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Background: Given students' lack of self-directed learning skills and the growing concern about implementing massive online open courses (MOOCs) in K12 education, learning strategies are needed to facilitate MOOC learning. Many studies have provided different strategies for effective learning in MOOCs. However, there is still limited research to confirm whether these strategies effectively support MOOC learning when deployed by secondary schools, which are not MOOC developers. Objectives: This mixed-method study examines the provision of different learning strategies, including a learning guide, an academic mentoring programme, a training workshop, and a reimbursement scheme, and investigates the impact of these strategies on student learning in MOOCs. Methods: The study uses two data sources: (1) surveys with 40 participants and (2) semi-structured interviews with 12 participants. The quantitative data were analysed with descriptive statistics and Fisher's exact test, and the qualitative data were analysed with thematic analysis. Results and Conclusion: The findings indicate that MOOC learners had positive attitudes towards the overall school support, with mentoring enjoying great popularity amongst the students. In terms of the effectiveness of the school support, the mentoring programme and reimbursement scheme were more effective than the university training and learning guide. The paper discusses the implications for researchers and educators.

Abstract Aiming at the shortcomings of the BP neural network in practical applications, such as easy to fall into local extremum and slow convergence speed, we optimized the initial weights and thresholds of the BP neural network using the particle swarm optimization (PSO). Additionally, cloud computing service, web technology, cloud database and numerical simulation were integrated to construct an intelligent feedback analysis cloud program for underground engineering safety monitoring based on the PSO-BP algorithm. The program could conveniently, quickly, and intelligently carry out numerical analysis of underground engineering and dynamic feedback analysis of surrounding rock parameters. The program was applied to the cloud inversion analysis of the surrounding rock parameters for the underground powerhouse of the Shuangjiangkou Hydropower Station. The calculated displacement simulated with the back-analyzed parameters matches the measured displacement very well. The posterior variance evaluation shows that the posterior error ratio is 0.045 and the small error probability is 0.999. The evaluation results indicate that the intelligent feedback analysis cloud program has high accuracy and can be applied to engineering practice.

Abstract Longwave radiation is an important open-air environmental factor that can significantly affect the temperature of concrete, but it has often been ignored in the temperature analysis of open-air concrete structures. In this article, an improved analytical model of concrete temperature was proposed by considering solar radiation, thermal convection, thermal conduction and especially longwave radiation. Temperature monitoring of an open-air concrete block was carried out to verify the proposed model and analyze the heat energy characteristics of open-air concrete. As demonstrated by the open-air experiment, under the influence of longwave radiation, the temperature at the top of the concrete block could decrease rapidly at night and even become lower than the minimum temperature at its bottom. Compared with the analytical model that ignores longwave radiation, the improved model that includes it better matches the measured temperature. According to the energy analysis, although solar radiation controls the transient variation in heat energy, the heat exchange caused by longwave radiation were more than that caused by convection on sunlit surfaces, which indicates the importance of considering longwave radiation.

Abstract Dysregulation of wild-type p53 turnover is a key cause of hepatocellular carcinoma (HCC), yet its mechanism remains poorly understood. Here, we report that WD repeat and SOCS box containing protein 2 (WSB2), an E3 ubiquitin ligase, is an independent adverse prognostic factor in HCC patients. WSB2 drives HCC tumorigenesis and lung metastasis in vitro and in vivo. Mechanistically, WSB2 is a new p53 destabilizer that promotes K48-linked p53 polyubiquitination at the Lys291 and Lys292 sites in HCC cells, leading to p53 proteasomal degradation. Degradation of p53 causes IGFBP3-dependent AKT/mTOR signaling activation. Furthermore, WSB2 was found to bind to the p53 tetramerization domain via its SOCS box domain. Targeting mTOR with everolimus, an oral drug, significantly blocked WSB2-triggered HCC tumorigenesis and metastasis in vivo. In clinical samples, high expression of WSB2 was associated with low wild-type p53 expression and high p-mTOR expression. These findings demonstrate that WSB2 is overexpressed and degrades wild-type p53 and then activates the IGFBP3-AKT/mTOR axis, leading to HCC tumorigenesis and lung metastasis, which indicates that targeting mTOR could be a new therapeutic strategy for HCC patients with high WSB2 expression and wild-type p53.

Abstract Background Kirsten rat sarcoma (KRAS) and mutant KRASG12D have been implicated in human cancers, but it remains unclear whether their activation requires ubiquitination. This study aimed to investigate whether and how F-box and leucine-rich repeat 6 (FBXL6) regulates KRAS and KRASG12D activity in hepatocellular carcinoma (HCC). Methods We constructed transgenic mouse strains LC (LSL-Fbxl6 KI/+ ;Alb-Cre, n = 13), KC (LSL-Kras G12D/+ ;Alb-Cre, n = 10) and KLC (LSL-Kras G12D/+ ;LSL-Fbxl6 KI/+ ;Alb-Cre, n = 12) mice, and then monitored HCC for 320 d. Multiomics approaches and pharmacological inhibitors were used to determine oncogenic signaling in the context of elevated FBXL6 and KRAS activation. Co‑immunoprecipitation (Co-IP), Western blotting, ubiquitination assay and RAS activity detection assay were employed to investigate the underlying molecular mechanism by which FBXL6 activates KRAS. The pathological relevance of the FBXL6/KRAS/extracellular signal-regulated kinase (ERK)/mammalian target of rapamycin (mTOR)/proteins of relevant evolutionary and lymphoid interest domain 2 (PRELID2) axis was evaluated in 129 paired samples from HCC patients. Results FBXL6 is highly expressed in HCC as well as other human cancers (P

Anti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data. Specifically, we encode the clinical text as numeric vectors featured with hidden topics for patients using Latent Dirichlet Allocation model. Then, to classify patients into two classes, responsive or non-responsive to a drug, drug efficacy predictors are established by machine learning based on the Latent Dirichlet Allocation topic representation. To evaluate the proposed method, we collected and collated clinical records of lung and bowel cancer patients treated with platinum. Experimental results on the data sets show the efficacy and effectiveness of the proposed method, suggesting the potential value of clinical data in cancer precision medicine. We hope that it will promote the research of drug efficacy prediction based on clinical data.

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P

Abstract Metastatic hepatocellular carcinoma (HCC) is the most lethal malignancy and lacks effective treatment. FBXL6 is overexpressed in human hepatocellular carcinoma (HCC), but whether this change drives liver tumorigenesis and lung metastasis in vivo remains unknown. In this study, we aimed to identify FBXL6 (F-Box and Leucine Rich Repeat Protein 6) as a key driver of HCC metastasis and to provide a new paradigm for HCC therapy. We found that elevated FBXL6 expression in hepatocytes drove HCC lung metastasis and was a much stronger driver than Kras mutation (Kras G12D/+ ;Alb-Cre), p53 haploinsufficiency (p53 +/- ) or Tsc1 loss (Tsc1 fl/fl ;Alb-Cre). Mechanistically, VRK2 promoted Thr287 phosphorylation of TKT and then recruited FBXL6 to promote TKT ubiquitination and activation. Activated TKT further increased PD-L1 and VRK2 expression via the ROS-mTOR axis, leading to immune evasion and HCC metastasis. Targeting or knockdown of TKT significantly blocked FBXL6-driven immune evasion and HCC metastasis in vitro and in vivo. Notably, the level of active TKT (p-Thr287 TKT) was increased and was positively correlated with the FBXL6 and VRK2 expression levels in HCC patients. Our work provides novel mechanistic insights into FBXL6-driven HCC metastasis and suggests that targeting the TKT-ROS-mTOR-PD-L1/VRK2 axis is a new paradigm for treating patients with metastatic HCC with high FBXL6 expression.