Living organisms have evolved protein phosphorylation, a rapid and versatile mechanism that drives signaling and regulates protein function. We report the phosphoproteomes of 18 fungal species and a phylogenetic-based approach to study phosphosite evolution. We observe rapid divergence, with only a small fraction of phosphosites conserved over hundreds of millions of years. Relative to recently acquired phosphosites, ancient sites are enriched at protein interfaces and are more likely to be functionally important, as we show for sites on H2A1 and eIF4E. We also observe a change in phosphorylation motif frequencies and kinase activities that coincides with the whole-genome duplication event. Our results provide an evolutionary history for phosphosites and suggest that rapid evolution of phosphorylation can contribute strongly to phenotypic diversity.

Introduction The ability to better prognosticate burn injury outcome is challenging and historically, most center use the Baux or revised Baux score to help prognosticate burn outcome, however, the weighted contribution of comorbidity on burn mortality has traditionally not been accounted for nor adequately studied. We therefore sought to determine the effect of comorbidities, using the Charlson comorbidity index (CCI) on burn mortality. Methods The purpose of this study was to determine the effect of comorbidities on burn injury mortality as determined by the LA50 (lethal TBSA burn at which 50% of the cohort will succumb from the burn injury) in a retrospective analysis of patients admitted to a regional burn center from 2002–2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA (total body surface area), length of hospital stay, and pre-existing comorbidities. Bivariate analysis was performed and logistic regression modeling using significant variables was utilized to estimate odds of death. Results 7640 patients were included in this study. Overall survival rate was 96%. 40% of our burn cohort had at least one comorbidity. There was a linear increase in the likelihood of death with an increase in CCI. The logistic regression model for mortality outcomes identified four statistically significant variables: age, TBSA, inhalational injury and the presence of comorbidities (OR = 1.59 for each 1 point increase in CCI; 95% CI 1.44–1.77). The unadjusted LA50 was 53% for the entire cohort. Partial adjustment multivariate regression controlling for burn mechanism and inhalation injury only, produced a slight reduction in LA50 for the 0–18 and 19–64 age categories to 76% and 48%, respectively, but a significant decrease occurred in the ≥ 65 years age group with a reduced LA50 to 20% (p<0.001). After full adjustment for all significant covariates, including comorbidities, the independent magnitude of effect of comorbidities on the LA50 was evident in the <65 cohort. The full adjustment showed a LA50 decreased by 15 and 5%, respectively in the 0–18 and >18–65 age groups respectively (p<0.001), however, in the >65 years age cohort there was no change in the LA50. Conclusion Preexisting comorbidities have a significant effect on burn injury mortality in all age groups, particularly the younger burn population. The measured effect of comorbidities in the >65yr age cohort was mitigated by the co-linearity between age and comorbidities. The inclusion of CCI is imperative so as to better prognosticate burn outcome and help guide expectations and resource utilization, particularly in the younger burn cohort..

Introduction-The ability to better prognosticate burn injury outcome is challenging and historically, most center use the Baux or revised Baux score to help prognosticate burn outcome, however, the weighted contribution of comorbidity on burn mortality has traditionally not been accounted for nor adequately studied. We therefore sought to determine the effect of comorbidities, using the Charlson comorbidity index (CCI) on burn mortality.

Introduction Burns cause physiologic changes in multiple organ systems in the body. Burn mortality is usually attributable to pulmonary complications, which can occur in up to 41% of patients admitted to the hospital after burn. Patients with preexisting comorbidities such as chronic lung diseases may be more susceptible. We therefore sought to examine the impact of preexisting respiratory disease on burn outcomes. Methods A retrospective analysis of patients admitted to a regional burn center from 2002–2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, smoker status, length of hospital stay, and days of mechanical ventilation. Bivariate analysis was performed and Cox regression modeling using significant variables was utilized to estimate hazard of progression to mechanical ventilation and mortality. Results There were a total of 7640 patients over the study period. Overall survival rate was 96%. 8% (n=672) had a preexisting respiratory disease. Chronic lung disease patients had a higher mortality rate (7%) compared to those without lung disease (4%, p<0.01). The adjusted Cox regression model to estimate the hazard of progression to mechanical ventilation in patients with respiratory disease was 21% higher compared to those without respiratory disease (HR=1.21, 95% CI=1.01–1.44). The hazard of progression to mortality is 56% higher (HR=1.56, 95% CI=1.10–2.19) for patients with pre-existing respiratory disease compared to those without respiratory disease after controlling for patient demographics and injury characteristics. Conclusion Preexisting chronic respiratory disease significantly increases the hazard of progression to mechanical ventilation and mortality in patients following burn. Given the increasing number of Americans with chronic respiratory diseases, there will likely be a greater number of individuals at risk for worse outcomes following burn.

Introduction Three factors that effect burn injury mortality are age, total body surface of burn (TBSA), and inhalation injury. Of the three, inhalation injury is the strongest predictor of mortality thus its inclusion in the revised Baux score (Age + TBSA +17* (Inhalation Injury, 1 = yes, 0 = no)). However, the weighted contribution of specific comorbidities such as smoker status on mortality has traditionally not been accounted for nor studied in this subset of burn patients. We therefore sought to examine the impact of current tobacco and/or marijuana smoking in patients with inhalation injury. Methods A retrospective analysis of patients admitted to a regional burn center from 2002-2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, and smoker status. Bivariate analysis was performed and logistic regression modeling using significant variables was utilized to estimate odds of mortality. Results There were a total of 7640 patients over the study period. 7% (n=580) of the burn cohort with inhalation injury were included in this study. In-hospital burn mortality for inhalation injury patients was 23%. Current smokers (20%) included cigarette smokers and marijuana users, 19% and 3%, respectively. Preexisting respiratory disease (17%) was present in 36% of smokers compared to 13% of non-smokers (p <0.001). Smokers had significantly lower mortality rate (9%) compared to non-smokers (26%, p <0.01). The logistic regression model for mortality outcomes identified statistically four significant variables: age, TBSA, race, and smoker status (OR = 0.41, 95% CI = 0.18-0.93). Presence of comorbidities, including preexisting respiratory disease, wasn't significant. Conclusion In the sub group of burn patients with inhalation injury, the odds of mortality significantly decreased in pre-existing smokers after adjusting for significant covariates. We postulate that an immune tolerance mechanism that modulates and diminishes the pro-inflammatory response confers a survival advantage in smokers after exposure to acute smoke inhalation injury. Future prospective studies in human and/or animal models are needed to confirm these findings.