Finding k-Dissimilar Paths with Minimum Collective Length

Shortest path computation is a fundamental problem in road networks. However, in many real-world scenarios, determining solely the shortest path is not enough. In this paper, we study the problem of finding k-Dissimilar Paths with Minimum Collective Length (kDPwML), which aims at computing a set of paths from a source s to a target t such that all paths are pairwise dissimilar by at least \theta and the sum of the path lengths is minimal. We introduce an exact algorithm for the kDPwML problem, which iterates over all possible s-t paths while employing two pruning techniques to reduce the prohibitively expensive computational cost. To achieve scalability, we also define the much smaller set of the simple single-via paths, and we adapt two algorithms for kDPwML queries to iterate over this set. Our experimental analysis on real road networks shows that iterating over all paths is impractical, while iterating over the set of simple single-via paths can lead to scalable solutions with only a small trade-off in the quality of the results.Comment: Extended version of the SIGSPATIAL'18 paper under the same titl

Nuclear Factor-κB-Independent Anti-Inflammatory Action of Salicylate in Human Endothelial Cells

In contrast to aspirin, salicylate, its active metabolite, possesses profound anti-inflammatory properties without blocking cyclooxygenase. Inhibition of the transcription factor nuclear factor-κB (NF-κB) has been discussed to play a role in the anti-inflammatory profile of salicylate. However, NF-κB-independent effects of salicylate have been assumed but have up to now been poorly investigated. Therefore, the aim of the present study was to investigate NF-κB-independent anti-inflammatory mechanisms of salicylate in human umbilical vein endothelial cells using interleukin-4 (IL-4) as NF-κB-independent proinflammatory stimulus and P-selectin as inflammatory read-out parameter. Using quantitative real-time reverse transcriptionpolymerase chain reaction, we found that salicylate decreases IL-4-induced P-selectin expression. As judged by Western blot analysis, salicylate increased endothelial heme oxygenase-1 (HO-1) protein levels. Using both the HO-1 inhibitor tin(II) protoporphyrin IX and HO-1 antisense oligonucleotides, we causally linked the induction of HO-1 to the decrease of P-selectin. Moreover, we were interested in the signaling mechanisms leading to the up-regulation of HO-1 by salicylate. c-Jun NH2-terminal kinase (JNK) was found to be activated by salicylate, and we could causally link this activation to the induction of HO-1 by using the JNK inhibitor 1,9-pyrazoloanthrone. By applying activator protein-1 (AP-1) decoys, it was shown that the transcription factor AP-1 is crucially involved in the up-regulation of HO-1 downstream of JNK. In summary, our study introduces HO-1 as novel NF-κB-independent anti-inflammatory target of salicylate in human endothelial cells. Moreover, we elucidated the JNK/AP-1 pathway as crucial for the induction of HO-1 by salicylate

Lensing by Lyman Limit Systems: Determining the Mass to Gas Ratio

We present a new method to determine the total mass-to-neutral gas ratio in Lyman-limits systems. The method exploits the relation between the neutral hydrogen column density and the magnification of background sources due to the weak gravitational lensing that these systems induce. Because weak lensing does not provide a direct measure of mass, one must use this relation in a statistical sense to solve for the average mass-to-gas ratio and its distribution. We use a detailed mock catalog of quasars (sources) and Lyman-limit systems (lenses) to demonstrate the applicability of this approach through our ability to recover the parameter. This mock catalog also allows us to check for systematics in the method and to sketch its limitations. For a universal constant mass-to-gas ratio and a sample of N quasars, we obtain an unbiased estimate of its value with 95% confidence limits (independent of its actual value) of +/- 140 {10^5/N)^0.5.Comment: 20 pages, 11 figures submitted to Ap

History of depression and survival after acute myocardial infarction

Objective: To compare survival in post-myocardial (MI) participants from the Enhancing Recovery In Coronary Heart Disease (ENRICHD) clinical trial with a first episode of major depression (MD) and those with recurrent MID, which is a risk factor for mortality after acute MI. Recent reports suggest that the level of risk may depend on whether the comorbid MD is a first or a recurrent episode. Methods: Survival was compared over a median of 29 months in 370 patients with an initial episode of MD, 550 with recurrent MD, and 408 who were free of depression. Results: After adjusting for an all-cause mortality risk score, initial Beck Depression Inventory score, and the use of selective serotonin reuptake inhibitor antidepressants, patients with a first episode of MD had poorer survival (18.4% all-cause mortality) than those with recurrent MD (11.8%) (hazard ratio (HR)=1.4; 95% Confidence Interval (CI)=1.0-2.0; p=.05). Both first depression (HR=3.1; 95% CI=1.6-6.1; p=.001) and recurrent MD (HR=2.2; 95% CI=1.1-4.4; p=.03) had significantly poorer survival than did the nondepressed patients (3.4%). A secondary analysis of deaths classified as probably due to a cardiovascular cause resulted in similar HRs, but the difference between depression groups was not significant. Conclusions: Both initial and recurrent episodes of MD predict shorter survival after acute MI, but initial MD episodes are more strongly predictive than recurrent episodes. Exploratory analyses suggest that this cannot be explained by more severe heart disease at index, poorer response to depression treatment, or a higher risk of cerebrovascular disease in patients with initial MD episodes

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Metalloporphyrins inactivate caspase-3 and -8

Activation of caspases represents one of the earliest biochemical indicators for apoptotic cell death. Therefore, measurement of caspase activity is a widely used and generally accepted method to determine apoptosis in a wide range of in vivo and in vitro settings. Numerous publications characterize the role of the heme-catabolizing enzyme heme oxygenase-1 (HO-1) in regulating apoptotic processes. Different metalloporphyrins representing inducers and inhibitors of this enzyme are often used, followed by assessment of apoptotic cell death. In the present work, we found that caspase-3-like activity, as well as activity of caspase-8 measured in either Fas (CD95) ligand-treated Jurkat T-lymphocytes or by the use of recombinant caspase-3 or -8, was inhibited by different metalloporphyrins (cobalt(III) protoporphyrin IX, tin and zinc II) protoporphyrin-IX). Moreover, employing the mouse model of Fas-induced liver apoptosis these properties of porphyrins could also be demonstrated in vivo. The metalloporphyrins were shown to inhibit caspase-3-mediated PARP cleavage. Molecular modeling studies demonstrated that porphyrins can occupy the active site of caspase-3 in an energetically favorable manner and in a binding mode similar to that of known inhibitors. The data shown here introduce metalloporphyrins as direct inhibitors of caspase activity. This finding points to the need for careful employment of metalloporphyrins as modulators of HO-1

Upper Bounding the Graph Edit Distance Based on Rings and Machine Learning

The graph edit distance (GED) is a flexible distance measure which is widely used for inexact graph matching. Since its exact computation is NP-hard, heuristics are used in practice. A popular approach is to obtain upper bounds for GED via transformations to the linear sum assignment problem with error-correction (LSAPE). Typically, local structures and distances between them are employed for carrying out this transformation, but recently also machine learning techniques have been used. In this paper, we formally define a unifying framework LSAPE-GED for transformations from GED to LSAPE. We also introduce rings, a new kind of local structures designed for graphs where most information resides in the topology rather than in the node labels. Furthermore, we propose two new ring based heuristics RING and RING-ML, which instantiate LSAPE-GED using the traditional and the machine learning based approach for transforming GED to LSAPE, respectively. Extensive experiments show that using rings for upper bounding GED significantly improves the state of the art on datasets where most information resides in the graphs' topologies. This closes the gap between fast but rather inaccurate LSAPE based heuristics and more accurate but significantly slower GED algorithms based on local search