Major Depletion of Plasmacytoid Dendritic Cells in HIV-2 Infection, an Attenuated Form of HIV Disease

Plasmacytoid dendritic cells (pDC) provide an important link between innate and acquired immunity, mediating their action mainly through IFN-α production. pDC suppress HIV-1 replication, but there is increasing evidence suggesting they may also contribute to the increased levels of cell apoptosis and pan-immune activation associated with disease progression. Although having the same clinical spectrum, HIV-2 infection is characterized by a strikingly lower viremia and a much slower rate of CD4 decline and AIDS progression than HIV-1, irrespective of disease stage. We report here a similar marked reduction in circulating pDC levels in untreated HIV-1 and HIV-2 infections in association with CD4 depletion and T cell activation, in spite of the undetectable viremia found in the majority of HIV-2 patients. Moreover, the same overexpression of CD86 and PD-L1 on circulating pDC was found in both infections irrespective of disease stage or viremia status. Our observation that pDC depletion occurs in HIV-2 infected patients with undetectable viremia indicates that mechanisms other than direct viral infection determine the pDC depletion during persistent infections. However, viremia was associated with an impairment of IFN-α production on a per pDC basis upon TLR9 stimulation. These data support the possibility that diminished function in vitro may relate to prior activation by HIV virions in vivo, in agreement with our finding of higher expression levels of the IFN-α inducible gene, MxA, in HIV-1 than in HIV-2 individuals. Importantly, serum IFN-α levels were not elevated in HIV-2 infected individuals. In conclusion, our data in this unique natural model of “attenuated” HIV immunodeficiency contribute to the understanding of pDC biology in HIV/AIDS pathogenesis, showing that in the absence of detectable viremia a major depletion of circulating pDC in association with a relatively preserved IFN-α production does occur

Optimization for large scale process based on evolutionary algorithms: Genetic algorithms

This work has as objective the development of an optimization methodology, using Genetic Algorithms (GAs), as evolutionary procedure coupled with the concepts of evolutionary. As case study a large scale multiphase catalytic reactor is considered. The reactor is tubular in shape and is built-up with concentric tubes using the same concept of the auto-thermal reactors, with coolant fluid flow in the external annular. The mathematical equations of the deterministic model are based on conservation principles (mass, energy and momentum) for the reactants and for the coolant fluid and validated with real operational data. The model represents the steady-state with the plug-flow assumption which is quite reasonable due to the large flow rates usually found in industrial reactors. The desired product is a specific cyclical alcohol (CA), and the minimization of the by-products is required for economical and environmental reasons. For that it is necessary to optimize some important operational parameters. This problem is of difficult solution since the reactor is a large scale system with complex behavior and conventional optimization tools as Successive Quadratic Programming tends to fail in such situation since local minima may be achieved. In this work is shown that the Genetic Algorithms technique can be useful to CA production maximization, obtaining good results with operational improvements (reduction in the catalyst rate, as well as in the undesired product rate-cycloalkane (C)). The GA parameters used for the process optimization are population size, crossover types with variation of crossover rates. The used coding was the binary form. The results are quite good, showing high performance in the CA productivity (considerable increase CA production) with changes in the operational parameters analyzed and showing that this optimization procedure is very robust and efficient. The results point out that this technique is very promising to deal with large scale system with complex behavior due to non-linearity and variable interactions. (c) 2007 Elsevier B.V. All rights reserved.132416991

Identifying pre-hospital factors associated with outcome for major trauma patients in a regional trauma network: an exploratory study

Background: Major trauma is often life threatening and the leading cause of death in the United Kingdom (UK) for adults aged less than 45 years old. This study aimed to identify pre-hospital factors associated with patient outcomes for major trauma within one Regional Trauma Network. Method: Secondary analysis of pre-hospital audit data and patient outcome data from the Trauma Audit Research Network (TARN) was undertaken. The primary outcome used in analysis was ‘Status at Discharge’ (alive/deceased). Independent variables considered included ‘Casualty Characteristics’ such as mechanism of injury (MOI), age, and physiological measurements, as well as ‘Response Characteristics’ such as response timings and skill mix. Binary Logistic Regression analysis using the ‘forward stepwise’ method was undertaken for physiological measures taken at the scene. Results: The study analysed 1033 major trauma records (mean age of 38.5 years, SD 21.5, 95% CI 37-40). Adults comprised 82.6% of the sample (n=853), whilst 12.9% of the sample were children (n=133). Men comprised 68.5% of the sample (n=708) in comparison to 28.8% women (n=298). Glasgow Coma Score (GCS) (p < 0.000), Respiration Rate (p < 0.001) and Age (p < 0.000), were all significant when associated with the outcome ‘Status at Discharge’ (alive/deceased). Isolated bivariate associations provided tentative support for response characteristics such as existing dispatching practices and the value of rapid crew arrival. However, these measurements appear to be of limited utility in predictive modelling of outcomes. Conclusion: Findings lend further validity to GCS, Respiration Rate and Age as predictive triggers for transport to a Major Trauma Centre. Analysis of interactions between response times, skill mix and triage demand further exploration but tentatively support the ‘Golden Hour’ concept and suggest a potential ‘load and go and play on the way’ approach