Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies ...involving online and traditional learning activities. Learning analytics is a conceptual framework and as a part of our Precision education used to analyze and predict students' performance and provide timely interventions based on student learning profiles. This study applied learning analytics and educational big data approaches for the early prediction of students' final academic performance in a blended Calculus course. Real data with 21 variables were collected from the proposed course, consisting of video-viewing behaviors, out-of-class practice behaviors, homework and quiz scores, and after-school tutoring. This study applied principal component regression to predict students' final academic performance. The experimental results show that students' final academic performance could be predicted when only one-third of the semester had elapsed. In addition, we identified seven critical factors that affect students' academic performance, consisting of four online factors and three traditional factors. The results showed that the blended data set combining online and traditional critical factors had the highest predictive performance.
Biomarkers that predict disease progression might assist the development of better therapeutic strategies for aggressive cancers, such as ovarian cancer. Here, we investigated the role of collagen ...type XI alpha 1 (COL11A1) in cell invasiveness and tumor formation and the prognostic impact of COL11A1 expression in ovarian cancer. Microarray analysis suggested that COL11A1 is a disease progression-associated gene that is linked to ovarian cancer recurrence and poor survival. Small interference RNA-mediated specific reduction in COL11A1 protein levels suppressed the invasive ability and oncogenic potential of ovarian cancer cells and decreased tumor formation and lung colonization in mouse xenografts. A combination of experimental approaches, including real-time RT-PCR, casein zymography and chromatin immunoprecipitation (ChIP) assays, showed that COL11A1 knockdown attenuated MMP3 expression and suppressed binding of Ets-1 to its putative MMP3 promoter-binding site, suggesting that the Ets-1-MMP3 axis is upregulated by COL11A1. Transforming growth factor (TGF)-beta (TGF-β1) treatment triggers the activation of smad2 signaling cascades, leading to activation of COL11A1 and MMP3. Pharmacological inhibition of MMP3 abrogated the TGF-β1-triggered, COL11A1-dependent cell invasiveness. Furthermore, the NF-YA-binding site on the COL11A1 promoter was identified as the major determinant of TGF-β1-dependent COL11A1 activation. Analysis of 88 ovarian cancer patients indicated that high COL11A1 mRNA levels are associated with advanced disease stage. The 5-year recurrence-free and overall survival rates were significantly lower (P=0.006 and P=0.018, respectively) among patients with high expression levels of tissue COL11A1 mRNA compared with those with low expression. We conclude that COL11A1 may promote tumor aggressiveness via the TGF-β1-MMP3 axis and that COL11A1 expression can predict clinical outcome in ovarian cancer patients.
Alloys with ultra-high strength and sufficient ductility are highly desired for modern engineering applications but difficult to develop. Here we report that, by a careful controlling alloy ...composition, thermomechanical process, and microstructural feature, a Co-Cr-Ni-based medium-entropy alloy (MEA) with a dual heterogeneous structure of both matrix and precipitates can be designed to provide an ultra-high tensile strength of 2.2 GPa and uniform elongation of 13% at ambient temperature, properties that are much improved over their counterparts without the heterogeneous structure. Electron microscopy characterizations reveal that the dual heterogeneous structures are composed of a heterogeneous matrix with both coarse grains (10∼30 μm) and ultra-fine grains (0.5∼2 μm), together with heterogeneous L1
-structured nanoprecipitates ranging from several to hundreds of nanometers. The heterogeneous L1
nanoprecipitates are fully coherent with the matrix, minimizing the elastic misfit strain of interfaces, relieving the stress concentration during deformation, and playing an active role in enhanced ductility.
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely ...intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model, the reason which affected the performance of the model was overlooked. This study collected seven datasets within three universities located in Taiwan and Japan and listed performance metrics of risk identification model after fed data into eight classification methods. U1, U2, and U3 were used to denote the three universities, which have three, two, and two cases of datasets (learning logs), respectively. According to the results of this study, the factors influencing the predictive performance of classification methods are the number of significant features, the number of categories of significant features, and Spearman correlation coefficient values. In U1 dataset case 1.3 and U2 dataset case 2.2, the numbers of significant features, numbers of categories of significant features, and Spearman correlation coefficient values for significant features were all relatively high, which is the main reason why these datasets were able to perform classification with high predictive ability.
Vascular disease remains the leading cause of death and disability, the etiology of which often involves atherosclerosis. The current treatment of atherosclerosis by pharmacotherapy has limited ...therapeutic efficacy. Here we report a biomimetic drug delivery system derived from macrophage membrane coated ROS-responsive nanoparticles (NPs). The macrophage membrane not only avoids the clearance of NPs from the reticuloendothelial system, but also leads NPs to the inflammatory tissues, where the ROS-responsiveness of NPs enables specific payload release. Moreover, the macrophage membrane sequesters proinflammatory cytokines to suppress local inflammation. The synergistic effects of pharmacotherapy and inflammatory cytokines sequestration from such a biomimetic drug delivery system lead to improved therapeutic efficacy in atherosclerosis. Comparison to macrophage internalized with ROS-responsive NPs, as a live-cell based drug delivery system for treatment of atherosclerosis, suggests that cell membrane coated drug delivery approach is likely more suitable for dealing with an inflammatory disease than the live-cell approach.
Summary
Sarcopenia was reported to be significantly associated with osteoporosis. In this study, we reported for the first time that sarcopenia was an independent risk predictor of osteoporotic ...vertebral compression refractures (OVCRFs). Other risk factors of OVCRFs are low bone mass density T-scores, female sex, and advanced age.
Introduction
The purpose of this study was to investigate the association between osteoporotic vertebral compression refractures (OVCRFs) and sarcopenia, and to identify other risk factors of OVCRFs.
Methods
We evaluated 237 patients with osteoporotic vertebral compression fracture who underwent percutaneous kyphoplasty (PKP) in our hospital from August 2016 to December 2017. To diagnose sarcopenia, a cross-sectional computed tomography (CT) image at the inferior aspect of the third lumbar vertebra (L3) was selected for estimating muscle mass. Grip strength was used to assess muscle strength. Possible risk factors, such as age, sex, body mass index (BMI), bone mineral density (BMD), location of the treated vertebra, anterior-posterior ratio (AP ratio) of the fractured vertebra, cement leakage, and vacuum clefts, were assessed. The multivariable analysis was used to determine the risk factors of OVCRFs.
Results
During the follow-up period, OVCRFs occurred in 64 (27.0%) patients. Sarcopenia was present in 48 patients (20.3%), including 21 OVCRFs and 27 non-OVCRFs patients. Sarcopenia was significantly correlated with advanced age, lower BMI, lower BMD, and hypoalbuminemia. Compared with non-sarcopenic patients, sarcopenic patients had higher OVCRFs risk. In univariate analysis, sarcopenia (
p
= 0.003), female (
p
= 0.024), advanced age (≥ 75 years;
p
< 0.001), lower BMD (
p
< 0.001), lower BMI (
p
= 0.01), TL junction (vertebral levels at the thoracolumbar junction) (
p
= 0.01), cardiopulmonary comorbidity (
p
= 0.042), and hypoalbuminemia (
p
= 0.003) were associated with OVCRFs. Multivariable analysis revealed that sarcopenia (OR 2.271; 95% CI 1.069–4.824,
p
= 0.033), lower BMD (OR 1.968; 95% CI 1.350–2.868,
p
< 0.001), advanced age (≥ 75 years; OR 2.431; 95% CI 1.246–4.744,
p
= 0.009), and female sex (OR 4.666; 95% CI 1.400–15.552,
p
= 0.012) were independent risk predictors of OVCRFs.
Conclusions
Sarcopenia is an independent risk predictor of osteoporotic vertebral compression refractures. Other factors affecting OVCRFs are low BMD T-scores, female sex, and advanced age.
Caveolin-1 (Cav1) is an integral membrane, scaffolding protein found in plasma membrane invaginations (caveolae). Cav1 regulates multiple cancer-associated processes. In breast cancer, a tumor ...suppressive role for Cav1 has been suggested; however, Cav1 is frequently overexpressed in aggressive breast cancer subtypes, suggesting an oncogenic function in advanced-stage disease. To further delineate Cav1 function in breast cancer progression, we evaluated its expression levels among a panel of cell lines representing a spectrum of breast cancer phenotypes. In basal-like (the most aggressive BC subtype) breast cancer cells, Cav1 was consistently upregulated, and positively correlated with increased cell proliferation, anchorage-independent growth, and migration and invasion. To identify mechanisms of Cav1 gene regulation, we compared DNA methylation levels within promoter 'CpG islands' (CGIs) with 'CGI shores', recently described regions that flank CGIs with less CG-density. Integration of genome-wide DNA methylation profiles ('methylomes') with Cav1 expression in 30 breast cancer cell lines showed that differential methylation of CGI shores, but not CGIs, significantly regulated Cav1 expression. In breast cancer cell lines having low Cav1 expression (despite promoter CGI hypomethylation), we found that treatment with a DNA methyltransferase inhibitor induced Cav1 expression via CGI shore demethylation. In addition, further methylome assessments revealed that breast cancer aggressiveness associated with Cav1 CGI shore methylation levels, with shore hypermethylation in minimally aggressive, luminal breast cancer cells and shore hypomethylation in highly aggressive, basal-like cells. Cav1 CGI shore methylation was also observed in human breast tumors, and overall survival rates of breast cancer patients lacking estrogen receptor α (ERα) negatively correlated with Cav1 expression. Based on this first study of Cav1 (a potential oncogene) CGI shore methylation, we suggest this phenomenon may represent a new prognostic marker for ERα-negative, basal-like breast cancer.
The first known magnetic mineral, magnetite, has unusual properties, which have fascinated mankind for centuries; it undergoes the Verwey transition around 120 K with an abrupt change in structure ...and electrical conductivity. The mechanism of the Verwey transition, however, remains contentious. Here we use resonant inelastic X-ray scattering over a wide temperature range across the Verwey transition to identify and separate out the magnetic excitations derived from nominal Fe
and Fe
states. Comparison of the experimental results with crystal-field multiplet calculations shows that the spin-orbital dd excitons of the Fe
sites arise from a tetragonal Jahn-Teller active polaronic distortion of the Fe
O
octahedra. These low-energy excitations, which get weakened for temperatures above 350 K but persist at least up to 550 K, are distinct from optical excitations and are best explained as magnetic polarons.
Inflammatory markers such as interleukin (IL)-6 and tumour necrosis factor-alpha (TNF-α) are elevated in dialysis patients and can predict cardiovascular events and all-cause mortality. Endotoxin is ...an important source and also another marker of inflammation in patients with chronic kidney disease. The aim of this study was to evaluate the impact of oral probiotics on serum levels of endotoxemia and cytokines in peritoneal dialysis (PD) patients. The decline of residual renal function, peritonitis episodes, and cardiovascular events were also recorded. From July 2011 to June 2012, a randomised, double-blind, placebo-controlled trial was conducted in PD patients. The intervention group received one capsule of probiotics containing 10(9) cfu Bifobacterium bifidum A218, 10(9) cfu Bifidobacterium catenulatum A302, 10(9) cfu Bifidobacterium longum A101, and 10(9) cfu Lactobacillus plantarum A87 daily for six months, while the placebo group received similar capsules containing maltodextrin for the same duration. Levels of serum TNF-α, interferon gamma, IL-5, IL-6, IL-10, IL-17, and endotoxin were measured before and six months after intervention. 39 patients completed the study (21 in the probiotics group and 18 in the placebo group). In patients receiving probiotics, levels of serum TNF-α, IL-5, IL-6, and endotoxin significantly decreased after six months of treatment, while levels of serum IL-10 significantly increased. In contrast, there were no significant changes in levels of serum cytokines and endotoxin in the placebo group after six months. In addition, the residual renal function was preserved in patients receiving probiotics. In conclusion, probiotics could significantly reduce the serum levels of endotoxin, pro-inflammatory cytokines (TNF-α and IL-6), IL-5, increase the serum levels of anti-inflammatory cytokine (IL-10), and preserve residual renal function in PD patients.
As information technology continues to evolve rapidly, programming skills become increasingly crucial. To be able to construct superb programming skills, the training must begin before college or ...even senior high school. However, when developing comprehensive training programmers, the learning and teaching processes must be considered. In order to improve the students' learning outcome and engagement in programming course, this study applied learning analytics into the proposed massive online open courses (MOOCs) enabled collaborative programming course. Through the proposed learning activity, instructors receive a monthly report that explains which students are at risk and in need of timely intervention. This study conducted an experiment to evaluate the effectiveness of the proposed learning activity. Students in the experimental group received learning interventions from an instructor according to the result of learning analytics, and students in the control group received interventions according to the instructor's observation. The data for this study were collected over 10 weeks at a university in Taiwan. The result indicated that the proposed programming course with learning analytics improved students' learning outcomes and levels of engagement.
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