Robust Analysis of Fluxes in Genome-Scale Metabolic Pathways.

Constraint-based optimization, such as flux balance analysis (FBA), has become a standard systems-biology computational method to study cellular metabolisms that are assumed to be in a steady state of optimal growth. The methods are based on optimization while assuming (i) equilibrium of a linear system of ordinary differential equations, and (ii) deterministic data. However, the steady-state assumption is biologically imperfect, and several key stoichiometric coefficients are experimentally inferred from situations of inherent variation. We propose an approach that explicitly acknowledges heterogeneity and conducts a robust analysis of metabolic pathways (RAMP). The basic assumption of steady state is relaxed, and we model the innate heterogeneity of cells probabilistically. Our mathematical study of the stochastic problem shows that FBA is a limiting case of our RAMP method. Moreover, RAMP has the properties that: A) metabolic states are (Lipschitz) continuous with regards to the probabilistic modeling parameters, B) convergent metabolic states are solutions to the deterministic FBA paradigm as the stochastic elements dissipate, and C) RAMP can identify biologically tolerable diversity of a metabolic network in an optimized culture. We benchmark RAMP against traditional FBA on genome-scale metabolic reconstructed models of E. coli, calculating essential genes and comparing with experimental flux data.

Dynamic programming used to align protein structures with a spectrum is robust.

Several efficient algorithms to conduct pairwise comparisons among large databases of protein structures have emerged in the recent literature. The central theme is the design of a measure between the Cα atoms of two protein chains, from which dynamic programming is used to compute an alignment. The efficiency and efficacy of these algorithms allows large-scale computational studies that would have been previously impractical. The computational study herein shows that the structural alignment algorithm eigen-decomposition alignment with the spectrum (EIGAs) is robust against both parametric and structural variation.

Characterization of airway device cuff volumes at simulated altitude.

INTRODUCTION: Cuff volume of an air-filled airway device varies inversely with ambient pressure at altitude. This may result in problems with ventilation, aspiration, and tissue ischemia in intubated patients transported by aircraft. We aimed to characterize cuff volume changes in airway devices as a function of altitude. METHODS: Four inflatable airway devices lendotracheal tube (ETT), Combitube, King tube, and laryngeal mask airway (LMA)I, each inflated with air or water, were evaluated for cuff volume changes in an altitude chamber simulating ascent and descent from ground level to 15,000 ft (4572 m). A novel cuff-less supraglottic device called i-gel was also tested. Multivariate linear regression was used to assess the effect of altitude and cuff content on cuff volume. RESULTS: We found a linear relationship between air-filled cuff volume and altitude in all the inflatable airway devices. The Combitube (correlation coefficient R = 0.94) and King tube (R = 0.98) showed the clearest linear relationship; the ETT (R = 0.70) and LMA (0.86) showed modest correlations. With water-filled cuffs, the rate of increase was relatively smaller in all the inflatable devices except the ETT, which remained constant. The difference between air- and water-filled cuffs was statistically significant in each inflatable device (P < 0.001). The i-gel showed no volume change at any of the tested altitudes. CONCLUSIONS: Cuff volume of inflatable airway devices increased linearly with altitude. The dual-cuffed supraglottic devices showed greater volume changes, likely due to the combined effect of their two cuffs. Of the inflatable devices, the water-filled ETT was the least sensitive to altitude changes.

A spectral approach to protein structure alignment.

A new intrinsic geometry based on a spectral analysis is used to motivate methods for aligning protein folds. The geometry is induced by the fact that a distance matrix can be scaled so that its eigenvalues are positive. We provide a mathematically rigorous development of the intrinsic geometry underlying our spectral approach and use it to motivate two alignment algorithms. The first uses eigenvalues alone and dynamic programming to quickly compute a fold alignment. Family identification results are reported for the Skolnick40 and Proteus300 data sets. The second algorithm extends our spectral method by iterating between our intrinsic geometry and the 3D geometry of a fold to make high-quality alignments. Results and comparisons are reported for several difficult fold alignments. The second algorithm's ability to correctly identify fold families in the Skolnick40 and Proteus300 data sets is also established.

Prospective observational study of United States (US) Air Force Critical Care Air Transport team operations in Iraq.

BACKGROUND: Current United States (US) military doctrine emphasizes rapid evacuation of casualties to fixed medical facilities remote from the theater of war. To support this strategy, the Air Force has formed Critical Care Air Transport (CCAT) teams consisting of a physician, nurse, and respiratory therapist. STUDY OBJECTIVE: To describe the characteristics of US Air Force CCAT team operations at Balad Air Base, Iraq over a 1-year period. METHODS: Balad Air Base was the primary collection point in Iraq for patients requiring evacuation outside of the country during the study period. The study authors deployed sequentially to Balad Air Base as CCAT team leaders. All patients transported by the authors were enrolled in the study. Injuries, illnesses, demographics, and in-flight data were collected prospectively. RESULTS: There were 133 patients transported on 61 separate flights between Iraq and Germany. Trauma was present in 65% (87/133) of all patients transported. Lower-extremity injuries were the most prevalent among combat-related trauma patients. Cardiac conditions were the most common diagnoses among the medical patients. Fifty-seven percent of patients were mechanically ventilated. Hypotension was the most common in-flight complication, occurring in 17% (22/133) of patients. No flights were diverted or turned back due to an unstable patient. No patient died during flight or in the 24 h after the flight. CONCLUSIONS: US Air Force CCAT teams can safely transport multiple critical patients over long distances while providing intensive care interventions. Medical patients make up over one-third of patients requiring CCAT team transport.

Designing radiotherapy plans with elastic constraints and interior point methods.

A new linear programming model used to aid in the design of radiotherapy plans is introduced. This model incorporates elastic constraints, and when solved with a path following interior point method, produces favorable plans. A sound mathematical analysis shows how to interpret the solution, and hence, the treatment planner receives meaningful knowledge about the radiotherapy plan being developed. Preliminary experiments are conducted.