Hydrogen-bond inter­actions in morpholinium bromide

In the title compound, C4H10NO+·Br−, which was synthesized by dehydration of diethano­lamine with HBr, morpholinium and bromide ions are linked into chains by N—H⋯Br hydrogen bonds describing a C 2 1(4) graph-set motif. Weaker bifurcated N—H⋯Br inter­actions join centrosymmetrically related chains through alternating binary graph-set R 4 2(8) and R 2 2(4) motifs, to form ladders along [100]. In addition, C—H⋯O inter­actions between centrosymmetric morpholinium cations link ladders, via (8) motifs, to yield sheets parallel to (101), which in turn are crosslinked by weak C—H⋯O inter­actions, related across a glide plane, to form a three-dimensional network

Data context informed data wrangling

The process of preparing potentially large and complex data sets for further analysis or manual examination is often called data wrangling. In classical warehousing environments, the steps in such a process have been carried out using Extract-Transform-Load platforms, with significant manual involvement in specifying, configuring or tuning many of them. Cost-effective data wrangling processes need to ensure that data wrangling steps benefit from automation wherever possible. In this paper, we define a methodology to fully automate an end-to-end data wrangling process incorporating data context, which associates portions of a target schema with potentially spurious extensional data of types that are commonly available. Instance-based evidence together with data profiling paves the way to inform automation in several steps within the wrangling process, specifically, matching, mapping validation, value format transformation, and data repair. The approach is evaluated with real estate data showing substantial improvements in the results of automated wrangling

The VADA Architecture for Cost-Effective Data Wrangling

Data wrangling, the multi-faceted process by which the data required by an application is identified, extracted, cleaned and integrated, is often cumbersome and labor intensive. In this paper, we present an architecture that supports a complete data wrangling lifecycle, orchestrates components dynamically, builds on automation wherever possible, is informed by whatever data is available, refines automatically produced results in the light of feedback, takes into account the user’s priorities, and supports data scientists with diverse skill sets. The architecture is demonstrated in practice for wrangling property sales and open government data

Declarative Event-Based Workflow as Distributed Dynamic Condition Response Graphs

We present Dynamic Condition Response Graphs (DCR Graphs) as a declarative, event-based process model inspired by the workflow language employed by our industrial partner and conservatively generalizing prime event structures. A dynamic condition response graph is a directed graph with nodes representing the events that can happen and arrows representing four relations between events: condition, response, include, and exclude. Distributed DCR Graphs is then obtained by assigning roles to events and principals. We give a graphical notation inspired by related work by van der Aalst et al. We exemplify the use of distributed DCR Graphs on a simple workflow taken from a field study at a Danish hospital, pointing out their flexibility compared to imperative workflow models. Finally we provide a mapping from DCR Graphs to Buchi-automata.Comment: In Proceedings PLACES 2010, arXiv:1110.385

Effects of 3,4-Methylenedioxymethamphetamine Administration on Retinal Physiology in the Rat

3,4-Methylenedioxymethamphetamine (MDMA; ecstasy) is known to produce euphoric states, but may also cause adverse consequences in humans, such as hyperthermia and neurocognitive deficits. Although MDMA consumption has been associated with visual problems, the effects of this recreational drug in retinal physiology have not been addressed hitherto. In this work, we evaluated the effect of a single MDMA administration in the rat electroretinogram (ERG). Wistar rats were administered MDMA (15 mg/kg) or saline and ERGs were recorded before (Baseline ERG), and 3 h, 24 h, and 7 days after treatment. A high temperature (HT) saline-treated control group was also included. Overall, significantly augmented and shorter latency ERG responses were found in MDMA and HT groups 3 h after treatment when compared to Baseline. Twenty-four hours after treatment some of the alterations found at 3 h, mainly characterized by shorter latency, tended to return to Baseline values. However, MDMA-treated animals still presented increased scotopic a-wave and b-wave amplitudes compared to Baseline ERGs, which were independent of temperature elevation though the latter might underlie the acute ERG alterations observed 3 h after MDMA administration. Seven days after MDMA administration recovery from these effects had occurred. The effects seem to stem from specific changes observed at the a-wave level, which indicates that MDMA affects subacutely (at 24 h) retinal physiology at the outer retinal (photoreceptor/bipolar) layers. In conclusion, we have found direct evidence that MDMA causes subacute enhancement of the outer retinal responses (most prominent in the a-wave), though ERG alterations resume within one week. These changes in photoreceptor/bipolar cell physiology may have implications for the understanding of the subacute visual manifestations induced by MDMA in humans

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease