Comparative Analysis of Endogenous Hormones and Metabolite Profiles in Early-Spring Flowering Plants and Unflowered Plants Revealing the Strategy of Blossom

Journal of Plant Growth Regulation - Early-spring plants are a special type of plant that complete their life cycle promptly in cold, early spring. Very little effort has been made into researching...     

Pollen size-number trade-off and pollen-pistil relationships in Pedicularis (Orobanchaceae)

Current patterns of floral design in Pedicularis must have undergone an evolutionary process of interacting among components of floral traits, and then formed internal relationships among these traits. To detect such correlations, which may provide insight to understand flower evolution, 40 Pedicularis species representing all corolla types of the genus were studied. Results show that, interspecifically, pollen size correlates negatively with pollen number, but positively with pistil length. This suggests that plants evolve an optimal pollen size, which balances the advantages of large pollen size for gametophytic competition against the fecundity disadvantages of fewer pollen grains. In contrast to sex allocation theory, this study does not find a trade-off, but an interspecific positive correlation between pollen and ovule number. This is consistent with the hypothesis that genetic variation for resource acquisition may in part be responsible for the lack of negative correlation between male and female function.This work was supported by the State Key Basic Research and Development Plan, China (Grant No. G2000046804) to YHG. The authors would like to thank Peter K. Endress and two anonymous reviewers for providing critical comments and helpful suggestions, Qing-Feng Wang, Jing-Yuan Wang and Jin-Ming Chen for their helpful suggestions. Shi-Guo Sun, Jing Xia, and Qian Yu are thanked for their assistance in both the field work and laboratory phases of the project.     

Extracellular vesicles in bone and tooth: A state-of-art paradigm in skeletal regeneration

Bone and tooth, fundamental parts of the craniofacial skeleton, are anatomically and developmentally interconnected structures. Notably, pathological processes in these tissues underwent together and progressed in multilevels. Extracellular vesicles (EVs) are cell-released small organelles and transfer proteins and genetic information into cells and tissues. Although EVs have been identified in bone and tooth, particularly EVs have been identified in the bone formation and resorption, the concrete roles of EVs in bone and tooth development and diseases remain elusive. As such, we review the recent progress of EVs in bone and tooth to highlight the novel findings of EVs in cellular communication, tissue homeostasis, and interventions. This will enhance our comprehension on the skeletal biology and shed new light on the modulation of skeletal disorders and the potential of genetic treatment.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Synthesis of a novel class of glycocluster with a cyclic α-(1→6)-octaglucoside as a scaffold and their binding abilities to concanavalin A

The synthesis of small glycoclusters with high affinity toward lectins is one of the important subjects in glycotechnology. Although cyclic α-(1→6)-d-octaglucoside (CI8) is an attractive scaffold on which to put glycosyl pendants, the compound has only secondary hydroxyl groups, which are relatively unreactive for substitution reactions. The oxidation of the vicinal diols of CI8 and reductive amination of the resultant dialdehydes with 2-aminoethyl mannoside gave mannose-CI8 conjugates with a variety of average mannose incorporation numbers (2-7). The average numbers were deduced from MALDI-TOF mass and ¹H NMR spectroscopy. The binding ability of mannose-CI8 conjugates to concanavalin A increased with the increasing numbers of average mannose incorporation, reaching a plateau at tetravalence, as estimated from a latex bead-based agglutination lectin assay. Toxicity tests demonstrated the biocompatibility of mannose-CI8 conjugates.     

Genetic diversity and population structure of Swertia tetraptera (Gentianaceae), an endemic species of Qinghai-Tibetan Plateau

Swertia tetraptera Maxim is an annual alpine herb endemic to the Qinghai-Tibetan Plateau (QTP). Its populations are locally scattered as isolated patches throughout this region. Genetic variation within and among thirty-four populations of this species was assessed using ISSR fingerprinting with 10 primers. High levels of genetic diversity exist within species (P = 98.9%, I = 0.3475; He = 0.2227), while the within-population diversity is low (P = 32.7%, I = 0.177; He = 0.12). High levels of genetic differentiation were detected among populations based on various statistics, including Nei’s genetic diversity analysis (G_ST = 0.4608), Bayesian analysis (θ^B = 0.476) and AMOVA (F_ST = 0.57). That is, populations shared low levels of genetic identity (I = 0.2622–0.0966). This genetic structure was probably due to severe genetic drift, breeding system and limited gene flow. The observed genetic structure of the populations implies that different populations across the distribution range of the species should be sampled to maintain high genetic diversity when a conservation strategy is implemented.     

Analysis of a common inheritable idiotype in IgA-deficient sera using monoclonal antibodies

In these studies we describe the production of three mAb raised to an idiotype on an IgG anticasein antibody isolated from the serum of one IgA-deficient blood donor. These are IgM kappa and block the binding of casein Ag to anticasein antibody. Sera of unrelated IgA-deficient donors were tested for the presence of the idiotype; 15 of 56 IgA-deficient sera (25%) contain the anticasein idiotype, whereas 1 of 45 normal sera was positive. Anticasein antibodies as a whole were predominantly of the IgG1 and IgG3 subclass; idiotype-positive anticaseins are predominantly of the IgG1 subclass. For IgA-deficient donors, the relative amount of idiotype-positive anticasein antibody was correlated with the level of anticasein present in the serum. Studies were done to investigate the potential inheritance of the idiotype in families; in three of four families the idiotype was inherited in an apparent autosomal dominant pattern. Our data show that a common cross-reactive idiotype can be detected in the sera of IgA-deficient individuals and their family members. This suggests that V region markers may be conserved in this humoral immunodeficiency disease.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.