Local re-inversion coronary MR angiography: arterial spin-labeling without the need for subtraction.

PURPOSE: To implement a double-inversion bright-blood coronary MR angiography sequence using a cylindrical re-inversion prepulse for selective visualization of the coronary arteries. MATERIALS AND METHODS: Local re-inversion bright-blood magnetization preparation was implemented using a nonselective inversion followed by a cylindrical aortic re-inversion prepulse. After an inversion delay that allows for in-flow of the labeled blood-pool into the coronary arteries, three-dimensional radial steady-state free-precession (SSFP) imaging (repetition/echo time, 7.2/3.6 ms; flip angle, 120 degrees, 16 profiles per RR interval; field of view, 360 mm; matrix, 512, twelve 3-mm slices) is performed. Coronary MR angiography was performed in three healthy volunteers and in one patient on a commercial 1.5 Tesla whole-body MR System. RESULTS: In all subjects, coronary arteries were selectively visualized with positive contrast. In addition, a middle-grade stenosis of the proximal right coronary artery was seen in one patient. CONCLUSION: A novel T1 contrast-enhancement strategy is presented for selective visualization of the coronary arteries without extrinsic contrast medium application. In comparison to former arterial spin-labeling schemes, the proposed magnetization preparation obviates the need for a second data set and subtraction.

Dissection of local and systemic transcriptional responses to phosphate starvation in Arabidopsis.

Phosphate is a crucial and often limiting nutrient for plant growth. To obtain inorganic phosphate (P(i) ), which is very insoluble, and is heterogeneously distributed in the soil, plants have evolved a complex network of morphological and biochemical processes. These processes are controlled by a regulatory system triggered by P(i) concentration, not only present in the medium (external P(i) ), but also inside plant cells (internal P(i) ). A 'split-root' assay was performed to mimic a heterogeneous environment, after which a transcriptomic analysis identified groups of genes either locally or systemically regulated by P(i) starvation at the transcriptional level. These groups revealed coordinated regulations for various functions associated with P(i) starvation (including P(i) uptake, P(i) recovery, lipid metabolism, and metal uptake), and distinct roles for members in gene families. Genetic tools and physiological analyses revealed that genes that are locally regulated appear to be modulated mostly by root development independently of the internal P(i) content. By contrast, internal P(i) was essential to promote the activation of systemic regulation. Reducing the flow of P(i) had no effect on the systemic response, suggesting that a secondary signal, independent of P(i) , could be involved in the response. Furthermore, our results display a direct role for the transcription factor PHR1, as genes systemically controlled by low P(i) have promoters enriched with P1BS motif (PHR1-binding sequences). These data detail various regulatory systems regarding P(i) starvation responses (systemic versus local, and internal versus external P(i) ), and provide tools to analyze and classify the effects of P(i) starvation on plant physiology.

Ulnar Nerve Transposition at the Elbow under Local Anesthesia: A Patient Satisfaction Study.

Background Ulnar nerve decompression at the elbow traditionally requires regional or general anesthesia. We wished to assess the feasibility of performing ulnar nerve decompression and transposition at the elbow under local anesthesia. Methods We examined retrospectively the charts of 50 consecutive patients having undergone ulnar nerve entrapment surgery either under general or local anesthesia. Patients were asked to estimate pain on postoperative days 1 and 7 and satisfaction was assessed at 1 year. Results On day 1, pain was comparable among all groups. On day 7, pain scores were twice as high when transposition was performed under general anesthesia when compared with local anesthesia. Patient satisfaction was slightly increased in the local anesthesia group. These patients were significantly more willing to repeat the surgery. Conclusion Ulnar nerve decompression and transposition at the elbow can be performed under local anesthesia without added morbidity when compared with general anesthesia.

No major impact of skin aging on the response of skin blood flow to a submaximal local thermal stimulus.

OBJECTIVE: This study was undertaken to investigate how aging affects dermal microvascular reactivity in skin areas differentially exposed to sunlight, and therefore to different degrees of photoaging. METHODS: We assessed, in young (18-30 years, n = 13) and aged males (≥60 years, n = 13), the thigh, forearm, and forehead's skin vasodilatory response to local heating (LTH) with a LDI. In each subject and at each location, local Tskin was brought from 34°C (baseline) to 39 or 41°C for 30 minutes, to effect submaximal vasodilation, with maximal vasodilation then elicited by further heating to 44°C. RESULTS: The CVCs evaluated at baseline and after maximal vasodilation (CVCmax ) were higher in the forehead than in the two other anatomical locations. On all locations, CVCmax decreased with age but less markedly in the forehead compared to the two other locations. When expressed in % of CVCmax , the plateau increase of CVCs in response to submaximal temperatures (39 and 41°C) did not vary with age, and minimally so with location. CONCLUSION: Skin aging, whether intrinsic or combined with photoaging, reduces the maximal vasodilatory capacity of the dermal microcirculation, but not its reactivity to local heating.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.