Search results for "EURA"
showing 10 items of 3336 documents
Contrasting coping styles meet the wall: A dopamine driven dichotomy in behavior and cognition
2017
Individual variation in the ability to modify previously learned behaviour is an important dimension of trait correlations referred to as coping styles, behavioral syndromes or personality. These trait clusters have been shaped by natural selection, and underlying control mechanisms are often conserved throughout vertebrate evolution. In teleost fishes, behavioral flexibility and coping style have been studied in the high (HR) and low-responsive (LR) rainbow trout lines. Generally, proactive LR trout show a behaviour guided by previously learned routines, while HR trout show a more flexible behaviour relying on environmental cues. In mammals, routine dependent vs flexible behavior has been …
TET3 prevents terminal differentiation of adult NSCs by a non-catalytic action at Snrpn.
2019
Ten-eleven-translocation (TET) proteins catalyze DNA hydroxylation, playing an important role in demethylation of DNA in mammals. Remarkably, although hydroxymethylation levels are high in the mouse brain, the potential role of TET proteins in adult neurogenesis is unknown. We show here that a non-catalytic action of TET3 is essentially required for the maintenance of the neural stem cell (NSC) pool in the adult subventricular zone (SVZ) niche by preventing premature differentiation of NSCs into non-neurogenic astrocytes. This occurs through direct binding of TET3 to the paternal transcribed allele of the imprinted gene Small nuclear ribonucleoprotein-associated polypeptide N (Snrpn), contr…
The claustrum is a target for projections from the supramammillary nucleus in the rat.
2019
Injection of the anterograde tracer Phaseolus vulgaris leucoagglutinin (PHAL) into the rat rostral and caudal supramammillary nucleus (SUM) provided expected patterns of projections into the hippocampus and the septal region. In addition, unexpectedly intense projections were observed into the claustrum defined by parvalbumin expression. Injections of the retrograde tracer fluorogold (FG) into the hippocampus and the region of the claustrum showed that the cells of origin of these projections distributed similarly within the borders of the SUM. The SUM is usually involved in control of hippocampal theta activity, but the observation of intense projections into the claustrum indicates that i…
Immunomodulatory effects of stem cells: Therapeutic option for neurodegenerative disorders.
2017
Stem cells have the capability of self-renewal and can differentiate into different cell types that might be used in regenerative medicine. Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and amyotrophic lateral sclerosis (ALS) currently lack effective treatments. Although stem cell therapy is still on the way from bench to bedside, we consider that it might provide new hope for patients suffering with neurodegenerative diseases. In this article, we will give an overview of recent studies on the potential therapeutic use of mesenchymal stem cells (MSCs), neural stem cells (NSCs), embryonic stem cells (ESCs), induced pluripotent…
Recurrent Deep Neural Networks for Nucleosome Classification
2020
Nucleosomes are the fundamental repeating unit of chromatin. A nucleosome is an 8 histone proteins complex, in which approximately 147–150 pairs of DNA bases bind. Several biological studies have clearly stated that the regulation of cell type-specific gene activities are influenced by nucleosome positioning. Bioinformatic studies have improved those results showing proof of sequence specificity in nucleosomes’ DNA fragment. In this work, we present a recurrent neural network that uses nucleosome sequence features representation for their classification. In particular, we implement an architecture which stacks convolutional and long short-term memory layers, with the main purpose to avoid t…
Retrieving infinite numbers of patterns in a spin-glass model of immune networks
2013
The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…
Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony
2016
In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relati…
Cellular Response to Spinal Cord Injury in Regenerative and Non-Regenerative Stages in Xenopus Laevis
2020
Abstract Background The efficient regenerative abilities at larvae stages followed by a non-regenerative response after metamorphosis in froglets makes Xenopus an ideal model organism to understand the cellular responses leading to spinal cord regeneration. Methods We compared the cellular response to spinal cord injury between the regenerative and non-regenerative stages of Xenopus laevis. For this analysis, we used electron microscopy, immunofluorescence and histological staining of the extracellular matrix. We generated two transgenic lines: i) the reporter line with the zebrafish GFAP regulatory regions driving the expression of EGFP, and ii) a cell specific inducible ablation line with…
Partitioned learning of deep Boltzmann machines for SNP data.
2016
Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…
Deep learning models for bacteria taxonomic classification of metagenomic data.
2018
Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…