186,347 research outputs found
Towards a liquid self: How time, geography, and life experiences reshape the biological identity
No full textThe conceptualization of immunological self is amongst the most important theories of modern biology, representing a sort of theoretical guideline for experimental immunologists, in order to understand how host constituents are ignored by the immune system (IS). A consistent advancement in this field has been represented by the danger/damage theory and its subsequent refinements, which at present represents the most comprehensive conceptualization of immunological self. Here, we present the new hypothesis of "liquid self," which integrates and extends the danger/damage theory. The main novelty of the liquid self hypothesis lies in the full integration of the immune response mechanisms into the host body's ecosystems, i.e., in adding the temporal, as well as the geographical/evolutionary and environmental, dimensions, which we suggested to call "immunological biography." Our hypothesis takes into account the important biological changes occurring with time (age) in the IS (including immunosenescence and inflammaging), as well as changes in the organismal context related to nutrition, lifestyle, and geography (populations). We argue that such temporal and geographical dimensions impinge upon, and continuously reshape, the antigenicity of physical entities (molecules, cells, bacteria, viruses), making them switching between "self" and "non-self" states in a dynamical, "liquid" fashion. Particular attention is devoted to oral tolerance and gut microbiota, as well as to a new potential source of unexpected self epitopes produced by proteasome splicing. Finally, our framework allows the set up of a variety of testable predictions, the most straightforward suggesting that the immune responses to defined molecules representing potentials antigens will be quantitatively and qualitatively quite different according to the immuno-biographical background of the host. © 2014 Grignolio, Mishto, Faria, Garagnani, Franceschi and Tieri
Linguaggio e contesto sociale: primi risultati di una ricerca condotta su un gruppo di studenti romani di scuola media
No full textEncoding the states of interacting proteins to facilitate biological pathways reconstruction
No full textAbstract Background In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruction of biological pathways. Results We propose a logical model of PPI that takes into account the "state" of proteins before and after the interaction. This information is necessary for proper reconstruction of the pathway. Conclusions The adoption of the proposed model, which can be easily integrated into existing machine-readable formats used to store the PPI data, would facilitate the automatic or semi-automated reconstruction of biological pathways. Reviewers This article was reviewed by Dr. Wen-Yu Chung (nominated by Kateryna Makova), Dr. Carl Herrmann (nominated by Dr. Purificación López-García) and Dr. Arcady Mushegian.</p
MIRROR: a miRNA regulation-level network-based algorithm to study sexual dimorphism in cancer
No full textOne of the open challenges in precision medicine, whose importance is growing every day, is sex-specific medicine: the study of how sex-based biological differences influence people’s health. These differences can be measured in terms of disease incidence, prevalence, mortality, and survival. Understanding the leading causes of these disparities is therefore of the utmost importance. With recent advancements in high-throughput technologies, large-scale molecular data are being generated for individual cancer patients; however, extracting meaningful insights from these complex datasets and translating them into clinical applications remains a challenge. Moreover, the functional interdependencies between the molecular components in a human cell often reflect the perturbations of a complex intracellular and intercellular network. Network-based approaches, being inherently holistic, can lead to a better understanding of the molecular mechanisms underlying a disease. For these reasons, this project focuses on the development of a network-based method to investigate sexual dimorphism in cancer using transcriptomic data. Many have already investigated transcriptomic data in this context, with particular interest in the role of miRNAs, showing the involvement of these regulatory elements in differentiating patients by sex in different types of cancer. However, these studies focus only on evaluating changes in the expression level, without conducting a more comprehensive analysis of miRNA expression and without investigating miRNAs’ targets. The aim of this project is therefore to carry out a multi- layer study involving both miRNAs and their target genes’ expression data. In particular, it focuses on the development of a novel and generalizable algorithm (MIRROR), which can be used on cancer patients to help identify key regulatory mechanisms and molecules that act as differentiators between males and females. Here we implemented and tested MIRROR on three different cancers (colon adenocarcinoma, hepatocellular carcinoma, and low-grade gliomas) and assessed its performance by comparing it to other state-of-the-art approaches. By doing so we proved MIRROR’s efficacy in identifying sex-specific key genes, presenting it as a viable alternative to the state-of-the-art methods which failed to capture these differences. Moreover, we also showed how the genes identified by MIRROR can be integrated with clinical features
Networks, Degeneracy and Bow ties: A Unifying Perspective of Immunological Paradigms and Architectures
No full textEnvisioning architectures, paradigms and principles is helpful and necessary to scientists to comprehend the complexity of biological systems. Network biology, for instance, is one of the most recent paradigms that have proven to be a successful approach to gain insights into the organization of biochemical networks and systems. We believe that a more integrated and unitary view of existing paradigms, principles, and concepts regarding biological systems will be even more helpful in understanding their complex organizational issues. In this view, we confront some of the most interesting ideas in systems biology such as those of network, degeneracy, and bow tie, and propose that the merging of such concepts into a more unitary view allows to re-interpret many biological phenomena in different and yet unexplored perspectives
Statistical ensemble of gene regulatory networks of macrophage differentiation
No full textBackground: Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions. Methods: Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory). Results: To test the model, we simulated a large number of such networks as in a statistical ensemble. In other words, to enable the inter-cellular crosstalk required to obtain an immune activation in which the macrophage plays its role, the simulated networks are not taken in isolation but combined with other cellular agents, thus setting up a discrete minimalistic model of the immune system at the microscopic/intracellular (i.e., genetic regulation) and mesoscopic/intercellular scale. Conclusions: We show that within the mesoscopic level description of cellular interaction and cooperation, the gene regulatory logic is coherent and contributes to the overall dynamics of the ensembles that shows, statistically, the expected behaviour
Exploring Drug Repurposing Success Stories Through a Network-based Approach: Insights from a Case Study
No full textDrug repositioning is a promising strategy to discover new therapeutic applications for existing drugs, significantly reducing the time and costs associated with traditional drug development. This study employs a network medicine approach to analyze successful cases of drug repositioning, focusing on the exploratory hypothesis that the efficacy of repositioning may be determined by functional similarity between between diseases for which the drug was originally designed and diseases for which the same drug is reused. Network medicine tools were employed to investigate the connections between disease-associated genes, proteins, and approved drugs. Biological networks, including protein-protein interactions and functional interactions networks, as well as gene- and drug-disease association data are analyzed to identify functional similarities and possible molecular connections between diseases and treatments. Using clustering techniques and topological analysis, the results reveal a suggestive overlap of involved genes and functional interactions, emphasizing the value of computational methods in accelerating drug repositioning efforts and improving understanding of drug repositioning dynamics for more efficient therapeutic interventions
Heterosexual, gay, and lesbian people’s reactivity to virtual caresses on their embodied avatars’ taboo zones
No full textEmbodying an artificial agent through immersive virtual reality (IVR) may lead to feeling vicariously somatosensory stimuli on one’s body which are in fact never delivered. To explore whether vicarious touch in IVR reflects the basic individual and social features of real-life interpersonal interactions we tested heterosexual men/women and gay men/lesbian women reacting subjectively and physiologically to the observation of a gender-matched virtual body being touched on intimate taboo zones (like genitalia) by male and female avatars. All participants rated as most erogenous caresses on their embodied avatar taboo zones. Crucially, heterosexual men/women and gay men/lesbian women rated as most erogenous taboo touches delivered by their opposite and same gender avatar, respectively. Skin conductance was maximal when taboo touches were delivered by female avatars. Our study shows that IVR may trigger realistic experiences and ultimately allow the direct exploration of sensitive societal and individual issues that can otherwise be explored only through imagination
Explainable Drug Repurposing Approach From Biased Random Walks
No full textDrug repurposing is a highly active research area, aiming at finding novel uses for drugs that have been previously developed for other therapeutic purposes. Despite the flourishing of methodologies, success is still partial, and different approaches offer, each, peculiar advantages. In this composite landscape, we present a novel methodology focusing on an efficient mathematical procedure based on gene similarity scores and biased random walks which rely on robust drug-gene-disease association data sets. The recommendation mechanism is further unveiled by means of the Markov chain underlying the random walk process, hence providing explainability about how findings are suggested. Performances evaluation and the analysis of a case study on rheumatoid arthritis show that our approach is accurate in providing useful recommendations and is computationally efficient, compared to the state of the art of drug repurposing approaches
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