Estrategia de comunicación política para capitalizar políticamente las decisiones del Gobierno Nacional. Caso de estudio: el uso de Twitter de Carlos Rabascall en las coyunturas políticas que marcaron el gobierno del presidente Guillermo Lasso en su primer año de gestión (2021-2022)

Esta investigación se enfoca en el análisis del uso de la red social Twitter por parte de Carlos Rabascall, un político y comunicador social ecuatoriano, durante el primer año de gestión del presidente Guillermo Lasso en Ecuador (2021-2022). El objetivo principal del estudio es analizar el uso de Twitter por parte de Rabascall en las coyunturas políticas que marcaron el gobierno de Lasso durante ese período. La metodología empleada consistió en la realización de un análisis cuantitativo y cualitativo de la cuenta de Twitter de Rabascall, centrado en el contenido de sus tweets y su relación con las coyunturas políticas del gobierno de Lasso. El análisis cuantitativo se centró en la frecuencia y distribución de los tweets en relación con las coyunturas políticas, mientras que el análisis cualitativo se centró en el contenido y el contexto de los tweets. En cuanto al análisis se recopilaron un total de 30 tweets relacionados a las coyunturas políticas del gobierno de Lasso en el periodo de análisis, temas como la salud, economía, política exterior y lucha contra la corrupción fueron los escogidos. En cuanto al uso de Twitter por parte de Rabascall en las coyunturas políticas del gobierno de Lasso, se observa en sus tweets que parece tener una actitud crítica y cuestionadora hacia ciertos temas, utiliza un lenguaje fuerte y enérgico para expresar sus puntos de vista, lo que sugiere una actitud apasionada y posiblemente indignada hacia los temas que aborda, Rabascall menciona la importancia de la transparencia y la lucha contra la corrupción, lo cual podría ser interpretado como una crítica al gobierno y su compromiso en estas áreas

Integrative System Biology Analysis of Transcriptomic Responses to Drought Stress in Soybean (Glycine max L.)

Drought is a major abiotic stressor that causes yield losses and limits the growing area for most crops. Soybeans are an important legume crop that is sensitive to water-deficit conditions and suffers heavy yield losses from drought stress. To improve drought-tolerant soybean cultivars through breeding, it is necessary to understand the mechanisms of drought tolerance in soybeans. In this study, we applied several transcriptome datasets obtained from soybean plants under drought stress in comparison to those grown under normal conditions to identify novel drought-responsive genes and their underlying molecular mechanisms. We found 2168 significant up/downregulated differentially expressed genes (DEGs) and 8 core modules using gene co-expression analysis to predict their biological roles in drought tolerance. Gene Ontology and KEGG analyses revealed key biological processes and metabolic pathways involved in drought tolerance, such as photosynthesis, glyceraldehyde-3-phosphate dehydrogenase and cytokinin dehydrogenase activity, and regulation of systemic acquired resistance. Genome-wide analysis of plants’ cis-acting regulatory elements (CREs) and transcription factors (TFs) was performed for all of the identified DEG promoters in soybeans. Furthermore, the PPI network analysis revealed significant hub genes and the main transcription factors regulating the expression of drought-responsive genes in each module. Among the four modules associated with responses to drought stress, the results indicated that GLYMA_04G209700, GLYMA_02G204700, GLYMA_06G030500, GLYMA_01G215400, and GLYMA_09G225400 have high degrees of interconnection and, thus, could be considered as potential candidates for improving drought tolerance in soybeans. Taken together, these findings could lead to a better understanding of the mechanisms underlying drought responses in soybeans, which may useful for engineering drought tolerance in plants

Integrative System Biology Analysis of Transcriptomic Responses to Drought Stress in Soybean (Glycine max L.)

Drought is a major abiotic stressor that causes yield losses and limits the growing area for most crops. Soybeans are an important legume crop that is sensitive to water-deficit conditions and suffers heavy yield losses from drought stress. To improve drought-tolerant soybean cultivars through breeding, it is necessary to understand the mechanisms of drought tolerance in soybeans. In this study, we applied several transcriptome datasets obtained from soybean plants under drought stress in comparison to those grown under normal conditions to identify novel drought-responsive genes and their underlying molecular mechanisms. We found 2168 significant up/downregulated differentially expressed genes (DEGs) and 8 core modules using gene co-expression analysis to predict their biological roles in drought tolerance. Gene Ontology and KEGG analyses revealed key biological processes and metabolic pathways involved in drought tolerance, such as photosynthesis, glyceraldehyde-3-phosphate dehydrogenase and cytokinin dehydrogenase activity, and regulation of systemic acquired resistance. Genome-wide analysis of plants’ cis-acting regulatory elements (CREs) and transcription factors (TFs) was performed for all of the identified DEG promoters in soybeans. Furthermore, the PPI network analysis revealed significant hub genes and the main transcription factors regulating the expression of drought-responsive genes in each module. Among the four modules associated with responses to drought stress, the results indicated that GLYMA_04G209700, GLYMA_02G204700, GLYMA_06G030500, GLYMA_01G215400, and GLYMA_09G225400 have high degrees of interconnection and, thus, could be considered as potential candidates for improving drought tolerance in soybeans. Taken together, these findings could lead to a better understanding of the mechanisms underlying drought responses in soybeans, which may useful for engineering drought tolerance in plants

Potential role of the regulatory miR1119-MYC2 module in wheat (Triticum aestivum L.) drought tolerance

MicroRNA (miRNA)-target gene modules are essential components of plants' abiotic stress signalling pathways Little is known about the drought-responsive miRNA-target modules in wheat, but systems biology approaches have enabled the prediction of these regulatory modules and systematic study of their roles in responses to abiotic stresses. Using such an approach, we sought miRNA-target module(s) that may be differentially expressed under drought and non-stressed conditions by mining Expressed Sequence Tag (EST) libraries of wheat roots and identified a strong candidate (miR1119-MYC2). We then assessed molecular and physiochemical differences between two wheat genotypes with contrasting drought tolerance in a controlled drought experiment and assessed possible relationships between their tolerance and evaluated traits. We found that the miR1119-MYC2 module significantly responds to drought stress in wheat roots. It is differentially expressed between the contrasting wheat genotypes and under drought versus non-stressed conditions. We also found significant associations between the module's expression profiles and ABA hormone content, water relations, photosynthetic activities, H2O2 levels, plasma membrane damage, and antioxidant enzyme activities in wheat. Collectively, our results suggest that a regulatory module consisting of miR1119 and MYC2 may play an important role in wheat's drought tolerance

Evaluation of Different RNA Extraction Methods from Agropatch Suppressor Assay for Small Quantities of Plant Tissue and Their Application for Analysis of Gene Expression

The agroinfiltration assay provides fast and efficient way to transiently express genes into plant cells by Agrobacterium tumefaciens. Extraction of RNA of high quality and sufficient amounts is prerequisite for gene expression studies such as quantitative Real Time PCR (q-PCR) from infiltrated areas in agropatch suppressor assay with small quantities of plant tissue. To attain prime RNA extraction from small tissues of infiltrated N. benthamiana plants with Potato virus A helper component proteinase viral suppressor protein, the efficiency of three RNA extraction methods (LiCl, TRIzol reagent and commercial kit) was evaluated. The total RNA yield with LiCl method was 2.83 and 33.2-fold greater than that of TRIzol reagent and commercial kit, respectively. Also, total RNA yield using TRIzol reagent was 11.7-fold higher than that with commercial kit. The A260/A280 ratio mean for TRI reagent (1.95) and kit (1.9) extractions were within the optimum range.q-PCR revealed that the cycle threshold values of housekeeping gene, EIF-1α and target genes AGO1 and ATG6 for RNA extracted using LiCl and kit were 1.07 to 1.3 and 1.02 to 1.12 times higher than those evaluated with the TRIzol method. Overall, TRIzol method showed the most effective approach for obtaining RNA from N. benthamiana patches in gene expression studies

TranSQL: A Transformer-based Model for Classifying SQL Queries

Domain-Specific Languages (DSL) are becoming popular in various fields as they enable domain experts to focus on domain-specific concepts rather than software-specific ones. Many domain experts usually reuse their previously-written scripts for writing new ones; however, to make this process straightforward, there is a need for techniques that can enable domain experts to find existing relevant scripts easily. One fundamental component of such a technique is a model for identifying similar DSL scripts. Nevertheless, the inherent nature of DSLs and lack of data makes building such a model challenging. Hence, in this work, we propose TRANSQL, a transformer-based model for classifying DSL scripts based on their similarities, considering their few-shot context. We build TRANSQL using BERT and GPT-3, two performant language models. Our experiments focus on SQL as one of the most commonly-used DSLs. The experiment results reveal that the BERT-based TRANSQL cannot perform well for DSLs since they need extensive data for the fine-tuning phase. However, the GPT-based TRANSQL gives markedly better and more promising results.acceptedVersio

Regulatory Network Identification, Promoter and Expression Analysis of Arabidopsis thaliana NPR1 in Defense Responses against Stresses

Salicylic acid (SA) and jasmonic acid (JA) phytohormones have been known for their roles in plant defense behaviour against biotic and abiotic stresses. They regulate defense pathways by antagonistic interaction. NPR1 as a key regulatory factor in the cross-talk between SA and JA, signaling is essential for the inhibition of JA-responsive gene expression by SA. In silico promoter analysis of 1.5 kb promoter regions of NPR1 gene revealed that NPR1 contains 23 MYB and 20 WRKY transcription factor binding sites. Different cis-elements associated with various stress responses were identified in Arabidopsis thaliana NPR1. The most common element was allocated to the defense responses against biotic stresses. Based on gene network analysis, NPR1, TGA2 and TGA3 were predicted to have functional cooperation with each other. Affymetrix microarray data analysis of A. thaliana under SA treatment demonstrated that most genes involved in NPR1 network are up-regulated under SA treatment. Therefore, interaction and cooperation between these factors might serve to fine-tune regulation of defense and immune responses against biotic and abiotic stresses