Applying SOAR Strategies to Curb Digital Distractions While Note Taking and Studying

Students are distracted by mobile technology in the classroom when learning from lectures and outside the classroom when studying. Students are susceptible to distractions because they are not fully engaged in learning. In the classroom, they record notes mindlessly that capture just one-third of important lesson ideas. When they study outside the classroom, they study information in a piecemeal fashion and employ mindless repetition strategies. These weak and unengaging learning strategies open the door for digital distractions. One potential means to engage students in meaningful learning and to offset digital distractions is an integrated strategy system called SOAR, which stands for select, organize, associate, and regulate. This chapter describes SOAR and how instructors can maximize SOAR's components to curb digital distractions by improving student note taking in the classroom and study behaviors outside the classroom. The chapter concludes by specifying how instructors can teach students to SOAR on their own.

Integrated Strategy From In Vitro, In Situ, In Vivo to In Silico for Predicting Active Constituents and Exploring Molecular Mechanisms of Tongfengding Capsule for Treating Gout by Inhibiting Inflammatory Responses

The study of screening active constituents from traditional Chinese medicine (TCM) is important for explicating the mechanism of action of TCM and further evaluating the safety and efficacy effectively. However, detecting and identifying the active constituents from complicated biological samples still remain a challenge. Here, a practical, quick, and novel integrated strategy from in vitro, in situ, in vivo to in silico for rapidly screening the active constituents was developed. Firstly, the chemical profile of TCM in vitro was identified using UPLC-Q Exactive-Orbitrap HRMS. Secondly, the in situ intestinal perfusion with venous sampling (IPVS) method was used to investigate the intestinal absorption components. Thirdly, after intragastric administration of the TCM extract, the in vivo absorbed prototype components were detected and identified. Finally, the target network pharmacology approach was applied to explore the potential targets and possible mechanisms of the absorbed components from TCM. The reliability and availability of this approach was demonstrated using Tongfengding capsule (TFDC) as an example of herbal medicine. A total of 141 compounds were detected and identified in TFDC, and among them, 64 components were absorbed into the plasma. Then, a total of 35 absorbed bioactive components and 50 related targets shared commonly by compounds and gout were integrated via target network pharmacology analysis. Ultimately, the effects of the absorbed components on metabolism pathways were verified by experiments. These results demonstrated that this original method may provide a practical tool for screening bioactive compounds from TCM treating particular diseases. Furthermore, it also can clarify the potential mechanism of action of TCM and rationalize the application of TFDC as an effective herbal therapy for gout.

Integrated Strategy of UHPLC-Q-TOF-MS and Molecular Networking for Identification of Diterpenoids from Euphorbia fischeriana Steud. and Prediction of the Anti-Breast-Cancer Mechanism by the Network Pharmacological Method

Breast cancer is one of the most common malignancies in women worldwide. Traditional Chinese medicine has been used as adjunctive or complementary therapy for breast cancer. Diterpenoids from Euphorbia fischeriana Steud. have been demonstrated to possess anti-breast-cancer activity. This research was aimed to systematically explore the diterpenoids from E. fischeriana and study the multiple mechanisms on breast cancer. The structures of diterpenoids were identified by the integrated strategy of UHPLC-Q-TOF-MS and molecular networking. A total of 177 diterpenoids belonging to 13 types were collected. In silico ADME analysis was performed on these compounds. It indicated that 130 of 177 diterpenoids completely adjusted to Lipinski’s rule. The targets of compounds were obtained from PharmMapper. The targets of breast cancer were collected from GeneCards. Then, 197 compounds-related targets and 544 breast cancer-related targets were identified. After the intersection process, 58 overlapping targets between compounds-related targets and breast cancer-related targets were acquired. The STRING database was applied to predict the protein-protein interactions. The GO and KEGG pathway enrichment analysis were performed by using the KOBAS database. It indicated that these predicted pathways were closely related to breast cancer. The treatment effect of E. fischeriana on breast cancer might be performed through signaling pathways, such as IL-17 signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. The predicted top genes such as EGFR, ESR, MAPK, SRC, CASP3, CDK2, and KDR were involved in cell proliferation, gene transcription, apoptosis, signal transduction, DNA damage and repair, tumor differentiation, metastasis, and cell cycle, which indicated that E. fischeriana might treat breast cancer comprehensively. A compounds-KEGG pathways-related targets network was built by using cytoHubba to analyze the hub compounds and targets. It concluded that E. fischeriana treated breast cancer not only by the main components but also by the microconstituents, which reflected the overall regulatory role of multicomponents treating breast cancer. To estimate the binding affinities, binding sites, and binding postures, molecular docking simulations between 177 diterpenoids and top 19 targets were carried out. The results are basically in line with expectations. In conclusion, these results can serve as references for researchers studying potential targets of diterpenoids from E. fischeriana on breast cancer in the future.

Based on Multi-Activity Integrated Strategy to Screening, Characterization and Quantification of Bioactive Compounds from Red Wine

According to French Paradox, red wine was famous for the potential effects on coronary heart disease (CHD), but the specific compounds against CHD were unclear. Therefore, screening and characterization of bioactive compounds from red wine was extremely necessary. In this paper, the multi-activity integrated strategy was developed and validated to screen, identify and quantify active compounds from red wine by using ultra high performance liquid chromatography-fraction collector (UHPLC-FC), ultra fast liquid chromatography-quadrupole-time-of-flight/mass spectrometry (UFLC-Q-TOF/MS) and bioactive analysis. UHPLC-FC was employed to separate and collect the components from red wine, which was further identified by UFLC-Q-TOF/MS to acquire their structural information. Furthermore, the active fractions were tested for antioxidant activity, inhibitory activity against thrombin and lipase activities in vitro by the activity screening kit. As the results, there were 37 fractions had antioxidant activity, 22 fractions had thrombin inhibitory activity and 28 fractions had lipase inhibitory activity. Finally, 77 active components from red wine were screened and 12 ingredients out of them were selected for quantification based on the integration of multi-activity. Collectively, the multi-activity integrated strategy was helpful for the rapid and effective discovery of bioactive components, which provided reference for exploring the health care function of food.