Cell-based therapies for stroke : promising solution or dead end?

The introduction of recanalization procedures has revolutionized acute stroke management, although the narrow time window, strict eligibility criteria and logistical limitations still exclude the majority of patients from treatment. In addition, residual deficits are present in many patients who undergo therapy, preventing their return to premorbid status. Hence, there is a strong need for novel, and ideally complementary, approaches to stroke management. In preclinical experiments, cell-based treatments have demonstrated beneficial effects in the subacute and chronic stages following stroke [1; 2; 3] and therefore are considered a promising option to supplement current clinical practice. At the same time, great progress has been made in developing clinically feasible delivery and monitoring protocols [4]. However, efficacy results initially reported in clinical studies fell short of expectations [5] raising concerns that cell treatment might eventually share the ‘dead end fate’ of many previous experimental stroke therapies. This Research Topic reviews some of the latest and most innovative studies to summarize the state of the art in translational cell treatments for stroke

Self-Adapting Point Location

Point location in spatial subdivision is one of the most studied problems in computational geometry. In the case of triangulations of Rd, we revisit the problem to exploit a possible coherence between the query-points. For a single query, walking in the triangulation is a classical strategy with good practical behavior and expected complexity O(n^(1/d)) if the points are evenly distributed. For a batch of query-points, the main idea is to use previous queries to improve the current one; we compare various strategies that have an influence on the constant hidden in the big-O notation. Still regarding the complexity of a query, we show how the Delaunay hierarchy can be used to answer, under some hypotheses, a query q with a O(log #(pq) ) randomized expected complexity, where #(.) indicates the number of simplices crossed by the line pq, and p is a previously located query. The data structure has O(n log n) construction complexity and O(n) memory complexity

“Na minha profissão, eu divido com os outros, não faço nada sozinho”

Entrevista inédita com Olivier Toni. Leia biografia do entrevistado nas pp. 137-139

Longueur moyenne de la marche de Vornoi dans une triangulation de Poisson-Delaunay en dimension dd

Let $X_n$ be a $d$ dimensional Poisson point process of intensity $n$.We prove that the expected length of the Voronoi path between twopoints at distance 1 in the Delaunay triangulation associated with $X_n$ is $\sqrt{\frac{2d}{\pi}}+O(d^{-\frac{1}{2}})$ for all $n\in\mathbb{N}$ and $d\rightarrow\infty$.In any dimension, we provide a precise interval containing the exactvalue, in 3D the expected length is between 1.4977 and 1.50007.Soit $X_n$ un processus ponctuel de Poisson d'intensité $n$ endimension $d$.Nous démontrons que l'espérance de la longueur du chemin de Voronoientre l'origine et un point à distance 1 dans la triangulation deDelaunay de $X_n$ est $\sqrt{\frac{2d}{\pi}}+O(d^{-\frac{1}{2}})$pour tout $n\in\mathbb{N}$ quand $d\rightarrow\infty$.Nous donnons des bornes inférieures et supérieures sur la bonne valeuren toute dimension, en 3D ces bornes sont 1.4977 et 1.50007

Practical Distribution-Sensitive Point Location in Triangulations

International audienceWe design, analyze, implement, and evaluate a distribution-sensitive point location algorithm based on the classical Jump & Walk, called Keep, Jump, & Walk. For a batch of query points, the main idea is to use previous queries to improve the current one. In practice, Keep, Jump, & Walk is ac- tually a very competitive method to locate points in a triangulation. We also study some constant- memory distribution-sensitive point location algorithms, which work well in practice with the classical space-filling heuristic for fast point location. Regarding point location in a Delaunay triangulation, we show how the Delaunay hierarchy can be used to answer, under some hypotheses, a query q with a O(log #(pq)) randomized expected complexity, where p is a previously located query and #(s) indicates the number of simplices crossed by the line segment s. The Delaunay hierarchy has O(nlogn) time complexity and O(n) memory complexity in the plane, and under certain realistic hypotheses these com- plexities generalize to any finite dimension. Finally, we combine the good distribution-sensitive behavior of Keep, Jump, & Walk, and the good complexity of the Delaunay hierarchy, into a novel point location algorithm called Keep, Jump, & Climb. To the best of our knowledge, Keep, Jump, & Climb is the first practical distribution-sensitive algorithm that works both in theory and in practice for Delaunay triangulations

State of the Art: Updating Delaunay Triangulations for Moving Points

This paper considers the problem of updating efficiently a two-dimensional Delaunay triangulation when vertices are moving. We investigate the three current state-of-the-art approaches to solve this problem: --1-- the use of kinetic data structures, --2-- the possibility of moving points from their initial to final position by deletion and insertion and --3-- the use of "almost" Delaunay structure that postpone the necessary modifications. Finally, we conclude with a global overview of the above-mentioned approaches while focusing on future works

Walking Faster in a Triangulation

Point location in a triangulation is one of the most studied problems in computational geometry. For a single query, stochastic walk is a good practical strategy. In this work, we propose two approaches improving the performance of the stochastic walk. The first improvement is based on a relaxation of the exactness of the predicate, whereas the second is based on termination guessing.La localisation d'un point dans une triangulation est un des problèmes les plus étudiés en géométrie algorithmique. Pour un petit nombre de requêtes, la marche stochastique est une bonne stratégie en pratique. Dans ce travail, nous proposons deux idées qui améliorent les performances de la marche stochastique. La première est basée sur une relaxation de l'exactitude du prédicat d'orientation, tandis que la deuxième est basée sur lune tentative de divination de la longueur de cette marche

On the Size of Some Trees Embedded in Rd

This paper extends the result of Steele [6,5] on the worst-case length of the Euclidean minimum spanning tree EMST and the Euclidean minimum insertion tree EMIT of a set of n points S contained in Rd. More precisely, we show that, if the weight w of an edge e is its Euclidean length to the power of α, the following quantities Σ_{e ∈ EMST} w(e) and Σ_{e ∈ EMIT} w(e) are both worst-case O(n^{1-α/d}), where d is the dimension and α, 0 < α < d, is the weight. Also, we analyze and compare the value of Σ_{e ∈ T} w(e) for some trees T embedded in Rd which are of interest in (but not limited to) the point location problem [2]

Expected Length of the Voronoi Path in a High Dimensional Poisson-Delaunay Triangulation

International audienceLet X be a d dimensional Poisson point process. We prove that the expected length of the Voronoi path between two points at distance 1 in the Delaunay triangulation associated with X is sqrt(2d/π) + O(d^(−1/2) when d → ∞. In any dimension, we also provide a precise interval containing the actual value; in 3D the expected length is between 1.4977 and 1.50007