35 research outputs found
Modeling Neurodegeneration in Zebrafish
The zebrafish, Danio rerio, has been established as an excellent vertebrate model for the study of developmental biology and gene function. It also has proven to be a valuable model to study human diseases. Here, we reviewed recent publications using zebrafish to study the pathology of human neurodegenerative diseases including Parkinson’s, Huntington’s, and Alzheimer’s. These studies indicate that zebrafish genes and their human homologues have conserved functions with respect to the etiology of neurodegenerative diseases. The characteristics of the zebrafish and the experimental approaches to which it is amenable make this species a useful complement to other animal models for the study of pathologic mechanisms of neurodegenerative diseases and for the screening of compounds with therapeutic potential
Simple model systems: a challenge for Alzheimer's disease
The success of biomedical researches has led to improvement in human health and increased life expectancy. An unexpected consequence has been an increase of age-related diseases and, in particular, neurodegenerative diseases. These disorders are generally late onset and exhibit complex pathologies including memory loss, cognitive defects, movement disorders and death. Here, it is described as the use of simple animal models such as worms, fishes, flies, Ascidians and sea urchins, have facilitated the understanding of several biochemical mechanisms underlying Alzheimer's disease (AD), one of the most diffuse neurodegenerative pathologies. The discovery of specific genes and proteins associated with AD, and the development of new technologies for the production of transgenic animals, has helped researchers to overcome the lack of natural models. Moreover, simple model systems of AD have been utilized to obtain key information for evaluating potential therapeutic interventions and for testing efficacy of putative neuroprotective compounds
In vivo cardiac pacemaker function of differentiated human mesenchymal stem cells from adipose tissue transplanted into porcine hearts
BACKGROUND Mesenchymal stem cells (MSC) modified by gene transfer to express cardiac pacemaker channels such as HCN2 or HCN4 were shown to elicit pacemaker function after intracardiac transplantation in experimental animal models. Human MSC derived from adipose tissue (haMSC) differentiate into cells with pacemaker properties in vitro, but little is known about their behavior after intracardiac transplantation. AIM To investigate whether haMSC elicit biological pacemaker function in vivo after transplantation into pig hearts. METHODS haMSC under native conditions (nhaMSC) or after preconditioning by medium differentiation (dhaMSC) (n = 6 pigs each, 5 × 106 cells per animal) were injected into the porcine left ventricular free wall. Animals receiving PBS injection served as controls (n = 6). Four weeks later, total atrioventricular (AV)-block was induced by radiofrequency catheter ablation, and electronic pacemaker devices were implanted for backup stimulation and heart rate monitoring. Ventricular rate and rhythm of pigs were evaluated during a follow-up of 15 d post ablation by 12-lead-ECG with heart rate assessment, 24-h continuous rate monitoring recorded by electronic pacemaker, assessment of escape recovery time, and pharmacological challenge to address catecholaminergic rate response. Finally, hearts were analyzed by histological and immunohistochemical investigations. RESULTS In vivo transplantation of dhaMSC into the left ventricular free wall of pigs elicited spontaneous and regular rhythms that were pace-mapped to ventricular injection sites (mean heart rate 72.2 ± 3.6 bpm; n = 6) after experimental total AV block. Ventricular rhythms were stably detected over a 15-d period and were sensitive to catecholaminergic stimulation (mean maximum heart rate 131.0 ± 6.2 bpm; n = 6; P < 0.001). Pigs, which received nhaMSC or PBS presented significantly lower ventricular rates (mean heart rates 47.2 ± 2.5 bpm and 37.4 ± 3.2 bpm, respectively; n = 6 each; P < 0.001) and exhibited little sensitivity towards catecholaminergic stimulation (mean maximum heart rates 76.4 ± 3.1 bpm and 60.5 ± 3.1 bpm, respectively; n = 6 each; P < 0.05). Histological and immunohistochemical evaluation of hearts treated with dhaMSC revealed local clusters of transplanted cells at the injection sites that lacked macrophage or lymphocyte infiltrations or tumor formation. Intense fluorescence signals at these sites indicated membrane expression of HCN4 and other pacemaker-specific proteins involved in cardiac automaticity and impulse propagation. CONCLUSION dhaMSC transplanted into pig left ventricles sustainably induced rate-responsive ventricular pacemaker activity after in vivo engraftment for four weeks. The data suggest that preconditioned MSC may further differentiate along a pacemaker-related lineage after myocardial integration and may establish superior pacemaker properties in vivo
Pacemaker cell characteristics of differentiated and HCN4-transduced human mesenchymal stem cells
AIMS: Cell-based biological pacemakers aim to overcome limitations and side effects of electronic pacemaker devices. We here developed and tested different approaches to achieve nodal-type differentiation using human adipose- and bone marrow-derived mesenchymal stem cells (haMSC, hbMSC). MAIN METHODS: haMSC and hbMSC were differentiated using customized protocols. Quantitative RT-PCR was applied for transcriptional pacemaker-gene profiling. Protein membrane expression was analyzed by immunocytochemistry. Pacemaker current (If) was studied in haMSC with and without lentiviral HCN4-transduction using patch clamp recordings. Functional characteristics were evaluated by co-culturing with neonatal rat ventricular myocytes (NRVM). KEY FINDINGS: Culture media-based differentiation for two weeks generated cells with abundant transcription of ion channel genes (Cav1.2, NCX1), transcription factors (TBX3, TBX18, SHOX2) and connexins (Cx31.9 and Cx45) characteristic for cardiac pacemaker tissue, but lack adequate HCN transcription. haMSC-derived cells revealed transcript levels, which were closer related to sinoatrial nodal cells than hbMSC-derived cells. To substitute for the lack of If, we performed lentiviral HCN4-transduction of haMSC resulting in stable If. Co-culturing with NRVM demonstrated that differentiated haMSC expressing HCN4 showed earlier onset of spontaneous contractions and higher beating regularity, synchrony and rate compared to co-cultures with non-HCN4-transduced haMSC or HCN4-transduced, non-differentiated haMSC. Confocal imaging indicated increased membrane expression of cardiac gap junctional proteins in differentiated haMSC. SIGNIFICANCE: By differentiation haMSC, rather than hbMSC attain properties favorable for cardiac pacemaking. In combination with lentiviral HCN4-transduction, a cellular phenotype was generated that sustainably controls and stabilizes rate in co-culture with NRVM
A review on distinct methods and approaches to perform triangulation for Bayesian networks
Summary. Triangulation of a Bayesian network (BN) is somehow a necessary step in order to perform inference in a more efficient way, either if we use a secondary structure as the join tree (JT) or implicitly when we try to use other direct techniques on the network. If we focus on the first procedure, the goodness of the triangulation will affect on the simplicity of the join tree and therefore on a quicker and easier inference process. The task of obtaining an optimal triangulation (in terms of producing the minimum number of triangulation links a.k.a. fill-ins) has been proved as an NP-hard problem. That is why many methods of distinct nature have been used with the purpose of getting as good as possible triangulations for any given network, especially important for big structures, that is, with a large number of variables and links. In this chapter, we attempt to introduce the problem of triangulation, locating it in the compilation process and showing first its relevance for inference, and consequently for working with Bayesian networks. After this introduction, the most popular and used strategies to cope with the triangulation problem are reviewed