Trait positive and negative emotionality differentially associate withdiurnal cortisol activity

Inter-individual variability in metrics of hypothalamic-pituitary-adrenocortical (HPA) activity, such asthe slope of the diurnal decline in cortisol, cortisol awakening response (CAR), and total cortisol out-put, have been found to associate inversely with trait ratings of extraversion and positive affect (E/PA)and positively with neuroticism and negative affect (N/NA) in some, but not all, investigations. Theseinconsistencies may partly reflect varied intensity of cortisol sampling among studies and reliance onself-rated traits, which are subject to reporting biases and limitations of introspection. Here, we furtherexamined dispositional correlates of HPA activity in 490 healthy, employed midlife volunteers (M age = 43years; 54% Female; 86% white). Trait ratings were requested from participants and 2 participant-electedinformants using the Positive and Negative Affect Schedule (PANAS) and Extraversion and Neuroticismdimensions of NEO personality inventories. CAR was assessed as percent increase in cortisol levels fromawakening to 30 min after awakening; and the diurnal slope and total output of cortisol [Area Underthe Curve (AUC)] were determined from cortisol measurements taken at awakening, +4 and +9 h later,and bedtime, across 3 workdays. Structural equation modeling was used to estimate multi-informantE/PA and N/NA factors. We used 3 days of measurement as indicators to model each of the three latentcortisol factors (slope, CAR, and AUC). With the two latent emotionality and three latent cortisol indicesincluded there was good fit to the data ( 2(200)= 278.38, p = 0.0002; RMSEA = 0.028, 90% CI = 0.02–0.04;CFI/TLI = 0.97/0.96; SRMR = 0.04). After controlling for covariates (age, sex, race), results showed higherlatent E/PA associated with a steeper diurnal slope (Standardized ˇ = −0.19, p = 0.02) and smaller CAR(Standardized ˇ = −0.26, p = 0.004), whereas N/NA did not associate with any cortisol metric (Standard-ized ˇ’s = −0.12 to 0.13, p’s = 0.10 to 0.53). These findings suggest that positive emotionality may be moreclosely associated with indices of diurnal cortisol release than negative emotionality

Trait positive and negative emotionality differentially associate withdiurnal cortisol activity

Inter-individual variability in metrics of hypothalamic-pituitary-adrenocortical (HPA) activity, such asthe slope of the diurnal decline in cortisol, cortisol awakening response (CAR), and total cortisol out-put, have been found to associate inversely with trait ratings of extraversion and positive affect (E/PA)and positively with neuroticism and negative affect (N/NA) in some, but not all, investigations. Theseinconsistencies may partly reflect varied intensity of cortisol sampling among studies and reliance onself-rated traits, which are subject to reporting biases and limitations of introspection. Here, we furtherexamined dispositional correlates of HPA activity in 490 healthy, employed midlife volunteers (M age = 43years; 54% Female; 86% white). Trait ratings were requested from participants and 2 participant-electedinformants using the Positive and Negative Affect Schedule (PANAS) and Extraversion and Neuroticismdimensions of NEO personality inventories. CAR was assessed as percent increase in cortisol levels fromawakening to 30 min after awakening; and the diurnal slope and total output of cortisol [Area Underthe Curve (AUC)] were determined from cortisol measurements taken at awakening, +4 and +9 h later,and bedtime, across 3 workdays. Structural equation modeling was used to estimate multi-informantE/PA and N/NA factors. We used 3 days of measurement as indicators to model each of the three latentcortisol factors (slope, CAR, and AUC). With the two latent emotionality and three latent cortisol indicesincluded there was good fit to the data ( 2(200)= 278.38, p = 0.0002; RMSEA = 0.028, 90% CI = 0.02–0.04;CFI/TLI = 0.97/0.96; SRMR = 0.04). After controlling for covariates (age, sex, race), results showed higherlatent E/PA associated with a steeper diurnal slope (Standardized ˇ = −0.19, p = 0.02) and smaller CAR(Standardized ˇ = −0.26, p = 0.004), whereas N/NA did not associate with any cortisol metric (Standard-ized ˇ’s = −0.12 to 0.13, p’s = 0.10 to 0.53). These findings suggest that positive emotionality may be moreclosely associated with indices of diurnal cortisol release than negative emotionality

Theory of coherent acoustic phonons in InGaN/GaN multi-quantum wells

A microscopic theory for the generation and propagation of coherent LA phonons in pseudomorphically strained wurzite (0001) InGaN/GaN multi-quantum well (MQW) p-i-n diodes is presented. The generation of coherent LA phonons is driven by photoexcitation of electron-hole pairs by an ultrafast Gaussian pump laser and is treated theoretically using the density matrix formalism. We use realistic wurzite bandstructures taking valence-band mixing and strain-induced piezo- electric fields into account. In addition, the many-body Coulomb ineraction is treated in the screened time-dependent Hartree-Fock approximation. We find that under typical experimental conditions, our microscopic theory can be simplified and mapped onto a loaded string problem which can be easily solved.Comment: 20 pages, 17 figure

Measurement of the residual energy of muons in the Gran Sasso underground Laboratories

The MACRO detector was located in the Hall B of the Gran Sasso underground Laboratories under an average rock overburden of 3700 hg/cm^2. A transition radiation detector composed of three identical modules, covering a total horizontal area of 36 m^2, was installed inside the empty upper part of the detector in order to measure the residual energy of muons. This paper presents the measurement of the residual energy of single and double muons crossing the apparatus. Our data show that double muons are more energetic than single ones. This measurement is performed over a standard rock depth range from 3000 to 6500 hg/cm^2.Comment: 28 pages, 9 figure

The impact of substance use on brain structure in people at high risk of developing schizophrenia

Ventricular enlargement and reduced prefrontal volume are consistent findings in schizophrenia. Both are present in first episode subjects and may be detectable before the onset of clinical disorder. Substance misuse is more common in people with schizophrenia and is associated with similar brain abnormalities. We employ a prospective cohort study with nested case control comparison design to investigate the association between substance misuse, brain abnormality, and subsequent schizophrenia. Substance misuse history, imaging data, and clinical information were collected on 147 subjects at high risk of schizophrenia and 36 controls. Regions exhibiting a significant relationship between level of use of alcohol, cannabis or tobacco, and structure volume were identified. Multivariate regression then elucidated the relationship between level of substance use and structure volumes while accounting for correlations between these variables and correcting for potential confounders. Finally, we established whether substance misuse was associated with later risk of schizophrenia. Increased ventricular volume was associated with alcohol and cannabis use in a dose-dependent manner. Alcohol consumption was associated with reduced frontal lobe volume. Multiple regression analyses found both alcohol and cannabis were significant predictors of these abnormalities when simultaneously entered into the statistical model. Alcohol and cannabis misuse were associated with an increased subsequent risk of schizophrenia. We provide prospective evidence that use of cannabis or alcohol by people at high genetic risk of schizophrenia is associated with brain abnormalities and later risk of psychosis. A family history of schizophrenia may render the brain particularly sensitive to the risk-modifying effects of these substances

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual’s emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation