Strong accumulators from collision-resistant hashing

Accumulator schemes were introduced in order to represent a large set of values as one short value called the accumulator. These schemes allow one to generate membership proofs, that is, short witnesses that a certain value belongs to the set. In universal accumulator schemes, efficient proofs of non-membership can also be created. Li et?al. (Proceedings of applied cryptography and network security—ACNS ’07, LNCS, vol 4521, 2007), building on the work of Camenisch and Lysyanskaya (Advances in cryptology—proceedings of Crypto ’02, LNCS, vol 2442. Springer, Berlin, pp 61–76, 2002), proposed an efficient accumulator scheme, which relies on a trusted accumulator manager. Specifically, a manager that correctly performs accumulator updates. In this work, we introduce the notion of strong universal accumulator schemes, which are similar in functionality to universal accumulator schemes, but do not assume the accumulator manager is trusted. We also formalize the security requirements for such schemes. We then give a simple construction of a strong universal accumulator scheme, which is provably secure under the assumption that collision-resistant hash functions exist. The weaker requirement on the accumulator manager comes at a price; our scheme is less efficient than known universal accumulator schemes—the size of (non)membership witnesses is logarithmic in the size of the accumulated set in contrast to constant in the scheme of Camenisch and Lysyanskaya. Finally, we show how to use strong universal accumulators to solve a problem of practical relevance, the so-called e-Invoice Factoring Problem.     

Methamphetamine Blocks Adenosine A2A Receptor Activation via Sigma 1 and Cannabinoid CB1 Receptors

Methamphetamine is, worldwide, one of the most consumed drugs of abuse. One important side effect is neurodegeneration leading to a decrease in life expectancy. The aim of this paper was to check whether the drug affects one of the receptors involved in neurodegeneration/neuroprotection events, namely the adenosine A_2A receptor (A_2AR). First, we noticed that methamphetamine does not affect A_2A functionality if the receptor is expressed in a heterologous system. However, A_2AR becomes sensitive to the drug upon complexes formation with the cannabinoid CB₁ receptor (CB₁R) and the sigma 1 receptor (σ₁R). Signaling via both adenosine A_2AR and cannabinoid CB₁R was affected by methamphetamine in cells co-expressing the two receptors. In striatal primary cultures, the A_2AR–CB₁R heteromer complex was detected and methamphetamine not only altered its expression but completely blocked the A_2AR- and the CB₁R-mediated activation of the mitogen activated protein kinase (MAPK) pathway. In conclusion, methamphetamine, with the participation of σ₁R, alters the expression and function of two interacting receptors, A_2AR, which is a therapeutic target for neuroprotection, and CB₁R, which is the most abundant G protein-coupled receptor (GPCR) in the brain.     

Curvature effects on electric-double-layer capacitance

Understanding the microscopic structure and thermodynamic properties of electrode/electrolyte interfaces is central to the rational design of electric-double-layer capacitors (EDLCs). Whereas practical applications often entail electrodes with complicated pore structures, theoretical studies are mostly restricted to EDLCs of simple geometry such as planar or slit pores ignoring the curvature effects of the electrode surface. Significant gaps exist regarding the EDLC performance and the interfacial structure. Herein the classical density functional theory (CDFT) is used to study the capacitance and interfacial behavior of spherical electric double layers within a coarse-grained model. The capacitive performance is associated with electrode curvature, surface potential, and electrolyte concentration and can be correlated with a regression-tree (RT) model. The combination of CDFT with machine-learning methods provides a promising quantitative framework useful for the computational screening of porous electrodes and novel electrolytes.     

Antisense Oligonucleotide-Based Rescue of Aberrant Splicing Defects Caused by 15 Pathogenic Variants in ABCA4

The discovery of novel intronic variants in the ABCA4 locus has contributed significantly to solving the missing heritability in Stargardt disease (STGD1). The increasing number of variants affecting pre-mRNA splicing makes ABCA4 a suitable candidate for antisense oligonucleotide (AON)-based splicing modulation therapies. In this study, AON-based splicing modulation was assessed for 15 recently described intronic variants (three near-exon and 12 deep-intronic variants). In total, 26 AONs were designed and tested in vitro using a midigene-based splice system. Overall, partial or complete splicing correction was observed for two variants causing exon elongation and all variants causing pseudoexon inclusion. Together, our results confirm the high potential of AONs for the development of future RNA therapies to correct splicing defects causing STGD1.     

The Role of LGR4 (GPR48) in Normal and Cancer Processes

Leucine-rich repeats containing G protein-coupled receptor 4 (LGR4) is a receptor that belongs to the superfamily of G protein-coupled receptors that can be activated by R-spondins (RSPOs), Norrin, circLGR4, and the ligand of the receptor activator of nuclear factor kappa-B (RANKL) ligands to regulate signaling pathways in normal and pathological processes. LGR4 is widely expressed in different tissues where it has multiple functions such as tissue development and maintenance. LGR4 mainly acts through the Wnt/β-catenin pathway to regulate proliferation, survival, and differentiation. In cancer, LGR4 participates in tumor progression, invasion, and metastasis. Furthermore, recent evidence reveals that LGR4 is essential for the regulation of the cancer stem cell population by controlling self-renewal and regulating stem cell properties. This review summarizes the function of LGR4 and its ligands in normal and malignant processes.     

BiOSS: A system for biomedical ontology selection

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service.     

FMAP: Distributed cooperative multi-agent planning

This paper proposes FMAP (Forward Multi-Agent Planning), a fully-distributed multi-agent planning method that integrates planning and coordination. Although FMAP is specifically aimed at solving problems that require cooperation among agents, the flexibility of the domain-independent planning model allows FMAP to tackle multi-agent planning tasks of any type. In FMAP, agents jointly explore the plan space by building up refinement plans through a complete and flexible forward-chaining partial-order planner. The search is guided by h _{D T G} , a novel heuristic function that is based on the concepts of Domain Transition Graph and frontier state and is optimized to evaluate plans in distributed environments. Agents in FMAP apply an advanced privacy model that allows them to adequately keep private information while communicating only the data of the refinement plans that is relevant to each of the participating agents. Experimental results show that FMAP is a general-purpose approach that efficiently solves tightly-coupled domains that have specialized agents and cooperative goals as well as loosely-coupled problems. Specifically, the empirical evaluation shows that FMAP outperforms current MAP systems at solving complex planning tasks that are adapted from the International Planning Competition benchmarks.     

Adsorption isotherms of sesame oil in a concentrated miscella system

The adsorption of peroxides, unsaturated carbonyls, free fatty acids and carotenoids from unrefined sesame oil on vegetable carbon (5%, w/w) in a miscella system was studied. Three different solvent conditions (hexane/ethanol, 100:0, 95:5 and 75:25, vol/vol), combined in a factorial design with five levels of solvent (0, 10, 20, 30 and 40%, w/w), were used to develop the miscella. Equilibrium adsorption was not achieved during the 100 min of adsorption, mainly because the oil components were involved in oxidation reactions during the adsorption process. However, for a given solvent concentration, adsorption of the oil components showed a significant linear regression on their respective initial concentration in the miscella (C_i). Peroxides and carbonyls showed, at all solvent levels investigated, an affinity for the carbon more independent of their C_i than free fatty acids and carotenoids. In general, at the same C_i, a higher adsorption was achieved as solvent concentration increased. The results indicated that free fatty acid adsorption may depend on competitive adsorption based on molecule hydrophobicity. However, in spite of the higher hydrophobicity of carotenoids, compared with free fatty acids, they might not be competing for the same adsorbing sites. Ethanol showed a prooxidant effect that increased peroxide production during adsorption but did not affect the reaction involved in carbonyl production.     

Novel fatty acid esters of (7E, 12E, 18R, 20Z)-variabilin from the marine sponge Ircinia felix

The methanolic extract of the marine sponge Ircinia felix has yielded nine novel fatty acid esters, (7E, 12E, 18R, 20Z)-variabilin (5Z, 9Z)-22-methyltricosadienoate, (7E, 12E, 18R, 20Z)-variabilin (5Z, 9Z)-tetracosadienoate, (7E, 12E, 18R, 20Z)-variabilin hexadecanoate, (7E, 12E, 18R, 20Z)-variabilin 10-methylhexadecanoate, (7E, 12E, 18R, 20Z)-variabilin 15-methylhexadecanoate, (7E, 12E, 18R, 20Z)-variabilin 14-methylhexadecanoate, (7E, 12E, 18R, 20Z)-variabilin 9-octadecenoate, (7E, 12E, 18R, 20Z)-variabilin octadecanoate, and (7E, 12E, 18R, 20Z)-variabilin 2,11-dimethyloctadecanoate, along with the recently described (7E, 12E, 18R, 20Z)-variabilin 11-methyloctadecanoate. The characterization of the new fatty acids (5Z, 9Z)-22-methyltricosadienoic and 2,11-dimethyloctadecanoic acids is also described. The chemical structures were determined by extensive spectroscopic, chromatographic, and chemical analyses.     

Effect of DAG on milk fat TAG crystallization

The effect of milk fat and standard DAG on the crystallization behavior of milk fat TAG (MF-TAG) was investigated. When milk fat DAG were added to MF-TAG at the 0.1 wt% level, crystallization was delayed. Racemic purity was shown to be an important factor in the ability of DAG to influence TAG crystallization. Only sn-1,2 isomers of blends of MF-TAG with 0.1 wt% of the racemic mixtures of dipalmitin and diolein increased the activation free energy barrier to MF-TAG nucleation (ΔG _c ) and delayed the subsequent crystallization process by increasing the crystallization induction time (τ_SFC) determined from solid fat content-time measurements. Although crystallization kinetics were affected, the properties of the resulting network structures remained unchanged upon addition of milk fat minor components at the 0.1 wt% level