633 research outputs found

    Methyl jasmonate-elicited herbivore resistance: does MeJA function as a signal without being hydrolyzed to JA?

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    Treatment with methyl jasmonate (MeJA) elicits herbivore resistance in many plant species and over-expression of JA carboxyl methyltransferase (JMT) constitutively increases JA-induced responses in Arabidopsis. When wild-type (WT) Nicotiana attenuata plants are treated with MeJA, a rapid transient endogenous JA burst is elicited, which in turn increases levels of nicotine and trypsin proteinase inhibitors (TPIs) and resistance to larvae of the specialist herbivore, Manduca sexta. All of these responses are impaired in plants silenced in lipoxygenase 3 expression (asLOX3) but are restored to WT levels by MeJA treatment. Whether these MeJA-induced responses are directly elicited by MeJA or by its cleavage product, JA, is unknown. Using virus-induced gene silencing (VIGS), we silenced MeJA-esterase (NaMJE) expression and found this gene responsible for most of the MeJA-cleaving activity in N. attenuata protein extracts. Silencing NaMJE in asLOX3, but not in WT plants, significantly reduced MeJA-induced nicotine levels and resistance to M. sexta, but not TPI levels. MeJA-induced transcript levels of threonine deaminase (NaTD) and phenylalanine ammonia lyase (NaPAL1) were also decreased in VIGS MJE (asLOX3) plants. Finally the performance of M. sexta larvae that fed on plants treated with JA or MeJA demonstrated that silencing NaMJE inhibited MeJA-induced but not JA-induced resistance in asLOX3 plants. From these results, we conclude that the resistance elicited by MeJA treatment is directly elicited not by MeJA but by its de-methylated product, JA

    Functional investigation of the coronary artery disease gene SVEP1

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    A missense variant of the sushi, von Willebrand factor type A, EGF and pentraxin domain containing protein 1 (SVEP1) is genome-wide significantly associated with coronary artery disease. The mechanisms how SVEP1 impacts atherosclerosis are not known. We found endothelial cells (EC) and vascular smooth muscle cells to represent the major cellular source of SVEP1 in plaques. Plaques were larger in atherosclerosis-prone Svep1 haploinsufficient (ApoE^{−/−}Svep1^{+/−}) compared to Svep1 wild-type mice (ApoE^{−/−}Svep1^{+/+}) and ApoE^{−/−}Svep1^{+/−} mice displayed elevated plaque neutrophil, Ly6C^{high} monocyte, and macrophage numbers. We assessed how leukocytes accumulated more inside plaques in ApoE^{−/−}Svep1^{+/−} mice and found enhanced leukocyte recruitment from blood into plaques. In vitro, we examined how SVEP1 deficiency promotes leukocyte recruitment and found elevated expression of the leukocyte attractant chemokine (C-X-C motif) ligand 1 (CXCL1) in EC after incubation with missense compared to wild-type SVEP1. Increasing wild-type SVEP1 levels silenced endothelial CXCL1 release. In line, plasma Cxcl1 levels were elevated in ApoE^{−/−}Svep1^{+/−} mice. Our studies reveal an atheroprotective role of SVEP1. Deficiency of wild-type Svep1 increased endothelial CXCL1 expression leading to enhanced recruitment of proinflammatory leukocytes from blood to plaque. Consequently, elevated vascular inflammation resulted in enhanced plaque progression in Svep1 deficiency

    Models and simulations for the photometric lsst astronomical time series classification challenge (Plasticc)

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    We describe the simulated data sample for the "Photometric LSST Astronomical Time Series Classification Challenge" (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the Large Synoptic Survey Telescope (LSST), a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to 2018 December 17, and included 1,094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at this https URL. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of type Ia supernova used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models

    Worry is associated with robust reductions in heart rate variability: a transdiagnostic study of anxiety psychopathology

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    Background Individuals with anxiety disorders display reduced resting-state heart rate variability (HRV), although findings have been contradictory and the role of specific symptoms has been less clear. It is possible that HRV reductions may transcend diagnostic categories, consistent with dimensional-trait models of psychopathology. Here we investigated whether anxiety disorders or symptoms of anxiety, stress, worry and depression are more strongly associated with resting-state HRV. Methods Resting-state HRV was calculated in participants with clinical anxiety (n = 25) and healthy controls (n = 58). Symptom severity measures of worry, anxiety, stress, and depression were also collected from participants, regardless of diagnosis. Results Participants who fulfilled DSM-IV criteria for an anxiety disorder displayed diminished HRV, a difference at trend level significance (p = .1, Hedges’ g = -.37, BF10 = .84). High worriers (Total n = 41; n = 22 diagnosed with an anxiety disorder and n = 19 not meeting criteria for any psychopathology) displayed a robust reduction in resting state HRV relative to low worriers (p = .001, Hedges’ g = -.75, BF10 = 28.16). Conclusions The specific symptom of worry – not the diagnosis of an anxiety disorder – was associated with the most robust reductions in HRV, indicating that HRV may provide a transdiagnostic biomarker of worry. These results enhance understanding of the relationship between the cardiac autonomic nervous system and anxiety psychopathology, providing support for dimensional-trait models consistent with the Research Domain Criteria framework

    The effect of verbalization strategy on wisconsin card sorting test performance in schizophrenic patients receiving classical or atypical antipsychotics

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    BACKGROUND: A number of reports showed en encouraging remediation in some patients' executive deficits thanks to the use of 'information processing strategies'. Moreover the impact of antipsychotics on cognitive functions of the schizophrenics is an important issue, especially if an integrated psychosocial treatment is needed. The aim of this paper is to evaluate different executive performance and response to verbalization, a strategy of the Wisconsin Card Sorting Test (WCST) remediation, in subjects on classical vs atypical antipsychotic (AP) treatment. METHODS: Sixty-three schizophrenic subjects undertook the WCST under standard and modified (verbalization) administration. Subjects were stratified by the kind of WCST response (i.e. good, poor and remediable) and AP treatment (i.e. atypical vs. classical). RESULTS: Subjects on atypical APs showed a better performance than those on classical ones. More poor performers who did not remediate were seen in the sample with classical Aps while subjects who remediated the performance were seen in the subgroup with atypical APs only. An increase of perseverative and total errors was seen in poor performers subjects on classical APs. CONCLUSION: Subjects on atypicals showed a better cognitive pattern in terms of WCST performance. Since the naturalistic assignment of medication we cannot draw conclusions about its effect on cognitive performance and its interaction with cognitive remediation potential. However the data lead us to hypothesize that subjects with potential room for remediation did so with the atypical APs

    Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach

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    <p>Abstract</p> <p>Background</p> <p>Relative to physical health conditions such as cardiovascular disease, little is known about risk factors that predict the prevalence of depression. The present study investigates the expected effects of a reduction of these risks over time, using the decision tree method favoured in assessing cardiovascular disease risk.</p> <p>Methods</p> <p>The PATH through Life cohort was used for the study, comprising 2,105 20-24 year olds, 2,323 40-44 year olds and 2,177 60-64 year olds sampled from the community in the Canberra region, Australia. A decision tree methodology was used to predict the presence of major depressive disorder after four years of follow-up. The decision tree was compared with a logistic regression analysis using ROC curves.</p> <p>Results</p> <p>The decision tree was found to distinguish and delineate a wide range of risk profiles. Previous depressive symptoms were most highly predictive of depression after four years, however, modifiable risk factors such as substance use and employment status played significant roles in assessing the risk of depression. The decision tree was found to have better sensitivity and specificity than a logistic regression using identical predictors.</p> <p>Conclusion</p> <p>The decision tree method was useful in assessing the risk of major depressive disorder over four years. Application of the model to the development of a predictive tool for tailored interventions is discussed.</p
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