Background YouTube is a valuable source of health-related educational material which can have a profound impact on people’s behaviors and decisions. However, YouTube contains a wide variety of unverified content that may promote unhealthy behaviors and activities. We aim in this systematic review to provide insight into the published literature concerning the quality of health information and educational videos found on YouTube. Methods We searched Google Scholar, Medline (through PubMed), EMBASE, Scopus, Direct Science, Web of Science, and ProQuest databases to find all papers on the analysis of medical and health-related content published in English up to August 2020. Based on eligibility criteria, 202 papers were included in our study. We reviewed every article and extracted relevant data such as the number of videos and assessors, the number and type of quality categories, and the recommendations made by the authors. The extracted data from the papers were aggregated using different methods to compile the results. Results The total number of videos assessed in the selected articles is 22,300 (median = 94, interquartile range = 50.5–133). The videos were evaluated by one or multiple assessors (median = 2, interquartile range = 1–3). The video quality was assessed by scoring, categorization, or based on creators’ bias. Researchers commonly employed scoring systems that are either standardized (e.g., GQS, DISCERN, and JAMA) or based upon the guidelines and recommendations of professional associations. Results from the aggregation of scoring or categorization data indicate that health-related content on YouTube is of average to below-average quality. The compiled results from bias-based classification show that only 32% of the videos appear neutral toward the health content. Furthermore, the majority of the studies confirmed either negative or no correlation between the quality and popularity of the assessed videos. Conclusions YouTube is not a reliable source of medical and health-related information. YouTube’s popularity-driven metrics such as the number of views and likes should not be considered quality indicators. YouTube should improve its ranking and recommender system to promote higher-quality content. One way is to consider expert reviews of medical and health-related videos and to include their assessment data in the ranking algorithm.

BackgroundThe aim was to study urinary angiostatin, CXC chemokine ligand 4 (CXCL4) and vascular cell adhesion molecule-1 (VCAM-1) as biomarkers of renal disease in systemic lupus erythematosus (SLE).MethodPatients who fulfilled ≥ 4 American College of Rheumatology (ACR) criteria for SLE with active renal, active non-renal or inactive disease, and a group of healthy controls were studied. Urine samples were assayed for angiostatin, CXCL4 and VCAM-1 by ELISA, and normalized by creatinine. Receiver operating characteristic analysis was performed to obtain the best cutoff values to calculate the performance of these markers in differentiating the different groups of patients as compared to anti-double-stranded DNA (anti-dsDNA) and complement C3. Correlation between these urinary biomarkers and various renal parameters was also tested.ResultsPatients with SLE (n = 227; 80 with inactive SLE, 67 with active non-renal disease and 80 with active renal disease; 94% women; age 39.2 ± 13.8 years) and 53 controls (96% women) were studied. All were ethnic Chinese. Urinary angiostatin, CXCL4 and VCAM-1 (normalized for creatinine) were significantly higher in patients with active renal disease than in patients with active non-renal disease, patients with inactive SLE and controls. These markers correlated significantly with total SLE disease activity index (SLEDAI) and renal SLEDAI scores, and with the urinary protein-to-creatinine ratio. Urine angiostatin exhibited higher specificity and sensitivity in differentiating active renal from active non-renal SLE (area under the curve (AUC) 0.87) than serum anti-dsDNA/C3. Urine CXCL4 (AUC 0.64) and VCAM-1 (AUC 0.73), on the other hand, performed similarly to anti-dsDNA/C3. All three markers performed comparably to anti-dsDNA/C3 in distinguishing active from inactive SLE. In a subgroup of 68 patients with paired renal biopsy, the urinary levels of these proteins did not differ significantly between the proliferative and non-proliferative types of lupus nephritis. Urinary CXCL4 and VCAM-1 correlated significantly with the histologic activity score, and urinary angiostatin correlated significantly with proteinuria in this subgroup.ConclusionsUrinary angiostatin, CXCL4 and VCAM-1 are potential biomarkers for SLE, in particular lupus nephritis. Further longitudinal studies are necessary to delineate the performance of these markers in predicting renal flares and prognosis in SLE patients.

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Most of query optimizers choose a single query plan for processing all the data based on the average data statistics. But this plan is usually not efficient with the uncertain stream data sets of modern applications as network monitoring, sensor networks and financial applications; where these data have continuous variations over time. In this paper we propose an optimized query mesh for data stream (OQMDS) frameworks.In which, process data streams over multiple query plans, each of them is optimal for the sub-set of data with the same statistics.The OQMDS solution depends on preparing multiple query plans and continuously chooses the best execution plan for each sub-set of incoming data streams based on their statistics. We also propose two optimization algorithms called Optimized Iterative Improvement Query Mesh (Oll-QM) and Non-Search based Query Mesh (NS-QM) algorithms, to efficiently generate the multiple plans (the optimized QM solution) which are used to process the online data streams. Our experimental results show that, the proposed solution OQMDS improves the overall performance of data stream processing.

Office buildings in Upper Egypt suffer from high temperature in summer due to solar radiation of this extreme hot arid climatic region. The effect of smart glass on reducing energy consumption in office buildings is well studied in temperature climates but rarely addressed for this Region. This paper aims to compare different types of glazing to define which achieves a better balance between reducing cooling energy consumption and daylight saving. Six types of glazing were simulated on the main office building of Sohag governorate-Egypt. The simulation was carried out for all orientations. Energy Plus-Design Builder simulation tool has been used to study the effect of smart glass on increasing energy efficiency. The window area-to-floor ratio was 8%, 16%, 24% and 32%. Simulation results show that smart glazing is more effective than traditional windows. Electro-chromic glass achieved the best results in reducing cooling energy consumption for window area of 32%. Also, achieving a significant reduction in cooling loads up to 43% in East orientation, 46% in South orientation and 45% in West orientation. On the other hand, it reduced glare in the East and West orientation by 64%. And, it reduced consumption of lighting energy by 60%, 61% and 57% in East, South and West, respectively. The effect of Gasochromic was increased when the window area ratio increased to 32%. For window area 32%, Gaso-chromic achieved the results of light energy similar to Electro-chromic.

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