Comparative analysis of the pathological events involved in immune and non-immune TRALI models

Background and Objectives Transfusion-related acute lung injury (TRALI) is characterized by leukocyte transmigration and alveolar capillary leakage shortly after transfusion. TRALI pathogenesis has not been fully elucidated. In some cases, the infusion of alloantibodies (immune model), whereas in others the combination of neutrophil priming by proinflammatory molecules with the subsequent infusion of biological response modifiers (BRMs) in the hemocomponent (non-immune model) have been implicated. Our aim was to compare the pathological events involved in TRALI induced by antibodies or BRMs using murine models. Materials and Methods In the immune model, human HNA-2+ neutrophils were incubated in vitro with a monoclonal antibody (anti-CD177, clone 7D8) directed against the HNA-2 antigen and injected i.v. in NOD/SCID mice. In the non-immune model, BALB/c mice were treated with low doses of lipopolysaccharide (LPS) followed by platelet-activating factor (PAF) infusion 2 h later. Forty minutes after PAF administration, or 6 h after neutrophil injection, lungs were isolated and histological analysis, determination of a variety of cytokines and chemokines including keratinocyte-derived chemokine (KC), MIP-2, the interleukins IL-1 beta, IL-6, IL-8 as well as TNFa, cell influx and alveolar capillary leakage were performed. Results In both models, characteristic histological findings of TRALI and an increase in KC and MIP-2 levels were detected. In contrast to the immune model, in the non-immune model, there was a dramatic increase in IL-1 beta and TNFa. However, capillary leakage was only detected if PAF was administrated. Conclusions Regardless of the triggering event(s), KC, MIP-2 and integrins participate in TRALI pathogenesis, whereas PAF is essential for capillary leakage when two events are involved.

The concept of quasi-integrability for modified non-linear Schrodinger models

We consider modifications of the nonlinear Schrodinger model (NLS) to look at the recently introduced concept of quasi-integrability. We show that such models possess an in finite number of quasi-conserved charges which present intriguing properties in relation to very specific space-time parity transformations. For the case of two-soliton solutions where the fields are eigenstates of this parity, those charges are asymptotically conserved in the scattering process of the solitons. Even though the charges vary in time their values in the far past and the far future are the same. Such results are obtained through analytical and numerical methods, and employ adaptations of algebraic techniques used in integrable field theories. Our findings may have important consequences on the applications of these models in several areas of non-linear science. We make a detailed numerical study of the modified NLS potential of the form V similar to (vertical bar psi vertical bar(2))(2+epsilon), with epsilon being a perturbation parameter. We perform numerical simulations of the scattering of solitons for this model and find a good agreement with the results predicted by the analytical considerations. Our paper shows that the quasi-integrability concepts recently proposed in the context of modifications of the sine-Gordon model remain valid for perturbations of the NLS model.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

Residence Time Distribution Models Derived from Non-Ideal Laminar Velocity Profiles in Tubes

The theoretical E-curve for the laminar flow of non-Newtonian fluids in circular tubes may not be accurate for real tubular systems with diffusion, mechanical vibration, wall roughness, pipe fittings, curves, coils, or corrugated walls. Deviations from the idealized laminar flow reactor (LFR) cannot be well represented using the axial dispersion or the tanks-in-series models of residence time distribution (RTD). In this work, four RTD models derived from non-ideal velocity profiles in segregated tube flow are proposed. They were used to represent the RTD of three tubular systems working with Newtonian and pseudoplastic fluids. Other RTD models were considered for comparison. The proposed models provided good adjustments, and it was possible to determine the active volumes. It is expected that these models can be useful for the analysis of LFR or for the evaluation of continuous thermal processing of viscous foods.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.