Advancing understanding of affect labeling with dynamic causal modeling

Mechanistic understandings of forms of incidental emotion regulation have implications for basic and translational research in the affective sciences. In this study we applied Dynamic Causal Modeling (DCM) for fMRI to a common paradigm of labeling facial affect to elucidate prefrontal to subcortical influences. Four brain regions were used to model affect labeling, including right ventrolateral prefrontal cortex (vlPFC), amygdala and Broca’s area. 64 models were compared, for each of 45 healthy subjects. Family level inference split the model space to a likely driving input and Bayesian Model Selection within the winning family of 32 models revealed a strong pattern of endogenous network connectivity. Modulatory effects of labeling were most prominently observed following Bayesian Model Averaging, with the dampening influence on amygdala originating from Broca’s area but much more strongly from right vlPFC. These results solidify and extend previous correlation and regression-based estimations of negative corticolimbic coupling

The volatile molecular profiles of seven Streptococcus pneumoniae serotypes

In this study, the volatile molecule profile of Streptococcus pneumoniae serotypes was evaluated using solid phase microextraction (SPME) and two dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS). Here, seven serotypes (6B, 14, 15, 18C, 19F, 9V, and 23F) were analyzed in an isogenic background. We identified 13 core molecules associated with all seven serotypes, and seven molecules that were differentially produced between serotypes. Serotype 14 was found to have the most distinct volatile profile, and could be discriminated from the other six serotypes in aggregate with an area under the curve (AUC) of 89%. This study suggests that molecules from S. pneumoniae culture headspace show potential for rapid serotype identification

The volatile molecular profiles of seven Streptococcus pneumoniae serotypes

In this study, the volatile molecule profile of Streptococcus pneumoniae serotypes was evaluated using solid phase microextraction (SPME) and two dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS). Here, seven serotypes (6B, 14, 15, 18C, 19F, 9V, and 23F) were analyzed in an isogenic background. We identified 13 core molecules associated with all seven serotypes, and seven molecules that were differentially produced between serotypes. Serotype 14 was found to have the most distinct volatile profile, and could be discriminated from the other six serotypes in aggregate with an area under the curve (AUC) of 89%. This study suggests that molecules from S. pneumoniae culture headspace show potential for rapid serotype identification