Radiogenomic Analysis of Papillary Thyroid Carcinoma for Prediction of Cervical Lymph Node Metastasis: A Preliminary Study

BackgroundPapillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors.MethodsIn total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis.ResultsThe radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with ‘Rectlike’ and ‘deviation ratio of tumor tissue and normal thyroid gland’ which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature ‘minimum calcification area’ which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature ‘Rectlike’ and ‘deviation ratio of tumor and normal thyroid gland’ (p<0.001; p<0.001); THBS1 was correlated with ‘minimum calcification area’ (p<0.001).ConclusionsThe radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management.

A Comprehensive Evaluation of Surface Air Temperature Reanalyses over China against Urbanization Bias–Adjusted Observations

The goal of this study is to compare the differences in surface air temperature (SAT) between observational and reanalysis data in mainland China from 1961–2015 for evaluating the reliability and applicability of the reanalysis datasets, based on an observational dataset of 763 stations which has been adjusted for urbanization bias, and 8 reanalysis datasets. The time series, anomaly correlations, standard deviations, climate state, and linear trends of the reanalysis data are evaluated against the observations. The reanalysis data are consistent with the observational climate characteristics to a large extent. The correlation and standard deviation ratio between the reanalysis data and observations exhibited highly consistent inter–annual variability and dispersion, with the inter–annual SAT variability of JRA55 and ERA5 the closest to the observations for the periods 1961–2015 and 1979–2015, and the dispersions of 20CRV3 and NCEPV1 the most consistent with the observations for the two periods. The annual mean SAT of the reanalyses is generally 0–2.0°C lower than the observations, while the linear trends of all datasets exhibited clear warming. The biases in the SAT climatology of 20CRV3 and CRA40 are lower than other reanalysis datasets, and the linear trends of NCEPV1 and 20CRV3 are closer to the observations. With increasing elevation, the biases of the reanalysis data in terms of correlation, standard deviation, climate state, and linear trend all increased. Overall, in terms of the similarity of multiple measures to the urbanization bias–adjusted observations, CRA40 and JRA55 show the best performance of the products in reproducing various aspects of climatological and climate change features in mainland China for the period 1979–2015 and 1961–2015 respectively.

Avaliações de Funções de Pedotransferência para Solos Brasileiros

Pedotransfer Functions (FPT) are mathematical models that estimate difficult-to-measure soil properties through more accessible variables, generating optimization of time and financial resources. In this study, six Pedotransfer Functions, based on the equation of Van Genuchten, analyzed for the prediction of volumetric moisture of Brazilian soils, with data from the global database Soil Data Task. Applied for pressures of 0, 0.01, 0.03, 0.10, 0.20, 0.50, 2.50 and 15.0 bar, the resulting values of the equations were compared with the measured volumetric moistures through five statistical parameters: confidence index, mean square error, deviation ratio, modeling efficiency and residual mass coefficient. Of the functions studied it was possible to verify that the FPT proposed by Barros, with 4 parameters, was the one that presented the best results, while that of Rawls and Brakensied obtained the lowest performance. It has been observed that the efficiency of a FPT is related to two factors: a) similarity between the pedological data of the soil studied and those used in the development of the FPT, and b) the amount of variables analyzed.

Assessment of the streamflow changes in the La Nga river basin

The paper aims to assess the changes of the streamflow under the impact of irrigation constructions in La Nga river basin using the Long and Short term runoff (LST) model. The LST model was calibrated and validated for the period of 1987–1995 and 1996–1999, respectively, to simulate the natural streamflow for the post–construction phase. Statistical metrics, including R2 coefficients, efficiency coefficients (NSE), percent error (PBIAS) and standard monitoring deviation ratio (RSR) were used to evaluate the model performance. The results showed that, LST model performed well in the flow simulation by the high values of R2 and NSE index greater than 0.80, RSR smaller than 0.50 and PBIAS lower than 7.22%. The comparison between the simulated (natural) and observed flows illustrated that there were changes of the flow regime in the post–construction phase. The average seasonal flow decreases 24.59% and increased 12.06% in the wet and dry season, respectively at Phu Dien station. Meanwhile, at Ta Pao station, the streamflow decreased 8.35% and increased 21.11% in the wet and dry season, respectively. The results of this study could be used in planning, managing and regulating the irrigation works'operation, and water resources management in the La Nga river basin.

Village Grouping In Southwest Maluku District Based On Poverty Characteristics Using Self Organizing Maps (SOM) Methods

Poverty is one of the fundamental problems that has become the center of attention of the Maluku Provincial government, especially Southwest Maluku Regency. This study aims to provide information to the government about village grouping based on poverty characteristics in Southwest Maluku Regency using the Self Organizing Map network method. In this network, a layer containing neurons will arrange itself based on the input of a certain value in a group known as a cluster. In the grouping process, 3 results were obtained with the best grouping II results because they had the smallest standard deviation ratio value.

Pengelompokkan Kabupaten/Kota Di Sulawesi Berdasarkan Indikator Pendidikan Menggunakan Analisis Klaster Average Linkage Dan Median Linkage

Cluster analysis is included in the method of multivariate analysis of interdependence. Cluster analysis is a multivariate technique that classifies objects into different groups between one group and another group. This research is applied to the case of education indicators, education is important for improving the quality of human resources. Educational indicators are a measuring tool used to see how well the quality of education. Educational indicators are classified using average linkage and median linkage. The results of the analysis showed that the median linkage obtained a standard deviation ratio value of 0.061 smaller than the standard deviation ratio average linkage value of 0.078. The method that has the smallest ratio is the method with the best performance. So that grouping City Districts in Sulawesi based on education indicators in 2017 is better to use the median linkage and obtained 5 clusters formed.

EFFECT OF EARTHQUAKE LOAD ON THE STRUCTURE OF THE HIGHWAY BRIDGE WITH I-GIRDER PRESTRESSED CONCRETE IN THE EVENT OF INACCURACIES IN PRESTRESSING LOSS PREDICTIONS

In planning a highway bridge girder using prestressed concrete, it must pay attention to two design categories, namely strength and service. Problems have arisen since the existence of earthquake resistance regulations for road bridges, so planners must calculate the amount of deflection and stress that occurs in the upper structure due to earthquake loads, which must be smaller than the deflection and voltage permits required by regulations. All of that was also greatly influenced by the accuracy of the predicted loss losses for prestressed concrete girders. The purpose of this study was to conduct a study which could be a solution for how to actually treat a good design, for the I-Girder design of prestressed concrete used as a highway bridge girder in the event of inaccurate prediction of loss of pressure during an earthquake, resulting in two design categories strength and service ability can be considered all well. The methodology of this study is to make as a starting point the prestressed concrete I girder whose dimensions are capable of being a highway bridge girder with a span of 30 m to 40 meters with standard loading for loading BM 100. For span bridges that have 100% prediction accuracy, use as a basic benchmark of deflection and stress values that occur for the type of combination of loads that have earthquake loads, then with the same span, varied values of inaccurate predictions lose pre-stress and analyzed deflection and stress values that occur for types of load combinations that have earthquake loads varied earthquake regions 1,2, 3 and 4, for medium soil types. The results of the study show that the greater the percentage of inaccurate prediction of loss of pressure, the greater the deviation ratio of deviations both deflection, upper fiber stress and lower fiber stress occur in the field. Which, if the prediction of losing pre-pressures is smaller than the actual one, then the level of the deviation ratio of the allowable deviation increases as well as vice versa. Also, predicting pre-suppression voltage loss that is located on the side greater than the actual loss of pressure that occurs will be on the part of the party that is harmful to the ability of service and the permissible power, when an earthquake occurs.

Pengklasteran Kabupaten/Kota di Jawa Tengah berdasarkan Tenaga Kesehatan dengan Menggunakan Metode Ward dan K-Means

Analisis klaster merupakan suatu metode yang digunakan untuk mengelompokkan objek (kasus) ke dalam klaster (kelompok) yang relatif sama. Tujuan penelitian ini untuk mengklasterkan Kabupaten/Kota di Provinsi Jawa Tengah berdasarkan tenaga kesehatan tahun 2015 seperti tenaga medis, tenaga keperawatan, tenaga kebidanan, tenaga kefarmasian dan tenaga kesehatan lainnya dengan menggunakan metode Ward dan K-Means. Hasil penelitian menunjukkan ada tiga klaster terbentuk dimana metode Ward menghasilkan nilai rasio simpangan baku sebesar 0,3019% lebih besar jika dibandingkan dengan nilai rasio simpangan baku pada metode K-Means yaitu 0,2974%. Pada kasus ini, metode K-Means merupakan metode yang lebih baik dibandingkan metode Ward. [Cluster analysis is a method used to group objects (cases) into clusters (groups) that are relatively the same. The purpose of this study is to classify districts/cities in Central Java Province based on health worker in 2015 such as medical personnel, nursing staff, midwifery staff, pharmacy personnel and health workers using the Ward and K-Means methods. The results show that there are three clusters formed where the Ward method produce a standard deviation ratio of 0.3019% greater than the standard deviation ratio in the K-Means method, which is 0.2974%. In this case, the K-Means method is a better method than the Ward method.]