An Inner Gaseous Disk around the Herbig Be Star MWC 147

We present high-spectral-resolution, optical spectra of the Herbig Be star MWC 147, in which we spectrally resolve several emission lines, including the [O I] lines at 6300 and 6363\deg. Their highly symmetric, double-peaked line profiles indicate that the emission originates in a rotating circumstellar disk. We deconvolve the Doppler-broadened [O I] emission lines to obtain a measure of emission as a function of distance from the central star. The resulting radial surface brightness profiles are in agreement with a disk structure consisting of a flat, inner, gaseous disk and a flared, outer, dust disk. The transition between these components at 2 to 3 AU corresponds to the estimated dust sublimation radius. The width of the double-peaked Mg II line at 4481\deg suggests that the inner disk extends to at least 0.10 AU, close to the corotation radius.Comment: accepted for ApJ Letters (Oct. 2010

A multi-scale area-interaction model for spatio-temporal point patterns

Models for fitting spatio-temporal point processes should incorporate spatio-temporal inhomogeneity and allow for different types of interaction between points (clustering or regularity). This paper proposes an extension of the spatial multi-scale area-interaction model to a spatio-temporal framework. This model allows for interactionbetween points at different spatio-temporal scales and for the inclusion of covariates. We present a simulation study and fit the new model to varicella cases registered during 2013 in Valencia, Spain

A multi-scale area-interaction model for spatio-temporal point patterns

Models for fitting spatio-temporal point processes should incorporate spatio-temporal inhomogeneity and allow for different types of interaction between points (clustering or regularity). This paper proposes an extension of the spatial multi-scale area-interaction model to a spatio-temporal framework. This model allows for interactionbetween points at different spatio-temporal scales and for the inclusion of covariates. We present a simulation study and fit the new model to varicella cases registered during 2013 in Valencia, Spain

Prenatal and postpartum maternal mental health and neonatal motor outcomes during the COVID-19 pandemic

Background: Rates of prenatal and postpartum stress and depression in pregnant individuals have increased during the COVID-19 pandemic. Perinatal maternal mental health has been linked to worse motor development in offspring, with motor deficits appearing in infancy and early childhood. We aimed to evaluate the relationship between prenatal and postpartum stress and depression and motor outcome in infants born during the COVID-19 pandemic. Methods: One hundred and seventeen participants completed an online prospective survey study at two timepoints: during pregnancy and within 2 months postpartum. Depression was self-reported using the Edinburgh Perinatal/Postpartum Depression Scale (EPDS), and stress via the Perceived Stress Scale (PSS). Mothers reported total infant motor ability (fine and gross) using the interRAI 0–3 Developmental Domains questionnaire. Results: Prenatal (EPDS median=10.0, interquartile range[IQR]=6.0 – 14.0, B=-0.035, 95%CI=-0.062 to -0.007, p = 0.014) and postpartum maternal depression outcomes (median=7, IQR=4–12, B=-0.037, 95%CI= -0.066 to -0.008, p = 0.012) were significantlynegatively associated with total infant motor ability. Neither pregnancy nor postpartum perceived stress was associated with infant motor function. A cluster analysis revealed that preterm and low-birth weight infants whose mothers reported elevated depressive symptoms during pregnancy and in the postpartum period had the poorest motor outcomes. Conclusions: Prenatal and postpartum depression, but not stress, was associated with early infant motor abilities. Preterm and low-birth weight infants whose mothers reported elevated depressive symptoms maybe at-risk of experiencing poor motor outcomes. These results highlight the importance of identifying pre- and postnatal maternal mental health issues, especially during the ongoing COVID-19 pandemic

Novel insights in the regulation of CCL18 secretion by monocytes and dendritic cells via cytokines, Toll-like receptors and rheumatoid synovial fluid

BACKGROUND: The T cell attracting chemokine CCL18 is produced by antigen presenting cells and a role for CCL18 has been suggested in the pathogenesis of a variety of diseases. Rheumatoid arthritis (RA) is one of these conditions, in which abundant CCL18 production is present. Although Th2 cytokines and IL-10 are known to have an effect on CCL18 production, there are several gaps in our knowledge regarding the exact regulation of CCL18 secretion, both in general and in RA. In this study we provide new insights in the regulation of CCL18 secretion by monocytes and dendritic cells. RESULTS: In contrast to a large panel of pro-inflammatory stimuli (IL-1β, TNF-α, IL-10, IL-13, IL-15, IL-17, IL-18, IFN-γ), T cell mimicking molecules (RANKL, CD40L) or TLR driven maturation, the anti-inflammatory IL-10 strongly stimulated DC to secrete CCL18. On freshly isolated monocytes, CCL18 secretion was induced by IL-4 and IL-13, in strong synergy with IL-10. This synergistic effect could already be observed after only 24 hours, indicating that not only macrophages and dendritic cells, but also monocytes secrete CCL18 under these stimulatory conditions. A high CCL18 expression was detected in RA synovial tissue and incubation of monocytes with synovial fluid from RA patients clearly enhanced the effects of IL-4, IL-13 and IL-10. Surprisingly, the effect of synovial fluid was not driven by IL-10 of IL-13, suggesting the presence of another CCL18 inducing factor in synovial fluid. CONCLUSION: In summary, IL-10 synergistically induces CCL18 secretion in combination with IL-4 of IL-13 on monocytes and monocyte derived cells. The effects of IL-14, IL-13 and IL-10 are strongly enhanced by synovial fluid. This synergy may contribute to the high CCL18 expression in RA

Machine learning-based predictive modeling of resilience to stressors in pregnant women during COVID-19: A prospective cohort study

During the COVID-19 pandemic, pregnant women have been at high risk for psychological distress. Lifestyle factors may be modifiable elements to help reduce and promote resilience to prenatal stress. We used Machine-Learning (ML) algorithms applied to questionnaire data obtained from an international cohort of 804 pregnant women to determine whether physical activity and diet were resilience factors against prenatal stress, and whether stress levels were in turn predictive of sleep classes. A support vector machine accurately classified perceived stress levels in pregnant women based on physical activity behaviours and dietary behaviours. In turn, we classified hours of sleep based on perceived stress levels. This research adds to a developing consensus concerning physical activity and diet, and the association with prenatal stress and sleep in pregnant women. Predictive modeling using ML approaches may be used as a screening tool and to promote positive health behaviours for pregnant women