Biochemical and biophysical research communications
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Biochem. Biophys. Res. Commun. · Oct 2011
Increased susceptibility to Candida infection following cecal ligation and puncture.
Secondary infection following septic insult represents a significant cause of morbidity and mortality in hospitalized patients. Sepsis induced immunosuppression is a major factor in the host's susceptibility to nosocomial infections and Candida albicans accounts for a growing number of these. Given the importance of improving our understanding of the immune response to sepsis and the increasing rates of C. albicans infections, we sought to develop a murine model of double injury consisting of primary peritonitis, i.e., cecal ligation and puncture (CLP), followed by a secondary challenge of C. albicans. ⋯ Although at four days post-CLP there is a partial reconstitution of the immune system, these animals remain more susceptible to infection compared to their single injury (C. albicans alone) counterparts. Collectively, these studies demonstrate that immunosuppression following initial septic insult changes over time. This novel, two hit model of CLP followed by Candida provides additional insight into the immune compromised state created by primary peritonitis, and thereby opens up another avenue of investigation into the causes and possible cures of an emerging clinical problem.
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Biochem. Biophys. Res. Commun. · Oct 2011
Pilot analysis of the plasma metabolite profiles associated with emphysematous Chronic Obstructive Pulmonary Disease phenotype.
The current pilot study examined the hypothesis that cigarette smokers who developed an emphysematous phenotype of Chronic Obstructive Pulmonary Disease (COPD) were associated with distinctive patterns in their corresponding metabolomics profile as compared to those who did not. Peripheral blood plasma samples were collected from 38 subjects with different phenotypes of COPD. They were categorized into three groups: healthy non-smokers (n=16), smokers without emphysema (n=8), and smokers with emphysema (n=14). ⋯ Subsequently predictive models were created with a supervised learning set, and these predictive models were found to be highly accurate in identifying the subjects with the emphysematous phenotype of COPD with excellent sensitivity and specificity. Our methodology provides a preliminary model that differentiates an emphysematous COPD phenotype from other COPD phenotypes on the basis of the metabolomics profiles. These results also suggest that the metabolomics profiling could potentially guide the characterization of relevant metabolites that leads to an emphysematous COPD phenotype.