression levels of P2X₇ immunoreactivity, P2X₇ messenger RNA (mRNA), and P2X₇ protein, interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and phosphorylated p38 mitogen-activated protein kinase (p38 MAPK) in the SG compared to MI rats. NONRATT021972 siRNA treatment prevented the pathophysiologic processes mediated by P2X₇ receptors in the SG after myocardial ischemic injury.     

Feeding Kinematics and Nectar Intake of the Honey Bee Tongue

Most flower-visiting insects employ highly-evolved organs to feed themselves rapidly and efficiently on the floral nectar. A honey bee drives its segmented tongue (glossa) covered by dense hairs reciprocatingly to load nectar. A high-speed camera system ameliorated by a microscope revealed morphological changes in glossal surfaces during live honey bees’ nectar dipping and surface configurations through the stretching of postmortem honey bees’ glossae. Both the in vivo and postmortem observations reveal that shortening and lengthening of the glossal segments perform high concordance with the erection of glossal hairs, which aids in developing deformable gaps between rows of glossal hairs during nectar trapping. A model was proposed to evaluate the nectar-intake volume considering the experimentally-measured average erection angle and tongue elongation length during nectar feeding. The theoretical results fit the experimental data well and disclose that these two factors contribute to an augmentation of nectar-intake observably. We also theoretically present that the extendible and deformable glossae have advantages for the polylectic feeding behavior.