Scale-Invariant Random Spatial Networks

Real-world road networks have an approximate scale-invariance property; can one devise mathematical models of random networks whose distributions are {\em exactly} invariant under Euclidean scaling? This requires working in the continuum plane. We introduce an axiomatization of a class of processes we call {\em scale-invariant random spatial networks}, whose primitives are routes between each pair of points in the plane. We prove that one concrete model, based on minimum-time routes in a binary hierarchy of roads with different speed limits, satisfies the axioms, and note informally that two other constructions (based on Poisson line processes and on dynamic proximity graphs) are expected also to satisfy the axioms. We initiate study of structure theory and summary statistics for general processes in this class.Comment: 56 page

Transit Node Routing Reconsidered

Transit Node Routing (TNR) is a fast and exact distance oracle for road networks. We show several new results for TNR. First, we give a surprisingly simple implementation fully based on Contraction Hierarchies that speeds up preprocessing by an order of magnitude approaching the time for just finding a CH (which alone has two orders of magnitude larger query time). We also develop a very effective purely graph theoretical locality filter without any compromise in query times. Finally, we show that a specialization to the online many-to-one (or one-to-many) shortest path further speeds up query time by an order of magnitude. This variant even has better query time than the fastest known previous methods which need much more space.Comment: 19 pages, submitted to SEA'201

Trip-Based Public Transit Routing

We study the problem of computing all Pareto-optimal journeys in a public transit network regarding the two criteria of arrival time and number of transfers taken. We take a novel approach, focusing on trips and transfers between them, allowing fine-grained modeling. Our experiments on the metropolitan network of London show that the algorithm computes full 24-hour profiles in 70 ms after a preprocessing phase of 30 s, allowing fast queries in dynamic scenarios.Comment: Minor corrections, no substantial changes. To be presented at ESA 201

Deconjugation Kinetics of Glucuronidated Phase II Flavonoid Metabolites by B-glucuronidase from Neutrophils

Flavonoids are inactivated by phase II metabolism and occur in the body as glucuronides. Mammalian ß-glucuronidase released from neutrophils at inflammatory sites may be able to deconjugate and thus activate flavonoid glucuronides. We have studied deconjugation kinetics and pH optimum for four sources of ß-glucuronidase (human neutrophil, human recombinant, myeloid PLB-985 cells, Helix pomatia) with five flavonoid glucuronides (quercetin-3-glucuronide, quercetin-3'-glucuronide, quercetin-4'-glucuronide, quercetin-7-glucuronide, 3'-methylquercetin-3-glucuronide), 4-methylumbelliferyl-ß-D-glucuronide, and para-nitrophenol-glucuronide. All substrate-enzyme combinations tested exhibited first order kinetics. The optimum pH for hydrolysis was between 3.5-5, with appreciable hydrolysis activities up to pH 5.5. At pH 4, the Km ranged 44-fold from 22 µM for quercetin-4'-glucuronide with Helix pomatia ß-glucuronidase, to 981 µM for para-nitrophenol-glucuronide with recombinant ß-glucuronidase. Vmax (range: 0.735-24.012 µmol·min-1·unit-1 [1 unit is defined as the release of 1 µM 4-methylumbelliferyl-ß-D-glucuronide per min]) and the reaction rate constants at low substrate concentrations (k) (range: 0.002-0.062 min-1·(unit/L)-1 were similar for all substrates-enzyme combinations tested. In conclusion, we show that ß-glucuronidase from four different sources, including human neutrophils, is able to deconjugate flavonoid glucuronides and non-flavonoid substrates at fairly similar kinetic rates. At inflammatory sites in vivo the pH, neutrophil and flavonoid glucuronide concentrations seem favorable for deconjugation. However, it remains to be confirmed whether this is actually the case

IO-Top-k: index-access optimized top-k query processing

Top-k query processing is an important building block for ranked retrieval, with applications ranging from text and data integration to distributed aggregation of network logs and sensor data. Top-k queries operate on index lists for a query's elementary conditions and aggregate scores for result candidates. One of the best implementation methods in this setting is the family of threshold algorithms, which aim to terminate the index scans as early as possible based on lower and upper bounds for the final scores of result candidates. This procedure performs sequential disk accesses for sorted index scans, but also has the option of performing random accesses to resolve score uncertainty. This entails scheduling for the two kinds of accesses: 1) the prioritization of different index lists in the sequential accesses, and 2) the decision on when to perform random accesses and for which candidates. The prior literature has studied some of these scheduling issues, but only for each of the two access types in isolation. The current paper takes an integrated view of the scheduling issues and develops novel strategies that outperform prior proposals by a large margin. Our main contributions are new, principled, scheduling methods based on a Knapsack-related optimization for sequential accesses and a cost model for random accesses. The methods can be further boosted by harnessing probabilistic estimators for scores, selectivities, and index list correlations. We also discuss efficient implementation techniques for the underlying data structures. In performance experiments with three different datasets (TREC Terabyte, HTTP server logs, and IMDB), our methods achieved significant performance gains compared to the best previously known methods: a factor of up to 3 in terms of execution costs, and a factor of 5 in terms of absolute run-times of our implementation. Our best techniques are close to a lower bound for the execution cost of the considered class of threshold algorithms

The challenges of developing rainfall intensity-duration-frequency curves and national flood hazard maps for the Caribbean

In many Caribbean countries a lack of established good practice methods means that engineers and planners are often unable to plan for and mitigate floods effectively. In most Caribbean states rainfall intensity – duration – frequency (IDF) curves are not readily available. This is a result of the limited quantity of short duration rainfall data available and also because the few IDF curves that have been developed in the region are generally not in the public domain. The lack of readily available IDF curves in the region often results in engineers responsible for the design of key infrastructure inappropriately “transferring” IDF curves developed for islands, where rainfall is less intense, for use in their designs. There are no countries in the Caribbean with nationally consistent flood hazard maps. This often leaves spatial and emergency planners with insufficient information to make important strategic decisions. This paper details the challenges that were faced in producing rainfall IDF curves for return periods up to 1 in 50 years and nationally consistent extreme fluvial flood extent maps with limited data for selected countries within the Caribbean. Recommendations are made for the future development of rainfall IDF curves and national flood maps in the region both in terms of data and organisational requirements

Inhibition of 26S proteasome activity by α-synuclein is mediated by the proteasomal chaperone Rpn14/PAAF1

\ua9 2024 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.Parkinson\u27s disease (PD) is characterized by aggregation of α-synuclein (α-syn) into protein inclusions in degenerating brains. Increasing amounts of aggregated α-syn species indicate significant perturbation of cellular proteostasis. Altered proteostasis depends on α-syn protein levels and the impact of α-syn on other components of the proteostasis network. Budding yeast Saccharomyces cerevisiae was used as eukaryotic reference organism to study the consequences of α-syn expression on protein dynamics. To address this, we investigated the impact of overexpression of α-syn and S129A variant on the abundance and stability of most yeast proteins using a genome-wide yeast library and a tandem fluorescent protein timer (tFT) reporter as a measure for protein stability. This revealed that the stability of in total 377 cellular proteins was altered by α-syn expression, and that the impact on protein stability was significantly enhanced by phosphorylation at Ser129 (pS129). The proteasome assembly chaperone Rpn14 was identified as one of the top candidates for increased protein stability by expression of pS129 α-syn. Elevated levels of Rpn14 enhanced the growth inhibition by α-syn and the accumulation of ubiquitin conjugates in the cell. We found that Rpn14 interacts physically with α-syn and stabilizes pS129 α-syn. The expression of α-syn along with elevated levels of Rpn14 or its human counterpart PAAF1 reduced the proteasome activity in yeast and in human cells, supporting that pS129 α-syn negatively affects the 26S proteasome through Rpn14. This comprehensive study into the alternations of protein homeostasis highlights the critical role of the Rpn14/PAAF1 in α-syn-mediated proteasome dysfunction

Immunotherapy of lung cancer: An update

In Germany lung cancer is the leading cause of cancer-associated death in men. Surgery, chemotherapy and radiation may enhance survival of patients suffering from lung cancer but the enhancement is typically transient and mostly absent with advanced disease; eventually more than 90% of lung cancer patients will die of disease. New approaches to the treatment of lung cancer are urgently needed. Immunotherapy may represent one new approach with low toxicity and high specificity but implementation has been a challenge because of the poor antigenic characterization of these tumors and their ability to escape immune responses. Several different immunotherapeutic treatment strategies have been developed. This review examines the current state of development and recent advances with respect to non-specific immune stimulation, cellular immunotherapy ( specific and non-specific), therapeutic cancer vaccines and gene therapy for lung cancer. The focus is primarily placed on immunotherapeutic cancer treatments that are already in clinical trial or well progressed in preclinical studies. Although there seems to be a promising future for immunotherapy in lung cancer, presently there is not standard immunotherapy available for clinical routine