Transmembrane Helix Assembly by Max–Min Ant System Algorithm

Because of the rapid progress in biochemical and structural studies of membrane proteins, considerable attention has been given on developing efficient computational methods for solving low‐to‐medium resolution structures using sparse structural data. In this study, we demonstrate a novel algorithm, max–min ant system (MMAS), designed to find an assembly of α‐helical transmembrane proteins using a rigid helix arrangement guided by distance constraints. The new algorithm generates a large variety with finite number of orientations of transmembrane helix bundle and finds the solution that is matched with the provided distance constraints based on the behavior of ants to search for the shortest possible path between their nest and the food source. To demonstrate the efficiency of the novel search algorithm, MMAS is applied to determine the transmembrane packing of KcsA and MscL ion channels from a limited distance information extracted from the crystal structures, and the packing of KvAP voltage sensor domain using a set of 10 experimentally determined constraints, and the results are compared with those of two popular used stochastic methods, simulated annealing Monte Carlo method and genetic algorithm.     

Prediction of massive transfusion in trauma patients in the surgical intensive care units (THAI-SICU study)

Purpose: After damage control surgery, trauma patients are transferred to intensive care units to restore the physiology. During this period, massive transfusion might be required for ongoing bleeding and coagulopathy. This research aimed to identify predictors of massive blood transfusion in the surgical intensive care units (SICUs). Methods: This is an analysis of the THAI-SICU study which was a prospective cohort that was done in the 9-university-based SICUs in Thailand. The study included only patients admitted due to trauma mechanisms. Massive transfusion was defined as received 10 units of packed red blood cells on the first day of admission. Patient characteristics and physiologic data were analyzed to identify the potential factors. A multivariable regression was then performed to identify the significant model. Results: Three hundred and seventy patients were enrolled. Sixteen patients (5%) received massive transfusion in the SICUs. The factors that significantly predicted massive transfusion were an initial sequential organ failure assessment (SOFA) ≥9 (risk difference (RD) 0.13, 95% confidence interval (CI): 0.03-0.22, p = 0.01); intra-operative blood loss ≥4900 mL (RD 0.33, 95% CI: 0.04-0.62, p = 0.02) and intra-operative blood transfusion ≥10 units (RD 0.45, 95% CI: 0.06 to 0.84, p = 0.02). The probability to have massive transfusion was 0.976 in patients who had these 3 factors. Conclusion: Massive blood transfusion in the SICUs occurred in 5%. An initial SOFA ≥9, intra-operative blood loss ≥4900 mL, and intra-operative blood transfusion 10 units were the significant factors to predict massive transfusion in the SICUs.