Genetic Deletion of Mmp9 Does Not Reduce Airway Inflammation and Structural Lung Damage in Mice with Cystic Fibrosis-like Lung Disease

Elevated levels of matrix metalloprotease 9 (MMP-9) and neutrophil elastase (NE) are associated with bronchiectasis and lung function decline in patients with cystic fibrosis (CF). MMP-9 is a potent extracellular matrix-degrading enzyme which is activated by NE and has been implicated in structural lung damage in CF. However, the role of MMP-9 in the in vivo pathogenesis of CF lung disease is not well understood. Therefore, we used β-epithelial Na⁺ channel-overexpressing transgenic (βENaC-Tg) mice as a model of CF-like lung disease and determined the effect of genetic deletion of Mmp9 (Mmp9^-/-) on key aspects of the pulmonary phenotype. We found that MMP-9 levels were elevated in the lungs of βENaC-Tg mice compared with wild-type littermates. Deletion of Mmp9 had no effect on spontaneous mortality, inflammatory markers in bronchoalveolar lavage, goblet cell metaplasia, mucus hypersecretion and emphysema-like structural lung damage, while it partially reduced mucus obstruction in βENaC-Tg mice. Further, lack of Mmp9 had no effect on increased inspiratory capacity and increased lung compliance in βENaC-Tg mice, whereas both lung function parameters were improved with genetic deletion of NE. We conclude that MMP-9 does not play a major role in the in vivo pathogenesis of CF-like lung disease in mice.     

Statistical segmentation and structural recognition for floor plan interpretation

A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents.     

A probabilistic language formalism for stochastic discrete-eventsystems

The formalism of probabilistic languages has been introduced for modeling the qualitative behavior of stochastic discrete-event systems. A probabilistic language is a unit interval-valued map over the set of traces of the system satisfying certain consistency constraints. Regular language operators such as choice, concatenation, and Kleene-closure have been defined in the setting of probabilistic languages to allow modeling of complex systems in terms of simpler ones. The set of probabilistic languages is closed under such operators, thus forming an algebra. It also is a complete partial order under a natural ordering in which the operators are continuous. Hence, recursive equations can be solved in this algebra. This is alternatively derived by using the contraction mapping theorem on the set of probabilistic languages which is shown to be a complete metric space. The notion of regularity, i.e., finiteness of automata representation, of probabilistic languages has been defined and it is shown that regularity is preserved under choice, concatenation, and Kleene-closure. We show that this formalism is also useful in describing system performance measures such as completion time, reliability, etc., and present properties to aide their computation     

Diagenetic transformation of dissolved organic nitrogen compounds under contrasting sedimentary redox conditions in the Black Sea

Remineralization of organic matter in reactive marine sediments releases nutrients and dissolved organic matter (DOM) into the ocean. Here we focused on the molecular-level characterization of DOM by high-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) in sediment pore waters and bottom waters from contrasting redox regimes in the northern Black Sea with particular emphasis on nitrogen-bearing compounds to derive an improved understanding of the molecular transformations involved in nitrogen release. The number of nitrogen-bearing molecules is generally higher in pore waters than in bottom waters. This suggests intensified degradation of nitrogen-bearing precursor molecules such as proteins in anoxic sediments: No significant difference was observed between sediments deposited under oxic vs anoxic conditions (average O/C ratios of 0.55) suggesting that the different organic matter quality induced by contrasting redox conditions does not impact protein diagenesis in the subseafloor. Compounds in the pore waters were on average larger, less oxygenated, and had a higher number of unsaturations. Applying a mathematical model, we could show that the assemblages of nitrogen-bearing molecular formulas are potential products of proteinaceous material that was transformed by the following reactions: (a) hydrolysis and deamination, both reducing the molecular size and nitrogen content of the products and intermediates; (b) oxidation and hydration of the intermediates; and (c) methylation and dehydration.     

Effects of pretreatments on colour alterations of litchi during drying and storage

The objective of this research was to study the effect of osmotic pretreatment with combined anti-browning agents (acid, glycerol and/or trehalose) on the colour characteristics of dried litchi after drying and during 5 months of storage compared to samples without pretreatment. The pretreated samples showed good inhibition of polyphenol oxidase activity when compared with the control, while the total phenolic contents in the dried products were not reduced. The results demonstrated that water activity, lightness difference, chroma, degree of browning (DB), and 5-hydroxymethylfurfural values of all pretreated samples increased, while hue angle decreased with storage time. Samples pretreated with glycerol showed the best potential for browning retardation, followed by glycerol combined with trehalose, and trehalose, respectively. In addition, the colour parameters were used to calculate the luminescence values, representing the data in grey scale, which were correlated with a non-enzymatic browning index. The results showed grey value could be adequately used to represent the DB of dried litchi with r ² value of 0.92.     

Glycosidase inhibitory phenolic compounds from the seed of Psoralea corylifolia

The seeds of Psoralea corylifolia were extracted into five different polar solvents: chloroform, 50% ethanol in water, ethanol, methanol and water. All extracts were evaluated for glycosidase inhibitory activity. The chloroform extract (CE) showed the lowest IC₅₀ values against α-glucosidase (82.9 μg/ml) and α-mannosidase (132 μg/ml). Chromatography of CE yielded nine phenolic compounds which were identified as isovabachalcone (1), 4′-O-methylbavachalcone (2), isobavachromene (3), corylifolin (4), bavachinin (5), psoralidin (6), neobavaisoflavone (7), corylifol A (8), and bakuchiol (9). All isolated compounds, apart from compound 5, possessed α-glucosidase inhibitory activities. Among them, compounds 6–8 exhibited potent inhibition with IC₅₀s of 13.7, 27.7 and 11.3 μM, respectively. Furthermore, compounds 2 and 6 showed α-mannosidase inhibitory activity. Mechanistic analysis of their inhibition modes against α-glucosidase showed that compounds (6 and 7) were noncompetitive, whereas compound 8 was mixed. Furthermore, the most active glycosidase inhibitors (2, 6–8) were proven to be present in the native seed in high quantities by an HPLC chromatogram.     

Science's Response to CoVID-19

CoVID-19 is a multi-symptomatic disease which has made a global impact due to its ability to spread rapidly, and its relatively high mortality rate. Beyond the heroic efforts to develop vaccines, which we do not discuss herein, the response of scientists and clinicians to this complex problem has reflected the need to detect CoVID-19 rapidly, to diagnose patients likely to show adverse symptoms, and to treat severe and critical CoVID-19. Here we aim to encapsulate these varied and sometimes conflicting approaches and the resulting data in terms of chemistry and biology. In the process we highlight emerging concepts, and potential future applications that may arise out of this immense effort.     

Investigation of the effects of a variation of fuel assembly position on the ex-core neutron flux detection in a PWR

This work shows the impact of potential displacements of the fuel assembly positions in the reactor core on the signal values of the ex-core instrumentation of a pressurized water reactor in order to understand in detail the impact on the calibration factor of ex-core detectors. This was done with a range of Monte Carlo calculations that simulated the detailed geometrical effect by stepwise changing of the positions of fuel assemblies for selected, conservative scenarios. First, criticality calculations were carried out for the chosen core configurations, and corresponding surface sources on the core barrel were determined. In these calculations, the distances were varied between the fuel assemblies which were in the line of sight of the ex-core instrumentation. A maximal change of the fluxes on the surface of the core barrel of 4%/mm could be calculated under conservative assumptions for the combination of displaced fuel assemblies. In addition, a dependence of this effect as a function of cycle burn-up was analyzed. In a second step, transport calculations for the ionization chambers were performed using the surface sources. An increase of the reaction rate at the chambers of up to 3%/mm has been calculated.