409 research outputs found

    Circulating skeletal muscle related microRNAs profile in Piedmontese cattle during different age

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    Piedmontese cattle is known for double-muscle phenotype. MicroRNAs (miRNAs) play important role as regulators in skeletal muscle physiological processes, and we hypothesize that plasma miRNAs expression profiles could be affected by skeletal muscle growth status related to age. Plasma samples of cattle were collected during four different ages from first week of life until the time of commercial end of the fattening period before slaughter. Small-RNA sequencing data analysis revealed the presence of 40% of muscle-related miRNAs among the top 25 highly expressed miRNAs and, 19 miRNAs showed differential expression too. Using qRT-PCR, we validated in a larger bovine population, miRNAs involved in skeletal muscle physiology pathways. Comparing new-born with the other age groups, miR-10b, miR-126-5p, miR-143 and miR-146b were significantly up-regulated, whereas miR-21-5p, miR-221, miR-223 and miR-30b-5p were significantly down-regulated. High expression levels of miR-23a in all the groups were found. Myostatin, a negative regulator of skeletal muscle hypertrophy, was predicted as the target gene for miR-23a and miR-126-5p and we demonstrated their direct binding. Correlation analysis revealed association between miRNAs expression profiles and animals’ weights along the age. Circulating miRNAs could be promising for future studies on their biomarker potentialities to beef cattle selection

    Circulating skeletal muscle related microRNAs profile in Piedmontese cattle during different age

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    Abstract Piedmontese cattle is known for double-muscle phenotype. MicroRNAs (miRNAs) play important role as regulators in skeletal muscle physiological processes, and we hypothesize that plasma miRNAs expression profiles could be affected by skeletal muscle growth status related to age. Plasma samples of cattle were collected during four different ages from first week of life until the time of commercial end of the fattening period before slaughter. Small-RNA sequencing data analysis revealed the presence of 40% of muscle-related miRNAs among the top 25 highly expressed miRNAs and, 19 miRNAs showed differential expression too. Using qRT-PCR, we validated in a larger bovine population, miRNAs involved in skeletal muscle physiology pathways. Comparing new-born with the other age groups, miR-10b, miR-126-5p, miR-143 and miR-146b were significantly up-regulated, whereas miR-21-5p, miR-221, miR-223 and miR-30b-5p were significantly down-regulated. High expression levels of miR-23a in all the groups were found. Myostatin, a negative regulator of skeletal muscle hypertrophy, was predicted as the target gene for miR-23a and miR-126-5p and we demonstrated their direct binding. Correlation analysis revealed association between miRNAs expression profiles and animals’ weights along the age. Circulating miRNAs could be promising for future studies on their biomarker potentialities to beef cattle selection

    Biological role of the HGF/MET ligand/receptor couple in bovine mammary epithelial cells

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    The mammary gland is an organ in which numerous remodelling events follow each other during the development and the reproductive cycle of the animal. After puberty and during pregnancy morphogenesis and proliferation transform the primordial epithelium to an extended network composed of hollow tubules and secreting acini. The development of the mammary gland requires several locally-derived growth factors such Hepatocyte Growth Factor (HGF). Hepatocyte Growth Factor (HGF) is a cytokine originally described as a mitogenic factor for hepatocytes during liver regeneration. HGF is secreted by mesenchymal/stromal cells and acts as a paracrine factor on adjacent epithelial cells that express the c-met tyrosine kinase receptor (Sonnenberg et al., 1993). Binding of HGF to its receptor induces multiple biological responses including proliferation, motility, invasion of the extracellular matrix, resistance to apoptosis and activation of angiogenesis (Bussolino et al., 1992; Brinkmann et al., 1995; Bardelli et al., 1996; Medico et al., 1996). HGF and c-met are expressed and temporally regulated during mammary development and differentiation; some mammary epithelial cell lines grown in a three dimensional collagen matrix with HGF generate tubules (Soriano et al., 1995) with a morphology resembling mammary ducts. Recently, bovine HGF and c-met have been analyzed for their expression in the mammary gland, but no data regarding their biological roles are yet available. We have therefore investigated whether the bovine mammary epithelial cell line BME-UV1 was responsive to HGF and what the biological effects induced by this cytokine were

    Cardiac overexpression of melusin protects from dilated cardiomyopathy due to long-standing pressure overload.

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    We have previously shown that genetic ablation of melusin, a muscle specific beta 1 integrin interacting protein, accelerates left ventricle (LV) dilation and heart failure in response to pressure overload. Here we show that melusin expression was increased during compensated cardiac hypertrophy in mice subjected to 1 week pressure overload, but returned to basal levels in LV that have undergone dilation after 12 weeks of pressure overload. To better understand the role of melusin in cardiac remodeling, we overexpressed melusin in heart of transgenic mice. Echocardiography analysis indicated that melusin over-expression induced a mild cardiac hypertrophy in basal conditions (30% increase in interventricular septum thickness) with no obvious structural and functional alterations. After prolonged pressure overload (12 weeks), melusin overexpressing hearts underwent further hypertrophy retaining concentric LV remodeling and full contractile function, whereas wild-type LV showed pronounced chamber dilation with an impaired contractility. Analysis of signaling pathways indicated that melusin overexpression induced increased basal phosphorylation of GSK3beta and ERK1/2. Moreover, AKT, GSK3beta and ERK1/2 were hyper-phosphorylated on pressure overload in melusin overexpressing compared with wild-type mice. In addition, after 12 weeks of pressure overload LV of melusin overexpressing mice showed a very low level of cardiomyocyte apoptosis and stromal tissue deposition, as well as increased capillary density compared with wild-type. These results demonstrate that melusin overexpression allows prolonged concentric compensatory hypertrophy and protects against the transition toward cardiac dilation and failure in response to long-standing pressure overload

    A biologically inspired neural network controller for ballistic arm movements

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    <p>Abstract</p> <p>Background</p> <p>In humans, the implementation of multijoint tasks of the arm implies a highly complex integration of sensory information, sensorimotor transformations and motor planning. Computational models can be profitably used to better understand the mechanisms sub-serving motor control, thus providing useful perspectives and investigating different control hypotheses. To this purpose, the use of Artificial Neural Networks has been proposed to represent and interpret the movement of upper limb. In this paper, a neural network approach to the modelling of the motor control of a human arm during planar ballistic movements is presented.</p> <p>Methods</p> <p>The developed system is composed of three main computational blocks: 1) a parallel distributed learning scheme that aims at simulating the internal inverse model in the trajectory formation process; 2) a pulse generator, which is responsible for the creation of muscular synergies; and 3) a limb model based on two joints (two degrees of freedom) and six muscle-like actuators, that can accommodate for the biomechanical parameters of the arm. The learning paradigm of the neural controller is based on a pure exploration of the working space with no feedback signal. Kinematics provided by the system have been compared with those obtained in literature from experimental data of humans.</p> <p>Results</p> <p>The model reproduces kinematics of arm movements, with bell-shaped wrist velocity profiles and approximately straight trajectories, and gives rise to the generation of synergies for the execution of movements. The model allows achieving amplitude and direction errors of respectively 0.52 cm and 0.2 radians.</p> <p>Curvature values are similar to those encountered in experimental measures with humans.</p> <p>The neural controller also manages environmental modifications such as the insertion of different force fields acting on the end-effector.</p> <p>Conclusion</p> <p>The proposed system has been shown to properly simulate the development of internal models and to control the generation and execution of ballistic planar arm movements. Since the neural controller learns to manage movements on the basis of kinematic information and arm characteristics, it could in perspective command a neuroprosthesis instead of a biomechanical model of a human upper limb, and it could thus give rise to novel rehabilitation techniques.</p

    Recursive Cluster Elimination Based Support Vector Machine for Disease State Prediction Using Resting State Functional and Effective Brain Connectivity

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    Brain state classification has been accomplished using features such as voxel intensities, derived from functional magnetic resonance imaging (fMRI) data, as inputs to efficient classifiers such as support vector machines (SVM) and is based on the spatial localization model of brain function. With the advent of the connectionist model of brain function, features from brain networks may provide increased discriminatory power for brain state classification.In this study, we introduce a novel framework where in both functional connectivity (FC) based on instantaneous temporal correlation and effective connectivity (EC) based on causal influence in brain networks are used as features in an SVM classifier. In order to derive those features, we adopt a novel approach recently introduced by us called correlation-purged Granger causality (CPGC) in order to obtain both FC and EC from fMRI data simultaneously without the instantaneous correlation contaminating Granger causality. In addition, statistical learning is accelerated and performance accuracy is enhanced by combining recursive cluster elimination (RCE) algorithm with the SVM classifier. We demonstrate the efficacy of the CPGC-based RCE-SVM approach using a specific instance of brain state classification exemplified by disease state prediction. Accordingly, we show that this approach is capable of predicting with 90.3% accuracy whether any given human subject was prenatally exposed to cocaine or not, even when no significant behavioral differences were found between exposed and healthy subjects.The framework adopted in this work is quite general in nature with prenatal cocaine exposure being only an illustrative example of the power of this approach. In any brain state classification approach using neuroimaging data, including the directional connectivity information may prove to be a performance enhancer. When brain state classification is used for disease state prediction, our approach may aid the clinicians in performing more accurate diagnosis of diseases in situations where in non-neuroimaging biomarkers may be unable to perform differential diagnosis with certainty

    Human Milk Protein Production in Xenografts of Genetically Engineered Bovine Mammary Epithelial Stem Cells

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    BACKGROUND: In the bovine species milk production is well known to correlate with mammary tissue mass. However, most advances in optimizing milk production relied on improvements of breeding and husbandry practices. A better understanding of the cells that generate bovine mammary tissue could facilitate important advances in milk production and have global economic impact. With this possibility in mind, we show that a mammary stem cell population can be functionally identified and isolated from the bovine mammary gland. We also demonstrate that this stem cell population may be a promising target for manipulating the composition of cow's milk using gene transfer. METHODS AND FINDINGS: We show that the in vitro colony-forming cell assay for detecting normal primitive bipotent and lineage-restricted human mammary clonogenic progenitors are applicable to bovine mammary cells. Similarly, the ability of normal human mammary stem cells to regenerate functional bilayered structures in collagen gels placed under the kidney capsule of immunodeficient mice is shared by a subset of bovine mammary cells that lack aldehyde dehydrogenase activity. We also find that this activity is a distinguishing feature of luminal-restricted bovine progenitors. The regenerated structures recapitulate the organization of bovine mammary tissue, and milk could be readily detected in these structures when they were assessed by immunohistochemical analysis. Transplantation of the bovine cells transduced with a lentivirus encoding human β-CASEIN led to expression of the transgene and secretion of the product by their progeny regenerated in vivo. CONCLUSIONS: These findings point to a common developmental hierarchy shared by human and bovine mammary glands, providing strong evidence of common mechanisms regulating the maintenance and differentiation of mammary stem cells from both species. These results highlight the potential of novel engineering and transplant strategies for a variety of commercial applications including the production of modified milk components for human consumption
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