Variables Influencing Chewing Electromyography Response in Food Texture Evaluation

Food choice is linked to many characteristics, among which texture is one of the most important. As a consequence, texture is a quality parameter that needs to be understood on a global perspective, including physical and psychological aspects. Texture perception is gained from a complex process of chewing, and not from a single action. Thus, there is a need for techniques that consider the whole process of chewing. Among those techniques, electromyography (EMG) seems promising. Different variables influence the chewing response as registered through EMG. Some of those variables are linked to the experimental set-up, where there is a need for standardization as well as data processing procedures. Other variables are linked to subject characteristics, both physical (e.g., facial anatomy, age) and psychological (e.g., personality, cognitive processes). Experimental planning can also constitute a source of variability, the number of products and trials per session being important items. The way the EMG signals are processed (parameters from EMG records) also must be considered in order to extract reliable and consistent conclusions. Because no standard practices have been established for the use of EMG in food texture assessment, it is important to review how this technique has been used, the variables involved, and the meaning or concepts associated with the outputs.     

Modification of appetite by bread consumption: A systematic review of randomized controlled trials

The inclusion of different ingredients or the use of different baking technologies may modify the satiety response to bread, and aid in the control of food intake. The aim of this study was to perform a systematic search of randomized clinical trials on the effect of bread consumption on appetite ratings in humans. The search equation was (“Bread”[MeSH]) AND (“Satiation”[MeSH] OR “Satiety response”[MeSH]), and the filter “clinical trials.” As a result of this procedure, 37 publications were selected. The satiety response was considered as the primary outcome. The studies were classified as follows: breads differing in their flour composition, breads differing in ingredients other than flours, breads with added organic acids, or breads made using different baking technologies. In addition, we have revised the data related to the influence of bread on glycemic index, insulinemic index and postprandial gastrointestinal hormones responses. The inclusion of appropriate ingredients such as fiber, proteins, legumes, seaweeds and acids into breads and the use of specific technologies may result in the development of healthier breads that increase satiety and satiation, which may aid in the control of weight gain and benefit postprandial glycemia. However, more well-designed randomized control trials are required to reach final conclusions.     

Effects of a citrus based juice on biomarkers of oxidative stress in metabolic syndrome patients

Bioactive substances found in numerous foods can be successfully and safely used to modify various cellular functions and affect the oxidative stress. The aim of this study was to analyze the effect of a citrus-based juice (juice citrus (95%) with 5% of aronia extract (Aronia melanocarpa)) on biomarkers of oxidative stress in patients with metabolic syndrome compared with healthy individuals. The study comprised 20 healthy subjects and 33 patients with metabolic syndrome. Eighteen patients consumed daily 300 mL of a citrus-based juice during 6 months and 15 patients consumed 300 mL of a placebo beverage. The control group consumed a citrus-based juice (CJ). Before, and at sixth months after consuming of a citrus-based juice the following parameters were determined: 15-isoprostane F₂, 8-hydroxydeoxyguanosine (8-OHdG), reduced and oxidized glutathione (GSH/GSSH), carbonyl groups and oxidized LDL (ox-LDL). After consuming CJ during 6 months the values of 8-OHdG, carbonyl groups and LDL-ox decreased in both analyzed groups and the values of GSH/GSSH increased. Significant differences were observed in both groups. Thus consumption of citrus-based juice improved the biomarkers of oxidative stress in metabolic syndrome patients.     

Molecular identification of nine commercial flaffish species by polymerase chain reaction-restriction fragment length polymorphism analysis of a segment of the cytochrome b region

Commercial refrigerated or frozen flatfish fillets are sometimes mislabeled, and identification of these mislabeled products is necessary to prevent fraudulent substitution. Identification of nine commercial flatfish species (order Pleuronectiformes), Hippoglossus hippoglossus (halibut), Lepidorhombus boscii (four-spotted scaldfish), Lepidorhombus whiffiagonis (megrin), Platichthys flesus (flounder), Pleuronectes platessa (European plaice), Reinhardtius hippoglossoides (Greenland halibut), Scophthalmus maximus (turbot), Scophthalmus rhombus (brill), and Solea vulgaris (=Solea solea) (sole), was carried out on the basis of the amplification of a 486-bp segment of the mitochondrial genome (tRNA(Glu)/cytochrome b) by using the polymerase chain reaction (PCR) and universal primers. Sequences of PCR-amplified DNA from the flatfish species were used to select eight restriction enzymes (REs). The PCR products were cut with each RE, resulting in species-specific restriction fragment length polymorphism. Seven species groups could be identified by application of the single RE DdeI and six species groups by using HaeIII, HinfI, MaeI, or MboI. Different combinations of only a couple of these REs could unambiguously identify the nine flatfish species. Genetic polymorphisms of the target sequence were examined by comparison with previously published DNA sequences, and the results of this comparison confirmed the usefulness of this technique in distinguishing and genetically characterizing refrigerated or frozen pieces of these nine flatfish species.     

Comparative Study of Monoclonal and Recombinant Antibody-Based Immunoassays for Fungicide Analysis in Fruit Juices

A comparative study of the analytical performance of enzyme-linked immunosorbent assays (ELISAs), based on monoclonal and recombinant antibodies, for the determination of fungicide residues in fruit juices has been carried out. To this aim, three murine hybridoma cell lines secreting specific monoclonal antibodies against (RS)-2-(2,4-dichlorophenyl)-3-(1H-1,2,4-triazol-1-yl)propyl-1,1,2,2-tetrafluoroethyl ether (tetraconazole), 2-(4-triazolyl)benzimidazole (thiabendazole), and (RS)-1-(β-allyloxy-2,4-dichlorophenylethyl)imidazole (imazalil) were used as a source of immunoglobulin gene fragments for the production of single-chain variable fragment (scFv) and fusion scFv-pIII recombinant antibodies in Escherichia coli. Selected recombinant antibodies displayed cross-reactivity profiles very similar to those of the parent monoclonal antibodies. Imazalil and tetraconazole recombinant antibodies showed one order of magnitude lower affinity than their respective monoclonal antibodies, whereas the thiabendazole recombinant antibodies showed an affinity similar to that of their parent monoclonal antibody. On the other hand, scFv-pIII fusion fragments showed similar analytical properties as, and occasionally better than, scFv recombinant antibodies. Finally, ELISAs developed from each antibody type showed similar analytical performance when applied to the analysis of the target fungicides in fruit juices.     

Data visualization for reliability analysis of repairable systems

The objective of this paper is to find out possible patterns of failure occurrences in a repairable system. We develop a graphical exploratory tool and perform visual inference considering non‐parametric local linear kernel estimators for the rate of occurrence of failures (ROCOF) and its first derivative. The shape characteristics of the ROCOF function are distinguished from those which are merely an artefact of the sampling variability of the data through the construction of confidence intervals for the first derivative. The proposal is illustrated with several real data sets, and its performance is evaluated through an extensive simulation study.     

Convolutional neural networks for segmenting xylem vessels in stained cross-sectional images

Xylem is a vascular tissue that conducts sap (water and dissolved minerals) from the roots to the rest of the plant while providing physical support and resources. Sap is conducted within dead hollow cells (called vessels in flowering plants) arranged to form long pipes. Once formed, vessels do not change their structure and last from years to millennia. Vessels’ configuration (size, abundance, and spatial pattern) constitutes a record of the plant–environment relationship, and therefore, a tool for monitoring responses at the plant and ecosystem level. This information can be extracted through quantitative anatomy; however, the effort to identify and measure hundreds of thousands of conductive cells is an inconvenience to the progress needed to have solid assessments of the anatomical–environment relationship. In this paper, we propose an automatic methodology based on convolutional neural networks to segment xylem vessels. It includes a post-processing stage based on the use of redundant information to improve the performance of the outcome and make it useful in different sample configurations. Three different neural networks were tested obtaining similar results (pixel accuracy about 90%), which indicates that the methodology can be effectively used for segmentation of xylem vessels into images with non-homogeneous variations of illumination. The development of accurate automatic tools using CNNs would reduce the entry barriers associated with quantitative xylem anatomy expanding the use of this technique by the scientific community.

     

A biased‐randomized iterated local search for the distributed assembly permutation flow‐shop problem

Modern production systems require multiple manufacturing centers—usually distributed among different locations—where the outcomes of each center need to be assembled to generate the final product. This paper discusses the distributed assembly permutation flow‐shop scheduling problem, which consists of two stages: the first stage is composed of several production factories, each of them with a flow‐shop configuration; in the second stage, the outcomes of each flow‐shop are assembled into a final product. The goal here is to minimize the makespan of the entire manufacturing process. With this objective in mind, we present an efficient and parameter‐less algorithm that makes use of a biased‐randomized iterated local search metaheuristic. The efficiency of the proposed method is evaluated through the analysis of an extensive set of computational experiments. The results show that our algorithm offers excellent performance when compared with other state‐of‐the‐art approaches, obtaining several new best solutions.