Absolute Value Of Correlation Coefficient Research Articles

Accuracy of Automatic Processing of Speech-Language Pathologist and Child Talk During School-Based Therapy Sessions.

This study examines the accuracy of Interaction Detection in Early Childhood Settings (IDEAS), a program that automatically transcribes audio files and estimates linguistic units relevant to speech-language therapy, including part-of-speech units that represent features of language complexity, such as adjectives and coordinating conjunctions. Forty-five video-recorded speech-language therapy sessions involving 27 speech-language pathologists (SLPs) and 56 children were used. The F measure determines the accuracy of IDEAS diarization (i.e., speech segmentation and speaker classification). Two additional evaluation metrics, namely, median absolute relative error and correlation, indicate the accuracy of IDEAS for the estimation of linguistic units as compared with two conditions, namely, Oracle (manual diarization) and Voice Type Classifier (existing diarizer with acceptable accuracy). The high F measure for SLP talk data suggests high accuracy of IDEAS diarization for SLP talk but less so for child talk. These differences are reflected in the accuracy of IDEAS linguistic unit estimates. IDEAS median absolute relative error and correlation values for nine of the 10 SLP linguistic unit estimates meet the accuracy criteria, but none of the child linguistic unit estimates meet these criteria. The type of linguistic units also affects IDEAS accuracy. IDEAS was tailored to educational settings to automatically convert audio recordings into text and to provide linguistic unit estimates in speech-language therapy sessions and classroom settings. Although not perfect, IDEAS is reliable in automatically capturing and returning linguistic units, especially in SLP talk, that are relevant in research and practice. The tool offers a way to automatically measure SLP talk in clinical settings, which will support research seeking to understand how SLP talk influences children's language growth.

Topographical characterization and permeability correlation of steel fiber reinforced concrete surface under freeze-thaw cycles and NaCl solution immersion

This study investigates the relationship between the surface topography of steel fiber reinforced concrete (SFRC) and both the freeze-thaw damage and permeability of the concrete matrix subjected to freeze-thaw cycles and immersion in a sodium chloride solution. Rapid freeze-thaw tests were conducted on concrete immersed in NaCl solution to introduce freeze-thaw damage. A custom-developed 3D laser-scanning device was employed to capture the surface topography information of concrete subjected to freeze-thaw cycles. Multivariate analysis was utilized to determine the suitable parameter for evaluating the roughness of the concrete surface. A correlation analysis was carried out between the surface topography of concrete and the freeze-thaw damage parameters, including mass loss (ΔWn), relative dynamic modulus of elasticity (RDME), and ultrasonic pulse velocity (Uv). A custom-designed vacuum permeability device was used to measure the permeability of concrete matrix. The relationship between the surface topography and permeability of concrete subjected to freeze-thaw damage is studied. The results show that the steel fibers significantly reduce the freeze-thaw damage and surface roughness of concrete subjected to freeze-thaw damage in the sodium chloride solution. Roughness number (RN) is the most representative parameter for evaluating the topographical characterization of concrete surface and can be used to quantify the surface topography of concrete exposed to freeze-thaw cycles. The absolute values of correlation coefficient between RN and its ΔWn, RDME, and Uv reach up to 0.89, which suggests that RN can indirectly evaluate the freeze-thaw damage of concrete. Furthermore, there exists a logarithmic relationship between RN and the permeability of the concrete matrix, with the correlation coefficient R2 exceeding 0.86. This relationship can be utilized to quickly estimate its permeability based on the surface roughness of SFRC exposed in cold coastal regions.

Ability Estimation with Polytomous Items in Computerized Multistage Tests

The aim of the study is to examine how the ability estimations of individuals change under different conditions in tests consisting of polytomous items in an computerized multistage test environment. The research is a simulation study. In the study, 108 (3x3x6x2=108) conditions were examined consisting of three categories (3, 4 and 5), three test lengths (10, 20 and 30), six panel designs (1-2, 1-2-2, 1-3, 1-3-3, 1-4 and 1-4-4) and two routing methods (Maximum Fisher Information (MFI) and Random). Simulations and analyses were carried out in the mstR package in R program, with a pool of 200 items, 1000 people and 100 replications (e.g., iterations). As the outcomes of the research, mean absolute bias, RMSE and correlation values were calculated. It was found that as the number of categories and test length increase, the mean absolute bias and RMSE values decrease, while the correlation values increase. In terms of routing methods, although MFI and random methods have similar tendencies, MFI gives better results. There is a similarity between the panel designs in terms of results.

Effect of simultaneous application of antioxidants in oil and in chicken on heterocyclic aromatic amine formation in deep-fat fried chicken breast

This study aimed to estimate the effects of simultaneous application of antioxidants in meat and in oil on heterocyclic aromatic amine (HAA) formation in fried chicken during 40 deep-fat frying cycles. The experiment was carried out by adding Adinandra nitida leaf extract (ANE) (200 mg/100 g) to chicken while adding tea polyphenols (TP) (40 mg/100 g), sesamol (SL) (40 mg/100 g), or rosemary extract (RE) (40 mg/100 g) to soybean oil. It was found that the addition of TP, SL or RE in oil reduced the lipid oxidation and the formation of total HAAs in meats. Adding ANE alone to meat reduced total HAA contents in meats by 11.98%–38.00%; simultaneously adding TP, SL or RE to oil reduced total HAA contents in meats by 33.98%–61.46%, 15.86%–44.94%, and 25.22%–48.01%, respectively, during 40 frying cycles. Pearson correlation analysis revealed significant correlations (all absolute values of correlation coefficients > 0.53) between HAA formation and oxidation indices. This research supplies evidence that adding antioxidants to both meat and oil inhibits HAA formation during deep-fat frying.

Improved multivariate modeling for soil organic matter content estimation using hyperspectral indexes and characteristic bands.

Soil organic matter (SOM) is a key index of soil fertility. Calculating spectral index and screening characteristic band reduce redundancy information of hyperspectral data, and improve the accuracy of SOM prediction. This study aimed to compare the improvement of model accuracy by spectral index and characteristic band. This study collected 178 samples of topsoil (0-20 cm) in the central plain of Jiangsu, East China. Firstly, visible and near-infrared (VNIR, 350-2500 nm) reflectance spectra were measured using ASD FieldSpec 4 Std-Res spectral radiometer in the laboratory, and inverse-log reflectance (LR), continuum removal (CR), first-order derivative reflectance (FDR) were applied to transform the original reflectance (R). Secondly, optimal spectral indexes (including deviation of arch, difference index, ratio index, and normalized difference index) were calculated from each type of VNIR spectra. Characteristic bands were selected from each type of spectra by the competitive adaptive reweighted sampling (CARS) algorithm, respectively. Thirdly, SOM prediction models were established based on random forest (RF), support vector regression (SVR), deep neural networks (DNN) and partial least squares regression (PLSR) methods using optimal spectral indexes, denoted here as SI-based models. Meanwhile, SOM prediction models were established using characteristic wavelengths, denoted here as CARS-based models. Finally, this research compared and assessed accuracy of SI-based models and CARS-based models, and selected optimal model. Results showed: (1) The correlation between optimal spectral indexes and SOM was enhanced, with absolute value of correlation coefficient between 0.66 and 0.83. The SI-based models predicted SOM content accurately, with the coefficient of determination (R2) and root mean square error (RMSE) values ranging from 0.80 to 0.87, 2.40 g/kg to 2.88 g/kg in validation sets, and relative percent deviation (RPD) value between 2.14 and 2.52. (2) The accuracy of CARS-based models differed with models and spectral transformations. For all spectral transformations, PLSR and SVR combined with CARS displayed the best prediction (R2 and RMSE values ranged from 0.87 to 0.92, 1.91 g/kg to 2.56 g/kg in validation sets, and RPD value ranged from 2.41 to 3.23). For FDR and CR spectra, DNN and RF models achieved more accuracy (R2 and RMSE values ranged from 0.69 to 0.91, 1.90 g/kg to 3.57 g/kg in validation sets, and RPD value ranged from 1.73 to 3.25) than LR and R spectra (R2 and RMSE values from 0.20 to 0.35, 5.08 g/kg to 6.44 g/kg in validation sets, and RPD value ranged from 0.96 to 1.21). (3) Overall, the accuracy of SI-based models was slightly lower than that of CARS-based models. But spectral index had a good adaptability to the models, and each SI-based model displayed the similar accuracy. For different spectra, the accuracy of CARS-based model differed from modeling methods. (4) The optimal CARS-based model was model CARS-CR-SVR (R2 and RMSE: 0.92 and 1.91 g/kg in validation set, RPD: 3.23). The optimal SI-based model was model SI3-SVR (R2 and RMSE: 0.87 and 2.40 g/kg in validation set, RPD: 2.57) and model SI-SVR (R2 and RMSE: 0.84 and 2.63 g/kg in validation set, RPD: 2.35).

Characteristics of spring maize sap flow and its environmental influencing factors in typical mollisol area.

Clarifying the variations of sap flow rate of spring maize in the typical mollisol area and its main control factors is of great significance to explore water consumption from transpiration and regulate field water management. In this study, we installed the wrapped sap flow sensors and TDR probes to continuously monitor the sap flow rate of spring maize during filling-maturity stage and soil water and heat conditions of topsoil. In combination with meteorological data collecting from a nearby automatic weather station, we analyzed the correlation between the sap flow rate of spring maize and environmental factors at different time scales. The results showed that the sap flow rate of spring maize in typical mollisol area had an obvious fluctuation of high diurnal and low nighttime. The instantaneous sap flow rate peaked at daytime, with a value of 139.9 g·h-1, but being weak at nighttime. The starting time, closing time, and peak values of spring maize sap flow were significantly inhibited in cloudy and rainy days, compared with that in sunny days. On hourly scale, the sap flow rate was significantly correlated to solar radiation, saturated vapor pressure deficit (VPD), relative humidity, air temperature, and wind speed. On daily scale, only solar radiation, VPD, and relative humidity were significantly correlated with sap flow rate, with the absolute values of correlation coefficient being all above 0.7. Due to high soil water content during the observation period, the sap flow rate was not significantly correlated with soil water content and soil temperature of 0-20 cm layer, with the absolute values of correlation coefficient being less than 0.1. Under the condition without water stress, solar radiation, VPD, and relative humidity were the top three influencing factors of sap flow rate in this region, on both hourly scale and daily scale.

National Economic Conditions May Impact the Financial Barriers to Travel for Cancer Operations.

Better cancer-related outcomes are associated with physicians and hospitals with higher case volume. This serves as an incentive to refer patients requiring complex cancer operations to large referral centers, which may require increased travel for patients. However, barriers exist for patients to travel for cancer care, some of which may be aggravated or alleviated by factors relating to the health of the national economy. This impact may be reflected in variability of travel distances for cancer operations over time particularly for complex operation such as pancreatectomy and esophagectomy compared with less complex resections such as those for breast cancer or melanoma. We obtained the estimated travel distance for patients undergoing operations for cancer of the pancreas, esophagus, skin (melanoma), and breast from the National Cancer Database from 2004 to 2017 and correlated them with economic factors obtained from public sources. We then examined the impact of unemployment rates, gas prices, and inflation on travel distances regarding disadvantaged groups. Correlations were measured by the (rank-based, nonparametric) Spearman's correlation coefficient, and the corresponding P value is obtained by the asymptotic distribution of the coefficient. A P value of 0.05 equates to an absolute correlation value of 0.532. To adjust for multiple tests, a more restrictive P value of 0.01 was also assessed, which equates to correlation coefficients of absolute value greater than 0.661. There were 4,222,380 cases in the dataset, of which 1,781,056 remained after exclusion. The economic factors that were associated most strongly with the distance patients traveled for all cancer operation types were the labor force participation rate, personal savings, consumer price index, and changes in gasoline prices. Inflation and rising gasoline prices were often inversely related with travel distance in lower-income and less well-educated regions and African American patients. Several macroeconomic factors correlate with the travel distance for operations, suggesting that the economic health of the nation may aggravate or alleviate the financial barriers to travel for cancer operations. Financially disadvantaged groups may be particularly vulnerable to changes in gasoline prices and inflation. Organizations serving these populations may need to increase patient support services during times of economic hardship to avoid the exacerbation of health care disparities.

Assessment of black rot development on apple surface using laser biospeckle technique

In our present study, the laser biospeckle technique has been applied to monitor the spread of black rot fungal disease and evaluate the infected area on apple surface for the first time to the best of our knowledge. Image processing algorithms such as inertia moment (IM), absolute value of differences (AVD) and spatial-temporal speckle correlation show the reduction of biospeckle activity of the black rot infected apples in comparison to that of the healthy apples with increase in time, once the visible symptom of the disease sets in. Spectral activity maps obtained using Fujii, inverse Fujii and parameterized Fujii show the spread of this infection with the progression of day. Under exposition test and histogram plot have been used to evaluate the increase of darkness of the infected apple with the progression of day and the results have come out as a replica of the change of colour of the region of interest. % biospeckle activity loss on the final day of the experiment has been found to be 17.83% and 11.91% for healthy apples & 92.42% and 78.63% for infected apples using IM and AVD respectively. An increase in the infected area and % increase in infected area of the region of interest on the image plane has been determined to be 0.33 mm2 and 58.57% respectively on the final day of the experiment.

Majorana correlations in quantum impurities coupled to a topological wire

In this paper, we investigate Majorana correlations in quantum impurities coupled to a topological superconducting wire. By employing a density matrix renormalization group approach, we have calculated the Majorana correlation functions in the ground state of the system for different positions of the impurities along the wire. We observe that the correlations decrease exponentially with the distance between the impurities and the ends of the wire. Moreover, different electron-electron interactions on the wire and on the impurities were also analyzed, and the results showed a stronger effect as the electron occupation in the wire is increased. In addition, while changing the occupation of the impurities by tuning their energy levels, we observe that, for specific values of $\ensuremath{\varepsilon}$, the absolute value of correlation is highly peaked when the chemical potential lies within the window of the topological regime. These peaks are associated with Coulomb blockade phenomena in the impurities, revealing very clearly its effect on the Majorana bound states in the topological phase of the system.

Practical Attacks on Full-round FRIET

FRIET is a duplex-based authenticated encryption scheme proposed at EUROCRYPT 2020. It follows a novel design approach for built-in countermeasures against fault attacks. By a judicious choice of components, the designers propose the permutation FRIET-PC that can be used to build an authenticated encryption cipher denoted as FRIET-AE. And FRIET-AE provides a 128-bit security claim for integrity and confidentiality. In this paper, we research the propagation of pairs of differences and liner masks through the round function of FRIET-PC. For the full-round FRIET-PC, we can construct a differential distinguisher whose probability is 1 and a linear distinguisher whose absolute value of correlation is 1. Moreover, we use the differential distinguisher with probability 1 to construct a set consisting of valid tags and ciphertexts which are not created by legal users. This breaks FRIET-AE’s security claim for integrity and confidentiality. As far as we know, this is the first practical attack that threatens the security of FRIET-AE.

Estimating bloodstain formation time by quantitative analysis of mtDNA degradation

The estimation of bloodstain formation time is still an unsolved problem in forensic science and lacks accurate quantitative methods. Whether DNA can be adopted to estimate bloodstain formation time is still controversial, and there is no study to confirm the potential of mtDNA markers. To address these issues, a triple quantification method based on the ratio of mtDNA fragments of different lengths of COⅠ (mitochondrially encoded cytochrome c oxidase Ⅰ) for estimating bloodstain formation time was established. A total of 152 samples (140 old samples, 12 fresh samples) were collected and tested, and the absolute copies of different-sized fragments of COⅠ (304 bp, 120 bp, 41 bp) in all samples were quantified by SYBR Green real-time qPCR. The natural logarithms of two copy number ratios (304 bp/41 bp, 120 bp/41 bp) of COⅠ in old samples were calculated, which were used as degradation indexes to evaluate the degradation degree of mtDNA. The 140 old human blood samples from 1 to 14 years of storage were accumulated from casework of forensic practice to establish the method of estimating bloodstain formation time and used to analyze the impact of gender factors on the two degradation indexes, and 10 animal samples and 2 fresh human samples were collected to verify the human specificity of the method. There was a high correlation between degradation indexes and bloodstain formation time (the absolute values of correlation coefficients of these two degradation indexes were 0.901 and 0.758 respectively). A method with triple quantification and dual indexes estimating bloodstain formation timewas successfully established, which was highly human-specific. There was no statistically significant difference in degradation indexes between different gender samples (P > 0.05). This study confirmed that mtDNA can be utilized to estimate bloodstain formation time, which provides a new solution to the forensic problem of estimating the time of bloodstain formation.

A New Crack Detection Method Based on the Correlation Analysis of Frequency Response Function Curvature Differentiation (FRFCD)

Structural inherent dynamic characteristics would change when damage occurs, and this fact is the theoretical basis of damage detection method based on vibration features. As one of structural inherent properties, frequency response function (FRF) contains rich information and has more potential in damage detection. On the basis of crack detection researches, a new method based on the change of FRF is proposed in this paper. First, the single-degree-of-freedom (SDOF) system is used to illustrated the change of dynamic features caused by cracks represented by changing stiffness, and it is found that the change of stiffness leads to the obvious nonlinear variation of frequency response function curvature (FRFC) and frequency response function curvature differentiation (FRFCD) near the natural frequency. To describe this phenomenon, the Pearson correlation coefficient is employed to analyze correlation relationship of FRF, FRFC and FRFCD between the undamaged and the damaged system. The results demonstrate that absolute values of these coefficients approach from 1 to 0 with the increase of stiffness change. The rail with cracks is taken as the research object, and relationships between the crack size and the correlation coefficients of FRF, FRFC and FRFCD are investigated through the combination of finite element simulation and frequency response experiment. The correlation coefficients of FRF, FRFC and FRFCD are close to 1 when the structure is intact. When cracks occur, the absolute value of the correlation coefficient will gradually trend from 1 to 0, and the sensitivity of FRFCD correlation coefficient to crack is much higher than that of FRF and FRFC. The selection of calculated frequency bands containing different modes and the damping of the structure would affect the absolute value of FRFCD correlation coefficient, but will not change the characteristics of high sensitivity of FRFCD and the relationship between the coefficient and crack size. Besides, noise signals would enhance the nonlinear relationship between responses of intact structure and the structure with cracks, and the FRFCD correlation coefficient value is influenced accordingly.

Analysis of Key Control Points of Microbial Contamination Risk in Pork Production Processes Using a Quantitative Exposure Assessment Model.

Pork is one of the most common foods causing microbial foodborne diseases. Since pork directly enters the market after slaughtering, the control of microbial contamination in the slaughtering processes is the key to ensuring the quality and safety of pork. The contamination level of Escherichia coli, a health-indicator bacterium, can reflect the risk level of potential pathogens. In order to assess the E. coli exposure risk of pork during slaughtering and to identify the key control points, we established an E. coli quantitative exposure assessment model for swine-slaughtering processes in slaughterhouses of different sizes. The model simulation data indicated the E. coli contamination pattern on the surfaces of swine carcasses during slaughtering. The changes in E. coli contamination were analyzed according to the simulation data of each slaughtering process. It was found that the number of E. coli after trimming in big and small slaughterhouses increased to the maximum values for the whole processes, which were 3.63 and 3.52 log10 CFU/100 cm2, respectively. The risk contribution of each slaughtering process to the E. coli contamination on the surface of terminal swine carcasses can be determined by correlation analysis. Because the absolute value of correlation coefficient during the trimming process was maximum (0.49), it was regarded as the most important key control point. This result can be further proved via the multilocus sequence typing of E. coli. The dominant sequence type before trimming processes was ST10. ST1434 began to appear in the trimming process and then became the dominant sequence type in the trimming and pre-cooling processes. The model can provide a theoretical basis for microbial hygiene supervision and risk control in swine-slaughtering processes.

Validation of the Chinese Version of the Stigma Scale of Epilepsy.

PurposeThis study was carried out to test the validity and reliability of the Chinese version of the Stigma Scale of Epilepsy (SSE), with aim to better understand the public stigmatizing attitudes of epilepsy in China and help elucidate stigma determinants for interventions.MethodsThe SSE was translated into Simplified Chinese Mandarin. In this study, most of the participants were enrolled via convenience sampling by randomly distributing questionnaires on the streets and parts of the participants were recruited by an online platform named Wenjuanxing. We assessed the psychometric properties of the SSE in 310 Chinese native-speaker. Cronbach's alpha was tested for reliability. Index of Content Validity (CVI) was calculated. Exploratory and confirmatory analysis were used to explore the factor structure and verify the validity of SSE.ResultsThe Cronbach's alpha is 0.936 for the overall scale, and the CVI value is greater than 0.78. The exploratory factor analysis (EFA) extracted SSE six factors: the fear of seizure attacks (factor 1), sympathy for patients with epilepsy (PWEs) (factor 2); difficulties faced by PWEs (factor 3); speculation on PWEs' feeling (factor 4); discrimination against PWEs (factor 5); and knowledge about epilepsy (factor 6). The item 13 was proven to be problematic and has been eliminated. The confirmatory factor analysis (CFA) ensured the great construct validity (χ2/SD = 1.725, goodness of fit index (GFI) = 0.916, and root mean square error of approximation (RMSEA) = 0.048), convergent validity (the factor loads of each item corresponding to each latent variable >0.6, average variance extracted (AVE) > 0.5, and composite reliability (CR) > 0.7), and discrimination validity (all of the absolute value of correlation coefficient are <0.5,and less than the square root of AVE) of the SSE.ConclusionsThe Chinese version of the SSE scale was a valid and reliable tool to measure epilepsy-associated stigma in the Chinese society.

Pavement Texture-Friction Relationship Establishment via Image Analysis Methods.

Pavement surface texture is one of the prevailing factors for friction realization on pavement surfaces. In this paper, an overview of pavement texture properties related to the pavement frictional response is given. Image analysis methods used for pavement texture characterization are thoroughly analyzed together with their potential for the establishment of a pavement texture–friction relationship. Digital pavement surface models derived from photogrammetry or laser scanning methods enable the extraction of texture parameters comparable to the ones acquired by common pavement surface measuring techniques. This paper shows the results of a preliminary small-scale research study of the pavement texture–friction relationship. This research was performed in a laboratory which produced asphalt samples, primarily to analyze the potential of developing a methodology for the digital pavement texture model setup. Furthermore, the relationship between selected 2D texture parameters calculated from the digital texture model and measured friction coefficient expressed as SRT value was analyzed. A significant correlation was established for standard texture indicator mean profile depth (MPD) and SRT values (R = 0.81). Other texture parameters showed moderate correlation with the frictional response of the surface, with absolute values of correlation coefficients varying from 0.7 to 0.75. A further analysis of this relationship will be performed by inclusion of other texture parameters that can be determined from the digital texture model acquired by the established methodology.

Two Correlations with Enhancement Near the Proton Gyroradius Scale in Solar Wind Turbulence: Parker Solar Probe (PSP) and Wind Observations

Abstract Based on the Parker Solar Probe mission, this paper presents the observations of two correlations in solar wind turbulence near the Sun for the first time, demonstrating the clear existence of the following two correlations. One is positive correlation between the proton temperature and turbulent magnetic energy density. The other is negative correlation between the spectral index and magnetic helicity. It is found that the former correlation has a maximum correlation coefficient (CC) at the wavenumber k ρ p ≃ 0.5 (ρ p being the proton thermal gyroradius), and the latter correlation has a maximum absolute value of CC at k ρ p ≃ 1.8. In addition, investigations based on 11 yr of Wind observations reveal that the dimensionless wavenumbers (k ρ p ) corresponding to the maximum (absolute) values of CC remain nearly the same for different data sets. These results tend to suggest that the two correlations enhanced near the proton gyroradius scale would be a common feature of solar wind turbulence.

N‐glycan profiling alterations of serum and immunoglobulin G in immune thrombocytopenia

BackgroundThe glycosylation alterations of serum and IgG are involved in a variety of autoimmune and inflammatory diseases and have shown great potential in biomarker field. The diagnosis of immune thrombocytopenia (ITP) is exclusive. Our study aimed to discover the potential glyco‐biomarkers for auxiliary diagnosis of ITP.MethodsThe serum samples were obtained from 61 ITP patients and 35 healthy controls, and IgG samples were purified from 34 out of 61 ITP patients and 35 healthy controls. DNA sequencer‐assisted fluorophore‐assisted carbohydrate electrophoresis (DSA‐FACE) was used to analyze serum and IgG N‐glycan profiling.Results6 of 12 serum N‐glycan peaks, 6 of 7 IgG N‐glycan peaks, serum fucosylation, and IgG galactosylation were significantly different between ITP patients and healthy controls (p < 0.05). IgG peak 7 showed good diagnostic efficacy for discriminating ITP patients from healthy individuals (AUC 0.967). ITP patients with severe thrombocytopenia had a significantly lower serum fucosylation than ITP patients with mild and moderate thrombocytopenia (p < 0.05). Serum fucosylation and serum peak 5 were correlated with platelet counts in ITP patients with severe thrombocytopenia, and the absolute values of correlation coefficient were both over 0.5.ConclusionsThe specific N‐glycan patterns of serum and IgG were observed in ITP patients. IgG peak 7 was a potential biomarker for auxiliary diagnosis of ITP.

Meta-Analysis of Esophageal Cancer Transcriptomes Using Independent Component Analysis.

Independent Component Analysis is a matrix factorization method for data dimension reduction. ICA has been widely applied for the analysis of transcriptomic data for blind separation of biological, environmental, and technical factors affecting gene expression. The study aimed to analyze the publicly available esophageal cancer data using the ICA for identification and comprehensive analysis of reproducible signaling pathways and molecular signatures involved in this cancer type. In this study, four independent esophageal cancer transcriptomic datasets from GEO databases were used. A bioinformatics tool « BiODICA—Independent Component Analysis of Big Omics Data» was applied to compute independent components (ICs). Gene Set Enrichment Analysis (GSEA) and ToppGene uncovered the most significantly enriched pathways. Construction and visualization of gene networks and graphs were performed using the Cytoscape, and HPRD database. The correlation graph between decompositions into 30 ICs was built with absolute correlation values exceeding 0.3. Clusters of components—pseudocliques were observed in the structure of the correlation graph. The top 1,000 most contributing genes of each ICs in the pseudocliques were mapped to the PPI network to construct associated signaling pathways. Some cliques were composed of densely interconnected nodes and included components common to most cancer types (such as cell cycle and extracellular matrix signals), while others were specific to EC. The results of this investigation may reveal potential biomarkers of esophageal carcinogenesis, functional subsystems dysregulated in the tumor cells, and be helpful in predicting the early development of a tumor.

Primary clinical study of radiomics for diagnosing simple bone cyst of the jaw.

To screen the radiomic features of simple bone cysts of the jaws and explore the potential application of radiomics in pre-operative diagnosis of jaw simple bone cysts. The investigators designed and implemented a case-control study. 19 patients with simple bone cysts who were admitted to the Department of Maxillofacial Surgery, Sun Yat-sen University Affiliated Stomatology Hospital from 2013 to 2019 were included in this study. Their clinical data and cone-beam computed tomography (CBCT) images were examined. The control group consisted of patients with odontogenic keratocyst. CBCT imaging features were analyzed and compared between the patient and control groups. Overall, 10,323 image features were extracted through feature analysis. A subset of 25 radiomic features obtained after feature selection were analyzed further. These 25 features were significantly different between the 2 groups (p < 0.05). The absolute value of correlation coefficient was 0.487-0.775. Gray-level co-occurrence matrix (GLCM) contrast, neighborhood gray tone difference matrix (NGTDM) contrast, and GLCM variance were the features with the highest correlation coefficients. Pre-operative radiomics analysis showed the differences between simple bone cysts and odontogenic keratocysts, can help to diagnose simple bone cysts. Three specific texture features-GLCM contrast, NGTDM contrast, and GLCM variance-may be the characteristic imaging features of simple bone cysts of the jaw.

Investigation into the Effect of Breast Volume on Irradiation Dose Distribution in Asian Women with Breast Cancer.

Reports on irradiation dose distribution in breast cancer radiotherapy with sufficient sample size are limited in Asian patients. Elucidating dose distribution in Asian patients is particularly important as their breast volume differs compared to patients in Europe and North America. Here, we examined dose distribution in the irradiation field relative to breast volume for three irradiation methods historically used in our facility. We investigated the influence of breast volume on each irradiation method for Asian women. A total of 573 women with early-stage breast cancer were treated with breast-conserving surgery and adjuvant radiotherapy. Three methods were compared: wedge (W), field-in-field (FIF), and wedge-field-in-field (W-FIF). In patients with small breast volume, FIF decreased low- and high-dose areas within the planning target volume, and increased optimal dose area more than W. In patients with medium and large breast volumes, FIF decreased high-dose area more than W. The absolute values of correlation coefficients of breast volume to low-, optimal-, and high-dose areas and mean dose were significantly lower in FIF than in W. The correlation coefficients of V107% were 0.00 and 0.28 for FIF and W, respectively. FIF is an excellent irradiation method that is less affected by breast volume than W in Asian breast cancer patients.