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Rising global food demand necessitates improved crop yields. Biostimulants offer a potential solution to meet these demands. Among them, antioxidants have shown potential to improve yield, nutritional quality, and resilience to climate change. However, large-scale production of many antioxidants is challenging. Here, we investigate Coenzyme M (CoM), a small, achiral antioxidant from archaea, as a potential biostimulant, investigating its effects on growth and physiology. CoM significantly increased shoot mass and root length of the model plant, Arabidopsis thaliana, in a concentration-dependent manner. Sulfur-containing CoM supplementation restored growth under sulfur-limited conditions in Arabidopsis, whereas similar recovery was not observed for other macronutrient deficiencies, consistent with it being metabolized. In tobacco, CoM increased photosynthetic light capture capacity, consistent with observed growth improvements. Interestingly, this effect was independent of carbon capture rates. Furthermore, CoM promoted early-stage shoot growth in various crops species, including tobacco, basil, cannabis, and soybean. Our results suggest CoM is a promising, scalable biostimulant with potential to modify photosynthesis and enhance crop productivity. 

Abstract Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod datasets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple datasets, indicating that there is no “one size fits all” when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa. 

Abstract Poor fit between models of sequence or trait evolution and empirical data is known to cause biases and lead to spurious conclusions about evolutionary patterns and processes. Bayesian posterior prediction is a flexible and intuitive approach for detecting such cases of poor fit. However, the expected behavior of posterior predictive tests has never been characterized for evolutionary models, which is critical for their proper interpretation. Here, we show that the expected distribution of posterior predictive P-values is generally not uniform, in contrast to frequentist P-values used for hypothesis testing, and extreme posterior predictive P-values often provide more evidence of poor fit than typically appreciated. Posterior prediction assesses model adequacy under highly favorable circumstances, because the model is fitted to the data, which leads to expected distributions that are often concentrated around intermediate values. Nonuniform expected distributions of P-values do not pose a problem for the application of these tests, however, and posterior predictive P-values can be interpreted as the posterior probability that the fitted model would predict a dataset with a test statistic value as extreme as the value calculated from the observed data. 

Humans possess an innate ability to incorporate tools into our body schema to perform a myriad of tasks not possible with our natural limbs. Human-in-the-loop telerobotic systems (HiLTS) are tools that extend human manipulation capabilities to remote and virtual environments. Unlike most hand-held tools, however, HiLTS often possess complex electromechanical architectures that introduce non-trivial transmission dynamics between the robot’s leader and follower, which alter or obfuscate the environment’s dynamics. While considerable research has focused on negating or circumventing these dynamics, it is not well understood how capable human operators are at incorporating these transmission dynamics into their sensorimotor control scheme. To begin answering this question, we recruited N=12 participants to use a novel reconfigurable teleoperator with varying transmission dynamics to perform a visuo-haptic tracking task. Contrary to our original hypothesis, our findings demonstrate that humans can account for substantial differences in teleoperator transmission dynamics and produce the compensatory strategies necessary to adequately control the teleoperator. These findings suggest that advances in transparency algorithms and haptic feedback approaches must be coupled with control designs that leverage the unique capabilities of the human operator in the loop. 

The temporal dynamics of morphogen presentation impacts transcriptional responses and tissue patterning (1). However, the mechanisms controlling morphogen release are far from clear. We found that inwardly rectifying potassium (Irk) channels regulate endogenous transient increases in intracellular calcium and Bone Morphogenetic Protein (BMP/Dpp) release for Drosophila wing development (2). Inhibition of Irk channels reduces BMP/Dpp signaling, and ultimately disrupts wing morphology (2, 3). Ion channels impact development of several tissues and organisms in which BMP signaling is essential (2-15). In neurons and pancreatic beta cells, Irk channels modulate membrane potential to affect intracellular Ca++ to control secretion of neurotransmitters and insulin (15-21). Based on Irk activity in neurons, we hypothesized that electrical activity controls endoplasmic reticulum Ca++ release into the cytoplasm to regulate the release of BMP. To test this hypothesis, we reduced expression of proteins that control endoplasmic reticulum calcium (Stim, Orai, SERCA, SK, and Best2) and documented wing phenotypes. We found that reduced Stim and SERCA function decreases amplitude and frequency of endogenous calcium transients in the wing disc and reduced Dpp/BMP release in the wing disc. Together, our results suggest control of endoplasmic reticulum is required for Dpp/BMP release. 

Haptic illusions provide unique insights into how we model our bodies separate from our environment. Popular illusions like the rubber-hand illusion and mirror-box illusion have demonstrated that we can adapt the internal representations of our limbs in response to visuo-haptic conflicts. In this manuscript, we extend this knowledge by investigating to what extent, if any, we also augment our external representations of the environment and its action on our bodies in response to visuo-haptic conflicts. Utilizing a mirror and a robotic brushstroking platform, we create a novel illusory paradigm that presents a visuo-haptic conflict using congruent and incongruent tactile stimuli applied to participants' fingers. Overall, we observed that participants perceived an illusory tactile sensation on their visually occluded finger when seeing a visual stimulus that was inconsistent with the actual tactile stimulus provided. We also found residual effects of the illusion after the conflict was removed. These findings highlight how our need to maintain a coherent internal representation of our body extends to our model of our environment. 

Abstract The scale of data sets used to infer phylogenies has grown dramatically in the last decades, providing researchers with an enormous amount of information with which to draw inferences about evolutionary history. However, standard approaches to assessing confidence in those inferences (e.g., nonparametric bootstrap proportions [BP] and Bayesian posterior probabilities [PPs]) are still deeply influenced by statistical procedures and frameworks that were developed when information was much more limited. These approaches largely quantify uncertainty caused by limited amounts of data, which is often vanishingly small with modern, genome-scale sequence data sets. As a consequence, today’s phylogenomic studies routinely report near-complete confidence in their inferences, even when different studies reach strongly conflicting conclusions and the sites and loci in a single data set contain much more heterogeneity than our methods assume or can accommodate. Therefore, we argue that BPs and marginal PPs of bipartitions have outlived their utility as the primary means of measuring phylogenetic support for modern phylogenomic data sets with large numbers of sites relative to the number of taxa. Continuing to rely on these measures will hinder progress towards understanding remaining sources of uncertainty in the most challenging portions of the Tree of Life. Instead, we encourage researchers to examine the ideas and methods presented in this special issue of Systematic Biology and to explore the area further in their own work. The papers in this special issue outline strategies for assessing confidence and uncertainty in phylogenomic data sets that move beyond stochastic error due to limited data and offer promise for more productive dialogue about the challenges that we face in reaching our shared goal of understanding the history of life on Earth.[Big data; gene tree variation; genomic era; statistical bias.] 

Abstract Plant growth and resilience require balancing an inherently oxidative metabolism with powerful antioxidant systems that help maintain homeostasis. When the environment changes, reactive oxygen species are potent indicators of that change, allowing adaptation through re-balancing metabolism and antioxidant systems. A large body of evidence supports the use of exogenously applied antioxidants to improve both plant growth and their resilience to stress. Notably, some phenotypic effects are similar upon the application of chemically diverse antioxidants, while others are distinct. In this review, we analyze research from antioxidant treatment experiments and highlight the similarities in their practical applications and their effects on plant stress tolerance, photosynthesis, native antioxidant systems, and phytohormones. We also briefly cover the specific effects of individually applied antioxidants and what is known about their potential modes of action. Given the strong potential of antioxidant applications, we discuss research needed to promote their agricultural use. Finally, we identify outstanding questions about how the exogenous application of antioxidants mechanistically affects plant growth.