Improving Reconstituted HDL Composition for Efficient Post-Ischemic Reduction of Ischemia Reperfusion Injury.

BACKGROUND: New evidence shows that high density lipoproteins (HDL) have protective effects beyond their role in reverse cholesterol transport. Reconstituted HDL (rHDL) offer an attractive means of clinically exploiting these novel effects including cardioprotection against ischemia reperfusion injury (IRI). However, basic rHDL composition is limited to apolipoprotein AI (apoAI) and phospholipids; addition of bioactive compound may enhance its beneficial effects. OBJECTIVE: The aim of this study was to investigate the role of rHDL in post-ischemic model, and to analyze the potential impact of sphingosine-1-phosphate (S1P) in rHDL formulations. METHODS AND RESULTS: The impact of HDL on IRI was investigated using complementary in vivo, ex vivo and in vitro IRI models. Acute post-ischemic treatment with native HDL significantly reduced infarct size and cell death in the ex vivo, isolated heart (Langendorff) model and the in vivo model (-48%, p<0.01). Treatment with rHDL of basic formulation (apoAI + phospholipids) had a non-significant impact on cell death in vitro and on the infarct size ex vivo and in vivo. In contrast, rHDL containing S1P had a highly significant, protective influence ex vivo, and in vivo (-50%, p<0.01). This impact was comparable with the effects observed with native HDL. Pro-survival signaling proteins, Akt, STAT3 and ERK1/2 were similarly activated by HDL and rHDL containing S1P both in vitro (isolated cardiomyocytes) and in vivo. CONCLUSION: HDL afford protection against IRI in a clinically relevant model (post-ischemia). rHDL is significantly protective if supplemented with S1P. The protective impact of HDL appears to target directly the cardiomyocyte.

Assessing the assignation of public subsidies: Do the experts choose the most efficient R and D projects?

[spa] La implementación de un programa de subvenciones públicas a proyectos empresariales de I+D comporta establecer un sistema de selección de proyectos. Esta selección se enfrenta a problemas relevantes, como son la medición del posible rendimiento de los proyectos de I+D y la optimización del proceso de selección entre proyectos con múltiples y a veces incomparables medidas de resultados. Las agencias públicas utilizan mayoritariamente el método peer review que, aunque presenta ventajas, no está exento de críticas. En cambio, las empresas privadas con el objetivo de optimizar su inversión en I+D utilizan métodos más cuantitativos, como el Data Envelopment Análisis (DEA). En este trabajo se compara la actuación de los evaluadores de una agencia pública (peer review) con una metodología alternativa de selección de proyectos como es el DEA.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

New formulation of vasoactive intestinal peptide using liposomes in hyaluronic acid gel for uveitis.

We evaluated the benefits of a novel formulation of vasoactive intestinal peptide (VIP) based on the incorporation of VIP-loaded rhodamine-conjugated liposomes (VIP-Rh-Lip) within hyaluronic acid (HA) gel (Gel-VIP-Rh-Lip) for the treatment of endotoxin-induced uveitis (EIU) in comparison with VIP-Rh-Lip alone. In vitro release study and rheological analysis showed that interactions between HA chains and liposomes resulted in increased viscosity and reinforced elasticity of the gel. In vivo a single intravitreal injection of Gel-VIP-Rh-Lip was performed in rats 7 days prior to uveitis induction by subcutaneous lipopolysaccharide injection. The maximal ocular inflammation occurs within 16-24 h in controls (VIP-Rh-Lip, unloaded-Rh-Lip). Whereas intraocular injection of VIP-Rh-Lip had no effect on EIU severity compared with controls, Gel-VIP-Rh-Lip reduced significantly the clinical score and number of inflammatory cells infiltrating the eye. The fate of liposomes, VIP and HA in the eyes, regional and inguinal lymph nodes and spleen was analyzed by immunostaining and fluorescence microscopy. Retention of liposomes by HA gel was observed in vitro and in vivo. Inflammation severity seemed to impact on system stability resulting in the delayed release of VIP. Thus, HA gel containing VIP-Rh-Lip is an efficient strategy to obtain a sustained delivery of VIP in ocular and lymph node tissues.

A regulatory network for the efficient control of transgene expression.

BACKGROUND: Expression of heterologous genes in mammalian cells or organisms for therapeutic or experimental purposes often requires tight control of transgene expression. Specifically, the following criteria should be met: no background gene activity in the off-state, high gene expression in the on-state, regulated expression over an extended period, and multiple switching between on- and off-states. METHODS: Here, we describe a genetic switch system for controlled transgene transcription using chimeric repressor and activator proteins functioning in a novel regulatory network. In the off-state, the target transgene is actively silenced by a chimeric protein consisting of multimerized eukaryotic transcriptional repression domains fused to the DNA-binding tetracycline repressor. In the on-state, the inducer drug doxycycline affects both the derepression of the target gene promoter and activation by the GAL4-VP16 transactivator, which in turn is under the control of an autoregulatory feedback loop. RESULTS: The hallmark of this new system is the efficient transgene silencing in the off-state, as demonstrated by the tightly controlled expression of the highly cytotoxic diphtheria toxin A gene. Addition of the inducer drug allows robust activation of transgene expression. In stably transfected cells, this control is still observed after months of repeated cycling between the repressed and activated states of the target genes. CONCLUSIONS: This system permits tight long-term regulation when stably introduced into cell lines. The underlying principles of this network system should have general applications in biotechnology and gene therapy.

Endoleak and in-stent thrombus detection with CT angiography in a thoracic aortic aneurysm phantom at different tube energies using filtered back projection and iterative algorithms.

PURPOSE: To determine the lower limit of dose reduction with hybrid and fully iterative reconstruction algorithms in detection of endoleaks and in-stent thrombus of thoracic aorta with computed tomographic (CT) angiography by applying protocols with different tube energies and automated tube current modulation. MATERIALS AND METHODS: The calcification insert of an anthropomorphic cardiac phantom was replaced with an aortic aneurysm model containing a stent, simulated endoleaks, and an intraluminal thrombus. CT was performed at tube energies of 120, 100, and 80 kVp with incrementally increasing noise indexes (NIs) of 16, 25, 34, 43, 52, 61, and 70 and a 2.5-mm section thickness. NI directly controls radiation exposure; a higher NI allows for greater image noise and decreases radiation. Images were reconstructed with filtered back projection (FBP) and hybrid and fully iterative algorithms. Five radiologists independently analyzed lesion conspicuity to assess sensitivity and specificity. Mean attenuation (in Hounsfield units) and standard deviation were measured in the aorta to calculate signal-to-noise ratio (SNR). Attenuation and SNR of different protocols and algorithms were analyzed with analysis of variance or Welch test depending on data distribution. RESULTS: Both sensitivity and specificity were 100% for simulated lesions on images with 2.5-mm section thickness and an NI of 25 (3.45 mGy), 34 (1.83 mGy), or 43 (1.16 mGy) at 120 kVp; an NI of 34 (1.98 mGy), 43 (1.23 mGy), or 61 (0.61 mGy) at 100 kVp; and an NI of 43 (1.46 mGy) or 70 (0.54 mGy) at 80 kVp. SNR values showed similar results. With the fully iterative algorithm, mean attenuation of the aorta decreased significantly in reduced-dose protocols in comparison with control protocols at 100 kVp (311 HU at 16 NI vs 290 HU at 70 NI, P ≤ .0011) and 80 kVp (400 HU at 16 NI vs 369 HU at 70 NI, P ≤ .0007). CONCLUSION: Endoleaks and in-stent thrombus of thoracic aorta were detectable to 1.46 mGy (80 kVp) with FBP, 1.23 mGy (100 kVp) with the hybrid algorithm, and 0.54 mGy (80 kVp) with the fully iterative algorithm.

Granulocyte-macrophage colony-stimulating factor elicits bone marrow-derived cells that promote efficient colonic mucosal healing.

BACKGROUND: Granulocyte-macrophage colony-stimulating factor (GM-CSF) therapy is effective in treating some Crohn's disease (CD) patients and protects mice from colitis induced by dextran sulfate sodium (DSS) administration. However, its mechanisms of action remain elusive. We hypothesized that GM-CSF affects intestinal mucosal repair. METHODS: DSS colitic mice were treated with daily pegylated GM-CSF or saline and clinical, histological, and inflammatory parameters were kinetically evaluated. Further, the role of bone marrow-derived cells in the impact of GM-CSF therapy on DSS colitis was addressed using cell transfers. RESULTS: GM-CSF therapy reduced clinical signs of colitis and the release of inflammatory mediators. GM-CSF therapy improved mucosal repair, with faster ulcer reepithelialization, accelerated hyperproliferative response of epithelial cells in ulcer-adjacent crypts, and lower colonoscopic ulceration scores in GM-CSF-administered mice relative to untreated mice. We observed that GM-CSF-induced promotion of mucosal repair is timely associated with a reduction in neutrophil numbers and increased accumulation of CD11b(+) monocytic cells in colon tissues. Importantly, transfer of splenic GM-CSF-induced CD11b(+) myeloid cells into DSS-exposed mice improved colitis, and lethally irradiated GM-CSF receptor-deficient mice reconstituted with wildtype bone marrow cells were protected from DSS-induced colitis upon GM-CSF therapy. Lastly, GM-CSF-induced CD11b(+) myeloid cells were shown to promote in vitro wound repair. CONCLUSIONS: Our study shows that GM-CSF-dependent stimulation of bone marrow-derived cells during DSS-induced colitis accelerates colonic tissue repair. These data provide a putative mechanism for the observed beneficial effects of GM-CSF therapy in Crohn's disease.

Evolving team compositions by agent swapping

Optimizing collective behavior in multiagent systems requires algorithms to find not only appropriate individual behaviors but also a suitable composition of agents within a team. Over the last two decades, evolutionary methods have emerged as a promising approach for the design of agents and their compositions into teams. The choice of a crossover operator that facilitates the evolution of optimal team composition is recognized to be crucial, but so far, it has never been thoroughly quantified. Here, we highlight the limitations of two different crossover operators that exchange entire agents between teams: restricted agent swapping (RAS) that exchanges only corresponding agents between teams and free agent swapping (FAS) that allows an arbitrary exchange of agents. Our results show that RAS suffers from premature convergence, whereas FAS entails insufficient convergence. Consequently, in both cases, the exploration and exploitation aspects of the evolutionary algorithm are not well balanced resulting in the evolution of suboptimal team compositions. To overcome this problem, we propose combining the two methods. Our approach first applies FAS to explore the search space and then RAS to exploit it. This mixed approach is a much more efficient strategy for the evolution of team compositions compared to either strategy on its own. Our results suggest that such a mixed agent-swapping algorithm should always be preferred whenever the optimal composition of individuals in a multiagent system is unknown.

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

On the efficient evaluation of ruin probabilities for completely monotone claim size distributions

In this paper we propose a highly accurate approximation procedure for ruin probabilities in the classical collective risk model, which is based on a quadrature/rational approximation procedure proposed in [2]. For a certain class of claim size distributions (which contains the completely monotone distributions) we give a theoretical justification for the method. We also show that under weaker assumptions on the claim size distribution, the method may still perform reasonably well in some cases. This in particular provides an efficient alternative to a related method proposed in [3]. A number of numerical illustrations for the performance of this procedure is provided for both completely monotone and other types of random variables.

Critical clusters and efficient dynamics for frustrated spin models

A general method to find, in a systematic way, efficient Monte Carlo cluster dynamics among the avast class of dynamics introduced by Kandel et al. [Phys. Rev. Lett. 65, 941 (1990)] is proposed. The method is successfully applied to a class of frustrated two-dimensional Ising systems. In the case of the fully frustrated model, we also find the intriguing result that critical clusters consist of self-avoiding walk at the theta point.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Automated scoring of AFLPs using RawGeno v 2.0, a free R CRAN library.

Amplified Fragment Length Polymorphisms (AFLPs) are a cheap and efficient protocol for generating large sets of genetic markers. This technique has become increasingly used during the last decade in various fields of biology, including population genomics, phylogeography, and genome mapping. Here, we present RawGeno, an R library dedicated to the automated scoring of AFLPs (i.e., the coding of electropherogram signals into ready-to-use datasets). Our program includes a complete suite of tools for binning, editing, visualizing, and exporting results obtained from AFLP experiments. RawGeno can either be used with command lines and program analysis routines or through a user-friendly graphical user interface. We describe the whole RawGeno pipeline along with recommendations for (a) setting the analysis of electropherograms in combination with PeakScanner, a program freely distributed by Applied Biosystems; (b) performing quality checks; (c) defining bins and proceeding to scoring; (d) filtering nonoptimal bins; and (e) exporting results in different formats.

CPT-11 and concomitant hyperfractionated accelerated radiotherapy induce efficient local control in rectal cancer patients: results from a phase II.

Patients with rectal cancer are at high risk of disease recurrence despite neoadjuvant radiochemotherapy with 5-Fluorouracil (5FU), a regimen that is now widely applied. In order to develop a regimen with increased antitumour activity, we previously established the recommended dose of neoadjuvant CPT-11 (three times weekly 90 mg m(-2)) concomitant to hyperfractionated accelerated radiotherapy (HART) followed by surgery within 1 week. Thirty-three patients (20 men) with a locally advanced adenocarcinoma of the rectum were enrolled in this prospective phase II trial (1 cT2, 29 cT3, 3 cT4 and 21 cN+). Median age was 60 years (range 43-75 years). All patients received all three injections of CPT-11 and all but two patients completed radiotherapy as planned. Surgery with total mesorectal excision (TME) was performed within 1 week (range 2-15 days). The preoperative chemoradiotherapy was overall well tolerated, 24% of the patients experienced grade 3 diarrhoea that was easily manageable. At a median follow-up of 2 years no local recurrence occurred, however, nine patients developed distant metastases. The 2-year disease-free survival was 66% (95% confidence interval 0.48-0.83). Neoadjuvant CPT-11 and HART allow for excellent local control; however, distant relapse remains a concern in this patient population.

CpG are efficient adjuvants for specific CTL induction against tumor antigen-derived peptide.

The identification of CTL-defined tumor-associated Ags has allowed the development of new strategies for cancer immunotherapy. To potentiate the CTL responses, peptide-based vaccines require the coadministration of adjuvants. Because oligodeoxynucleotides (ODN) containing CpG motifs are strong immunostimulators, we analyzed the ability of CpG ODN to act as adjuvant of the CTL response against tumor-derived synthetic peptide in the absence or presence of IFA. Mice transgenic for a chimeric MHC class I molecule were immunized with a peptide analog of MART-1/Melan-A(26-35) in the presence of CpG ODN alone or CpG ODN emulsified in IFA. The CTL response was monitored ex vivo by tetramer staining of lymphocytes. In blood, spleen, and lymph nodes, peptide mixed with CpG ODN alone was able to elicit a stronger systemic CTL response as compared with peptide emulsified in IFA. Moreover, CpG ODN in combination with IFA further enhanced the CTL response in terms of the frequency of tetramer+CD8+ T cells ex vivo. The CTL induced in vivo against peptide analog in the presence of CpG ODN are functional, as they were able to recognize and kill melanoma cells in vitro. Overall, these results indicate that CpG ODN by itself is a good candidate adjuvant of CTL response and can also enhance the effect of classical adjuvant.