3-Pyridinylboronic Acid Ameliorates Rotenone-Induced Oxidative Stress Through Nrf2 Target Genes in Zebrafish Embryos

Neurochemical Research - Parkinson’s disease (PD) is one of the most common forms of neurodegenerative diseases and research on potential therapeutic agents for PD continues. Rotenone is a...     

Room temperature crystal structure of the fast switching M159T mutant of the fluorescent protein dronpa

The fluorescent protein Dronpa undergoes reversible photoswitching reactions between the bright “on” and dark “off” states via photoisomerization and proton transfer reactions. We report the room temperature crystal structure of the fast switching Met159Thr mutant of Dronpa at 2.0‐Å resolution in the bright on state. Structural differences with the wild type include shifted backbone positions of strand β8 containing Thr159 as well as an altered A‐C dimer interface involving strands β7, β8, β10, and β11. The Met159Thr mutation increases the cavity volume for the p‐hydroxybenzylidene‐imidazolinone chromophore as a result of both the side chain difference and the backbone positional differences. Proteins 2015; 83:397–402. © 2014 Wiley Periodicals, Inc.     

Experimental evidence for the effect of habitat loss on the dynamics of migratory networks

Migratory animals present a unique challenge for understanding the consequences of habitat loss on population dynamics because individuals are typically distributed over a series of interconnected breeding and non‐breeding sites (termed migratory network). Using replicated breeding and non‐breeding populations of Drosophila melanogaster and a mathematical model, we investigated three hypotheses to explain how habitat loss influenced the dynamics of populations in networks with different degrees of connectivity between breeding and non‐breeding seasons. We found that habitat loss increased the degree of connectivity in the network and influenced population size at sites that were not directly connected to the site where habitat loss occurred. However, connected networks only buffered global population declines at high levels of habitat loss. Our results demonstrate why knowledge of the patterns of connectivity across a species range is critical for predicting the effects of environmental change and provide empirical evidence for why connected migratory networks are commonly found in nature.     

Farnesol kinase is involved in farnesol metabolism, ABA signaling and flower development in Arabidopsis

Farnesol, which is toxic to plant cells at high concentrations, is sequentially phosphorylated to farnesyl phosphate and farnesyl diphosphate. However, the genes responsible for the sequential phosphorylation of farnesol have not been identified and the physiological role of farnesol phosphorylation has not been fully elucidated. To address these questions, we confirmed the presence of farnesol kinase activity in Arabidopsis (Arabidopsis thaliana) membranes and identified the corresponding gene (At5g58560, FOLK). Heterologous expression in recombinant yeast cells established farnesol as the preferred substrate of the FOLK-encoded kinase. Moreover, loss-of-function mutations in the FOLK gene abolished farnesol kinase activity, caused an abscisic acid-hypersensitive phenotype and promoted the development of supernumerary carpels under water-stress conditions. In wild-type plants, exogenous abscisic acid repressed FOLK gene expression. These observations demonstrate a role for farnesol kinase in negative regulation of abscisic acid signaling, and provide molecular evidence for a link between farnesol metabolism, abiotic stress signaling and flower development.     

Forecasting the future of biodiversity: a test of single‐ and multi‐species models for ants in North America

The geographic distributions of many taxonomic groups remain mostly unknown, hindering attempts to investigate the response of the majority of species on Earth to climate change using species distributions models (SDMs). Multi‐species models can incorporate data for rare or poorly‐sampled species, but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single‐species models to those from a multi‐species modeling approach, Generalized Dissimilarity Modeling (GDM). We found that both single‐ and multi‐species models forecasted large changes in ant community composition in relatively warm environments. GDM predicted higher turnover than SDMs and across a larger contiguous area, including the southern third of North America and notably Central America, where the proportion of ants with relatively small ranges is high and where data limitations are most likely to impede the application of SDMs. Differences between approaches were also influenced by assumptions regarding dispersal, with forecasts being more similar if no‐dispersal was assumed. When full‐dispersal was assumed, SDMs predicted higher turnover in southern Canada than did GDM. Taken together, our results suggest that 1) warm rather than cold regions potentially could experience the greatest changes in ant fauna under climate change and that 2) multi‐species models may represent an important complement to SDMs, particularly in analyses involving large numbers of rare or poorly‐sampled species. Comparisons of the ability of single‐ and multi‐species models to predict observed changes in community composition are needed in order to draw definitive conclusions regarding their application to investigating climate change impacts on biodiversity.     

Investigation of Design Space for Freeze-Drying: Use of Modeling for Primary Drying Segment of a Freeze-Drying Cycle

In this work, we explore the idea of using mathematical models to build design space for the primary drying portion of freeze-drying process. We start by defining design space for freeze-drying, followed by defining critical quality attributes and critical process parameters. Then using mathematical model, we build an insilico design space. Input parameters to the model (heat transfer coefficient and mass transfer resistance) were obtained from separate experimental runs. Two lyophilization runs are conducted to verify the model predictions. This confirmation of the model predictions with experimental results added to the confidence in the insilico design space. This simple step-by-step approach allowed us to minimize the number of experimental runs (preliminary runs to calculate heat transfer coefficient and mass transfer resistance plus two additional experimental runs to verify model predictions) required to define the design space. The established design space can then be used to understand the influence of critical process parameters on the critical quality attributes for all future cycles.