Redox Active Motifs in Selenoproteins

Selenoproteins use the rare amino acid selenocysteine (Sec) to act as the first line of defense against oxidants, which are linked to aging, cancer, and neurodegenerative diseases. Many selenoproteins are oxidoreductases in which the reactive Sec is connected to a neighboring Cys and able to form a ring. These Sec-containing redox motifs govern much of the reactivity of selenoproteins. To study their fundamental properties, we have used Se-77 NMR spectroscopy in concert with theoretical calculations to determine the conformational preferences and mobility of representative motifs. This use of Se-77 as a probe enables the direct recording of the properties of Sec as its environment is systematically changed. We find that all motifs have several ring conformations in their oxidized state. These ring structures are most likely stabilized by weak, nonbonding interactions between the selenium and the amide carbon. To examine how the presence of selenium and ring geometric strain governs the motifs\u27 reactivity, we measured the redox potentials of Sec-containing motifs and their corresponding Cys-only variants. The comparisons reveal that for C-terminal motifs the redox potentials increased between 20-25 mV when the selenenylsulfide bond was changed to a disulfide bond. Changes of similar magnitude arose when we varied ring size or the motifs\u27 flanking residues. This suggests that the presence of Sec is not tied to unusually low redox potentials. The unique roles of selenoproteins in human health and their chemical reactivities may therefore not necessarily be explained by lower redox potentials, as has often been claimed

Norms of Presentational Force

This is the author's accepted manuscript, made available with permission of the American Forensic Association.Can style or presentational devices reasonably compel us to believe, agree, act? I submit that they can, and that the normative pragmatic project explains how. After describing a normative pragmatic approach to presentational force, I analyze and evaluate presentational force in Susan B. Anthony's "Is it a Crime for a U. S. Citizen to Vote" as it apparently proceeds from logic, emotion, and style. I conclude with reflections on the compatibility of the normative pragmatic approach with the recently-developed pragma-dialectical treatment of presentational devices

Factors influencing terrestriality in primates of the Americas and Madagascar

Among mammals, the order Primates is exceptional in having a high taxonomic richness in which the taxa are arboreal, semiterrestrial, or terrestrial. Although habitual terrestriality is pervasive among the apes and African and Asian monkeys (catarrhines), it is largely absent among monkeys of the Americas (platyrrhines), as well as galagos, lemurs, and lorises (strepsirrhines), which are mostly arboreal. Numerous ecological drivers and species-specific factors are suggested to set the conditions for an evolutionary shift from arboreality to terrestriality, and current environmental conditions may provide analogous scenarios to those transitional periods. Therefore, we investigated predominantly arboreal, diurnal primate genera from the Americas and Madagascar that lack fully terrestrial taxa, to determine whether ecological drivers (habitat canopy cover, predation risk, maximum temperature, precipitation, primate species richness, human population density, and distance to roads) or species-specific traits (bodymass, group size, and degree of frugivory) associate with increased terrestriality. We collated 150,961 observation hours across 2,227 months from 47 species at 20 sites in Madagascar and 48 sites in the Americas. Multiple factors were associated with ground use in these otherwise arboreal species, including increased temperature, a decrease in canopy cover, a dietary shift away from frugivory, and larger group size. These factors mostly explain intraspecific differences in terrestriality. As humanity modifies habitats and causes climate change, our results suggest that species already inhabiting hot, sparsely canopied sites, and exhibiting more generalized diets, are more likely to shift toward greater ground use

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe