Constituent aspects of riverside isomorphic governance on the Ilha do Careiro (Amazonas, Brazil)

Understanding governance in rural communities in the state of Amazonas requires interdisciplinary knowledge, as understanding the network of political articulation involves a collection of knowledge. Despite the existence of numerous works related to this subject, an a prior state is presumed in the representation of the network of political articulation, which leads to an exacerbated role of the State, in the face of other forms of social organization. Hence, the objective of the article was to analyze the environmental governance in the São Francisco community, located on the Ilha do Careiro da Várzea, in the state of Amazonas. We built Venn diagrams of agriculture, fishing, and plant extractivism to achieve this. The evidence provided indicates that the existing governance in the studied community is an isomorphic governance, which is the materialization of organized molecular power, originating from the triumvirate correspondence between the activities developed on lands, in forests, and on waters.

DEVELOPMENT OF LEARNING TRAJECTORY ON THE SET TOPIC FOR 7TH GRADE IN THE CONTEXT OF SEDEKAH LAUT TRADITION

Set is an important topic to be mastered by students because it influences the development of mathematics in daily life. However, many students still have difficulty learning the topic. Therefore, it is necessary to design a learning trajectory using the appropriate approach, context, and media. This research resulted in the learning development using Sedekah Laut context to create meaningful learning and increase students' understanding of sets. The method used in this study was design research proposed by Gravemeijer & Cobb with three stages: preliminary design, experimental design (pilot experiments and teaching experiments), and retrospective analysis. However, this article only presented the results from the Preliminary design stage. The participants involved in this study were 7th-grade students of SMP Negeri 6 Semarang. The resulting hypothetical learning trajectory consists of a series of learning processes: observing context videos to find the concepts of sets, non-sets, empty sets, universal sets, and Venn diagrams; explaining the properties of the set; defining set operations; and solving problems related to sets.

ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the advantages of existing packages, such as venn, RVenn, VennDiagram, and sf. Satisfactory results can be obtained with minimal configurations. Furthermore, we designed comprehensive objects to store the entire data of the Venn diagram, which allowed free access to both intersection values and Venn plot sub-elements, such as set label/edge and region label/filling. Therefore, high customization of every Venn plot sub-element can be fulfilled without increasing the cost of learning when the user is familiar with ggplot2 methods. To date, ggVennDiagram has been cited in more than 10 publications, and its source code repository has been starred by more than 140 GitHub users, suggesting a great potential in applications. The package is an open-source software released under the GPL-3 license, and it is freely available through CRAN (https://cran.r-project.org/package=ggVennDiagram).

Plasma checkpoint protein 1 (Chk1) as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma

BACKGROUND: Patients infected with a parasite often develop opisthorchiasis viverrini, which often progresses into cholangiocarcinoma (CCA) due to the asymptomatic nature of the infection. Currently, there are no effective diagnostic methods for opisthorchiasis or cholangiocarcinoma. OBJECTIVE: The aim of this study was to identify the host-responsive protein that can be developed as a diagnostic biomarker of opisthorchiasis and cholangiocarcinoma. METHODS: Plasma samples were collected from non-OVCCA, OV, and CCA subjects, and the proteomes were investigated by LC-MS/MS. Venn diagrams and protein network prediction by STITCH were used to identify the potential biomarkers. The level of candidate protein, the plasma checkpoint protein 1 (Chk1), was measured by indirect enzyme-linked immunosorbent assay (ELISA). RESULTS: Chk1 was present in the center of the protein network analysis in both the OV and CCA groups. In addition, the plasma Chk1 levels were significantly increased in both groups (P< 0.05). The sensitivity of the opisthorchiasis viverrini and cholangiocarcinoma was 59.38% and 65.62%, respectively, while the specificity of both was 85.71%. CONCLUSION: Chk1 was identified by differential plasma proteomes and was increased in O. viverrini-infected and cholangiocarcinoma-derived plasma samples. Higher levels of plasma Chk1 levels may serve as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma.

Identification of 4-genes model in papillary renal cell tumor microenvironment based on comprehensive analysis

Background The tumor microenvironment acts a pivotal part in the occurrence and development of tumor. However, there are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC. Methods PRCC expression profiles and clinical data were extracted from The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Immune/stromal scores were performed utilizing the ESTIMATE algorithm. Three hundred fifty-seven samples were split into two groups on the basis of median immune/stromal score, and comparison of gene expression was conducted. Intersect genes were obtained by Venn diagrams. Hub genes were selected through protein-protein interaction (PPI) network construction, and relevant functional analysis was conducted by DAVID. We used Kaplan–Meier analysis to identify the correlations between genes and overall survival (OS) and progression-free survival (PFS). Univariate and multivariate cox regression analysis were employed to construct survival model. Cibersort was used to predict the immune cell composition of high and low risk group. Combined nomograms were built to predict PRCC prognosis. Immune properties of PRCC were validated by The Cancer Immunome Atlas (TCIA). Results We found immune/stromal score was correlated with T pathological stages and PRCC subtypes. Nine hundred eighty-nine differentially expressed genes (DEGs) and 1169 DEGs were identified respectively on the basis of immune and stromal score. Venn diagrams indicated that 763 co-upregulated genes and 4 co-downregulated genes were identified. Kaplan-Meier analysis revealed that 120 genes were involved in tumor prognosis. Then PPI network analysis identified 22 hub genes, and four of which were significantly related to OS in patients with PRCC confirmed by cox regression analysis. Finally, we constructed a prognostic nomogram which combined with influence factors. Conclusions Four tumor microenvironment-related genes (CD79A, CXCL13, IL6 and CCL19) were identified as biomarkers for PRCC prognosis.