A computational fluid dynamic investigation of inhomogeneous hydrogen flame acceleration and transition to detonation

Gas explosions in homogeneous reactive mixtures have been widely studied both experimentally and numerically. However, in practice and industrial applications, combustible mixtures are usually inhomogeneous and subject to vertical concentration gradients. Limited studies have been conducted in such context which resulted in limited understanding of the explosion characteristics in such situations. The present numerical investigation aims to study the dynamics of Deflagration to Detonation Transition (DDT) in inhomogeneous hydrogen/air mixtures and examine the effects of obstacle blockage ratio in DDT. VCEFoam, a reactive density-based solver recently assembled by the authors within the frame of OpenFOAM CFD toolbox has been used. VCEFoam uses the Harten–Lax–van Leer–Contact (HLLC) scheme fr the convective fluxes contribution and shock capturing. The solver has been verified by comparing its predictions with the analytical solutions of two classical test cases. For validation, the experimental data of Boeck et al. (1) is used. The experiments were conducted in a rectangular channel the three different blockage ratios and hydrogen concentrations. Comparison is presented between the predicted and measured flame tip velocities. The shaded contours of the predicted temperature and numerical Schlieren (magnitude of density gradient) will be analysed to examine the effects of the blockage ratio on flame acceleration and DDT

Ornithine Transcarbamylase Deficiency: If at First You Do Not Diagnose, Try and Try Again

Ornithine transcarbamylase (OTC) deficiency is well known for its diagnosis in the neonatal period. Presentation often occurs after protein feeding and manifests as poor oral intake, vomiting, lethargy progressing to seizure, respiratory difficulty, and eventually coma. Presentation at adulthood is rare (and likely underdiagnosed); however, OTC deficiency can be life-threatening and requires prompt investigation and treatment. Reports and guidelines are scarce due to its rarity. Here, we present a 59-year-old woman with a past history of irritable bowel syndrome who underwent a reparative operation for rectal prolapse and enterocele. Her postoperative course was complicated by a bowel perforation (which was repaired), prolonged mechanical ventilation, tracheostomy, critical illness myopathy, protein-caloric malnutrition, and altered mental status. After standard therapy for delirium failed, further investigation showed hyperammonemia and increased urine orotic acid, ultimately leading to the diagnosis of OTC deficiency. This case highlights the importance of considering OTC deficiency in hospitalized adults, especially during the diagnostic evaluation for altered mental status

BALL-SNP: combining genetic and structural information to identify candidate non-synonymous single nucleotide polymorphisms

Background: High-throughput genetic testing is increasingly applied in clinics. Next-Generation Sequencing (NGS) data analysis however still remains a great challenge. The interpretation of pathogenicity of single variants or combinations of variants is crucial to provide accurate diagnostic information or guide therapies. Methods: To facilitate the interpretation of variants and the selection of candidate non-synonymous polymorphisms (nsSNPs) for further clinical studies, we developed BALL-SNP. Starting from genetic variants in variant call format (VCF) files or tabular input, our tool, first, visualizes the three-dimensional (3D) structure of the respective proteins from the Protein Data Bank (PDB) and highlights mutated residues, automatically. Second, a hierarchical bottom up clustering on the nsSNPs within the 3D structure is performed to identify nsSNPs, which are close to each other. The modular and flexible implementation allows for straightforward integration of different databases for pathogenic and benign variants, but also enables the integration of pathogenicity prediction tools. The collected background information of all variants is presented below the 3D structure in an easily interpretable table format. Results: First, we integrated different data resources into BALL-SNP, including databases containing information on genetic variants such as ClinVar or HUMSAVAR; third party tools that predict stability or pathogenicity in silico such as I-Mutant2.0; and additional information derived from the 3D structure such as a prediction of binding pockets. We then explored the applicability of BALL-SNP on the example of patients suffering from cardiomyopathies. Here, the analysis highlighted accumulation of variations in the genes JUP, VCL, and SMYD2. Conclusion: Software solutions for analyzing high-throughput genomics data are important to support diagnosis and therapy selection. Our tool BALL-SNP, which is freely available at http://www.ccb.uni-saarland.de/BALL-SNP , combines genetic information with an easily interpretable and interactive, graphical representation of amino acid changes in proteins. Thereby relevant information from databases and computational tools is presented. Beyond this, proximity to functional sites or accumulations of mutations with a potential collective effect can be discovered

So rare we need to hunt for them: reframing the ethical debate on incidental findings

Incidental findings are the subject of intense ethical debate in medical genomic research. Every human genome contains a number of potentially disease-causing alterations that may be detected during comprehensive genetic analyses to investigate a specific condition. Yet available evidence shows that the frequency of incidental findings in research is much lower than expected. In this Opinion, we argue that the reason for the low level of incidental findings is that the filtering techniques and methods that are applied during the routine handling of genomic data remove these alterations. As incidental findings are systematically filtered out, it is now time to evaluate whether the ethical debate is focused on the right issues. We conclude that the key question is whether to deliberately target and search for disease-causing variations outside the indication that has originally led to the genetic analysis, for instance by using positive lists and algorithms

Ultraconformable, Self‐Adhering Surface Electrodes for Measuring Electrical Signals in Plants

The electrical signals in plant's physiological processes are of great interest in biology, biohybrid robotics, and sensors for interfacing the living organisms with an electronic readout and control. This paper reports on the application of conformable, self-adhering surface electrodes for the measurement and bidirectional stimulation of electrical signals in plants. The inkjet-printed poly(3,4-ethylenedioxythiophene) polystyrene sulfonate based electrodes are <3 µm thick, light-weight, soft and flexible, and can be easily and non-invasively transferred onto plant's outer organs for surface potential recordings due to their realization on tattoo transfer paper. The devices prove to be extremely versatile for analyzing electrical signals in Dionaea muscipula, Arabidopsis thaliana, and Codariocalyx motorius and for stimulating mechanical responses in D. muscipula. A benefit over traditional electrodes is the van der Waals self-adherence of the thin electrodes, their intrinsic flexibility and adaptation also on small leaves while providing excellent readout. The same electrode allows long-term multicycle measurements over at least 10 days and, moreover, straightforward recordings on fast-moving organs such as snapping fly traps and endogenously oscillating leaflets. The results confirm that self-adhering soft organic electronics are particularly suitable for plant electrical signal analysis when easy-application, self-adaptation, and long-term performance are required in plant science, biohybrid robotics, and biohybrid sensors