225 research outputs found
Active learning and optimal climate policy
This paper develops a climate-economy model with uncertainty, irreversibility, and active learning. Whereas previous papers assume learning from one observation per period, or experiment with control variables to gain additional information, this paper considers active learning from investment in monitoring, specifically in improved observations of the global mean temperature. We find that the decision maker invests a significant amount of money in climate research, far more than the current level, in order to increase the rate of learning about climate change. This helps the decision maker make improved decisions. The level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations. As the uncertainty about climate change is smaller, active learning reduces the optimal carbon tax. The greater the risk, the larger is the effect of learning. The method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable, for instance, the precision at which we observe GDP, unemployment, or the quality of education
Body mass index and circulating oestrone sulphate in women treated with adjuvant letrozole
Background: Obesity is an independent adverse prognostic factor in early breast cancer patients, but it is still controversial whether obesity may affect adjuvant endocrine therapy efficacy. The aim of our study (ancillary to the two clinical trials Gruppo Italiano Mammella (GIM)4 and GIM5) was to investigate whether the circulating oestrogen levels during treatment with the aromatase inhibitor letrozole are related to body mass index (BMI) in postmenopausal women with breast cancer. Methods: Plasma concentration of oestrone sulphate (ES) was evaluated by radioimmunoassay in 370 patients. Plasma samples were obtained after at least 6 weeks of letrozole therapy (steady-state time). Patients were divided into four groups according to BMI. Differences among the geometric means (by ANOVA and ANCOVA) and correlation (by Spearman's rho) between the ES levels and BMI were assessed. Results: Picomolar geometric mean values (95% confidence interval, n=patients) of circulating ES during letrozole were 58.6 (51.0-67.2, n=150) when BMI was <25.0 kg m-2; 65.6 (57.8-74.6, n=154) when 25.0-29.9 kg m-2; 59.3 (47.1-74.6, n=50) when 30.0-34.9 kg m -2; and 43.3 (23.0-81.7, n=16) when 6535.0 kg m-2. No statistically significant difference in terms of ES levels among groups and no correlation with BMI were observed. Conclusions: Body mass index does not seem to affect circulating oestrogen levels in letrozole-treated patient
Differential information in large games with strategic complementarities
We study equilibrium in large games of strategic complementarities (GSC) with differential information. We define an appropriate notion of distributional Bayesian Nash equilibrium and prove its existence. Furthermore, we characterize order-theoretic properties of the equilibrium set, provide monotone comparative statics for ordered perturbations of the space of games, and provide explicit algorithms for computing extremal equilibria. We complement the paper with new results on the existence of Bayesian Nash equilibrium in the sense of Balder and Rustichini (J Econ Theory 62(2):385–393, 1994) or Kim and Yannelis (J Econ Theory 77(2):330–353, 1997) for large GSC and provide an analogous characterization of the equilibrium set as in the case of distributional Bayesian Nash equilibrium. Finally, we apply our results to riot games, beauty contests, and common value auctions. In all cases, standard existence and comparative statics tools in the theory of supermodular games for finite numbers of agents do not apply in general, and new constructions are required
Genome-wide association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects.
To identify the genomic regions that confer risk and protection for major depressive disorder (MDD) in humans, large-scale studies are needed. Such studies should collect multiple phenotypes, DNA, and ideally, biological material that allows gene expression analysis, transcriptomic, proteomic, and metabolomic studies. In this paper, we briefly review linkage studies of MDD and then describe the large-scale nationwide biological sample collection in Dutch twin families from the Netherlands Twin Register (NTR) and in participants in the Netherlands Study of Depression and Anxiety (NESDA). Within these studies, 1862 participants with a diagnosis of MDD and 1857 controls at low liability for MDD have been selected for genome-wide genotyping by the US Foundation for the National Institutes of Health Genetic Association Information Network. Stage 1 genome-wide association results are scheduled to be accessible before the end of 2007. Genome-wide association results are open-access and can be viewed at the dbGAP web portal (http://www.ncbi.nlm.nih.gov). Approved users can download the genotype and phenotype data, which have been made available as of 9 October 2007
Perspectives and Integration in SOLAS Science
Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm.
Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency.
The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling.
Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter
Blood-Based Gene Expression Profiles Models for Classification of Subsyndromal Symptomatic Depression and Major Depressive Disorder
Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls
Control of Canalization and Evolvability by Hsp90
Partial reduction of Hsp90 increases expression of morphological novelty in qualitative traits of Drosophila and Arabidopsis, but the extent to which the Hsp90 chaperone also controls smaller and more likely adaptive changes in natural quantitative traits has been unclear. To determine the effect of Hsp90 on quantitative trait variability we deconstructed genetic, stochastic and environmental components of variation in Drosophila wing and bristle traits of genetically matched flies, differing only by Hsp90 loss-of-function or wild-type alleles. Unexpectedly, Hsp90 buffering was remarkably specific to certain normally invariant and highly discrete quantitative traits. Like the qualitative trait phenotypes controlled by Hsp90, highly discrete quantitative traits such as scutellor and thoracic bristle number are threshold traits. When tested across genotypes sampled from a wild population or in laboratory strains, the sensitivity of these traits to many types of variation was coordinately controlled, while continuously variable bristle types and wing size, and critically invariant left-right wing asymmetry, remained relatively unaffected. Although increased environmental variation and developmental noise would impede many types of selection response, in replicate populations in which Hsp90 was specifically impaired, heritability and ‘extrinsic evolvability’, the expected response to selection, were also markedly increased. However, despite the overall buffering effect of Hsp90 on variation in populations, for any particular individual or genotype in which Hsp90 was impaired, the size and direction of its effects were unpredictable. The trait and genetic-background dependence of Hsp90 effects and its remarkable bias toward invariant or canalized traits support the idea that traits evolve independent and trait-specific mechanisms of canalization and evolvability through their evolution of non-linearity and thresholds. Highly non-linear responses would buffer variation in Hsp90-dependent signaling over a wide range, while over a narrow range of signaling near trait thresholds become more variable with increasing probability of triggering all-or-none developmental responses
Changes in global groundwater organic carbon driven by climate change and urbanization
YesClimate change and urbanization can increase pressures on groundwater resources, but little is known about how groundwater quality will change. Here, we rely on a global synthesis (n = 9,404) to reveal the drivers of dissolved organic carbon (DOC), which is an important component of water chemistry and substrate for microorganisms which control many biogeochemical reactions. Groundwater ions, local climate and land use explained ~ 31% of observed variability in groundwater DOC, whilst aquifer age explained an additional 16%. We identify a 19% increase in DOC associated with urban land cover. We predict major groundwater DOC increases following changes in precipitation and temperature in key areas relying on groundwater. Climate change and conversion of natural or agricultural areas to urban areas will decrease groundwater quality and increase water treatment costs, compounding existing threats to groundwater resources
Factor structure of the Hospital Anxiety and Depression Scale in Japanese psychiatric outpatient and student populations
<p>Abstract</p> <p>Background</p> <p>The Hospital Anxiety and Depression Scale (HADS) is a common screening instrument excluding somatic symptoms of depression and anxiety, but previous studies have reported inconsistencies of its factor structure. The construct validity of the Japanese version of the HADS has yet to be reported. To examine the factor structure of the HADS in a Japanese population is needed.</p> <p>Methods</p> <p>Exploratory and confirmatory factor analyses were conducted in the combined data of 408 psychiatric outpatients and 1069 undergraduate students. The data pool was randomly split in half for a cross validation. An exploratory factor analysis was performed on one half of the data, and the fitness of the plausible model was examined in the other half of the data using a confirmatory factor analysis. Simultaneous multi-group analyses between the subgroups (outpatients vs. students, and men vs. women) were subsequently conducted.</p> <p>Results</p> <p>A two-factor model where items 6 and 7 had dual loadings was supported. These factors were interpreted as reflecting anxiety and depression. Item 10 showed low contributions to both of the factors. Simultaneous multi-group analyses indicated a factor pattern stability across the subgroups.</p> <p>Conclusion</p> <p>The Japanese version of HADS indicated good factorial validity in our samples. However, ambiguous wording of item 7 should be clarified in future revisions.</p
Anti-depressant and anxiolytic like behaviors in PKCI/HINT1 knockout mice associated with elevated plasma corticosterone level
<p>Abstract</p> <p>Background</p> <p>Protein kinase C interacting protein (PKCI/HINT1) is a small protein belonging to the histidine triad (HIT) family proteins. Its brain immunoreactivity is located in neurons and neuronal processes. PKCI/HINT1 gene knockout (KO) mice display hyper-locomotion in response to D-amphetamine which is considered a positive symptom of schizophrenia in animal models. <it>Postmortem </it>studies identified PKCI/HINT1 as a candidate molecule for schizophrenia and bipolar disorder. We investigated the hypothesis that the PKCI/HINT1 gene may play an important role in regulating mood function in the CNS. We submitted PKCI/HINT1 KO mice and their wild type (WT) littermates to behavioral tests used to study anti-depressant, anxiety like behaviors, and goal-oriented behavior. Additionally, as many mood disorders coincide with modifications of hypothalamic-pituitary-adrenal (HPA) axis function, we assessed the HPA activity through measurement of plasma corticosterone levels.</p> <p>Results</p> <p>Compared to the WT controls, KO mice exhibited less immobility in the forced swim (FST) and the tail suspension (TST) tests. Activity in the TST tended to be attenuated by acute treatment with valproate at 300 mg/kg in KO mice. The PKCI/HINT1 KO mice presented less thigmotaxis in the Morris water maze and spent progressively more time in the lit compartment in the light/dark test. In a place navigation task, KO mice exhibited enhanced acquisition and retention. Furthermore, the afternoon basal plasma corticosterone level in PKCI/HINT1 KO mice was significantly higher than in the WT.</p> <p>Conclusion</p> <p>PKCI/HINT1 KO mice displayed a phenotype of behavioral and endocrine features which indicate changes of mood function, including anxiolytic-like and anti-depressant like behaviors, in conjunction with an elevated corticosterone level in plasma. These results suggest that the PKCI/HINT 1 gene could be important for the mood regulation function in the CNS.</p
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