Platform Embedded Security Technology Revealed

Computer scienc

Cooperation in health governance between China and Argentina in the context of COVID-19 from the perspective of multilevel governance

Este artículo tiene por objetivo analizar la cooperación en salud entre China y Argentina ante la crisis sanitaria de la COVID-19 desde la perspectiva de la gobernanza multinivel. Se ha demostrado que los actores estatales y subestatales desempeñaron un papel dominante en la primera etapa cooperativa, mientras que los actores no estatales empezaron a jugar un rol cada vez más activo y significativo en la segunda etapa. Mediante la cooperación sanitaria entre ambas naciones, Argentina ha logrado superar algunos desafíos traídos por la pandemia y ha mejorado la capacidad de gobernanza en salud frente al coronavirus. Para encarar la segunda ola de epidemia, existe la necesidad de profundizar la cooperación sanitaria entre los dos países a múltiples niveles.This article aims to analyze the China-Argentina health cooperation in the face of the COVID-19 health crisis from the perspective of multilevel governance. It has been shown that state and sub-state actors played a dominant role in the first cooperative stage, while non-state actors started to play an increasingly active and significant role in the second stage. Through health cooperation between the two nations, Argentina has managed to overcome some of the challenges posed by the pandemic and has improved its health governance capacity in facing the coronavirus. To cope with the second wave of the epidemic, these two countries’ health cooperation needs to be strengthened at multiple levels.Instituto de Relaciones Internacionale

Cooperación en la gobernanza sanitaria entre China y Argentina en el contexto de la COVID-19 desde la perspectiva de la gobernanza multinivel

This article aims to analyze the China-Argentina health cooperation in the face of the COVID-19 health crisis from the perspective of multilevel governance. It has been shown that state and sub-state actors played a dominant role in the first cooperative stage, while non-state actors started to play an increasingly active and significant role in the second stage. Through health cooperation between the two nations, Argentina has managed to overcome some of the challenges posed by the pandemic and has improved its health governance capacity in facing the coronavirus. To cope with the second wave of the epidemic, these two countries’ health cooperation needs to be strengthened at multiple levels.Este artículo tiene por objetivo analizar la cooperación en salud entre China y Argentina ante la crisis sanitaria de la COVID-19 desde la perspectiva de la gobernanza multinivel. Se ha demostrado que los actores estatales y subestatales desempeñaron un papel dominante en la primera etapa cooperativa, mientras que los actores no estatales empezaron a jugar un rol cada vez más activo y significativo en la segunda etapa. Mediante la cooperación sanitaria entre ambas naciones, Argentina ha logrado superar algunos desafíos traídos por la pandemia y ha mejorado la capacidad de gobernanza en salud frente al coronavirus. Para encarar la segunda ola de epidemia, existe la necesidad de profundizar la cooperación sanitaria entre los dos países a múltiples niveles

siRNA-mediated off-target gene silencing triggered by a 7 nt complementation

A growing body of evidence suggests that siRNA could generate off-target effects through different mechanisms. However, the full impact of off-target gene regulation on phenotypic induction and accordingly on data interpretation in the context of large-scale siRNA library screen has not been reported. Here we report on off-target gene silencing effects observed in a large-scale knockdown experiment designed to identify novel regulators of the HIF-1 pathway. All of the three ‘top hits’ from our screen have been demonstrated to result from off-target gene silencing. Two of the three ‘siRNA hits’ were found to directly trigger down-regulation of hif-1α mRNA through a 7 nt motif, AGGCAGT, that is present in both the hif-1α mRNA and the siRNAs. Further analysis revealed that the generation of off-target gene silencing via this 7 nt motif depends on the characteristics of the target mRNA, including the sequence context surrounding the complementary region, the position of the complementary region in the mRNA and the copy number of the complementary region. Interestingly, the off-target siRNA against hif-1α was also shown to trigger mRNA degradation with high probability of other genes that possess multiple copies of the AGGCAGT motif in the 3′-untranslated region. Lessons learned from this study will be a valuable asset to aid in designing siRNAs with more stringent target selectivity and improving ‘hits-follow-up’ strategies for future large-scale knockdown experiments

Optimizing Terminal Delivery of Perishable Products considering Customer Satisfaction

Freshness of products and timeliness of delivery are two critical factors which have impact on customer satisfaction in terminal delivery of perishable products. This paper investigates how to make a cost-saving vehicle scheduling for perishable products by maximizing customer satisfaction. Customer satisfaction is defined from the two aspects of freshness and time window. Then we develop a priority function based on customer satisfaction and use the hierarchical clustering method to identify customer service priority. Based on the priority, a multiobjective vehicle scheduling optimization model for perishable products is formulated to maximize customer satisfaction and minimize total delivery costs. To solve the proposed model, a priority-based genetic algorithm (PB-GA) is designed. Numerical experiments and sensitivity analysis are performed to show the validity and advantage of our approach. Results indicate that PB-GA can achieve better solutions than traditional genetic algorithm. The improvement of customer satisfaction is higher than the decrease rate of total costs within a certain shelf life range, which reveals that the proposed method is applicable to the terminal delivery of perishable products

Improved protein arrays for quantitative systems analysis of the dynamics of signaling pathway interactions

An improved version of quantitative protein array platform utilizing linear Quantum dot signaling for systematically measuring protein levels and phosphorylation states is presented. The signals are amplified linearly by a confocal laser Quantum dot scanner resulting in ~1000-fold more sensitivity than traditional Western blots, but are not linear by the enzyme-based amplification. Software is developed to facilitate the quantitative readouts of signaling network activities. Kinetics of EGFRvIII mutant signaling was analyzed to quantify cross-talks between EGFR and other signaling pathways

Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data.

Single-cell RNA-sequencing (scRNAseq) technologies are rapidly evolving. Although very informative, in standard scRNAseq experiments, the spatial organization of the cells in the tissue of origin is lost. Conversely, spatial RNA-seq technologies designed to maintain cell localization have limited throughput and gene coverage. Mapping scRNAseq to genes with spatial information increases coverage while providing spatial location. However, methods to perform such mapping have not yet been benchmarked. To fill this gap, we organized the DREAM Single-Cell Transcriptomics challenge focused on the spatial reconstruction of cells from the Drosophila embryo from scRNAseq data, leveraging as silver standard, genes with in situ hybridization data from the Berkeley Drosophila Transcription Network Project reference atlas. The 34 participating teams used diverse algorithms for gene selection and location prediction, while being able to correctly localize clusters of cells. Selection of predictor genes was essential for this task. Predictor genes showed a relatively high expression entropy, high spatial clustering and included prominent developmental genes such as gap and pair-rule genes and tissue markers. Application of the top 10 methods to a zebra fish embryo dataset yielded similar performance and statistical properties of the selected genes than in the Drosophila data. This suggests that methods developed in this challenge are able to extract generalizable properties of genes that are useful to accurately reconstruct the spatial arrangement of cells in tissues