Serum Metabolomics as a Powerful Tool in Distinguishing Trauma from Other Critical Illness Conditions

Critical illness is highly variable, complicating patient care and recovery. We have previously used metabolomics to investigate several causes of intensive care unit admission, seeking to assess changes in metabolism occurring with each condition. We present a meta-analysis of these serum metabolomes, exploring how the metabolomes differ with each condition. We also present how mass spectrometry-based metabolomics could be used for predictive monitoring. Serum metabolites were previously quantified using nuclear magnetic resonance spectroscopy in patients with traumatic injury, respiratory failure, pancreatitis, and combat trauma. Healthy controls are also included. Spectral features were analyzed with principal component analysis (PCA) to explore patterns in patients’ underlying conditions. PCA suggests trauma metabolic profiles, particularly combat casualties, differ from other conditions. Principal components 2 and 3, accounting for 16% of the variation in the model, distinguish samples obtained from trauma patients. Metabolomics is a powerful tool for quantifying variability in critical illness, highlighting trauma as separate from other conditions. This observation is in line with the -omics literature, which has described a massive global “genomic storm” in response to severe injury. Mass spectrometry highlights this extreme variability, which occurs in ICU patients but not healthy controls. With new technology, metabolomics could be used to bring faster, individualized patient care to the ICU

Modeling the Heart as a Communication System

Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in 2-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry, and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.Comment: 26 pages (including Appendix), 6 figures, 8 videos (not uploaded due to size limitation

Metabolic networks in a porcine model of trauma and hemorrhagic shock demonstrate different control mechanism with carbohydrate pre-feed

Background: Treatment with oral carbohydrate prior to trauma and hemorrhage confers a survival benefit in small animal models. The impact of fed states on survival in traumatically injured humans is unknown. This work uses regulatory networks to examine the effect of carbohydrate pre-feeding on metabolic response to polytrauma and hemorrhagic shock in a clinically-relevant large animal model. Methods: Male Yorkshire pigs were fasted overnight (n = 64). Pre-fed animals (n = 32) received an oral bolus of Karo\textregistered\syrup before sedation. All animals underwent a standardized trauma, hemorrhage, and resuscitation protocol. Serum samples were obtained at set timepoints. Proton NMR was used to identify and quantify serum metabolites. Metabolic regulatory networks were constructed from metabolite concentrations and rates of change in those concentrations to identify controlled nodes and controlling nodes of the network. Results: Oral carbohydrate pre-treatment was not associated with survival benefit. Six metabolites were identified as controlled nodes in both groups: adenosine, cytidine, glycerol, hypoxanthine, lactate, and uridine. Distinct groups of controlling nodes were associated with controlled nodes; however, the composition of these groups depended on feeding status. Conclusions: A common metabolic output, typically associated with injury and hypoxia, results from trauma and hemorrhagic shock. However, this output is directed by different metabolic inputs depending upon the feeding status of the subject. Nodes of the network that are related to mortality can potentially be manipulated for therapeutic effect; however, these nodes differ depending upon feeding status

Observations of the Askaryan Effect in Ice

We report on the first observations of the Askaryan effect in ice: coherent impulsive radio Cherenkov radiation from the charge asymmetry in an electromagnetic (EM) shower. Such radiation has been observed in silica sand and rock salt, but this is the first direct observation from an EM shower in ice. These measurements are important since the majority of experiments to date that rely on the effect for ultra-high energy neutrino detection are being performed using ice as the target medium. As part of the complete validation process for the Antarctic Impulsive Transient Antenna (ANITA) experiment, we performed an experiment at the Stanford Linear Accelerator Center (SLAC) in June 2006 using a 7.5 metric ton ice target, yielding results fully consistent with theoretical expectations

New Limits on the Ultra-high Energy Cosmic Neutrino Flux from the ANITA Experiment

We report initial results of the first flight of the Antarctic Impulsive Transient Antenna (ANITA-1) 2006-2007 Long Duration Balloon flight, which searched for evidence of a diffuse flux of cosmic neutrinos above energies of 3 EeV. ANITA-1 flew for 35 days looking for radio impulses due to the Askaryan effect in neutrino-induced electromagnetic showers within the Antarctic ice sheets. We report here on our initial analysis, which was performed as a blind search of the data. No neutrino candidates are seen, with no detected physics background. We set model-independent limits based on this result. Upper limits derived from our analysis rule out the highest cosmogenic neutrino models. In a background horizontal-polarization channel, we also detect six events consistent with radio impulses from ultra-high energy extensive air showers.Comment: 4 pages, 2 table

Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles

Purpose Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. Methods This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. Results The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30- fold (HR:7.30, 95% CI:(3.11-17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10-6.00), p = 0.03) increases in hazard of death relative to phenotype III. Conclusion We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design

Observations of the Askaryan Effect in Ice

We report on the first observations of the Askaryan effect in ice: coherent impulsive radio Cherenkov radiation from the charge asymmetry in an electromagnetic (EM) shower. Such radiation has been observed in silica sand and rock salt, but this is the first direct observation from an EM shower in ice. These measurements are important since the majority of experiments to date that rely on the effect for ultra-high energy neutrino detection are being performed using ice as the target medium. As part of the complete validation process for the Antarctic Impulsive Transient Antenna (ANITA) experiment, we performed an experiment at the Stanford Linear Accelerator Center (SLAC) in June 2006 using a 7.5 metric ton ice target, yielding results fully consistent with theoretical expectations.Comment: 4 pages, 5 figures, minor correction

Observation of Ultra-high-energy Cosmic Rays with the ANITA Balloon-borne Radio Interferometer

We report the observation of sixteen cosmic ray events of mean energy of 1.5 x 10^{19} eV, via radio pulses originating from the interaction of the cosmic ray air shower with the Antarctic geomagnetic field, a process known as geosynchrotron emission. We present the first ultra-wideband, far-field measurements of the radio spectral density of geosynchrotron emission in the range from 300-1000 MHz. The emission is 100% linearly polarized in the plane perpendicular to the projected geomagnetic field. Fourteen of our observed events are seen to have a phase-inversion due to reflection of the radio beam off the ice surface, and two additional events are seen directly from above the horizon.Comment: 5 pages, 5 figures, new figure adde