HvALMT1 from barley is involved in the transport of organic anions

Members of the ALMT gene family contribute to the Al3+ resistance of several plant species by facilitating malate efflux from root cells. The first member of this family to be cloned and characterized, TaALMT1, is responsible for most of the natural variation of Al3+ resistance in wheat. The current study describes the isolation and characterization of HvALMT1, the barley gene with the greatest sequence similarity to TaALMT1. HvALMT1 is located on chromosome 2H which has not been associated with Al3+ resistance in barley. The relatively low levels of HvALMT1 expression detected in root and shoot tissues were independent of external aluminium or phosphorus supply. Transgenic barley plants transformed with the HvALMT1 promoter fused to the green fluorescent protein (GFP) indicated that expression of HvALMT1 was relatively high in stomatal guard cells and in root tissues containing expanding cells. GFP fused to the C-terminus of the full HvALMT1 protein localized to the plasma membrane and motile vesicles within the cytoplasm. HvALMT1 conferred both inward and outward currents when expressed in Xenopus laevis oocytes that were bathed in a range of anions including malate. Both malate uptake and efflux were confirmed in oocyte assays using [14C]malate as a radiotracer. It is suggested that HvALMT1 functions as an anion channel to facilitate organic anion transport in stomatal function and expanding cells

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Pandemic Influenza A H1N1 2009 Infection versus Vaccination: A Cohort Study Comparing Immune Responses in Pregnancy

Background: With the emergence of H1N1 pandemic (pH1N1) influenza, the CDC recommended that pregnant women be one of five initial target groups to receive the 2009 monovalent H1N1 vaccine, regardless of prior infection with this influenza strain. We sought to compare the immune response of pregnant women to H1N1 infection versus vaccination and to determine the extent of passive immunity conferred to the newborn. Methods/Findings: During the 2009-2010 influenza season, we enrolled a cohort of women who either had confirmed pH1N1 infection during pregnancy, did not have pH1N1 during pregnancy but were vaccinated against pH1N1, or did not have illness or vaccination. Maternal and umbilical cord venous blood samples were collected at delivery. Hemagglutination inhibition assays (HAI) for pH1N1 were performed. Data were analyzed using linear regression analyses. HAIs were performed for matched maternal/cord blood pairs for 16 women with confirmed pH1N1 infection, 14 women vaccinated against pH1N1, and 10 women without infection or vaccination. We found that pH1N1 vaccination and wild-type infection during pregnancy did not differ with respect to (1) HAI titers at delivery, (2) HAI antibody decay slopes over time, and (3) HAI titers in the cord blood. Conclusions: Vaccination against pH1N1 confers a similar HAI antibody response as compared to pH1N1 infection durin

The impact of thought speed and variability on psychological state and threat perception: Further exploration of the theory of mental motion.

Thought speed and variability are purportedly common features of specific psychological states, such as mania and anxiety. The present study explored the independent and combinational influence of these variables upon condition-specific symptoms and affective state, as proposed by Pronin and Jacobs’ (2008) theory of mental motion. A general population sample was recruited online (N = 263). Participants completed a thought speed and variability manipulation task, inducing a combination of fast/slow and varied/repetitive thought. Change in mania and anxiety symptoms was assessed through direct self-reported symptom levels and indirect, processing bias assessment (threat interpretation). Results indicated that fast and varied thought independently increased self-reported mania symptoms. Affect was significantly less positive and more negative during slow thought. No change in anxiety symptoms or threat interpretation was found between manipulation conditions. No evidence for the proposed combinational influence of speed and variability was found. Implications and avenues for therapeutic intervention are discussed

Proteome Analysis of Borrelia burgdorferi Response to Environmental Change

We examined global changes in protein expression in the B31 strain of Borrelia burgdorferi, in response to two environmental cues (pH and temperature) chosen for their reported similarity to those encountered at different stages of the organism's life cycle. Multidimensional nano-liquid chromatographic separations coupled with tandem mass spectrometry were used to examine the array of proteins (i.e., the proteome) of B. burgdorferi for different pH and temperature culture conditions. Changes in pH and temperature elicited in vitro adaptations of this spirochete known to cause Lyme disease and led to alterations in protein expression that are associated with increased microbial pathogenesis. We identified 1,031 proteins that represent 59% of the annotated genome of B. burgdorferi and elucidated a core proteome of 414 proteins that were present in all environmental conditions investigated. Observed changes in protein abundances indicated varied replicon usage, as well as proteome functional distributions between the in vitro cell culture conditions. Surprisingly, the pH and temperature conditions that mimicked B. burgdorferi residing in the gut of a fed tick showed a marked reduction in protein diversity. Additionally, the results provide us with leading candidates for exploring how B. burgdorferi adapts to and is able to survive in a wide variety of environmental conditions and lay a foundation for planned in situ studies of B. burgdorferi isolated from the tick midgut and infected animals

Should UI Eligibility Be Expanded to Low-Earning Workers? Evidence on Employment, Transfer Receipt, and Income from Administrative Data

Recent efforts to expand unemployment insurance (UI) eligibility are expected to increase low-earning workers’ access to UI. Although the expansion’s aim is to smooth the income and consumption of previously ineligible workers, it is possible that UI benefits simply displace other sources of income. Standard economic models predict that UI delays reemployment, thereby reducing wage income. Additionally, low-earning workers are often eligible for benefits from means-tested programs, which may decrease with UI benefits. In this paper, we estimate the impact of UI eligibility on employment, means-tested program participation, and income after job loss using a unique individual-level administrative data set from the state of Michigan. To identify a causal effect, we implement a fuzzy regression discontinuity design around the minimum earnings threshold for UI eligibility. Our main finding is that while UI eligibility increases jobless durations by up to 25 percent and temporarily lowers receipt of cash assistance (TANF) by 63 percent, the net impact on total income is still positive and large. In the quarter immediately following job loss, UI-eligible workers have 46-61 percent higher incomes than ineligibles

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p