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Comunicación ciudadana en la campaña presidencial del 2022 en Costa Rica: el caso de los grupos de WhatsApp
(2024) Carazo Barrantes, Carolina; Granados Sánchez, Kevin; Mesén Vargas, Pablo; Zúñiga Picado, Camila
Capítulo del libro “Del like al voto”, el cual arroja luz sobre las complejas dinámicas de comunicación que moldearon las elecciones presidenciales de 2022 en Costa Rica en un contexto marcado por el uso creciente de plataformas digitales de comunicación. Mediante enfoques interdisciplinarios y metodologías diversas, los capítulos que integran este libro ofrecen perspectivas analíticas indispensables y contribuciones esenciales para comprender la intersección entre la política y la comunicación en la era de las redes sociales y las aplicaciones móviles.
A transcriptional regulatory network model reveals miR-34a as a potential regulator of proliferation in cancer cell lines
(2018-09-13) Vargas Mora, Cristian; Acón Chan, Man Sai; Mora Rodríguez, Rodrigo Antonio; Quirós Barrantes, Steve
The genetic instability caused by the disruption of the mechanism of the DNA-damage response (DDR) has been linked to cancer development. One of the most important and studied mechanism of the DDR is the p53 pathway. This protein acts as a tumor suppressor. MDM2, MDM4 and PLK1 inhibit its proapoptotic activity by binding to its sequence-specific DNA-binding site. To model the interactions between the species with the purpose of finding key points in the regulation of proliferation in cancer cell lines, we propose a transcriptional regulatory network conformed by miRNAs, mARNs and transcription factors involved in the modulation of p53 tumor suppressor protein using Ordinary Differential Equations. Our results suggest miR-34a has a strong control in the regulation of MDM4 and its overexpression results in the decrease of the expression of this protein without significantly affecting the expression of p53. We propose that the combination of miR-34a and small molecule inhibitors of MDM2 may be a therapeutic alternative for treating cancer progression and relapse prevention.
A systems biology approach to identify candidate targets to downregulate angiogenic gene expression in Cancer
(2018-09-13) Calderón Gómez, Paola; Acón Chan, Man Sai; Mora Rodríguez, Rodrigo Antonio
The control of angiogenesis in cancer has been recognized as a promising therapeutic target for many diseases like cancer. Specifically, the Angiopoietin-2 - Vascular Endothelial Growth Factor system has demonstrated special relevance in the regulation of angiogenesis, highlighting the importance of the complex coordination among vascular signaling molecules [3] for the identification of targets for future anti-angiogenic therapy. Current approaches to regulate the angiogenesis process focus their efforts only on VEGF regulation but this has proven ineffective in many kinds of cancer, prompting the need for further understanding of how the vasculature can be effectively targeted in tumors [9]. Given the complex properties of gene expression in this process, a Systems Biology approach is required to identify putative candidates to robustly regulate genes involved in angiogenesis. We propose a model with candidate targets to downregulate the angiogenic genes expression. We identified a strong regulation of the AKT1-ANGPT2-KDR axis by miR200B and miR200C. Also, we identified a strong regulation of SRC by miR34a. These candidate miRNAs could therefore have a potential for the development of novel therapeutic strategies against angiogenesis in cancer.
A biocomputational application for the automated construction of large-scale metabolic models from transcriptomic data
(2017-05-08) Báez Villalobos, Edwin; de Paula Siles Canales, Francisco; Mora Rodríguez, Rodrigo Antonio
Cancer is a very complex disease with particular metabolic features that turn it into a very difficult system to approach from the solely experimental research. Therefore a systems biology approach is absolutely required to shed light on the subjacent mechanisms in order to derive reliable predictions about cancer evolution or behavior. In the present work, we developed a computational application that implements existing methods using a general metabolic model and gene expression data to generate cancer-specific models. As a working example, we used expression data of breast cancer cell lines to generate 3 models where we could consistently observe cancer-specific alterations at aldehyde dehydrogenase in the glycolysis, which is related to breast cancer stem cells and also in a reaction of glutathione peroxidase related to cancer chemoresistance. This computational application of metabolic modeling can be extended easily to add more methods of model generation and can be adapted to automatically construct personalized metabolic models that could be helpful in the prediction of chemotherapy response and find personalized cancer targets to optimize cell death and overcome therapy resistance.
A systems biology approach to investigate control targets of intracellular calcium transients induced by Clostridium perfringens Phospholipase C
(2018-09-13) Brenes Guillén, Laura; Acón Chan, Man Sai; Mora Rodríguez, Rodrigo Antonio; Monturiol Gross, Laura
Clostridium perfringens phospholipase C (CpPLC) plays a key role in the pathogenesis of gas gangrene, an acute and life-threatening infection in humans. CpPLC leads to the unregulated production of second messengers, such as calcium, and activates important signaling pathways like PKC, MEK, and NFkB, inducing ROS production, that leads towards cellular damage. We propose a systems biology approach to identify potential microRNAs which could be used as tools to explore the role of calcium channels in the mechanism of action of CpPLC, and eventually as therapeutic agents that render cells less sensitive to this toxin. Results show that miR19B1 and miR449B are interesting candidate targets which perturbations may affect the expression of genes involved in calcium transport. This approach may be useful to elucidate calcium molecular interactions involved in the CpPLC mechanism of action.