Data-Driven Modeling of Engagement Analytics for Quality Blended Learning

Engagement analytics is a branch of learning analytics (LA) that focuses on student engagement, with the majority of studies conducted by computer scientists.Thus, rather than focusing on learning, research in this field usually treats education as a scenario for algorithms optimization and it rarely concludes with implications for practice. While LA as a research field is reaching ten years, its contribution to our understanding of teaching and learning and its impact on learning enhancement are still underdeveloped. This paper argues that data-driven modeling of engagement analytics is helpful to assess student engagement and to promote reflections on the quality of teaching and learning. In this article, the authors a) introduce four key constructs (student engagement, learning analytics, engagement analytics, modeling and data-driven modeling); b) explain why data-driven modeling is chosen for engagement analytics and the limitations of using a predefined framework; c) discuss how to use engagement analytics to promote pedagogical reflection using a pilot study as a demonstration. As a final remark, the authors see the need of interdisciplinary collaboration on engagement analytics between computer science and educational science. In fact, this collaboration should enhance the use of machine learning and data mining methods to explore big data in education as a means to provide effective insights for quality educational practice.Peer reviewe

Cardiovascular Disease Prediction Modelling: A Machine Learning Approach

The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the target. In logistic regression, the independent variables included all features in the data set except for “target,” which is a categorical variable that indicates whether the patient has cardiovascular disease. The dependent variable included the “target” variable. The findings suggest that the logistic regression model had the highest accuracy in predicting cardiovascular disease. The results of this study can be beneficial to healthcare professionals in developing new preventative protocols for assessing and treating cardiovascular disease

Depression in Chinese patients with type 2 diabetes: associations with hyperglycemia, hypoglycemia, and poor treatment adherence.

BackgroundWe hypothesize that depression in type 2 diabetes might be associated with poor glycemic control, in part due to suboptimal self-care. We tested this hypothesis by examining the associations of depression with clinical and laboratory findings in a multicenter survey of Chinese type 2 diabetic patients.Method2538 patients aged 18-75 years attending hospital-based clinics in four cities in China underwent detailed clinical-psychological-behavioral assessment during a 12-month period between 2011 and 2012. Depression was diagnosed if Patient Health Questionnaire-9 (PHQ-9) score ≥10. Diabetes self-care and medication adherence were assessed using the Summary of Diabetes Self-care Activities and the 4-item Morisky medication adherence scale respectively.ResultsIn this cross-sectional study (mean age: 56.4 ± 10.5[SD] years, 53% men), 6.1% (n = 155) had depression. After controlling for study sites, patients with depression had higher HbA(1c) (7.9 ± 2.0 vs. 7.7 ± 2.0%, P = 0.008) and were less likely to achieve HbA(1c) goal of <7.0% (36.2% vs 45.6%, P = 0.004) than those without depression. They were more likely to report hypoglycemia and to have fewer days of being adherent to their recommended diet, exercise, foot care and medication. In logistic regression, apart from young age, poor education, long disease duration, tobacco use, high body mass index, use of insulin, depression was independently associated with failure to attain HbA(1c) target (Odds Ratio [OR] = 1.56, 95%CI:1.05-2.32, P = 0.028). The association between depression and glycemic control became non-significant after inclusion of adherence to diet, exercise and medication (OR = 1.48, 95% CI 0.99-2.21, P = 0.058).ConclusionDepression in type 2 diabetes was closely associated with hyperglycemia and hypoglycemia, which might be partly mediated through poor treatment adherence

The epidemiology and transmissibility of Zika virus in Girardot and San Andres Island, Colombia, September 2015 to January 2016

Transmission of Zika virus (ZIKV) was first detected in Colombia in September 2015. As of April 2016, Colombia had reported over 65,000 cases of Zika virus disease (ZVD). We analysed daily surveillance data of ZVD cases reported to the health authorities of San Andres and Girardot, Colombia, between September 2015 and January 2016. ZVD was laboratory-confirmed by reverse transcription-polymerase chain reaction (RT-PCR) in the serum of acute cases within five days of symptom onset. We use daily incidence data to estimate the basic reproductive number (R0) in each population. We identified 928 and 1,936 reported ZVD cases from San Andres and Girardot, respectively. The overall attack rate for reported ZVD was 12.13 cases per 1,000 residents of San Andres and 18.43 cases per 1,000 residents of Girardot. Attack rates were significantly higher in females in both municipalities (p < 0.001). Cases occurred in all age groups with highest rates in 20 to 49 year-olds. The estimated R0 for the Zika outbreak was 1.41 (95% confidence interval (CI): 1.15-1.74) in San Andres and 4.61 (95% CI: 4.11-5.16) in Girardot. Transmission of ZIKV is ongoing in the Americas. The estimated R0 from Colombia supports the observed rapid spread

Innate NKT lymphocytes confer superior adaptive immunity via tumor-capturing dendritic cells

If irradiated tumor cells could be rendered immunogenic, they would provide a safe, broad, and patient-specific array of antigens for immunotherapies. Prior approaches have emphasized genetic transduction of live tumor cells to express cytokines, costimulators, and surrogate foreign antigens. We asked if immunity could be achieved by delivering irradiated, major histocompatibility complex–negative plasmacytoma cells to maturing mouse dendritic cells (DCs) within lymphoid organs. Tumor cells injected intravenously (i.v.) were captured by splenic DCs, whereas subcutaneous (s.c.) injection led only to weak uptake in lymph node or spleen. The natural killer T (NKT) cells mobilizing glycolipid α-galactosyl ceramide, used to mature splenic DCs, served as an effective adjuvant to induce protective immunity. This adjuvant function was mimicked by a combination of poly IC and agonistic αCD40 antibody. The adjuvant glycolipid had to be coadministered with tumor cells i.v. rather than s.c. Specific resistance was generated both to a plasmacytoma and lymphoma. The resistance afforded by a single vaccination lasted >2 mo and required both CD4+ and CD8+ T cells. Mature tumor capturing DCs stimulated the differentiation of P1A tumor antigen-specific, CD8+ T cells and uniquely transferred tumor resistance to naive mice. Therefore, the access of dying tumor cells to DCs that are maturing to activated NKT cells efficiently induces long-lived adaptive resistance

Impacts of chronic kidney disease and albuminuria on associations between coronary heart disease and its traditional risk factors in type 2 diabetic patients – the Hong Kong diabetes registry

<p>Abstract</p> <p>Background</p> <p>Glycated haemoglobin (HbA_1c), blood pressure and body mass index (BMI) are risk factors for albuminuria, the latter in turn can lead to hyperlipidaemia. We used novel statistical analyses to examine how albuminuria and chronic kidney disease (CKD) may influence the effects of other risk factors on coronary heart disease (CHD).</p> <p>Methods</p> <p>A prospective cohort of 7067 Chinese type 2 diabetic patients without history of CHD enrolled since 1995 were censored on July 30^th, 2005. Cox proportional hazard regression with restricted cubic spline was used to auto-select predictors. Hazard ratio plots were used to examine the risk of CHD. Based on these plots, non-linear risk factors were categorised and the categorised variables were refitted into various Cox models in a stepwise manner to confirm the findings.</p> <p>Results</p> <p>Age, male gender, duration of diabetes, spot urinary albumin: creatinine ratio, estimated glomerular filtration rate, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and current smoking status were risk factors of CHD. Linear association between TC and CHD was observed only in patients with albuminuria. Although in general, increased HDL-C was associated with decreased risk of CHD, full-range HDL-C was associated with CHD in an A-shaped manner with a zenith at 1.1 mmol/L. Albuminuria and CKD were the main contributors for the paradoxically positive association between HDL-C and CHD for HDL-C values less than 1.1 mmol/L.</p> <p>Conclusion</p> <p>In type 2 diabetes, albuminuria plays a linking role between conventional risk factors and CHD. The onset of CKD changes risk associations between lipids and CHD.</p

Coronary Artery Remodeling in a Model of Left Ventricular Pressure Overload is Influenced by Platelets and Inflammatory Cells

Left ventricular hypertrophy (LVH) is usually accompanied by intensive interstitial and perivascular fibrosis, which may contribute to arrhythmogenic sudden cardiac death. The mechanisms underlying the development of cardiac fibrosis are incompletely understood. To investigate the role of perivascular inflammation in coronary artery remodeling and cardiac fibrosis during hypertrophic ventricular remodeling, we used a well-established mouse model of LVH (transverse aortic constriction [TAC]). Three days after pressure overload, macrophages and T lymphocytes accumulated around and along left coronary arteries in association with luminal platelet deposition. Consistent with these histological findings, cardiac expression of IL-10 was upregulated and in the systemic circulation, platelet white blood cell aggregates tended to be higher in TAC animals compared to sham controls. Since platelets can dynamically modulate perivascular inflammation, we investigated the impact of thrombocytopenia on the response to TAC. Immunodepletion of platelets decreased early perivascular T lymphocytes\u27 accumulation and altered subsequent coronary artery remodeling. The contribution of lymphocytes were examined in Rag1(-/-) mice, which displayed significantly more intimal hyperplasia and perivascular fibrosis compared to wild-type mice following TAC. Collectively, our studies support a role of early perivascular accumulation of platelets and T lymphocytes in pressure overload-induced inflammation

Lipid control and use of lipid-regulating drugs for prevention of cardiovascular events in Chinese type 2 diabetic patients: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Dyslipidaemia is an important but modifiable risk factor of cardiovascular disease (CVD) in type 2 diabetes. Yet, the effectiveness of lipid regulating drugs in Asians is lacking. We examined the effects of lipid control and treatment with lipid regulating drugs on new onset of CVD in Chinese type 2 diabetic patients.</p> <p>Methods</p> <p>In this prospective cohort consisting of 4521 type 2 diabetic patients without history of CVD and naïve for lipid regulating treatment recruited consecutively from 1996 to 2005, 371 developed CVD after a median follow-up of 4.9 years. We used Cox proportional hazard regression to obtain the hazard ratios (HR) of lipids and use of lipid regulating drugs for risk of CVD.</p> <p>Results</p> <p>The multivariate-adjusted HR (95% confidence interval) of CVD in patients with high LDL-cholesterol (≥ 3.0 mmol/L) was 1.36 (1.08 - 1.71), compared with lower values. Using the whole range value of HDL-cholesterol, the risk of CVD was reduced by 41% with every 1 mmol/L increase in HDL-cholesterol. Plasma triglyceride did not predict CVD. Statins use was associated with lower CVD risk [HR = 0.66 (0.50 - 0.88)]. In sub-cohort analysis, statins use was associated with a HR of 0.60 (0.44 - 0.82) in patients with high LDL-cholesterol (≥ 3.0 mmol/L) and 0.49 (0.28 - 0.88) in patients with low HDL-cholesterol. In patients with LDL-cholesterol < 3.0 mmol/L, use of fibrate was associated with HR of 0.34 (0.12 - 1.00). Only statins were effective in reducing incident CVD in patients with metabolic syndrome [(HR = 0.58(0.42--0.80)].</p> <p>Conclusions</p> <p>In Chinese type 2 diabetic patients, high LDL-cholesterol and low HDL-cholesterol predicted incident CVD. Overall, patients treated with statins had 40-50% risk reduction in CVD compared to non-users.</p