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 Melanesian α-thalassemia mutation suggests a novel mechanism for regulating gene expression

A Melanesian variant of the genetic disease α-thalassemia has recently been shown to be due to a single-nucleotide polymorphism located between the adult α-globin genes and their enhancers. The finding that this mutation creates a novel promoter provides support for a mechanism of gene regulation by facilitated chromatin looping.     

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.     

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.