SeQuery: an interactive graph database for visualizing the GPCR superfamily

The Construction and Application of E-Learning Curricula Evaluation Metrics for Competency-Based Teacher Professional Development

Today, students at universities in advanced countries typically enroll in colleges, such as the College of Education, which offer interdisciplinary programs for undergraduates in their first and second years, allowing them to explore personal interests, experience educational research fields, complete their integrated curricula, and then choose a major in their third year. To cooperate with the government’s epidemic prevention policies and measures in the post-COVID-19 era, the trend of e-learning and distance teaching has accelerated the establishment of integrated online curricula with interdisciplinary programs for undergraduates in the College of Education to facilitate effective future teacher professional development (TPD). Therefore, it is very important to construct e-learning curricula evaluation metrics for competency-based teacher professional development (CB-TPD) and to implement them in teaching practice. This research used social network analysis (SNA) methods, approaches, and theoretical concepts, such as affiliation networks and bipartite graphs comprised of educational occupational titles and common professional competencies (i.e., Element Name and ID), as well as knowledge, skills, abilities, and other characteristics (KSAOs), from the U.S. occupational information network (O*NET) 26.1 OnLine database, to collect data on the occupations of educational professionals. This study also used Gephi network analysis and visualization software to carry out descriptive statistics of keyword co-occurrences to measure their centrality metrics, including weighted degree centrality, degree centrality, betweenness centrality, and closeness centrality, and to verify their importance and ranking in professional competency in eight categories of educational professionals (i.e., three categories of special education teachers and five categories of teachers, except special education). The analysis of the centrality metrics identified the educational common professional competency (ECPC) keyword co-occurrences, which were then used to design, develop, and apply e-learning curricula evaluation metrics for CB-TPD. The results of this study can be used as a reference for conducting related academic research and cultivating educational professionals’ online curricula, including ECPC keywords, integrated curricula design and the development of transdisciplinary programs, and teacher education, as well as to facilitate the construction and application of future e-learning curricula evaluation metrics for CB-TPD.

Development and Interrogation of a Transcriptomic Resource for the Giant Triton Snail (Charonia tritonis)

Gastropod molluscs are among the most abundant species that inhabit coral reef ecosystems. Many are specialist predators, along with the giant triton snail Charonia tritonis (Linnaeus, 1758) whose diet consists of Acanthaster planci (crown-of-thorns starfish), a corallivore known to consume enormous quantities of reef-building coral. C. tritonis are considered vulnerable due to overexploitation, and a decline in their populations is believed to have contributed to recurring A. planci population outbreaks. Aquaculture is considered one approach that could help restore natural populations of C. tritonis and mitigate coral loss; however, numerous questions remain unanswered regarding their life cycle, including the molecular factors that regulate their reproduction and development. In this study, we have established a reference C. tritonis transcriptome derived from developmental stages (embryo and veliger) and adult tissues. This was used to identify genes associated with cell signalling, such as neuropeptides and G protein-coupled receptors (GPCRs), involved in endocrine and olfactory signalling. A comparison of developmental stages showed that several neuropeptide precursors are exclusively expressed in post-hatch veligers and functional analysis found that FFamide stimulated a significant (20.3%) increase in larval heart rate. GPCRs unique to veligers, and a diversity of rhodopsin-like GPCRs located within adult cephalic tentacles, all represent candidate olfactory receptors. In addition, the cytochrome P450 superfamily, which participates in the biosynthesis and degradation of steroid hormones and lipids, was also found to be expanded with at least 91 genes annotated, mostly in gill tissue. These findings further progress our understanding of C. tritonis with possible application in developing aquaculture methods.

Exploring Molecular Mechanism of Huangqi in Treating Heart Failure Using Network Pharmacology

Heart failure (HF), a clinical syndrome with a high incidence due to various reasons, is the advanced stage of most cardiovascular diseases. Huangqi is an effective treatment for cardiovascular disease, which has multitarget, multipathway functions. Therefore, we used network pharmacology to explore the molecular mechanism of Huangqi in treating HF. In this study, 21 compounds of Huangqi, which involved 407 targets, were obtained and reconfirmed using TCMSP and PubChem databases. Moreover, we used Cytoscape 3.7.1 to construct compound-target network and screened the top 10 compounds. 378 targets related to HF were obtained from CTD and GeneCards databases and HF-target network was constructed by Cytoscape 3.7.1. The 46 overlapping targets of HF and Huangqi were gotten by Draw Venn Diagram. STRING database was used to set up a protein-protein interaction network, and MCODE module and the top 5 targets with the highest degree for overlapping targets were obtained. GO analysis performed by Metascape indicated that the overlapping targets were mainly enriched in blood vessel development, reactive oxygen species metabolic process, response to wounding, blood circulation, and so on. KEGG analysis analyzed by ClueGO revealed that overlapping targets were mainly enriched in AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, c-type lectin receptor signaling pathway, relaxin signaling pathway, and so on. Finally, molecular docking showed that top 10 compounds of Huangqi also had good binding activities to important targets compared with digoxin, which was carried out in CB-Dock molecular docking server. In conclusion, Huangqi has potential effect on regulating overlapping targets and GE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, and so on to be a latent multitarget, multipathway treatment for HF.

A network pharmacology-based strategy for predicting anti-inflammatory targets of ephedra in treating asthma

Asthma, the most common chronic respiratory disease in the world, is involved in a sustained inflammatory response caused by a variety of immune cells. Ephedra with multi-target, multi-pathway functions is an effective treatment for asthma. However, the ingredients and anti-inflammatory targets of ephedra in treating asthma are unclear. Therefore, there is a need for further research. Ephedra-related and anti-inflammatory targets were found and then combined to get intersection, which represented potential anti-inflammatory targets of ephedra. Moreover, compound-anti-inflammatory target and asthma-target protein-protein interaction network were merged to get the protein-protein interaction network intersection and core genes in asthma-target protein-protein interaction network. For the anti-inflammatory targets of ephedra in treating asthma, Gene Ontology and pathway analysis were executed to confirm gene functions of ephedra in antagonizing inflammation of asthma. Finally, molecular docking, qRT-PCR, WB and ELISA were performed to assess the binding activities between the compounds and anti-inflammatory targets of ephedra in treating asthma. Critical compounds and anti-inflammatory targets of ephedra in treating asthma were identified, including quercetin, luteolin, kempferol, naringenin, beta-sitosterol, SELE, IL-2 and CXCL10. The biological processes of anti-inflammatory targets of ephedra in treating asthma were involved in immune response, inflammatory response, cell-cell signaling and response to lipopolysaccharide. Moreover, 22 pathways were obtained and we proved that critical compounds inhabited the expression of SELE, IL-2 and CXCL10 at mRNA and protein levels.

GPCR-PEnDB: a database of protein sequences and derived features to facilitate prediction and classification of G protein-coupled receptors

G protein-coupled receptors (GPCRs) constitute the largest group of membrane receptor proteins in eukaryotes. Due to their significant roles in various physiological processes such as vision, smell and inflammation, GPCRs are the targets of many prescription drugs. However, the functional and sequence diversity of GPCRs has kept their prediction and classification based on amino acid sequence data as a challenging bioinformatics problem. There are existing computational approaches, mainly using machine learning and statistical methods, to predict and classify GPCRs based on amino acid sequence and sequence derived features. In this paper, we describe a searchable MySQL database, named GPCR-PEnDB (GPCR Prediction Ensemble Database), of confirmed GPCRs and non-GPCRs. It was constructed with the goal of allowing users to conveniently access useful information of GPCRs in a wide range of organisms and to compile reliable training and testing datasets for different combinations of computational tools. This database currently contains 3129 confirmed GPCR and 3575 non-GPCR sequences collected from the UniProtKB/Swiss-Prot protein database, encompassing over 1200 species. The non-GPCR entries include transmembrane proteins for evaluating various prediction programs' abilities to distinguish GPCRs from other transmembrane proteins. Each protein is linked to information about its source organism, classification, sequence lengths and composition, and other derived sequence features. We present examples of using this database along with its graphical user interface, to query for GPCRs with specific sequence properties and to compare the accuracies of five tools for GPCR prediction. This initial version of GPCR-PEnDB will provide a framework for future extensions to include additional sequence and feature data to facilitate the design and assessment of software tools and experimental studies to help understand the functional roles of GPCRs. Database URL: gpcr.utep.edu/database.