Dataset Information

Data concerning statistical relation between obliquity and Dansgaard-Oeschger events.

ABSTRACT: Data presented are related to the research article entitled "Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity" (J. Deng et al., 2018). The datasets in Deng et al. (2018) are analyzed on the foundation of ensemble empirical mode decomposition (EEMD) (Z.H. Wu and N.E. Huang, 2009), and reveal more occurrences of Dansgaard-Oeschger (DO) events in the decreasing phase of obliquity. Here, we report the number of significant high Shannon entropy (SE) (C.E. Shannon and W. Weaver, 1949) of 95% significance level of DO events in the increasing and decreasing phases of obliquity, respectively. First, the proxy time series are filtered by EEMD to obtain DO events. Then, the time-varying SE of DO modes are calculated on the basis of principle of histogram. The 95% significance level is evaluated through surrogate data (T. Schreiber and A. Schmitz, 1996). Finally, a comparison between the numbers of SE values that are larger than 95% significance level in the increasing and decreasing phases of obliquity, respectively, is reported.

SUBMITTER: Deng J

PROVIDER: S-EPMC6660458 | biostudies-other | 2019 Apr

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Data concerning statistical relation between obliquity and Dansgaard-Oeschger events.

Deng Jia J Wu Zhaohua Z Zhang Min M Huang Norden E NE Wang Shizhu S Qiao Fangli F

Data in brief 20190307

Data presented are related to the research article entitled "Using Holo-Hilbert spectral analysis to quantify the modulation of Dansgaard-Oeschger events by obliquity" (J. Deng et al., 2018). The datasets in Deng et al. (2018) are analyzed on the foundation of ensemble empirical mode decomposition (EEMD) (Z.H. Wu and N.E. Huang, 2009), and reveal more occurrences of Dansgaard-Oeschger (DO) events in the decreasing phase of obliquity. Here, we report the number of significant high Shannon entropy ...[more]

PMID: 31372394

Similar Datasets

Project description:BackgroundEmotional stress is associated with increased risk of cardiovascular disease. We imaged the amygdala, a brain region involved in stress, to determine whether its resting metabolic activity predicts risk of subsequent cardiovascular events.MethodsIndividuals aged 30 years or older without known cardiovascular disease or active cancer disorders, who underwent 18F-fluorodexoyglucose PET/CT at Massachusetts General Hospital (Boston, MA, USA) between Jan 1, 2005, and Dec 31, 2008, were studied longitudinally. Amygdalar activity, bone-marrow activity, and arterial inflammation were assessed with validated methods. In a separate cross-sectional study we analysed the relation between perceived stress, amygdalar activity, arterial inflammation, and C-reactive protein. Image analyses and cardiovascular disease event adjudication were done by mutually blinded researchers. Relations between amygdalar activity and cardiovascular disease events were assessed with Cox models, log-rank tests, and mediation (path) analyses.Findings293 patients (median age 55 years [IQR 45·0-65·5]) were included in the longitudinal study, 22 of whom had a cardiovascular disease event during median follow-up of 3·7 years (IQR 2·7-4·8). Amygdalar activity was associated with increased bone-marrow activity (r=0·47; p<0·0001), arterial inflammation (r=0·49; p<0·0001), and risk of cardiovascular disease events (standardised hazard ratio 1·59, 95% CI 1·27-1·98; p<0·0001), a finding that remained significant after multivariate adjustments. The association between amygdalar activity and cardiovascular disease events seemed to be mediated by increased bone-marrow activity and arterial inflammation in series. In the separate cross-sectional study of patients who underwent psychometric analysis (n=13), amygdalar activity was significantly associated with arterial inflammation (r=0·70; p=0·0083). Perceived stress was associated with amygdalar activity (r=0·56; p=0·0485), arterial inflammation (r=0·59; p=0·0345), and C-reactive protein (r=0·83; p=0·0210).InterpretationIn this first study to link regional brain activity to subsequent cardiovascular disease, amygdalar activity independently and robustly predicted cardiovascular disease events. Amygdalar activity is involved partly via a path that includes increased bone-marrow activity and arterial inflammation. These findings provide novel insights into the mechanism through which emotional stressors can lead to cardiovascular disease in human beings.FundingNone.

Project description:BackgroundRecurrent events data analysis is common in biomedicine. Literature review indicates that most statistical models used for such data are often based on time to the first event or consider events within a subject as independent. Even when taking into account the non-independence of recurrent events within subjects, data analyses are mostly done with continuous risk interval models, which may not be appropriate for treatments with sustained effects (e.g., drug treatments of malaria patients). Furthermore, results can be biased in cases of a confounding factor implying different risk exposure, e.g. in malaria transmission: if subjects are located at zones showing different environmental factors implying different risk exposures.MethodsThis work aimed to compare four different approaches by analysing recurrent malaria episodes from a clinical trial assessing the effectiveness of three malaria treatments [artesunate + amodiaquine (AS + AQ), artesunate + sulphadoxine-pyrimethamine (AS + SP) or artemether-lumefantrine (AL)], with continuous and discontinuous risk intervals: Andersen-Gill counting process (AG-CP), Prentice-Williams-Peterson counting process (PWP-CP), a shared gamma frailty model, and Generalized Estimating Equations model (GEE) using Poisson distribution. Simulations were also made to analyse the impact of the addition of a confounding factor on malaria recurrent episodes.ResultsUsing the discontinuous interval analysis, AG-CP and Shared gamma frailty models provided similar estimations of treatment effect on malaria recurrent episodes when adjusted on age category. The patients had significant decreased risk of recurrent malaria episodes when treated with AS + AQ or AS + SP arms compared to AL arm; Relative Risks were: 0.75 (95% CI (Confidence Interval): 0.62-0.89), 0.74 (95% CI: 0.62-0.88) respectively for AG-CP model and 0.76 (95% CI: 0.64-0.89), 0.74 (95% CI: 0.62-0.87) for the Shared gamma frailty model.With both discontinuous and continuous risk intervals analysis, GEE Poisson distribution models failed to detect the effect of AS + AQ arm compared to AL arm when adjusted for age category. The discontinuous risk interval analysis was found to be the more appropriate approach.ConclusionRepeated event in infectious diseases such as malaria can be analysed with appropriate existing models that account for the correlation between multiple events within subjects with common statistical software packages, after properly setting up the data structures.

Dataset Information

Data concerning statistical relation between obliquity and Dansgaard-Oeschger events.

Publications

Data concerning statistical relation between obliquity and Dansgaard-Oeschger events.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure