2,300 research outputs found
The upper and lower respiratory tract microbiome in severe aspiration pneumonia
Uncertainty persists whether anaerobic bacteria represent important pathogens in aspiration pneumonia. In a nested case-control study of mechanically ventilated patients classified as macro-aspiration pneumonia (MAsP, n = 56), non-macro-aspiration pneumonia (NonMAsP, n = 91), and uninfected controls (n = 11), we profiled upper (URT) and lower respiratory tract (LRT) microbiota with bacterial 16S rRNA gene sequencing, measured plasma host-response biomarkers, analyzed bacterial communities by diversity and oxygen requirements, and performed unsupervised clustering with Dirichlet Multinomial Models (DMM). MAsP and NonMAsP patients had indistinguishable microbiota profiles by alpha diversity and oxygen requirements with similar host-response profiles and 60-day survival. Unsupervised DMM clusters revealed distinct bacterial clusters in the URT and LRT, with low-diversity clusters enriched for facultative anaerobes and typical pathogens, associated with higher plasma levels of SPD and sCD14 and worse 60-day survival. The predictive inter-patient variability in these bacterial profiles highlights the importance of microbiome study in patient sub-phenotyping and precision medicine approaches for severe pneumonia
The Relationship of Positive and Negative Alcohol Expectancies to Patterns of Consumption of Alcohol in Social Drinkers
Negative alcohol expectancies have recently come to occupy a more important position in the expectancy literature, but recent claims that positive expectancies are unimportant in the consumption of alcohol when compared with negative expectancies are based on potentially flawed methodology. This study investigated the relative contribution of positive and negative expectancies to the consumption of alcohol using an instrument designed to measure both positive and negative expectancies. One hundred ninety-three men and women from the general community participated in the study. Findings showed while negative expectancies accounted for the greater proportion of variance of frequency of consumption, positive expectancies remained an important predictor of consumption, accounting for the greater proportion of variance of quantity consumed per session. The interesting but sometimes counterintuitive directions of these relationships can be explained in terms of social learning principles. The relatively neglected concept of negative expectancies is worthy of further use and investigation
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