Genome-Wide identification and expression analysis of metal tolerance protein gene family in Medicago truncatula under a broad range of heavy metal stress

Metal tolerance proteins (MTPs) encompass plant membrane divalent cation transporters to specifically participate in heavy metal stress resistance and mineral acquisition. However, the molecular behaviors and biological functions of this family in Medicago truncatula are scarcely known. A total of 12 potential MTP candidate genes in the M. truncatula genome were successfully identified and analyzed for a phylogenetic relationship, chromosomal distributions, gene structures, docking analysis, gene ontology, and previous gene expression. M. truncatula MTPs (MtMTPs) were further classified into three major cation diffusion facilitator (CDFs) groups: Mn-CDFs, Zn-CDFs, and Fe/Zn-CDFs. The structural analysis of MtMTPs displayed high gene similarity within the same group where all of them have cation_efflux domain or ZT_dimer. Cis-acting element analysis suggested that various abiotic stresses and phytohormones could induce the most MtMTP gene transcripts. Among all MTPs, PF16916 is the specific domain, whereas GLY, ILE, LEU, MET, ALA, SER, THR, VAL, ASN, and PHE amino acids were predicted to be the binding residues in the ligand-binding site of all these proteins. RNA-seq and gene ontology analysis revealed the significant role of MTP genes in the growth and development of M. truncatula. MtMTP genes displayed differential responses in plant leaves, stems, and roots under five divalent heavy metals (Cd2+, Co2+, Mn2+, Zn2+, and Fe2+). Ten, seven, and nine MtMTPs responded to at least one metal ion treatment in the leaves, stems, and roots, respectively. Additionally, MtMTP1.1, MtMTP1.2, and MtMTP4 exhibited the highest expression responses in most heavy metal treatments. Our results presented a standpoint on the evolution of MTPs in M. truncatula. Overall, our study provides a novel insight into the evolution of the MTP gene family in M. truncatula and paves the way for additional functional characterization of this gene family

GAPDH controls extracellular vesicle biogenesis and enhances the therapeutic potential of EV mediated siRNA delivery to the brain.

Extracellular vesicles (EVs) are biological nanoparticles with important roles in intercellular communication, and potential as drug delivery vehicles. Here we demonstrate a role for the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in EV assembly and secretion. We observe high levels of GAPDH binding to the outer surface of EVs via a phosphatidylserine binding motif (G58), which promotes extensive EV clustering. Further studies in a Drosophila EV biogenesis model reveal that GAPDH is required for the normal generation of intraluminal vesicles in endosomal compartments, and promotes vesicle clustering. Fusion of the GAPDH-derived G58 peptide to dsRNA-binding motifs enables highly efficient loading of small interfering RNA (siRNA) onto the EV surface. Such vesicles efficiently deliver siRNA to multiple anatomical regions of the brain in a Huntington's disease mouse model after systemic injection, resulting in silencing of the huntingtin gene in different regions of the brain

Estimation of tail risk based on extreme expectiles

We use tail expectiles to estimate alternative measures to the Value at Risk (VaR) and Marginal Expected Shortfall (MES), two instruments of risk protection of utmost importance in actuarial science and statistical _nance. The concept of expectiles is a least squares analogue of quantiles. Both are M-quantiles as the minimizers of an asymmetric convex loss function, but expectiles are the only M-quantiles that are coherent risk measures. Moreover, expectiles de_ne the only coherent risk measure that is also elicitable. The estimation of expectiles has not, however, received any attention yet from the perspective of extreme values. Two estimation methods are proposed here, either making use of quantiles or relying directly on least asymmetrically weighted squares. A main tool is to _rst estimate large values of expectile-based VaR and MES located within the range of the data, and then to extrapolate the obtained estimates to the very far tails. We establish the limit distributions of both of the resulting intermediate and extreme estimators. We show via a detailed simulation study the good performance of the procedures, and present concrete applications to medical insurance data and three large US investment banks

Power plant maintenance scheduling using ant colony optimization: an improved formulation

Abstract It is common practice in the hydropower industry to either shorten the maintenance duration or to postpone maintenance tasks in a hydropower system when there is expected unserved energy based on current water storage levels and forecast storage inflows. It is therefore essential that a maintenance scheduling optimizer can incorporate the options of shortening the maintenance duration and/or deferring maintenance tasks in the search for practical maintenance schedules. In this article, an improved ant colony optimization-power plant maintenance scheduling optimization (ACO-PPMSO) formulation that considers such options in the optimization process is introduced. As a result, both the optimum commencement time and the optimum outage duration are determined for each of the maintenance tasks that need to be scheduled. In addition, a local search strategy is presented in this article to boost the robustness of the algorithm. When tested on a five-station hydropower system problem, the improved formulation is shown to be capable of allowing shortening of maintenance duration in the event of expected demand shortfalls. In addition, the new local search strategy is also shown to have significantly improved the optimization ability of the ACO-PPMSO algorithm

Antigenotoxic Studies of Different Substances to Reduce the DNA Damage Induced by Aflatoxin B1 and Ochratoxin A

Mycotoxins are produced mainly by the mycelial structure of filamentous fungi, or more specifically, molds. These secondary metabolites are synthesized during the end of the exponential growth phase and appear to have no biochemical significance in fungal growth and development. The contamination of foods and feeds with mycotoxins is a significant problem for the adverse effects on humans, animals, and crops that result in illnesses and economic losses. The toxic effect of the ingestion of mycotoxins in humans and animals depends on a number of factors including intake levels, duration of exposure, toxin species, mechanisms of action, metabolism, and defense mechanisms. In general, the consumption of contaminated food and feed with mycotoxin induces to neurotoxic, immunosuppressive, teratogenic, mutagenic, and carcinogenic effect in humans and/or animals. The most significant mycotoxins in terms of public health and agronomic perspective include the aflatoxins, ochratoxin A (OTA), trichothecenes, fumonisins, patulin, and the ergot alkaloids. Due to the detrimental effects of these mycotoxins, several strategies have been developed in order to reduce the risk of exposure. These include the degradation, destruction, inactivation or removal of mycotoxins through chemical, physical and biological methods. However, the results obtained with these methods have not been optimal, because they may change the organoleptic characteristics and nutritional values of food. Another alternative strategy to prevent or reduce the toxic effects of mycotoxins is by applying antimutagenic agents. These substances act according to several extra- or intracellular mechanisms, their main goal being to avoid the interaction of mycotoxins with DNA; as a consequence of their action, these agents would inhibit mutagenesis and carcinogenesis. This article reviews the main strategies used to control AFB1 and ochratoxin A and contains an analysis of some antigenotoxic substances that reduce the DNA damage caused by these mycotoxins

Cell‐penetrating peptides: Achievements and challenges in application for cancer treatment

One of the major hurdles to cure cancer lies in the low potency of currently available drugs, which could eventually be solved by using more potent therapeutic macromolecules, such as proteins or genes. However, although these macromolecules possess greater potency inside the cancer cells, the barely permeable cell membrane remains a formidable barrier to exert their efficacy. A widely used strategy is to use cell penetrating peptides (CPPs) to improve their intracellular uptake. Since the discovery of the first CPP, numerous CPPs have been derived from natural or synthesized products. Both in vitro and in vivo studies have demonstrated that those CPPs are highly efficient in transducing cargoes into almost all cell types. Therefore, to date, CPPs have been widely used for intracellular delivery of various cargoes, including peptides, proteins, genes, and even nanoparticles. In addition, recently, based on the successes of CPPs in cellular studies, their applications in vivo have been actively pursued. This review will focus on the advanced applications of CPP‐based in vivo delivery of therapeutics (e.g., small molecule drugs, proteins, and genes). In addition, we will highlight certain updated applications of CPPs for intracellular delivery of nanoparticulate drug carriers, as well as several “smart” strategies for tumor targeted delivery of CPP‐cargoes. © 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 102A: 575–587, 2014.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102051/1/jbma34859.pd