Targeting the intragraft microenvironment and the development of chronic allograft rejection.

In this review, we discuss a paradigm whereby changes in the intragraft microenvironment promote or sustain the development of chronic allograft rejection. A key feature of this model involves the microvasculature including (a) endothelial cell (EC) destruction, and (b) EC proliferation, both of which result from alloimmune leukocyte- and/or alloantibody-induced responses. These changes in the microvasculature likely create abnormal blood flow patterns and thus promote local tissue hypoxia. Another feature of the chronic rejection microenvironment involves the overexpression of vascular endothelial growth factor (VEGF). VEGF stimulates EC activation and proliferation and it has potential to sustain inflammation via direct interactions with leukocytes. In this manner, VEGF may promote ongoing tissue injury. Finally, we review how these events can be targeted therapeutically using mTOR inhibitors. EC activation and proliferation as well as VEGF-VEGFR interactions require PI-3K/Akt/mTOR intracellular signaling. Thus, agents that inhibit this signaling pathway within the graft may also target the progression of chronic rejection and thus promote long-term graft survival.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Morbidity, survival, and site of recurrence after mediastinal lymph-node dissection versus systematic sampling after complete resection for non-small cell lung cancer

BACKGROUND: Mediastinal lymph-node dissection was compared to systematic mediastinal lymph-node sampling in patients undergoing complete resection for non-small cell lung cancer with respect to morbidity, duration of chest tube drainage and hospitalization, survival, disease-free survival, and site of recurrence. METHODS: A consecutive series of one hundred patients with non-small-cell lung cancer, clinical stage T1-3 N0-1 after standardized staging, was divided into two groups of 50 patients each, according to the technique of intraoperative mediastinal lymph-node assessment (dissection versus sampling). Mediastinal lymph-node dissection consisted of removal of all lymphatic tissues within defined anatomic landmarks of stations 2-4 and 7-9 on the right side, and stations 4-9 on the left side according to the classification of the American Thoracic Society. Systematic mediastinal lymph-node sampling consisted of harvesting of one or more representative lymph nodes from stations 2-4 and 7-9 on the right side, and stations 4-9 on the left side. RESULTS: All patients had complete resection. A mean follow-up time of 89 months was achieved in 92 patients. The two groups of patients were comparable with respect to age, gender, performance status, tumor stage, histology, extent of lung resection, and follow-up time. No significant difference was found between both groups regarding the duration of chest tube drainage, hospitalization, and morbidity. However, dissection required a longer operation time than sampling (179 +/- 38 min versus 149 +/- 37 min, p < 0.001). There was no significant difference in overall survival between the two groups; however, patients with stage I disease had a significantly longer disease-free survival after dissection than after sampling (60.2 +/- 7 versus 44.8 +/- 8 months, p < 0.03). Local recurrence was significantly higher after sampling than after dissection in patients with stage I tumor (12.5% versus 45%, p = 0.02) and in patients with nodal tumor negative mediastinum (N0/N1 disease) (46% versus 13%, p = 0.004). CONCLUSION: Our results suggest that mediastinal lymph-node dissection may provide a longer disease-free survival in stage I non-small cell lung cancer and, most importantly, a better local tumor control than mediastinal lymph-node sampling after complete resection for N0/N1 disease without leading to increased morbidity.

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

Speculative parallelization of multipath radiosity algorithm

In computer graphics, global illumination algorithms take into account not only the light that comes directly from the sources, but also the light interreflections. This kind of algorithms produce very realistic images, but at a high computational cost, especially when dealing with complex environments. Parallel computation has been successfully applied to such algorithms in order to make it possible to compute highly-realistic images in a reasonable time. We introduce here a speculation-based parallel solution for a global illumination algorithm in the context of radiosity, in which we have taken advantage of the hierarchical nature of such an algorithm

Partial disjoint path for multi-layer protection in GMPLS networks

In this paper, different recovery methods applied at different network layers and time scales are used in order to enhance the network reliability. Each layer deploys its own fault management methods. However, current recovery methods are applied to only a specific layer. New protection schemes, based on the proposed partial disjoint path algorithm, are defined in order to avoid protection duplications in a multi-layer scenario. The new protection schemes also encompass shared segment backup computation and shared risk link group identification. A complete set of experiments proves the efficiency of the proposed methods in relation with previous ones, in terms of resources used to protect the network, the failure recovery time and the request rejection ratio

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Gene transfer of interleukin-18-binding protein attenuates cardiac allograft rejection.

Interleukin (IL) 18 is a potent pro-inflammatory Th1 cytokine that exerts pleiotropic effector functions in both innate and acquired immune responses. Increased IL-18 production during acute rejection has been reported in experimental heart transplantation models and in kidney transplant recipients. IL-18-binding protein (IL-18BP) binds IL-18 with high affinity and neutralizes its biologic activity. We have analyzed the efficacy of an adenoviral vector expressing an IL-18BP-Ig fusion protein in a rat model of heart transplantation. IL-18BP-Ig gene transfer into Fisher (F344) rat donor hearts resulted in prolonged graft survival in Lewis recipients (15.8 +/- 1.4 days vs. 10.3 +/- 2.5 and 10.1 +/- 2.1 days with control virus and buffer solution alone, respectively; P < 0.001). Immunohistochemical analysis revealed decreased intra-graft infiltrates of monocytes/macrophages, CD4(+), CD8alpha(+) and T-cell receptor alphabeta(+) cells after IL-18BP-Ig versus mock gene transfer (P < 0.05). Real-time reverse transcriptase polymerase chain reaction analysis showed decreased cytokine transcripts for the RANTES chemokine and transforming growth factor-beta after IL-18BP-Ig gene transfer (P < 0.05). IL-18BP-Ig gene transfer attenuates inflammatory cell infiltrates and prolongs cardiac allograft survival in rats. These results suggest a contributory role for IL-18 in acute rejection. Further studies aiming at defining the therapeutic potential of IL-18BP are warranted.

Preanalytical mistakes in samples from primary care patients.

BACKGROUND Preanalytical mistakes (PAMs) in samples usually led to rejection upon arrival to the clinical laboratory. However, PAMs might not always be detected and result in clinical problems. Thus, PAMs should be minimized. We detected PAMs in samples from Primary Health Care Centres (PHCC) served by our central laboratory. Thus, the goal of this study was to describe the number and types of PAMs, and to suggest some strategies for improvement. METHODS The presence of PAMs, as sample rejection criteria, in samples submitted from PHCC to our laboratory during October and November 2007 was retrospectively analysed. RESULTS Overall, 3885 PAMs (7.4%) were detected from 52,669 samples for blood analyses. This included missed samples (n=1763; 45.4% of all PAMs, 3.3% of all samples), haemolysed samples (n=1408; 36.2% and 2.7%, respectively), coagulated samples (n=391; 10% and 0.7%, respectively), incorrect sample volume (n=110; 2.8% and 0.2%, respectively), and others (n=213; 5.5% and 0.4%, respectively). For urine samples (n=18,852), 1567 of the samples were missing (8.3%). CONCLUSIONS We found the proportion of PAMs in blood and urine samples to be 3-fold higher than that reported in the literature. Therefore, strategies for improvement directed towards the staff involved, as well as an exhaustive audit of preanalytical process are needed. To attain this goal, we first implemented a continued education programme, financed by our Regional Health Service and focused in Primary Care Nurses.

Field optimisation of MosquiTRAP sampling for monitoring Aedes aegypti Linnaeus (Diptera: Culicidae)

A sticky trap designed to capture gravid Aedes (Stegomyia) aegypti mosquitoes, MosquiTRAP, has been evaluated for monitoring this species in Brazil. However, the effects of trap densities on the capture rate of Ae. aegypti females and the sensitivity of vector detection are still unknown. After a preliminary study has identified areas of high and low female mosquito abundance, a set of experiments was conducted in four neighbourhoods of Belo Horizonte (state of Minas Gerais, Brazil) using densities of 1, 2, 4, 8, 16, 32 and 64 traps per block. Trap sensitivity (positive MosquiTRAP index) increased significantly when 1-8 MosquiTRAPs were installed per block in both high and low abundance areas. A strong fit was obtained for the total number of mosquitoes captured with increasing trap densities through a non-linear function (Box-Lucas) (r² = 0,994), which likely exhibits saturation towards an equilibrium level. The capacity of the Mean Female Aedes Index to distinguish between areas of high and low Ae. aegypti abundance was also investigated; the achieved differentiation was shown to be dependent on the MosquiTRAP density.

Constraint algorithm for k-presymplectic Hamiltonian systems. Application to singular field theories

The k-symplectic formulation of field theories is especially simple, since only tangent and cotangent bundles are needed in its description. Its defining elements show a close relationship with those in the symplectic formulation of mechanics. It will be shown that this relationship also stands in the presymplectic case. In a natural way,one can mimick the presymplectic constraint algorithm to obtain a constraint algorithmthat can be applied to k-presymplectic field theory, and more particularly to the Lagrangian and Hamiltonian formulations offield theories defined by a singular Lagrangian, as well as to the unified Lagrangian-Hamiltonian formalism (Skinner--Rusk formalism) for k-presymplectic field theory. Two examples of application of the algorithm are also analyzed.