1,721,011 research outputs found
The Epithelial-Mesenchymal Transition, as Hacked by a microRNA Combinatorial Code
Full text linkA new study coupling bioinformatic and experimental investigations highlights the importance of combinatorial microRNA targeting in human EMT, a phenotypic program underlying normal and pathological processes
Polygenic risk modeling of tumor stage and survival in bladder cancer
Full text linkINTRODUCTION: Bladder cancer assessment with non-invasive gene expression signatures facilitates the detection of patients at risk and surveillance of their status, bypassing the discomforts given by cystoscopy. To achieve accurate cancer estimation, analysis pipelines for gene expression data (GED) may integrate a sequence of several machine learning and bio-statistical techniques to model complex characteristics of pathological patterns. METHODS: Numerical experiments tested the combination of GED preprocessing by discretization with tree ensemble embeddings and nonlinear dimensionality reductions to categorize oncological patients comprehensively. Modeling aimed to identify tumor stage and distinguish survival outcomes in two situations: complete and partial data embedding. This latter experimental condition simulates the addition of new patients to an existing model for rapid monitoring of disease progression. Machine learning procedures were employed to identify the most relevant genes involved in patient prognosis and test the performance of preprocessed GED compared to untransformed data in predicting patient conditions. RESULTS: Data embedding paired with dimensionality reduction produced prognostic maps with well-defined clusters of patients, suitable for medical decision support. A second experiment simulated the addition of new patients to an existing model (partial data embedding): Uniform Manifold Approximation and Projection (UMAP) methodology with uniform data discretization led to better outcomes than other analyzed pipelines. Further exploration of parameter space for UMAP and t-distributed stochastic neighbor embedding (t-SNE) underlined the importance of tuning a higher number of parameters for UMAP rather than t-SNE. Moreover, two different machine learning experiments identified a group of genes valuable for partitioning patients (gene relevance analysis) and showed the higher precision obtained by preprocessed data in predicting tumor outcomes for cancer stage and survival rate (six classes prediction). CONCLUSIONS: The present investigation proposed new analysis pipelines for disease outcome modeling from bladder cancer-related biomarkers. Complete and partial data embedding experiments suggested that pipelines employing UMAP had a more accurate predictive ability, supporting the recent literature trends on this methodology. However, it was also found that several UMAP parameters influence experimental results, therefore deriving a recommendation for researchers to pay attention to this aspect of the UMAP technique. Machine learning procedures further demonstrated the effectiveness of the proposed preprocessing in predicting patients’ conditions and determined a sub-group of biomarkers significant for forecasting bladder cancer prognosis
MicroRNA-mediated regulatory circuits: outlook and perspectives
Full text linkMicroRNAs have been found to be necessary for regulating genes implicated in almost all signaling pathways, and consequently their dysfunction influences many diseases, including cancer. Understanding of the complexity of the microRNA-mediated regulatory network has grown in terms of size, connectivity and dynamics with the development of computational and, more recently, experimental high-throughput approaches for microRNA target identification. Newly developed studies on recurrent microRNA-mediated circuits in regulatory networks, also known as network motifs, have substantially contributed to addressing this complexity, and therefore to helping understand the ways by which microRNAs achieve their regulatory role. This review provides a summarizing view of the state-of-the-art, and perspectives of research efforts on microRNA-mediated regulatory motifs. In this review, we discuss the topological properties characterizing different types of circuits, and the regulatory features theoretically enabled by such properties, with a special emphasis on examples of circuits typifying their biological significance in experimentally validated contexts. Finally, we will consider possible future developments, in particular regarding microRNA-mediated circuits involving long non-coding RNAs and epigenetic regulators
Semaphorins in cardiovascular medicine.
Full text linkDuring organogenesis, patterning is primarily achieved by the combined actions of morphogens. Among these, semaphorins represent a general system for establishing the appropriate wiring architecture of biological nets. Originally discovered as evolutionarily conserved steering molecules for developing axons, subsequent studies on semaphorins expanded their functions to the cardiovascular and immune systems. Semaphorins participate in cardiac organogenesis and control physiological vasculogenesis and angiogenesis, which result from a balance between pro- and anti-angiogenic signals. These signals are altered in several diseases. In this review, we discuss the role of semaphorins in vascular biology, emphasizing the mechanisms by which these molecules control vascular patterning and lymphangiogenesis, as well as in genetically inherited and degenerative vascular disease
VRG: A database of vascular dysfunctions related genes
Full text linkAbstractHeart and vascular defects occur in a large number of hereditary and sporadic human diseases as a result of a complex interplay of genetic factors. Since genome sequencing of many organisms disclosed similarities among genomes, animal models are crucial for the discovery of genes involved in those pathological processes. Therefore we propose a VRG database, in which human data have been manually managed and integrated with mouse information in order to create a catalogue of genes involved in vascular diseases
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
IRF-1 expression is induced by cisplatin in ovarian cancer cells and limits drug effectiveness.
No full textBACKGROUND:
The Interferon Regulatory Factors (IRFs) are transcription factors involved in immune responses and oncogenesis and most of them are classified as tumour suppressors. The expression and activation of IRF(s) are stimulated by several cytokines and by DNA damage. Here we examine the role of the IRF-1 in the response of ovarian cancer cells to the front-line chemotherapeutic drug cisplatin (CDDP).
METHODS:
We evaluated the transcriptional response of three ovarian cancer cell lines to CDDP both under control conditions and after IRF-1 silencing using expression microarrays. The role played by IRF-1 in the response of these cells to CDDP was evaluated after silencing and overexpressing IRF-1. We studied cell cycle progression, colony forming ability in monolayer culture and semisolid medium, and apoptosis in the response to the drug.
RESULTS:
The treatment of ovarian cancer cells with CDDP boosted the expression and the nuclear translocation of IRF-1, which in turn modulated the expression of putative IRF-1 target genes. Accordingly, IRF-1 silencing re-orchestrated the expression profiles of CDDP-treated cells. In agreement with its role as a tumour suppressor, overexpressing IRF-1 suppressed the transformed phenotype of ovarian cancer cells. Nevertheless, IRF-1 silencing sensitized cells to the apoptotic death induced by CDDP. Over-expression was associated with cell G1 arrest and p21 induction irrespective of p53 proficiency, while IRF-1 silencing reduced the induction of p21 by CDDP.
CONCLUSIONS:
These data demonstrate that IRF-1 is up-regulated by CDDP in ovarian cancer cells and might limit the cell response to CDDP, likely by inhibiting cell proliferation. Data suggest that IRF-1 induction might interfere with the effectiveness of combination therapy with platinum drugs and cytokines
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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