Defensin-Like ZmES4 Mediates Pollen Tube Burst in Maize via Opening of the Potassium Channel KZM1

Species-preferential osmotic pollen tube burst and sperm discharge in maize involve induced opening of the pollen tube-expressed potassium channel KZM1 by the egg apparatus-derived defensin-like protein ZmES4

Promotion of prostatic metastatic migration towards human bone marrow stoma by Omega 6 and its inhibition by Omega 3 PUFAs

Epidemiological studies have shown not only a relationship between the intake of dietary lipids and an increased risk of developing metastatic prostate cancer, but also the type of lipid intake that influences the risk of metastatic prostate cancer. The Omega-6 poly-unsaturated fatty acid, Arachidonic acid, has been shown to enhance the proliferation of malignant prostate epithelial cells and increase the risk of advanced prostate cancer. However, its role in potentiating the migration of cancer cells is unknown. Here we show that arachidonic acid at concentrations ⩽5 μM is a potent stimulator of malignant epithelial cellular invasion, which is able to restore invasion toward hydrocortisone-deprived adipocyte-free human bone marrow stroma completely. This observed invasion is mediated by the arachidonic acid metabolite prostaglandin E2 and is inhibited by the Omega-3 poly-unsaturated fatty acids eicosapentaenoic acid and docosahexaenoic acid at a ratio of 1 : 2 Omega-3 : Omega-6, and by the COX-2 inhibitor NS-398. These results identify a mechanism by which arachidonic acid may potentiate the risk of metastatic migration and secondary implantation in vivo, a risk which can be reduced with the uptake of Omega-3 poly-unsaturated fatty acids

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)

1. Climate change is a world‐wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high‐quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best‐practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re‐use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re‐use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second‐order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world

A taxonomic backbone for the global synthesis of species diversity in the angiosperm order Caryophyllales

The Caryophyllales constitute a major lineage of flowering plants with approximately 12500 species in 39 families. A taxonomic backbone at the genus level is provided that reflects the current state of knowledge and accepts 749 genera for the order. A detailed review of the literature of the past two decades shows that enormous progress has been made in understanding overall phylogenetic relationships in Caryophyllales. The process of re-circumscribing families in order to be monophyletic appears to be largely complete and has led to the recognition of eight new families (Anacampserotaceae, Kewaceae, Limeaceae, Lophiocarpaceae, Macarthuriaceae, Microteaceae, Montiaceae and Talinaceae), while the phylogenetic evaluation of generic concepts is still well underway. As a result of this, the number of genera has increased by more than ten percent in comparison to the last complete treatments in the Families and genera of vascular plants” series. A checklist with all currently accepted genus names in Caryophyllales, as well as nomenclatural references, type names and synonymy is presented. Notes indicate how extensively the respective genera have been studied in a phylogenetic context. The most diverse families at the generic level are Cactaceae and Aizoaceae, but 28 families comprise only one to six genera. This synopsis represents a first step towards the aim of creating a global synthesis of the species diversity in the angiosperm order Caryophyllales integrating the work of numerous specialists around the world

The fate of organic and inorganic nitrogen inputs in an old-growth forest of the central Oregon Cascade Range

Forests in the Pacific Northwest receive very little nitrogen through atmospheric deposition and thus studying the nitrogen cycle in this region can provide insights into how the unpolluted nitrogen cycle functions. I examined the fate of organic nitrogen versus inorganic nitrogen and the effect of tamlins on N retention by tracing N from ¹⁵N-labeled ammonium, organic nitrogen, tannincomplexed organic nitrogen, and the N₂-fixing lichen Lobaria oregana to in situ soil cores. The litter/organic horizon was the largest nitrogen retention pool for all forms of nitrogen added. Within the litter/organic horizon, the microbial biomass initially accounted for most of the added nitrogen. from the animonium additions. On a different time scale, microbial biomass also played a significant role in the retention of nitrogen from other N forms. I also studied mass loss and nitrogen dynamics during the decomposition of Lobaria oregana using ¹⁵N. Lichens placed in the field during the spring had a smaller decay constant (k=1.24 yr⁻¹) than the lichens placed in the field during the fall (k=3.1 yr⁻¹). The spring rate is similar to some labile leaf litters, but the fall rate is among the fastest decomposition rates measured for complex organic matter. Lichen from both seasons took up N from the surrounding environment during decay, while simultaneously losing N. In an additional project I ran several simple models to explore the effects that added N could have on carbon sequestration. If CO₂ emissions can not be reduced globally, other methods of sequestering carbon need to be explored. Because N is usually the most limiting nutrient in temperate terrestrial ecosystems, I hypothesized that adding N to land plants should cause the plants to grow bigger and therefore sequester more carbon. Various model runs showed that adding N, especially to the most N limited forests, could sequester large amounts of carbon. Although excess N in the environment has a variety of deleterious effects, the wise use of N₂-fixing plants and N fertilizer on the most N-limited sites, especially high C:N forests, would increase C sequestration, at least temporarily

Soil carbon in the South Atlantic United States: Land use change, forest management, and physiographic context

Evidence-based forest carbon (C) management requires identifying baseline patterns and drivers of soil organic carbon (SOC) stocks, and their responses to land use change and management, at scales relevant to landowners and resource professionals. The growth of datasets related to SOC, which is the largest terrestrial C pool, facilitates use of synthesis techniques to assess SOC stocks and changes at management-relevant scales. We report results from a synthesis using meta-analysis of published studies, as well as two large databases, in which we identify baseline patterns and drivers, quantify influences of land use change and forest management, and provide ecological context for distinct management regimes and their SOC impacts. We conducted this, the fourth in a series of ecoregional SOC assessments, for the South Atlantic States, which are disproportionately important to the national-scale forest C sink and forest products industry in the U.S. At the ecoregional level, baseline SOC stocks vary with climatic, topographic, and soil physical factors such as temperature and precipitation, slope gradient and aspect, and soil texture. Land use change and forest management modestly influence SOC stocks. Reforestation on previously cultivated lands increases SOC stocks, while deforestation for cultivation has the opposite effect; for continuously forested lands, harvesting is associated with SOC increases and prescribed fire with SOC declines. Effects of reforestation are large and positive for upper mineral soils (+30%) but not detectable in lower mineral soils. Negative effects of prescribed fire are due to significant C losses from organic horizons (-46%); fire and harvest have no impacts on upper mineral soils but both increase SOC in lower mineral soils (+8.2 and +46%, respectively, with high uncertainty in the latter). Inceptisols are generally more negatively impacted by prescribed fire or harvest than Ultisols, and covariance between inherent factors (including soil taxonomy) and management impacts indicates how interior vs. coastal physiographic sections differ in their management regimes and SOC trends. In the cooler, wetter, topographically rugged interior hardwood forests, which have larger baseline SOC stocks, prescribed fire and even light harvesting generally decrease SOC; in contrast, intensively managed coastal plain pine plantations begin with small initial SOC stocks, but exhibit rapid gains over even a single rotation. This covariance between place (physiography) and practice (management regime) suggests that distinct approaches to forest C management may be complementary to other ecological or production goals, when implemented as part of wider (e.g., state-level) forest C or climate policy

Land use change and forest management effects on soil carbon stocks in the Northeast U.S.

Abstract Background In most regions and ecosystems, soils are the largest terrestrial carbon pool. Their potential vulnerability to climate and land use change, management, and other drivers, along with soils’ ability to mitigate climate change through carbon sequestration, makes them important to carbon balance and management. To date, most studies of soil carbon management have been based at either large or site-specific scales, resulting in either broad generalizations or narrow conclusions, respectively. Advancing the science and practice of soil carbon management requires scientific progress at intermediate scales. Here, we conducted the fifth in a series of ecoregional assessments of the effects of land use change and forest management on soil carbon stocks, this time addressing the Northeast U.S. We used synthesis approaches including (1) meta-analysis of published literature, (2) soil survey and (3) national forest inventory databases to examine overall effects and underlying drivers of deforestation, reforestation, and forest harvesting on soil carbon stocks. The three complementary data sources allowed us to quantify direction, magnitude, and uncertainty in trends. Results Our meta-analysis findings revealed regionally consistent declines in soil carbon stocks due to deforestation, whether for agriculture or urban development. Conversely, reforestation led to significant increases in soil C stocks, with variation based on specific geographic factors. Forest harvesting showed no significant effect on soil carbon stocks, regardless of place-based or practice-specific factors. Observational soil survey and national forest inventory data generally supported meta-analytic harvest trends, and provided broader context by revealing the factors that act as baseline controls on soil carbon stocks in this ecoregion of carbon-dense soils. These factors include a range of soil physical, parent material, and topographic controls, with land use and climate factors also playing a role. Conclusions Forest harvesting has limited potential to alter forest soil C stocks in either direction, in contrast to the significant changes driven by land use shifts. These findings underscore the importance of understanding soil C changes at intermediate scales, and the need for an all-lands approach to managing soil carbon for climate change mitigation in the Northeast U.S