References of "del Sol Mesa, Antonio 50001581"
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See detailModeling of Cellular Systems: Application in Stem Cell Research and Computational Disease Modeling
Ali, Muhammad UL; del Sol Mesa, Antonio UL

Book published by Springer International Publishing (2018)

The large-scale development of high-throughput sequencing technologies has allowed the generation of reliable omics data at different regulatory levels. Integrative computational models enable the ... [more ▼]

The large-scale development of high-throughput sequencing technologies has allowed the generation of reliable omics data at different regulatory levels. Integrative computational models enable the disentangling of a complex interplay between these interconnected levels of regulation by interpreting these large quantities of biomedical information in a systematic way. In the context of human diseases, network modeling of complex gene-gene interactions has been successfully used for understanding disease-related dysregulations and for predicting novel drug targets to revert the diseased phenotype. Furthermore, these computational network models have emerged as a promising tool to dissect the mechanisms of developmental processes such as cellular differentiation, transdifferentiation, and reprogramming. In this chapter, we provide an overview of recent advances in the field of computational modeling of cellular systems and known limitations. A particular attention is paid to highlight the impact of computational modeling on our understanding of stem cell biology and the complex multifactorial nature of human diseases and their treatment. [less ▲]

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See detailSignaling-Dependent Control of Apical Membrane Size and Self-Renewal in Rosette-Stage Human Neuroepithelial Stem Cells
Medelnik, Jan-Philip; Roensch, Kathleen; Okawa, Satoshi UL et al

in Stem Cell Reports (2018)

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See detailAbsence of regulator of G-protein signaling 4 does not protect against dopamine neuron dysfunction and injury in the mouse 6-hydroxydopamine lesion model of Parkinson's disease
Ashrafi, Amer UL; Garcia, Pierre UL; Kollmus, Heike et al

in Neurobiology of Aging (2017), 58

Regulator of G-Protein Signaling 4 (RGS4), a member of the RGS family of proteins that inactivate G-proteins, has gained interest as a potential drug target for neurological disorders, such as epilepsy ... [more ▼]

Regulator of G-Protein Signaling 4 (RGS4), a member of the RGS family of proteins that inactivate G-proteins, has gained interest as a potential drug target for neurological disorders, such as epilepsy and Parkinson’s disease (PD). In the case of PD, the main current option for alleviating motor symptoms are dopamine replacement therapies, which have limitations because of side effects, and reduced effectiveness over the long term. Research on new non-dopaminergic PD drug targets has indicated that inhibition of RGS4 could be an effective adjuvant treatment option. The effectiveness of RGS4 inhibition for an array of PD-linked functional and structural neuroprotection endpoints has not yet been demonstrated. Here, we use the 6-Hydroxydopamine (6-OHDA) lesioning model of the nigrostriatal pathway in mice to address this question. We observe, using a battery of behavioral and pathological measures, that mice deficient for RGS4 are not protected from 6-OHDA induced injury, and show enhanced susceptibility in some measures of motor function. Our results suggest that inhibition of RGS4 as a non-dopaminergic target for PD should be approached with caution. [less ▲]

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See detailBioinformatics Tools for Genome-Wide Epigenetic Research
del Sol Mesa, Antonio UL

in Neuroepigenomics in Aging and Disease (2017)

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See detailRegulation of Fn14 Receptor and NF-κB Underlies Inflammation in Meniere’s Disease
Frejo, Lidia; Requena, Teresa; Okawa, Satoshi UL et al

in Frontiers in Immunology (2017)

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See detailA systems biology approach to identify niche determinants of cellular phenotypes
Ravichandran, Srikanth UL; Okawa, Satoshi UL; Martinez Arbas, Susana UL et al

in Stem Cell Research (2016)

Recent reports indicate a dominant role for cellular microenvironment or niche for stably maintaining cellular phenotypic states. Identification of key niche mediated signaling that maintains stem cells ... [more ▼]

Recent reports indicate a dominant role for cellular microenvironment or niche for stably maintaining cellular phenotypic states. Identification of key niche mediated signaling that maintains stem cells in specific phenotypic states remains a challenge, mainly due to the complex and dynamic nature of stem cell-niche interactions. In order to overcome this, we consider that stem cells maintain their phenotypic state by experiencing a constant effect created by the niche by integrating its signals via signaling pathways. Such a constant niche effect should induce sustained activation/inhibition of specific stem cell signaling pathways that controls the gene regulatory program defining the cellular phenotypic state. Based on this view, we propose a computational approach to identify the most likely receptor mediated signaling responsible for transmitting niche signals to the transcriptional regulatory network that maintain cell-specific gene expression patterns, termed as niche determinants. We demonstrate the utility of our method in different stem cell systems by identifying several known and novel niche determinants. Given the key role of niche in several degenerative diseases, identification of niche determinants can aid in developing strategies for potential applications in regenerative medicine. [less ▲]

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See detailModeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation
Espinosa Angarica, Vladimir UL; del Sol Mesa, Antonio UL

in BioEssays (2016), 38(8),

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within ... [more ▼]

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self-renewal and differentiation. In particular, we suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation-specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine [less ▲]

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