An integrated look at the effect of structure on nutrient bioavailability in plant foods

The true bioavailability of a nutrient being intrinsically coupled to the specific food matrix in which it occurs remains poorly considered in nutrition science. During digestion, the food matrix and, in particular, the structure of food modulate the extent and kinetics to which nutrients and bioactive compounds make themselves available for absorption. In this perspective, we describe an integrated look at the effect of structure on nutrient bioavailability in plant foods. Based on this integrated look, cell wall integrity and the particle size of the plant material during its transit in the small intestine determine the bioavailability of plant nutrients; in turn, cell wall integrity and particle size are determined by the level of oral processing and, accordingly, what subsequently escapes digestion in the upper intestine and is utilized by colon microbiota. Ultimately, the effect on nutrient digestion is linked to food structure through each step of digestion. A consideration of the structure rather than just the composition of foods opens up possibilities for the design of healthier foods. © 2018 Society of Chemical Industry     

Coupling hydrothermal liquefaction and aqueous phase reforming for integrated production of biocrude and renewable H2

Lignin-rich stream from lignocellulosic ethanol production was converted into biocrude by continuous hydrothermal liquefaction (HTL) while hydrogen was produced by aqueous phase reforming (APR) of the HTL aqueous by-product. The effects of Na₂CO₃ and NaOH were investigated both in terms of processability of the feedstock as well as yield and composition of the obtained products. A maximum biocrude yield of 27 wt% was reached in the NaOH-catalyzed runs. A relevant amount of dissolved phenolics were detected in the co-produced aqueous phase (AP), and removed by liquid–liquid extraction using butyl acetate or diethyl ether, preserving the APR catalyst stability and reaching an hydrogen yield up to 146 mmol H₂ L⁻¹ AP. Preliminary mass balances integrating HTL and APR showed that the hydrogen provided by APR may account for up to 46% of the hydrogen amount theoretically required for upgrading the HTL biocrude, thus significantly improving the process performance and sustainability.     

Evaluation of the salt leaching method for the production of ethylene propylene diene monomer rubber foams

The thermomechanical behavior of ethylene propylene diene monomer (EPDM) foams produced with the salt leaching method has been investigated and compared with the behavior of EPDM foams obtained from conventional blowing agents. Moreover, the salt-leaching process has been optimized to minimize salt residues and the influence of different parameters (such as average particle size and particle size distribution) has been investigated. Scanning electron microscopy and density measurements highlighted that salt-leaching leads to the formation of open-cell porosity with cell dimensions of around 60 to 80 μm, while foams obtained with the two traditional foaming agents lead to closed-cell porosity. Compression set values indicate that the behavior of the foams produced with salt leaching are more similar to the unfoamed rubber, characterized by higher elasticity and low residual deformation. Two theoretical models were successfully applied to the compression curves (Mooney-Rivlin and Exponential-Logarithmic) and they highlighted the effect of foaming on the properties of EPDM rubber and in particular the higher chain extensibility obtained through the salt leaching foaming method.     

Discovery of an Allosteric Ligand Binding Site in SMYD3 Lysine Methyltransferase

SMYD3 is a multifunctional epigenetic enzyme with lysine methyltransferase activity and various interaction partners. It is implicated in the pathophysiology of cancers but with an unclear mechanism. To discover tool compounds for clarifying its biochemistry and potential as a therapeutic target, a set of drug-like compounds was screened in a biosensor-based competition assay. Diperodon was identified as an allosteric ligand; its R and S enantiomers were isolated, and their affinities to SMYD3 were determined (K_D=42 and 84 μM, respectively). Co-crystallization revealed that both enantiomers bind to a previously unidentified allosteric site in the C-terminal protein binding domain, consistent with its weak inhibitory effect. No competition between diperodon and HSP90 (a known SMYD3 interaction partner) was observed although SMYD3–HSP90 binding was confirmed (K_D=13 μM). Diperodon clearly represents a novel starting point for the design of tool compounds interacting with a druggable allosteric site, suitable for the exploration of noncatalytic SMYD3 functions and therapeutics with new mechanisms of action.     

Cyclic Nigerosyl-Nigerose as Oxygen Nanocarrier to Protect Cellular Models from Hypoxia/Reoxygenation Injury: Implications from an In Vitro Model

Heart failure (HF) prevalence is increasing among the aging population, and the mortality rate remains unacceptably high despite improvements in therapy. Myocardial ischemia (MI) and, consequently, ischemia/reperfusion injury (IRI), are frequently the basis of HF development. Therefore, cardioprotective strategies to limit IRI are mandatory. Nanocarriers have been proposed as alternative therapy for cardiovascular disease. Controlled reoxygenation may be a promising strategy. Novel nanocarriers, such as cyclic nigerosyl-nigerose (CNN), can be innovative tools for oxygen delivery in a controlled manner. In this study we analyzed new CNN-based formulations as oxygen nanocarriers (O₂-CNN), and compared them with nitrogen CNN (N₂-CNN). These different CNN-based formulations were tested using two cellular models, namely, cardiomyoblasts (H9c2), and endothelial (HMEC) cell lines, at different concentrations. The effects on the growth curve during normoxia (21% O₂, 5% CO₂ and 74% N₂) and their protective effects during hypoxia (1% O₂, 5% CO₂ and 94% N₂) and reoxygenation (21% O₂, 5% CO₂ and 74% N₂) were studied. Neither O₂-CNN nor N₂-CNN has any effect on the growth curve during normoxia. However, O₂-CNN applied before hypoxia induces a 15–30% reduction in cell mortality after hypoxia/re-oxygenation when compared to N₂-CNN. O₂-CNN showed a marked efficacy in controlled oxygenation, which suggests an interesting potential for the future medical application of soluble nanocarrier systems for MI treatment.     

On the asymptotic behaviour of shells of revolution in free vibration

We consider the free vibration problem of thin shells of revolution of constant type of geometry, focusing on the asymptotic behaviour of the lowest eigenfrequency, as the thickness tends to zero. Numerical experiments are computed using two discretization methods, collocation and finite elements, each corresponding to a different shell model. Our results are in agreement with theoretical results obtained using interpolation theory and cited in literature.     

Switching supervisory control based on controller falsification and closed-loop performance inference

The paper addresses two of the basic issues of switching supervisory control (SSC): controller falsification (CF) and inference of candidate loop behaviour (ICLB). CF is approached as a statistical fault detection problem in that the currently operating controller is falsified as soon as a divergence trend is detected. This is achieved by considering a statistic (or residual) in the form of a ratio of closed-loop variables, and the falsification test is carried out by comparing at each time the ratio statistic with a threshold. It is constructively shown that the thresholds can be fixed, irrespective of the disturbance intensity, in such a way that faults are detected with probability one while probability of false alarms can be made as small as we wish. The ICLB issue is approached by the virtual reference approach. This allows one to obtain an inference of the performance of a candidate loop via a mean-square average of suitably filtered prediction errors. It is shown how a supervisory logic can be built by combining the results on CF with those on ICLB.     

Local SVM approaches for fast and accurate classification of remote-sensing images

In this article, the task of remote-sensing image classification is tackled with local maximal margin approaches. First, we introduce a set of local kernel-based classifiers that alleviate the computational limitations of local support vector machines (SVMs), maintaining at the same time high classification accuracies. Such methods rely on the following idea: (a) during training, build a set of local models covering the considered data and (b) during prediction, choose the most appropriate local model for each sample to evaluate. Additionally, we present a family of operators on kernels aiming to integrate the local information into existing (input) kernels in order to obtain a quasi-local (QL) kernel. To compare the performances achieved by the different local approaches, an experimental analysis was conducted on three distinct remote-sensing data sets. The obtained results show that interesting performances can be achieved in terms of both classification accuracy and computational cost.