28 resultados para decomposition of a support

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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To conduct a systematic review and meta-analysis on the relevance of low social support for the development and course of coronary heart disease (CHD).

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Social support has been found to be protective from adverse health effects of psychological stress. We hypothesized that higher social support would predict a more favorable course of Crohn's disease (CD) directly (main effect hypothesis) and via moderating other prognostic factors (buffer hypothesis).

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Acute stress reactions (ASR) and postpartum depressive symptoms (PDS) are frequent after childbirth. The present study addresses the change and overlap of ASR and PDS from the 1- to 3-week postpartum and examines the interplay of caregiver support and subjective birth experience with regard to the development of ASR/PDS within a longitudinal path model.

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OBJECTIVES: This paper examines four different levels of possible variation in symptom reporting: occasion, day, person and family. DESIGN: In order to rule out effects of retrospection, concurrent symptom reporting was assessed prospectively using a computer-assisted self-report method. METHODS: A decomposition of variance in symptom reporting was conducted using diary data from families with adolescent children. We used palmtop computers to assess concurrent somatic complaints from parents and children six times a day for seven consecutive days. In two separate studies, 314 and 254 participants from 96 and 77 families, respectively, participated. A generalized multilevel linear models approach was used to analyze the data. Symptom reports were modelled using a logistic response function, and random effects were allowed at the family, person and day level, with extra-binomial variation allowed for on the occasion level. RESULTS: Substantial variability was observed at the person, day and occasion level but not at the family level. CONCLUSIONS: To explain symptom reporting in normally healthy individuals, situational as well as person characteristics should be taken into account. Family characteristics, however, would not help to clarify symptom reporting in all family members.

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Postmortem decomposition of brain tissue was investigated by (1)H-magnetic resonance spectroscopy (MRS) in a sheep head model and selected human cases. Aiming at the eventual estimation of postmortem intervals in forensic medicine, this study focuses on the characterization and identification of newly observed metabolites. In situ single-voxel (1)H-MRS at 1.5 T was complemented by multidimensional homo- and heteronuclear high-resolution NMR spectroscopy of an extract of sheep brain tissue. The inclusion of spectra of model solutions in the program LC Model confirmed the assignments in situ. The first postmortem phase was characterized mainly by changes in the concentrations of metabolites usually observed in vivo and by the appearance of previously reported decay products. About 3 days postmortem, new metabolites, including free trimethylammonium, propionate, butyrate, and iso-butyrate, started to appear in situ. Since the observed metabolites and the time course is comparable in sheep and human brain tissue, the model system seems to be appropriate.

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OBJECTIVE: To investigate the relationship between social support and coagulation parameter reactivity to mental stress in men and to determine if norepinephrine is involved. Lower social support is associated with higher basal coagulation activity and greater norepinephrine stress reactivity, which in turn, is linked with hypercoagulability. However, it is not known if low social support interacts with stress to further increase coagulation reactivity or if norepinephrine affects this association. These findings may be important for determining if low social support influences thrombosis and possible acute coronary events in response to acute stress. We investigated the relationship between social support and coagulation parameter reactivity to mental stress in men and determined if norepinephrine is involved. METHODS: We measured perceived social support in 63 medication-free nonsmoking men (age (mean +/- standard error of the mean) = 36.7 +/- 1.7 years) who underwent an acute standardized psychosocial stress task combining public speaking and mental arithmetic in front of an audience. We measured plasma D-dimer, fibrinogen, clotting Factor VII activity (FVII:C), and plasma norepinephrine at rest as well as immediately after stress and 20 minutes after stress. RESULTS: Independent of body mass index, mean arterial pressure, and age, lower social support was associated with higher D-dimer and fibrinogen levels at baseline (p < .012) and with greater increases in fibrinogen (beta = -0.36, p = .001; DeltaR(2) = .12), and D-dimer (beta = -0.21, p = .017; DeltaR(2) = .04), but not in FVII:C (p = .83) from baseline to 20 minutes after stress. General linear models revealed significant main effects of social support and stress on fibrinogen, D-dimer, and norepinephrine (p < .035). Controlling for norepinephrine did not change the significance of the reported associations between social support and the coagulation measures D-dimer and fibrinogen. CONCLUSIONS: Our results suggest that lower social support is associated with greater coagulation activity before and after acute stress, which was unrelated to norepinephrine reactivity.

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Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.