1,721,102 research outputs found
Sperm activation and sperm-egg interaction
No full textDifferent steps of sperm activation such as acrosomal reaction and capacitation are described in details. The molecules involved in sperm-egg interaction are also reported
EZcount: An all-in-one software for microRNA expression quantification from NGS sequencing data
No full textMicroRNAs (miRNAs) are short endogenous molecules of RNA that influence cell regulation by suppressing genes. Their ubiquity throughout all branches of the tree of life has suggested their central role in many cellular functions. Nowadays, several personalized medicine applications rely on miRNAs as biomarkers for diagnoses, prognoses, and prediction of drug response. The increasing ease of sequencing miRNAs contrasts with the difficulty of accurately quantifying their concentration. The use of general purpose aligners is only a partial solution as they have limited possibilities to accurately solve ambiguous mapping due to the short length of these sequences. We developed EZcount, an all-in-one software that, with a single command, performs the entire quantification process: from raw fastq files to read counts. Experiments show that EZcount is more sensitive and accurate than methods based on sequence alignment, independently of the library preparation protocol and sequencing machine. The parallel architecture of EZcount makes it fast enough to process a sample in minutes using a standard workstation. EZcount runs on all of the most common operating systems (Linux, Windows and MacOS) and is freely available for download at https://gitlab.com/BioAlgo/miR-pipe. A detailed description of the datasets, the raw experimental results, and all the scripts used for testing are available as supplementary material
Oxidative stress induces necropolis in mouse mesoangioblast stem cells
No full textNowadays stem cells are extensively used in regenerative medicine, as they show a great potential in restoration of several pathologies such as ischaemic heart disease, stroke, degenerative disorders and so on. However, it is well known that their therapeutic efficacy is compromised not only due to a reduced homing towards the target site, but also for their massive death during the first several days post-transplantation caused by the cytotoxic environment. In fact, the microenvironment within damaged tissues is unfavourable for stem cell survival due to hypoxia, inflammatory mediators and above all oxidative stress, which is particularly detrimental. H2O2 that diffuses freely into and out of cells may play a significant role in inducing death of injected stem cells. The most common types of cell death are represented by apoptosis, autophagy and necrosis. Apoptosis is a process of programmed cell death that occurs in multicellular organisms generally by activating caspases, or enzymes that degrade proteins. Autophagy is an important mechanism of cell self-protection, which helps cells maintain the synthesis and degradation cycles and promotes cell survival through the lysosomal degradation mechanism. Finally, necrosis is known as a fortuitous and regulated means of cell death that is induced by non specific and non physiological stress. The aim of our study was to determine the mechanism of mesoangioblast cell death after an in vitro H2O2 treatment, focusing whether apoptosis, autophagy or necrosis were implied. Mouse mesoangioblasts are vessel associated progenitor stem cells, which are able to differentiate in almost all mesodermal tissues.
FACS analysis with annexinV/sytox green demonstrated that H2O2 induced a dose- and time-dependent decrement in mesoangioblast viability. We have also found an increase in caspases 8, 9 and 3 activity after hydrogen peroxide treatment. To assess whether they were involved in causing cell death, the pan caspase inhibitor Z-VAD-fmk was used to inhibit caspase activity. Neither early apoptosis, nor late apoptosis/necrosis, nor necrosis were reduced, suggesting that the cell death induced by hydrogen peroxide was caspase-independent.
For this reason we tested whether H2O2 is responsible for the autophagic pathway activation. To study autophagy we evaluated the expression of specific markers (e.g., LC3II, beclin1, p62, Atg7, Atg5). H2O2 decreased beclin1, Atg5, Atg7 levels and the ratio LC3II/I, in a dose dependent way. At the same time H2O2 increased p62 protein expression indicating an impaired autophagic flux, also confirmed by the increase of phospho AKT, responsible for the activation of mTOR, a negative regulator of autophagy. According to these data mesoangioblast treatment with hydrogen peroxide seems to not induce nor apoptosis or autophagy. For this reason we hypothesized the activation of necroptosis, which is a specific form of caspase-independent, non-apoptotic or necrotic cell death that is triggered by cell death ligands via a unique downstream signaling pathway. To confirm whether the observed cell death was due to enhanced necroptosis, the proportion of necrotic cells was determined by annexin V/sytox green staining. FACS analysis showed an increase in percentage of both late apoptotic/necrotic and necrotic cells, which were further increased by pretreatment with Z-VAD-fmk.
To investigate the relationship between physiological autophagy and necroptosis cells were treated with H2O2 in the presence of the autophagic inhibitor 3-MA. Annexin V/sytox green staining showed that the inhibition of autophagy by 3-MA significantly enhanced necroptosis in mesoangioblast treated cells. On the contrary, 3-MA had no effect on apoptosis.
In conclusion, our in vitro data indicate that the cytotoxicity of H2O2 in mesoangioblast mainly occurred via the induction of necroptosis, enhanced by both apoptosis and autophagy inhibition
A Multi-sequence Alignment Algorithm for Web Template Detection
No full textNowadays most of Web pages are automatically assembled by content management systems or editing tools that apply a fixed template to give a uniform structure to all the documents beloging to the same site. The tem- plate usually contains side information that provides better graphics, navigation bars and menus, banners and advertisements that are aimed to improve the users’ browsing experience but may hinder tools for automatic processing of Web documents. In this paper, we present a novel template removing technique that exploits a sequence alignment algorithm from bioinformatics that is able to automatically extract the template from a quite small sample of pages from the same site. The algorithm detects the common structure of HTML tags among pairs of pages and merges the partial hypotheses using a binary tree consensus schema. The experi- mental results show that the algorithm is able to attain a good precision and recall in the retrieval of the real template structure exploiting just 16 sample pages from the site. Moreover, the positive impact of the template removing technique is shown on a Web page clustering task
Weighted simplicial complexes and their representation power of higher-order network data and topology
Full text linkHypergraphs and simplical complexes both capture the higher-order interactions of complex systems, ranging from higher-order collaboration networks to brain networks. One open problem in the field is what should drive the choice of the adopted mathematical framework to describe higher-order networks starting from data of higher-order interactions. Unweighted simplicial complexes typically involve a loss of information of the data, though having the benefit to capture the higher-order topology of the data. In this work we show that weighted simplicial complexes allow one to circumvent all the limitations of unweighted simplicial complexes to represent higher-order interactions. In particular, weighted simplicial complexes can represent higher-order networks without loss of information, allowing one at the same time to capture the weighted topology of the data. The higher-order topology is probed by studying the spectral properties of suitably defined weighted Hodge Laplacians displaying a normalized spectrum. The higher-order spectrum of (weighted) normalized Hodge Laplacians is studied combining cohomology theory with information theory. In the proposed framework we quantify and compare the information content of higher-order spectra of different dimension using higher-order spectral entropies and spectral relative entropies. The proposed methodology is tested on real higher-order collaboration networks and on the weighted version of the simplicial complex model "Network Geometry with Flavor.
Mesenchymal and Induced Pluripotent Stem Cells-Derived Extracellular Vesicles: The New Frontier for Regenerative Medicine?
Full text linkRegenerative medicine aims to repair damaged, tissues or organs for the treatment of various diseases, which have been poorly managed with conventional drugs and medical procedures. To date, multimodal regenerative methods include transplant of healthy organs, tissues, or cells, body stimulation to activate a self-healing response in damaged tissues, as well as the combined use of cells and bio-degradable scaffold to obtain functional tissues. Certainly, stem cells are promising tools in regenerative medicine due to their ability to induce de novo tissue formation and/or promote organ repair and regeneration. Currently, several studies have shown that the beneficial stem cell effects, especially for mesenchymal stem cells (MSCs) and induced pluripotent stem cells (iPSCs) in damaged tissue restore are not dependent on their engraftment and differentiation on the injury site, but rather to their paracrine activity. It is now well known that paracrine action of stem cells is due to their ability to release extracellular vesicles (EVs). EVs play a fundamental role in cell-to-cell communication and are directly involved in tissue regeneration. In the present review, we tried to summarize the molecular mechanisms through which MSCs and iPSCs-derived EVs carry out their therapeutic action and their possible application for the treatment of several diseases
Graph-Based Integration of Histone Modification Profiles
Full text linkIn this work, we introduce a similarity-network-based approach to explore the role of interacting single-cell histone modification signals in haematopoiesis—the process of differentiation of blood cells. Histones are proteins that provide structural support to chromosomes. They are subject to chemical modifications—acetylation or methylation—that affect the degree of accessibility of genes and, in turn, the formation of different phenotypes. The concentration of histone modifications can be modelled as a continuous signal, which can be used to build single-cell profiles. In the present work, the profiles of cell types involved in haematopoiesis are built based on all the major histone modifications (i.e., H3K27ac, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3) by counting the number of peaks in the modification signals; then, the profiles are used to compute modification-specific similarity networks among the considered phenotypes. As histone modifications come as interacting signals, we applied a similarity network fusion technique to integrate these networks in a unique graph, with the aim of studying the simultaneous effect of all the modifications for the determination of different phenotypes. The networks permit defining of a graph-cut-based separation score for evaluating the homogeneity of subgroups of cell types corresponding to the myeloid and lymphoid phenotypes in the classical representation of the haematopoietic tree. Resulting scores show that separation into myeloid and lymphoid phenotypes reflects the actual process of haematopoiesis
Packet classification via improved space decomposition techniques
No full textPacket classification is a common task in modern Internet routers. The goal is to classify packets into "classes" or "flows" according to some ruleset that looks at multiple fields of each packet. Differentiated actions can then be applied to the traffic depending on the result of the classification. Even though rulesets can be expressed in a relatively compact way by using high level languages, the resulting decision trees can partition the search space (the set of possible attribute values) in a potentially very large (106 and more) number of regions. This calls for methods that scale to such large problem sizes, though the only scalable proposal in the literature so far is the one based on a fat inverted segment tree (A. Feldmann and S. Muthukrishnan). In this paper we propose a new geometric technique called G-filter for packet classification on d dimensions. G-filter is based on an improved space decomposition technique. In addition to a theoretical analysis showing that classification in G-filter has O(1) time complexity and slightly super-linear space in the number of rules, we provide thorough experiments showing that the constants involved are extremely small on a wide range of problem sizes, and that G-filter improve the best results in the literature for large problem sizes, and is competitive for small sizes as well
A Fast Method for Web Template Extraction via a Multi-sequence Alignment Approach
No full textThe increased richness of the page contents and the diffusion of content management systems are responsible for the impressive changes happened in the last decade in a typical Web site layout. In fact, most of the Web sites are endowed with a template which gives them a uniform graphical and functional structure. Templates, by themselves, do not change the informative content of the pages, but they are typically designed to enhance the usability by uniformly organizing the contents following a standardized arrangement of functional blocks and by providing navigation tools, like menus or banners. However, the additional information provided by the template can worsen the performances of many algorithms for automatic Web processing. In fact, templates are designed for human users and provide redundant information that is marginally correlated with the main contents of a given page. These additional parts act as a noise source for many automated tasks such as web crawling, indexing, page classification and clustering. Hence, a preprocessing step to detect and strip the parts related to the template is needed to extract only the specific contents of each page. The critical part for the automation of this process is the accurate detection of the template, given a minimal set of pages from a given site.
The template consists in parts of the HTML tag structure that are shared by all the pages from the site, and its detection is made difficult by the variable parts intermixed with them. We propose an algorithm for template extraction that is based on the alignment of the HTML sequences of a set of pages. This approach is quite fast since it exploits efficient alignment algorithms proposed in bioinformatics and does not require complex tree matching or visual layout analysis. The algorithm aligns the HTML tag streams from pairs of pages and extracts a set of candidate templates that are merged following a binary tree consensus schema to increase the algorithm precision. The experimental evaluation shows that 16 sample pages are enough to extract the site template with good accuracy. The effects of the template stripping on a clustering task are also investigated, showing that the clustering quality can be effectively improved
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