Treatment rationale and study design for a phase III, double-blind, placebo-controlled study of maintenance pemetrexed plus best supportive care versus best supportive care immediately following induction treatment with pemetrexed plus cisplatin for advanced nonsquamous non-small cell lung cancer.

BACKGROUND: To improve the efficacy of first-line therapy for advanced non-small cell lung cancer (NSCLC), additional maintenance chemotherapy may be given after initial induction chemotherapy in patients who did not progress during the initial treatment, rather than waiting for disease progression to administer second-line treatment. Maintenance therapy may consist of an agent that either was or was not present in the induction regimen. The antifolate pemetrexed is efficacious in combination with cisplatin for first-line treatment of advanced NSCLC and has shown efficacy as a maintenance agent in studies in which it was not included in the induction regimen. We designed a phase III study to determine if pemetrexed maintenance therapy improves progression-free survival (PFS) and overall survival (OS) after cisplatin/pemetrexed induction therapy in patients with advanced nonsquamous NSCLC. Furthermore, since evidence suggests expression levels of thymidylate synthase, the primary target of pemetrexed, may be associated with responsiveness to pemetrexed, translational research will address whether thymidylate synthase expression correlates with efficacy outcomes of pemetrexed. METHODS/DESIGN: Approximately 900 patients will receive four cycles of induction chemotherapy consisting of pemetrexed (500 mg/m2) and cisplatin (75 mg/m2) on day 1 of a 21-day cycle. Patients with an Eastern Cooperative Oncology Group performance status of 0 or 1 who have not progressed during induction therapy will randomly receive (in a 2:1 ratio) one of two double-blind maintenance regimens: pemetrexed (500 mg/m2 on day 1 of a 21-day cycle) plus best supportive care (BSC) or placebo plus BSC. The primary objective is to compare PFS between treatment arms. Secondary objectives include a fully powered analysis of OS, objective tumor response rate, patient-reported outcomes, resource utilization, and toxicity. Tumor specimens for translational research will be obtained from consenting patients before induction treatment, with a second biopsy performed in eligible patients following the induction phase. DISCUSSION: Although using a drug as maintenance therapy that was not used in the induction regimen exposes patients to an agent with a different mechanism of action, evidence suggests that continued use of an agent present in the induction regimen as maintenance therapy enables the identification of patients most likely to benefit from maintenance treatment.

Gap junction reduction in cardiomyocytes following transforming growth factor-β treatment and Trypanosoma cruzi infection

Gap junction connexin-43 (Cx43) molecules are responsible for electrical impulse conduction in the heart and are affected by transforming growth factor-β (TGF-β). This cytokine increases during Trypanosoma cruzi infection, modulating fibrosis and the parasite cell cycle. We studied Cx43 expression in cardiomyocytes exposed or not to TGF-β T. cruzi, or SB-431542, an inhibitor of TGF-β receptor type I (ALK-5). Cx43 expression was also examined in hearts with dilated cardiopathy from chronic Chagas disease patients, in which TGF-β signalling had been shown previously to be highly activated. We demonstrated that TGF-β treatment induced disorganised gap junctions in non-infected cardiomyocytes, leading to a punctate, diffuse and non-uniform Cx43 staining. A similar pattern was detected in T. cruzi-infected cardiomyocytes concomitant with high TGF-β secretion. Both results were reversed if the cells were incubated with SB-431542. Similar tests were performed using human chronic chagasic patients and we confirmed a down-regulation of Cx43 expression, an altered distribution of plaques in the heart and a significant reduction in the number and length of Cx43 plaques, which correlated negatively with cardiomegaly. We conclude that elevated TGF-β levels during T. cruzi infection promote heart fibrosis and disorganise gap junctions, possibly contributing to abnormal impulse conduction and arrhythmia that characterise severe cardiopathy in Chagas disease.

Management of bleeding following major trauma: a European guideline

INTRODUCTION Evidence-based recommendations can be made with respect to many aspects of the acute management of the bleeding trauma patient, which when implemented may lead to improved patient outcomes. METHODS The multidisciplinary Task Force for Advanced Bleeding Care in Trauma was formed in 2005 with the aim of developing guidelines for the management of bleeding following severe injury. Recommendations were formulated using a nominal group process and the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) hierarchy of evidence and were based on a systematic review of published literature. RESULTS Key recommendations include the following: The time elapsed between injury and operation should be minimised for patients in need of urgent surgical bleeding control, and patients presenting with haemorrhagic shock and an identified source of bleeding should undergo immediate surgical bleeding control unless initial resuscitation measures are successful. A damage control surgical approach is essential in the severely injured patient. Pelvic ring disruptions should be closed and stabilised, followed by appropriate angiographic embolisation or surgical bleeding control, including packing. Patients presenting with haemorrhagic shock and an unidentified source of bleeding should undergo immediate further assessment as appropriate using focused sonography, computed tomography, serum lactate, and/or base deficit measurements. This guideline also reviews appropriate physiological targets and suggested use and dosing of blood products, pharmacological agents, and coagulation factor replacement in the bleeding trauma patient. CONCLUSION A multidisciplinary approach to the management of the bleeding trauma patient will help create circumstances in which optimal care can be provided. By their very nature, these guidelines reflect the current state-of-the-art and will need to be updated and revised as important new evidence becomes available.

Sulfur isotope analysis of cinnabar from Roman wall paintings by elemental analysis/isotope ratio mass spectrometry - tracking the origin of archaeological red pigments and their authenticity

The most valuable pigment of the Roman wall paintings was the red color obtained from powdered cinnabar (Minium Cinnabaris pigment), the red mercury sulfide (HgS), which was brought from mercury (Hg) deposits in the Roman Empire. To address the question of whether sulfur isotope signatures can serve as a rapid method to establish the provenance of the red pigment in Roman frescoes, we have measured the sulfur isotope composition (delta(34) S value in parts per thousand VCDT) in samples of wall painting from the Roman city Aventicum (Avenches, Vaud, Switzerland) and compared them with values from cinnabar from European mercury deposits (Almaden in Spain, Idria in Slovenia, Monte Amiata in Italy, Moschellandsberg in Germany, and Genepy in France). Our study shows that the delta(34) S values of cinnabar from the studied Roman wall paintings fall within or near to the composition of Almaden cinnabar; thus, the provenance of the raw material may be deduced. This approach may provide information on provenance and authenticity in archaeological, restoration and forensic studies of Roman and Greek frescoes. Copyright (c) 2010 John Wiley & Sons, Ltd.

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).

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

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

Dam wall detection and tracking using a Mechanically Scanned Imaging Sonar

In dam inspection tasks, an underwater robot has to grab images while surveying the wall meanwhile maintaining a certain distance and relative orientation. This paper proposes the use of an MSIS (mechanically scanned imaging sonar) for relative positioning of a robot with respect to the wall. An imaging sonar gathers polar image scans from which depth images (range & bearing) are generated. Depth scans are first processed to extract a line corresponding to the wall (with the Hough transform), which is then tracked by means of an EKF (Extended Kalman Filter) using a static motion model and an implicit measurement equation associating the sensed points to the candidate line. The line estimate is referenced to the robot fixed frame and represented in polar coordinates (rho&thetas) which directly corresponds to the actual distance and relative orientation of the robot with respect to the wall. The proposed system has been tested in simulation as well as in water tank conditions

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

Complete longitudinal analyses of the randomized, placebo-controlled, phase III trial of sunitinib in patients with gastrointestinal stromal tumor following imatinib failure.

PURPOSE: To analyze final long-term survival and clinical outcomes from the randomized phase III study of sunitinib in gastrointestinal stromal tumor patients after imatinib failure; to assess correlative angiogenesis biomarkers with patient outcomes. EXPERIMENTAL DESIGN: Blinded sunitinib or placebo was given daily on a 4-week-on/2-week-off treatment schedule. Placebo-assigned patients could cross over to sunitinib at disease progression/study unblinding. Overall survival (OS) was analyzed using conventional statistical methods and the rank-preserving structural failure time (RPSFT) method to explore cross-over impact. Circulating levels of angiogenesis biomarkers were analyzed. RESULTS: In total, 243 patients were randomized to receive sunitinib and 118 to placebo, 103 of whom crossed over to open-label sunitinib. Conventional statistical analysis showed that OS converged in the sunitinib and placebo arms (median 72.7 vs. 64.9 weeks; HR, 0.876; P = 0.306) as expected, given the cross-over design. RPSFT analysis estimated median OS for placebo of 39.0 weeks (HR, 0.505, 95% CI, 0.262-1.134; P = 0.306). No new safety concerns emerged with extended sunitinib treatment. No consistent associations were found between the pharmacodynamics of angiogenesis-related plasma proteins during sunitinib treatment and clinical outcome. CONCLUSIONS: The cross-over design provided evidence of sunitinib clinical benefit based on prolonged time to tumor progression during the double-blind phase of this trial. As expected, following cross-over, there was no statistical difference in OS. RPSFT analysis modeled the absence of cross-over, estimating a substantial sunitinib OS benefit relative to placebo. Long-term sunitinib treatment was tolerated without new adverse events.

A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

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