Influencing factors of self-regulated learning of medical-related students in a traditional Chinese medical university: a cross-sectional study.

BACKGROUND: In recent years, self-regulated learning (SRL) has become a hot topic in medical education. However, the factors that affect the SRL ability of medical-related specialties, such as clinical medicine, traditional Chinese medicine (TCM), and nursing specialty in TCM colleges and universities are unclear. Whether the teaching of learning strategies can help improve students' SRL also needs to be further examined. METHOD: A cross-sectional survey was distributed, and 878 medical-related students who were from a TCM university were recruited for this study. Descriptive statistics illustrated the status quo of SRL and learning strategies, and an independent t-test and analysis of variance were used to analyze the factors associated with SRL. The relationship between SRL and learning strategies was analyzed with multi-linear regression analysis. RESULTS: The scores of SRL on learning motivation, learning setting, self-regulation, and total scores were 34.76 ± 4.62, 41.14 ± 4.30, 39.26 ± 4.74, and 115.16 ± 12.42, respectively. The metacognitive, emotion, cognitive, resource management and total scores of learning strategies were 58.54 ± 12.02, 43.24 ± 8.42, 35.49 ± 7.34, 22.89 ± 4.20, 160.16 ± 29.45, and the mean was all above the midpoint. Learning strategies were positively correlated with SRL (r = 0.421, P < 0.01). Some factors can predict 32% of the variation of SRL, including whether they liked their specialty, educational system, specialty, score ranking, scholarship, whether they were taught by a tutor in middle school, gender, monthly family income, the father's educational background, metacognitive strategy, resource management strategy, and cognitive strategy. CONCLUSIONS: The SRL of medical-related students was better. Learning strategies, as well as personal or social factors, can affect SRL. Educators should pay more attention to the cultivation of learning strategies, exercising learning skills, and monitoring, adjustment, and guidance of learning time. It should adopt various methods to improve the SRL of medical-related students according to the different factors.

Improving Friend Recommendation for Online Learning with Fine-Grained Evolving Interest.

Friend recommendation plays a key role in promoting user experience in online social networks (OSNs). However, existing studies usually neglect users' fine-grained interest as well as the evolving feature of interest, which may cause unsuitable recommendation. In particular, some OSNs, such as the online learning community, even have little work on friend recommendation. To this end, we strive to improve friend recommendation with fine-grained evolving interest in this paper. We take the online learning community as an application scenario, which is a special type of OSNs for people to learn courses online. Learning partners can help improve learners' learning effect and improve the attractiveness of platforms. We propose a learning partner recommendation framework based on the evolution of fine-grained learning interest (LPRF-E for short). We extract a sequence of learning interest tags that changes over time. Then, we explore the time feature to predict evolving learning interest. Next, we recommend learning partners by fine-grained interest similarity. We also refine the learning partner recommendation framework with users' social influence (denoted as LPRF-F for differentiation). Extensive experiments on two real datasets crawled from Chinese University MOOC and Douban Book validate that the proposed LPRF-E and LPRF-F models achieve a high accuracy (i.e., approximate 50% improvements on the precision and the recall) and can recommend learning partners with high quality (e.g., more experienced and helpful). Supplementary Information: The online version contains supplementary material available at 10.1007/s11390-021-2124-z.

Lectin microarrays differentiate carcinoma cells from reactive mesothelial cells in pleural effusions.

The aim of this study was to evaluate the diagnostic utility of lectin microarrays in pleural effusions of patients with lung cancer. A lectin microarray, LTL, PSA, LCA, UEA-1, AAL, MAL-I, MAL-II, SNA, WGA, ECL, DSA, STL, SWGA, HPA, ConA, GNA, HHL, BPL, EEL, Jacalin, WFA, ACL, MPL, DBA, SBA, was used to determine the glycoprotein profile of cells in pleural effusions from patients with lung cancer (54 cases), and with benign lung disease (54 cases). The A549 cell line, used as an experimental control, was positive for AAL, MAL-I, WGA, STL, Jacalin and ACL binding. Adenocarcinoma cells in pleural effusions were positive for ECL, DSA, AAL, MAL-I, WGA, STL, Jacalin, and ACL binding. AAL, WGA, and ACL positive binding was the most common, found in 54, 48, and 38 samples, respectively. ECL and DSA binding was positive in only 4 samples. In comparison, reactive mesothelial cells displayed positive binding for all markers in the microarray panel. SNA and AAL positive binding was detected in the majority of samples; 50/54 and 48/54 samples, respectively. Positive binding of DBA, MAL-II and EEL was present in only 2, 4 and 4 samples, respectively. SNA binding had the highest sensitivity (92.6 %), specificity (100 %), and accuracy (96.3 %). SNA may be used as a biomarker to distinguish reactive mesothelial cells from adenocarcinoma cells. The lectin microarrays proved able to distinguish carcinoma cells from reactive mesothelial cells in pleural effusions.

[A cross-sectional study about the effects of residential exposure to power transmission line on human nervous system symptoms and hematology].

OBJECTIVE: To investigate the possible effects on nervous system and health condition under the exposure to electromagnetic field. METHODS: Take the resident around the power transmission line as the objects and were divided into 3 groups by the distance from the power transmission line 20 m, 100 m and 500 m, respectively. Some living conditions and health conditions were recorded by face-to-face the questionnaire survey, and Hematological indices of each groups were examined including IgG, IgM, leukocyte formulae, erythrocyte, hemoglobin and platelet. RESULTS: There was no significant difference in each group, according exposure of daily life, such as drinking and smoking (P > 0.05). Compared with the each distance groups, it was presented significant difference between the distance from the power transmission line and the incidence of headache or dizziness, insomnia and easy weary and so on (P < 0.05). In hematology aspect, with the horizontal distance from the power transmission line decreasing, PLT level of residents was reductive and the difference was statistically significant (P < 0.001), whereas leukocyte formulae, erythrocyte, hemoglobin, IgG and IgM had no significant difference among each group (P < 0.05). CONCLUSION: Closely exposure to electromagnetic field may induce headache and so on and decrease the level of PLT.