120 research outputs found
Anomaly Detection by Recombining Gated Unsupervised Experts
Inspired by mixture-of-experts models and the analysis of the hidden
activations of neural networks, we introduce a novel unsupervised anomaly
detection method called ARGUE. Current anomaly detection methods struggle when
the training data does contain multiple notions of normal. We designed ARGUE as
a combination of multiple expert networks, which specialise on parts of the
input data. For its final decision, ARGUE fuses the distributed knowledge
across the expert systems using a gated mixture-of-experts architecture. ARGUE
achieves superior detection performance across several domains in a purely
data-driven way and is more robust to noisy data sets than other
state-of-the-art anomaly detection methods
Mendelian randomization indicates causal effects of estradiol levels on kidney function in males
ContextChronic kidney disease (CKD) is a public health burden worldwide. Epidemiological studies observed an association between sex hormones, including estradiol, and kidney function.ObjectiveWe conducted a Mendelian randomization (MR) study to assess a possible causal effect of estradiol levels on kidney function in males and females.DesignWe performed a bidirectional two-sample MR using published genetic associations of serum levels of estradiol in men (n = 206,927) and women (n = 229,966), and of kidney traits represented by estimated glomerular filtration rate (eGFR, n = 567,460), urine albumin-to-creatinine ratio (UACR, n = 547,361), and CKD (n = 41,395 cases and n = 439,303 controls) using data obtained from the CKDGen Consortium. Additionally, we conducted a genome-wide association study using UK Biobank cohort study data (n = 11,798 men and n = 6,835 women) to identify novel genetic associations with levels of estradiol, and then used these variants as instruments in a one-sample MR.ResultsThe two-sample MR indicated that genetically predicted estradiol levels are significantly associated with eGFR in men (beta = 0.077; p = 5.2E-05). We identified a single locus at chromosome 14 associated with estradiol levels in men being significant in the one-sample MR on eGFR (beta = 0.199; p = 0.017). We revealed significant results with eGFR in postmenopausal women and with UACR in premenopausal women, which did not reach statistical significance in the sensitivity MR analyses. No causal effect of eGFR or UACR on estradiol levels was found.ConclusionsWe conclude that serum estradiol levels may have a causal effect on kidney function. Our MR results provide starting points for studies to develop therapeutic strategies to reduce kidney disease
Identification of a protein encoded in the EB-viral open reading frame BMRF2
Using monospecific rabbit sera against a peptide derived from a potential antigenic region of the Epstein-Barr viral amino acid sequence encoded in the open reading frame BMRF2 we could identify a protein-complex of 53/55 kDa in chemically induced B95-8, P3HR1 and Raji cell lines. This protein could be shown to be membrane-associated, as predicted by previous computer analysis of the secondary structure and hydrophilicity pattern, and may be a member of EBV-induced membrane proteins in lytically infected cells
Tandem Mass Spectrometry Measurement of the Collision Products of Carbamate Anions Derived from CO2 Capture Sorbents: Paving the Way for Accurate Quantitation
The reaction between CO2 and aqueous amines to produce a charged carbamate product plays a crucial role in post-combustion capture chemistry when primary and secondary amines are used. In this paper, we report the low energy negative-ion CID results for several anionic carbamates derived from primary and secondary amines commonly used as post-combustion capture solvents. The study was performed using the modern equivalent of a triple quadrupole instrument equipped with a T-wave collision cell. Deuterium labeling of 2-aminoethanol (1,1,2,2,-d4-2-aminoethanol) and computations at the M06-2X/6-311++G(d,p) level were used to confirm the identity of the fragmentation products for 2-hydroxyethylcarbamate (derived from 2-aminoethanol), in particular the ions CNâ, NCOâ and facile neutral losses of CO2 and water; there is precedent for the latter in condensed phase isocyanate chemistry. The fragmentations of 2-hydroxyethylcarbamate were generalized for carbamate anions derived from other capture amines, including ethylenediamine, diethanolamine, and piperazine. We also report unequivocal evidence for the existence of carbamate anions derived from sterically hindered amines (Tris(2-hydroxymethyl)aminomethane and 2-methyl-2-aminopropanol). For the suite of carbamates investigated, diagnostic losses include the decarboxylation product (âCO2, 44 mass units), loss of 46 mass units and the fragments NCOâ (m/z 42) and CNâ (m/z 26). We also report low energy CID results for the dicarbamate dianion (âO2CNHC2H4NHCO2â) commonly encountered in CO2 capture solution utilizing ethylenediamine. Finally, we demonstrate a promising ion chromatography-MS based procedure for the separation and quantitation of aqueous anionic carbamates, which is based on the reported CID findings. The availability of accurate quantitation methods for ionic CO2 capture products could lead to dynamic operational tuning of CO2 capture-plants and, thus, cost-savings via real-time manipulation of solvent regeneration energies
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Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms
Background: Intracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to coâoccur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs. Methods and Results: We performed a megaâanalysis of 1000 Genomes Projectâimputed genomeâwide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IAâ, AAAâ, and TAAâassociated SNPs and tested these scores for association to caseâcontrol status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibriumâscore regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk singleânucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]=1.11; P=4.1Ă10â5) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1Ă10â3). Conclusions: Although there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication
Neuromonitoring im Rahmen der SchilddrĂŒsenresektion, Ă€ndert sich dadurch die OP-Strategie? Langzeitbeobachtung in der SchilddrĂŒsenchirurgie
Deep Reinforcement Fuzzing
Fuzzing is the process of finding security vulnerabilities in input-processing code by repeatedly testing the code with modified inputs. In this paper, we formalize fuzzing as a reinforcement learning problem using the concept of Markov decision processes. This in turn allows us to apply state-of-the-art deep Q -learning algorithms that optimize rewards, which we define from runtime properties of the program under test. By observing the rewards caused by mutating with a specific set of actions performed on an initial program input, the fuzzing agent learns a policy that can next generate new higher-reward inputs. We have implemented this new approach, and preliminary empirical evidence shows that reinforcement fuzzing can outperform baseline random fuzzing
Visual Study of the Benguela Upwelling System using Pathline Predicates
Due to the nutrient-rich water transported to the upper layer of the ocean, coastal upwelling systems are regions especially important for marine life and fishery. In this work, we focus on a visual analysis of the spatio-temporal structure of the Benguela upwelling system using pathline predicates. Based on the 3D flow field from an ocean model simulation, we first derive space- filling trajectories covering the full model grid. From these, we select and visualize pathlines related to upwelling. In a second step, we derive a 3D scalar field representing the pathline density, which is visualized using volume rendering techniques. Further analyses of the pathlines show a distinct annual cycle in the upwelling activity, which fits well to observation-based analyses found in literature
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