28 research outputs found

    Modeling stochasticity and robustness in gene regulatory networks

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    Motivation: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. Results: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Availability: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/∌garg/genysis.html. Contact: [email protected]

    Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

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    An amendment to this paper has been published and can be accessed via the original article

    Patient and stakeholder engagement learnings: PREP-IT as a case study

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    Application of C-Terminal Clostridium Perfringens Enterotoxin in Treatment of Brain Metastasis from Breast Cancer

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    Claudin-4 is part of the Claudin family of transmembrane tight junction (TJ) proteins found in almost all tissues and, together with adherens junctions and desmosomes, forms epithelial and endothelial junctional complexes. Although the distribution of Claudin-4 occurs in many cell types, the level of expression is cell-specific. Claudin proteins regulate cell proliferation and differentiation by binding cell-signaling ligands, and its expression is upregulated in several cancers. As a result, alterations in Claudin expression patterns or distribution are vital in the pathology of cancer. Profiling the genetic expression of Claudin-4 showed that Claudin-4 is also a receptor for the clostridium perfringens enterotoxin (CPE) and that Claudin-4 has a high sequence similarity with CPE’s high-affinity receptor. CPE is cytolytic due to its ability to form pores in cellular membranes, and CPE treatment in breast cancer cells have shown promising results due to the high expression of Claudin-4. The C-terminal fragment of CPE (c-CPE) provides a less toxic alternative for drug delivery into breast cancer cells, particularly metastatic tumors in the brain, especially as Claudin-4 expression in the central nervous system (CNS) is low. Therefore, c-CPE provides a unique avenue for the treatment of breast–brain metastatic tumors

    Peripapillary sparing in <i>RDH12</i>-associated Leber congenital amaurosis

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    <p><i>Background</i>: Peripapillary sparing is a characteristic that is traditionally described as pathognomonic for Stargardt disease.</p> <p><i>Materials and methods</i>: We present a multimodal assessment of four Leber congenital amaurosis (LCA) cases with congenital macular atrophy and severely attenuated electroretinogram findings caused by bilallelic mutations in <i>RDH12</i>.</p> <p><i>Results</i>: Fundus autofluorescence imaging revealed a general loss of retinal pigment epithelium across the macula except for the peripapillary region in both eyes of all patients. Spectral domain-optical coherence tomography confirmed relative preservation in this area along with retinal thinning and excavation throughout the rest of the macula. LCA was diagnosed based on clinical exam and retinal imaging, and subsequently confirmed with genetic testing.</p> <p><i>Conclusions</i>: Peripapillary sparing is a novel phenotypic feature of <i>RDH12</i>-associated LCA.</p
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