Screening and Evaluating Novel Autoantibodies Based on Proteomic Chips in Diagnosis of Esophageal Squamous Cell Carcinoma

Background More and more studies have confirmed that TAAbs could be used as potential biomarkers for tumor patients. The aim of this study is to identify novel TAAbs through proteomic chips and construct a diagnostic model to discriminate esophageal squamous cell carcinoma (ESCC) cases from benign esophageal diseases cases and normal controls (NCs). Methods The human proteomic chips were used to screen TAAbs. Enzyme-linked immunosorbent assay (ELISA) was adopted to verify and validate the candidate TAAbs which were screened by the chips in verification phase (90 ESCC cases and 90 NCs) and validation phase (126 ESCC cases, 237 benign esophageal diseases cases and 126 NCs). Based on the candidate TAAbs, then the diagnostic model for ESCC was constructed by logistic regression analysis in the training group and validated in the testing group. Results Firstly, thirteen potential candidate TAAbs were identified by proteomic chips. In verification phase, the titers of six TAAbs (anti-MAGEA1, anti-VCL, anti-PRKCZ, anti-TP53, anti-NFKB1 and anti- MAGEA4) in ESCC cases were higher than those in NCs while other seven TAAbs showed no difference. Subsequently, six candidate TAAbs were validated further in validation phase. Finally, the logistic regression model with 3 TAAbs (anti-MAGEA1, anti-VCL, anti-TP53) could discriminate ESCC cases from NCs with area under curve(AUC)of 0.80 in the training group and 0.73 in the testing group, respectively. Meanwhile, the model could discriminate ESCC cases from benign esophageal diseases cases with AUC of 0.74. Conclusion The study has identified six novel TAAbs through protein chips and constructed a diagnostic model. The panel showed great performance to distinguish ESCC cases from benign esophageal diseases cases and NCs.

Circulating Exosomal miRNAs as Novel Biomarkers Perform Superior Diagnostic Efficiency Compared With Plasma miRNAs for Large-Artery Atherosclerosis Stroke

Recently, exosomal miRNAs have been reported to be associated with some diseases, and these miRNAs can be used for diagnosis and treatment. However, diagnostic biomarkers of exosomal miRNAs for ischemic stroke have rarely been studied. In the present study, we aimed to identify exosomal miRNAs that are associated with large-artery atherosclerosis (LAA) stroke, the most common subtype of ischemic stroke; to further verify their diagnostic efficiency; and to obtain promising biomarkers. High-throughput sequencing was performed on samples from 10 subjects. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed on exosomes and plasma in the discovery phase (66 subjects in total) and the validation phase (520 subjects in total). We identified 5 candidate differentially expressed miRNAs (miR-369-3p, miR-493-3p, miR-379-5p, miR-1296-5p, and miR-1277-5p) in the discovery phase according to their biological functions, 4 of which (miR-369-3p, miR-493-3p, miR-379-5p, and miR-1296-5p) were confirmed in the validation phase. These four exosomal miRNAs could be used to distinguish LAA samples from small artery occlusion (SAO) samples, LAA samples from atherosclerosis (AS) samples, and LAA samples from control samples and were superior to plasma miRNAs. In addition, composite biomarkers achieved higher area under the curve (AUC) values than single biomarkers. According to our analysis, the expression levels of exosomal miR-493-3p and miR-1296-5p were negatively correlated with the National Institutes of Health Stroke Scale (NIHSS) score. The four identified exosomal miRNAs are promising biomarkers for the diagnosis of LAA stroke, and their diagnostic efficiency is superior to that of their counterparts in plasma.

Development of a Low-Cost Optical Sensor to Detect Eutrophication in Irrigation Reservoirs

In irrigation ponds, the excess of nutrients can cause eutrophication, a massive growth of microscopic algae. It might cause different problems in the irrigation infrastructure and should be monitored. In this paper, we present a low-cost sensor based on optical absorption in order to determine the concentration of algae in irrigation ponds. The sensor is composed of 5 LEDs with different wavelengths and light-dependent resistances as photoreceptors. Data are gathered for the calibration of the prototype, including two turbidity sources, sediment and algae, including pure samples and mixed samples. Samples were measured at a different concentration from 15 mg/L to 4000 mg/L. Multiple regression models and artificial neural networks, with a training and validation phase, are compared as two alternative methods to classify the tested samples. Our results indicate that using multiple regression models, it is possible to estimate the concentration of alga with an average absolute error of 32.0 mg/L and an average relative error of 11.0%. On the other hand, it is possible to classify up to 100% of the samples in the validation phase with the artificial neural network. Thus, a novel prototype capable of distinguishing turbidity sources and two classification methodologies, which can be adapted to different node features, are proposed for the operation of the developed prototype.

Perancangan Mobile Game sebagai Media Literasi Keuangan untuk Remaja

AbstrakHampir segala aktivitas manusia dipermudah dan dipercepat dengan smartphone, yang tanpa kita sadari telah mengubah perilaku masyarakat dalam berbelanja. Kemudahan transaksi digital telah membuat penggunaan aplikasi belanja daring meningkat. Sayangnya, hal ini masih belum diimbangi dengan pengetahuan dalam mengelola keuangan. Perlu adanya perancangan media untuk mengedukasi masyarakat mengenai pentingnya literasi keuangan. Tujuan dari perancangan ini adalah merancang mobile game untuk menyampaikan pembelajaran tentang keuangan kepada remaja secara efektif untuk menambah dan meningkatkan kesadaran mereka tentang pentingnya manajemen keuangan. Metode Perancangan terdiri dari tahap pengumpulan dan analisis data menggunakan model Miles & Huberman, tahap perancangan konsep, tahap perancangan GDD (Game Design Document), tahap perancangan aset visual, tahap perancangan purwarupa, tahap uji coba dan validasi kelayakan media. Berdasarkan hasil ujicoba dan validasi ahli materi menunjukkan bahawa mobile game ini dikatakan layak. Kata Kunci: game edukasi, literasi keuangan, mobile game, remaja AbstractAlmost all human activities are facilitated and accelerated with the help of smartphones, without us knowing has changed people's shopping behavior. The flexibility of digital transactions has increased the use of shopping applications. Unfortunately, this has not been equal to the knowledge of financial management. A media design is needed to educate the public about the importance of financial literacy. The purpose of this research is to design a mobile game that can convey financial knowledge to teenagers and effectively enhance as well as increase their awareness about the importance of financial management. The design method consists of data collection & analysis using the Miles & Huberman Model, the concept design stage, the GDD (Game Design Document) design stage, the visual asset design stage, the prototyping stage, the testing, and the validation phase. From the testing and the validation phase, the results of the media expert's test got a value of 4.87 (very feasible), the results of the material expert's test got 4.5 (very feasible), and the test results against the intended end-user get a value of 4.68 (very feasible). Keywords: education game, financial literacy, mobile game, teenager

Creative Methodologies: Designing a Framework for Teacher Reflection and Authorship

This research has as its main objective to create, test and improve methodologies and artefacts that help teachers to reflect to transform their practices, making them more creative. Actions are expected that go beyond envisioned planning, but that the teacher is able to concretize, evaluate and continuously improve his/her pedagogical actions. This paper describes the creation of a framework that aims to promote reflection on creative methodologies by teachers, helping them to make explicit the creative movements they already make highlighting their authorial moments, their limits, challenges and difficulties, as well as getting to know new creative possibilities.The data used for the initial construction of this framework was collected in two online courses on Design of Pedagogical Strategies, in which the participating teachers had to describe their teaching practices. From the qualitative analysis of this data, we mapped the challenges and strains in the construction of pedagogical strategies, as well as the fashions and trends that appeared in the discourses. An analysis of formative needs was made and a categorization was created based on a theoretical reflection and critical analysis of the trends presented in the teachers’ data, emphasizing the importance of teachers’ authorial and creative stances in their methodological construction. In this article, we will describe the mapped data, the categorization and the theoretical foundations that supported the construction of this framework. We will also describe the categories and the first validation phase already carried out as well as the next steps for a large-scale application.

Integrating IHACRES with a data-driven model to investigate the possibility of improving monthly flow estimates

Estimating the outflow of basins is a critical step in surface water resources planning and management, especially in basins that lack reliable long-term observed data of streamflow. Hydrological models, which can simulate the process of rainfall-runoff, can be used to obtain reliable estimates of streamflow from precipitation data and the physical characteristics of basins. The focus of the present study was to estimate the outflow of 19 sub-basins located in Guilan Province, northern Iran. To achieve this, hybrid models were developed by integrating the IHACRES (identification of unit hydrograph and component flows from rainfall, evapotranspiration, and streamflow) hydrological model with the intelligent-based GMDH (group method of data handling) model. The IHACRES model was calibrated using monthly ground-based precipitation and temperature data as well as satellite-based precipitation data. The lowest and highest Nash-Sutcliffe coefficient (NS) for the IHACRES models were, respectively, 0.14 and 0.68 in the calibration phase and 0.11 and 0.73 in the validation phase. It was also observed that using satellite-based precipitation data reduces NS by 10–75% in the 19 sub-basins under study. After calibrating and validating the IHACRES models, the hybrid models were developed by integrating IHACRES and GMDH models. The lowest and highest NS for the hybrid models were, respectively, 0.23 and 0.81 in the calibration phase and 0.11 and 0.81 in the validation phase. It was observed that, on average, integrating IHACRES and GMDH increases the NS by 44.1% in the calibration phase and 37.0% in the validation phase in comparison with the IHACRES model. According to the NS, the hybrid model had ‘acceptable’ performance in six sub-basins in which the IHCRES model had ‘unacceptable’ performance. It was observed that integrating the IHACRES model with a data-driven model (the GMDH model) can generally improve the simulation results in all sub-basins under study.

Prognostic Factors of Survival of Advanced Liver Cancer Patients Treated With Palliative Radiotherapy: A Retrospective Study

AimsSurvival benefit of liver cancer patients who undergo palliative radiotherapy varies from person to person. The present study aims to identify indicators of survival of advanced liver cancer patients receiving palliative radiotherapy.Patients and MethodsOne hundred and fifty-nine patients treated with palliative radiotherapy for advanced liver cancer were retrospectively assessed. Of the 159 patients, 103 patients were included for prediction model construction in training phase, while other 56 patients were analyzed for external validation in validation phase. In model training phase, clinical characteristics of included patients were evaluated by Kaplan-Meier curves and log-rank test. Thereafter, multivariable Cox analysis was taken to further identify characteristics with potential for prediction. In validation phase, a separate dataset including 56 patients was used for external validation. Harrell’s C-index and calibration curve were used for model evaluation. Nomograms were plotted based on the model of multivariable Cox analysis.ResultsThirty-one characteristics of patients were investigated in model training phase. Based on the results of Kaplan-Meier plots and log-rank tests, 6 factors were considered statistically significant. On multivariable Cox regression analysis, bone metastasis (HR = 1.781, P = 0.026), portal vein tumor thrombus (HR = 2.078, P = 0.015), alpha-fetoprotein (HR = 2.098, P = 0.007), and radiation dose (HR = 0.535, P = 0.023) show significant potential to predict the survival of advanced liver cancer patients treated with palliative radiotherapy. Moreover, nomograms predicting median overall survival, 1- and 2-year survival probability were plotted. The Harrell’s C-index of the predictive model is 0.709(95%CI, 0.649-0.769) and 0.735 (95%CI, 0.666-0.804) for training model and validation model respectively. Calibration curves of the 1- and 2-year overall survival of the predictive model indicate that the predicted probabilities of OS are very close to the actual observed outcomes both in training and validation phase.ConclusionBone metastasis, portal vein tumor thrombus, alpha-fetoprotein and radiation dose are independent prognostic factors for the survival of advanced liver cancer patients treated with palliative radiotherapy.

ICT-Based Learning Media in the Form of Powerpoint for Grade IV Elementary School Students

The learning process was still not carried out effectively due to the lack of learning facilities. In addition, teachers only use lecture methods in providing materials. This causes students to get tired of learning. This research aimed to develop ICT-based learning media for grade IV elementary school students. This type of research was research development using ADDIE procedure. Product trial subjects numbered six experts. The methods used in collecting data were interviews, documentation and questionnaires. The instrument used in this study was a questionnaire with a Likert scale. The data analysis techniques in this study were qualitative descriptive analysis and quantitative descriptive analysis methods. The results of the study, namely learning media 3 in validation phase 1, obtained an average score of 83% and in the validation of stage 2 obtained results of 89%. This can be said in the learning media for learning three increased by 6%. Furthermore, in learning media 3 for the validation phase, 1 obtained an average score of 84% and in validation stage 2 got 92%. This can be said in the learning media for learning 4 increased by 8%. Then, for learning media 5 in validation phase 1, an average score of 83% and in the validation phase 2 obtained 92%. This can be said that the learning media for learning 5 had also increased by 9%. This shows ICT-based learning media in the form of powerpoints worthy of being applied to the learning process. This research implied that teachers could use the media developed by PowerPoint to help students with learning difficulties.

The Ockham’s razor for estimating the needs of ICU beds during a pandemic

Background It is possible to monitor an epidemic evolution by plotting the number of patients, or its log-transform, as a function of time. However, these representations do not allow quick identifications of significant changes in the outbreak; a key information for estimating the needs for hospital and ICU beds, for decision-making, and resource allocation. Moreover, an epidemic is characterised by a heterogeneous evolution that depends on many unpredictable factors, coming from the virus itself or from its ecosystem. Simulations are very complex and based on hypotheses that are impossible to certify a priori, since each outbreak is different and has specific characteristics. A validation phase is necessary that may delay the usefulness of these tools. We tested a simpler method for monitoring the epidemic and rapidly predicting the peak. Results We present here a simple and easy-to-draw figure by plotting the daily rate of change in the number of patients as a function of time. This allows: (1) to rapidly identify the changes in the infection growth, (2) to extrapolate the regression lines for predicting the peaks, and (3) to use simple statistical models for identifying the significant inflexions and deriving the uncertainties. This figure predicted confidently the peak epidemic of the three waves in France. Conclusion Plotting the daily rate of change in the number of patients as a function of time is a simple tool for monitoring an epidemic growth, allowing to quickly identify significant changes and to help in predicting the peak of the infection, with its confidence interval.

Diagnostic utility of a novel magnifying endoscopic classification system for superficial Barrett’s esophagus-related neoplasms: a nationwide multicenter study

Background Currently, no classification system using magnification endoscopy for the diagnosis of superficial Barrett’s esophagus (BE)-related neoplasia has been widely accepted. This nationwide multicenter study aimed to validate the diagnostic accuracy and reproducibility of the magnification endoscopy classification system, including the diagnostic flowchart developed by the Japan Esophageal Society—Barrett’s esophagus working group (JES-BE) for superficial Barrett’s esophagus-related neoplasms. Methods The JES-BE acquired high-definition magnification narrow-band imaging (HM-NBI) images of non-dysplastic and dysplastic BE from 10 domestic institutions. A total of 186 high-quality HM-NBI images were selected. Thirty images were used for the training phase and 156 for the validation (test) phase. We invited five non-experts and five expert reviewers. In the training phase, the reviewers discussed how to correctly predict the histology based on the JES-BE criteria. In the validation phase, they evaluated whether the criteria accurately predicted the histology results according to the diagnostic flowchart. The validation phase was performed immediately after the training phase and at 6 weeks thereafter. Results The sensitivity and specificity for all reviewers were 87% and 97%, respectively. Overall accuracy, positive predictive value, and negative predictive value were 91%, 98%, and 83%, respectively. The overall strength of inter-observer and intra-observer agreements for dysplastic histology prediction was κ = 0.77 and κ = 0.83, respectively. No significant difference in diagnostic accuracy and reproducibility between experts and non-experts was found. Conclusion The JES-BE classification system, including the diagnostic flowchart for predicting dysplastic BE, is acceptable and reliable, regardless of the clinician’s experience level.