Investigation on the effect of different levels of dried sweet orange (Citrus sinensis) pulp on performance,carcass characteristics and physiological and biochemical parameters in broiler chicken

Utilization of agricultural by-products in animal nutrition is a matter of great concern. Dried sweet orange (Citrus sinensis) pulp (DCSP) is a potential source of valuable nutrients and natural antioxidants for poultry feed. In the experiment, a feeding trial was conducted in order to investigate the effect of different levels of dried orange residues in diet on broiler growth performance, carcass characteristics, blood metabolites, humoral immunity, and cecum microbial population. A total of 200 one day experimental broiler chicks were distributed into a completely randomized design (CRD) which included 5 dietary treatments with 4 replicates per each treatment and 10 birds fed in each replicate. The experimental treatments consist of a control group (without additive), 0.5%, 1.0%, 1.5%, and 2% of DCSP (residue) in diet. Weight gain, feed intake and feed conversion ratio (FCR) were measured. Blood parameters and carcass traits were measured in the postnatal 35th day. The highest level of dried orange residues in treatment 5 (T5) had significantly increased the feed intake and body weight of broilers in groups and overall during the rearing period (P > 0.05). Different levels of dried orange residues had no significant effect on chicken FCR. Using of dried orange residues significantly decreased the liver and abdominal fat of broilers (P < 0.05). T5 has also significantly lower level of triglyceride than the control (T1) and treatment 2 (T2) (P < 0.05). In conclusion, the use of dried orange residues improved some performance (e.g. feed intake and body weight gain), decreased liver and abdominal fat and also serum triglyceride level in broiler chicken.     

Angiogenesis Is Induced and Wound Size Is Reduced by Electrical Stimulation in an Acute Wound Healing Model in Human Skin

Angiogenesis is critical for wound healing. Insufficient angiogenesis can result in impaired wound healing and chronic wound formation. Electrical stimulation (ES) has been shown to enhance angiogenesis. We previously showed that ES enhanced angiogenesis in acute wounds at one time point (day 14). The aim of this study was to further evaluate the role of ES in affecting angiogenesis during the acute phase of cutaneous wound healing over multiple time points. We compared the angiogenic response to wounding in 40 healthy volunteers (divided into two groups and randomised), treated with ES (post-ES) and compared them to secondary intention wound healing (control). Biopsy time points monitored were days 0, 3, 7, 10, 14. Objective non-invasive measures and H&E analysis were performed in addition to immunohistochemistry (IHC) and Western blotting (WB). Wound volume was significantly reduced on D7, 10 and 14 post-ES (p = 0.003, p = 0.002, p<0.001 respectively), surface area was reduced on days 10 (p = 0.001) and 14 (p<0.001) and wound diameter reduced on days 10 (p = 0.009) and 14 (p = 0.002). Blood flow increased significantly post-ES on D10 (p = 0.002) and 14 (p = 0.001). Angiogenic markers were up-regulated following ES application; protein analysis by IHC showed an increase (p<0.05) in VEGF-A expression by ES treatment on days 7, 10 and 14 (39%, 27% and 35% respectively) and PLGF expression on days 3 and 7 (40% on both days), compared to normal healing. Similarly, WB demonstrated an increase (p<0.05) in PLGF on days 7 and 14 (51% and 35% respectively). WB studies showed a significant increase of 30% (p>0.05) on day 14 in VEGF-A expression post-ES compared to controls. Furthermore, organisation of granulation tissue was improved on day 14 post-ES. This randomised controlled trial has shown that ES enhanced wound healing by reduced wound dimensions and increased VEGF-A and PLGF expression in acute cutaneous wounds, which further substantiates the role of ES in up-regulating angiogenesis as observed over multiple time points. This therapeutic approach may have potential application for clinical management of delayed and chronic wounds.     

Chemometrics models for overcoming high between subject variability: applications in clinical metabolic profiling studies

In human metabolic profiling studies, between-subject variability is often the dominant feature and can mask the potential classifications of clinical interest. Conventional models such as principal component analysis (PCA) are usually not effective in such situations and it is therefore highly desirable to find a suitable model which is able to discover the underlying pattern hidden behind the high between-subject variability. In this study we employed two clinical metabolomics data sets as the testing grounds, in which such variability had been observed, and we demonstrate that a proper choice of chemometrics model can help to overcome this issue of high between-subject variability. Two data sets were used to represent two different types of experiment designs. The first data set was obtained from a small-scale study investigating volatile organic compounds (VOCs) collected from chronic wounds using a skin patch device and analysed by thermal desorption-gas chromatography-mass spectrometry. Five patients were recruited and for each patient three sites sampled in triplicate: healthy skin, boundary of the lesion and top of the lesion, the aim was to discriminate these three types of samples based on their VOC profile. The second data set was from a much larger study involving 35 healthy subjects, 47 patients with chronic obstructive pulmonary disease and 33 with asthma. The VOCs in the breath of each subject were collected using a mask device and analysed again by GC–MS with the aim of discriminating the three types of subjects based on breath VOC profiles. Multilevel simultaneous component analysis, multilevel partial least squares for discriminant analysis, ANOVA-PCA, and a novel simplified ANOVA-PCA model—which we have named ANOVA-Mean Centre (ANOVA-MC)—were applied on these two data sets. Significantly improved results were obtained by using these models. We also present a novel validation procedure to verify statistically the results obtained from those models.     

Capturing the songs of mice with an improved detection and classification method for ultrasonic vocalizations (BootSnap)

House mice communicate through ultrasonic vocalizations (USVs), which are above the range of human hearing (>20 kHz), and several automated methods have been developed for USV detection and classification. Here we evaluate their advantages and disadvantages in a full, systematic comparison, while also presenting a new approach. This study aims to 1) determine the most efficient USV detection tool among the existing methods, and 2) develop a classification model that is more generalizable than existing methods. In both cases, we aim to minimize the user intervention required for processing new data. We compared the performance of four detection methods in an out-of-the-box approach, pretrained DeepSqueak detector, MUPET, USVSEG, and the Automatic Mouse Ultrasound Detector (A-MUD). We also compared these methods to human visual or ‘manual’ classification (ground truth) after assessing its reliability. A-MUD and USVSEG outperformed the other methods in terms of true positive rates using default and adjusted settings, respectively, and A-MUD outperformed USVSEG when false detection rates were also considered. For automating the classification of USVs, we developed BootSnap for supervised classification, which combines bootstrapping on Gammatone Spectrograms and Convolutional Neural Networks algorithms with Snapshot ensemble learning. It successfully classified calls into 12 types, including a new class of false positives that is useful for detection refinement. BootSnap outperformed the pretrained and retrained state-of-the-art tool, and thus it is more generalizable. BootSnap is freely available for scientific use.     

Comparative microbiome analysis of Diaphorina citri and its associated parasitoids Tamarixia radiata and Diaphorencyrtus aligarhensis reveals Wolbachia as a dominant endosymbiont

Microbiome analysis in a host–parasitoid interaction network was conducted to compare the taxonomic composition of bacterial communities of Diaphornia citri, Tamarixia radiata, and Diaphorencyrtus aligarhensis. The comparative analysis revealed differences in the composition and diversity of the symbiont populations across the host and its associated parasitoids. Proteobacteria was the most dominant phylum, representing 67.80% of the total bacterial community, while Candidatus Profftella armature and Wolbachia were the dominant genera across the host and parasitoids. There were clear differences observed in alpha and beta diversity of microbiota through the host and its associated parasitoids. The function prediction of bacterial communities and Pearson correlation analysis showed that specific bacterial communities displayed positive correlations with the carbohydrate metabolism pathway. Furthermore, when symbiotic bacteria were eliminated using a broad-spectrum antibiotic, tetracycline hydrochloride, the parasitoids' median survival time and longevity were significantly reduced. We confirmed the physiological effects of symbiotic bacteria on the fitness of parasitoids and demonstrated the effect of antibiotics in decreasing the food intake and measurement of amino acids in the hemolymph. This study sheds light on basic information about the mutualism between parasitoids and bacteria, which may be a potential source for biocontrol strategies for citrus psyllid, especially D. citri.     

High-fat diet intake ameliorates the expression of hedgehog signaling pathway in adult rat liver

Molecular Biology Reports - Disproportionate fatty diet intake provokes hepatic lipid accumulation that causes non-alcoholic fatty liver disease, triggering the embryonically conserved Hedgehog...     

CentiServer: A Comprehensive Resource,Web-Based Application and R Package for Centrality Analysis

Various disciplines are trying to solve one of the most noteworthy queries and broadly used concepts in biology, essentiality. Centrality is a primary index and a promising method for identifying essential nodes, particularly in biological networks. The newly created CentiServer is a comprehensive online resource that provides over 110 definitions of different centrality indices, their computational methods, and algorithms in the form of an encyclopedia. In addition, CentiServer allows users to calculate 55 centralities with the help of an interactive web-based application tool and provides a numerical result as a comma separated value (csv) file format or a mapped graphical format as a graph modeling language (GML) file. The standalone version of this application has been developed in the form of an R package. The web-based application (CentiServer) and R package (centiserve) are freely available at http://www.centiserver.org/