Multi-feature Fusion Network on Gray Scale Ultrasonography: Effective Differentiation of Adenolymphoma and Pleomorphic Adenoma.

RATIONALE AND OBJECTIVES: to develop a deep learning radiomics graph network (DLRN) that integrates deep learning features extracted from gray scale ultrasonography, radiomics features and clinical features, for distinguishing parotid pleomorphic adenoma (PA) from adenolymphoma (AL) MATERIALS AND METHODS: A total of 287 patients (162 in training cohort, 70 in internal validation cohort and 55 in external validation cohort) from two centers with histologically confirmed PA or AL were enrolled. Deep transfer learning features and radiomics features extracted from gray scale ultrasound images were input to machine learning classifiers including logistic regression (LR), support vector machines (SVM), KNN, RandomForest (RF), ExtraTrees, XGBoost, LightGBM, and MLP to construct deep transfer learning radiomics (DTL) models and Rad models respectively. Deep learning radiomics (DLR) models were constructed by integrating the two features and DLR signatures were generated. Clinical features were further combined with the signatures to develop a DLRN model. The performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis, calibration, decision curve analysis (DCA), and the Hosmer-Lemeshow test. RESULTS: In the internal validation cohort and external validation cohort, comparing to Clinic (AUC=0.767 and 0.777), Rad (AUC=0.841 and 0.748), DTL (AUC=0.740 and 0.825) and DLR (AUC=0.863 and 0.859), the DLRN model showed greatest discriminatory ability (AUC=0.908 and 0.908) showed optimal discriminatory ability. CONCLUSION: The DLRN model built based on gray scale ultrasonography significantly improved the diagnostic performance for benign salivary gland tumors. It can provide clinicians with a non-invasive and accurate diagnostic approach, which holds important clinical significance and value. Ensemble of multiple models helped alleviate overfitting on the small dataset compared to using Resnet50 alone.

Sulfasalazine inhibits esophageal cancer cell proliferation by mediating ferroptosis.

This study aimed to explore the potential mechanism by which sulfasalazine (SAS) inhibits esophageal cancer cell proliferation. A cell counting kit-8 (CCK-8) assay was used to detect the effect of SAS (0, 1, 2, and 4 mM) on the proliferation of TE-1 cells. Subsequently, TE-1 cells were divided into control group, SAS group, SAS + ferrostatin-1 (ferroptosis inhibitor) group, and SAS + Z-VAD (OH)-FMK (apoptosis inhibitor) group, and cell proliferation was measured using a CCK-8 assay. Real-time quantitative polymerase chain reaction and western blotting were used to determine the expression of solute carrier family member 7 11 (SLC7A11, also called xCT), glutathione peroxidase 4 (GPX4), and acyl-CoA synthase long-chain family member 4 (ACSL4) in TE-1 cells. Measurement of ferroptosis in TE-1 cells was achieved by flow cytometry. Compared with the control group (0 mM SAS), the proliferation of TE-1 cells was significantly inhibited by different concentrations of SAS for different time lengths, and 4 mM SAS treatment for 48 h could obtain the maximum inhibition rate (53.9%). In addition, SAS treatment caused a significant decrease in the mRNA and protein expression of xCT and GPX4, and a significant increase in ACSL4 expression in TE-1 cells treated with SAS. Flow cytometry results showed that the ferroptosis level was significantly increased after SAS treatment. However, the activation of ferroptosis by SAS was partially eliminated by treatment with ferrostatin-1 or Z-VAD (OH)-FMK. In conclusion, SAS inhibits the proliferation of esophageal carcinoma cells by activating the ferroptosis pathway.

Radiomic nomogram for discriminating parotid pleomorphic adenoma from parotid adenolymphoma based on grayscale ultrasonography.

Objectives: To differentiate parotid pleomorphic adenoma (PA) from adenolymphoma (AL) using radiomics of grayscale ultrasonography in combination with clinical features. Methods: This retrospective study aimed to analyze the clinical and radiographic characteristics of 162 cases from December 2019 to March 2023. The study population consisted of a training cohort of 113 patients and a validation cohort of 49 patients. Grayscale ultrasonography was processed using ITP-Snap software and Python to delineate regions of interest (ROIs) and extract radiomic features. Univariate analysis, Spearman's correlation, greedy recursive elimination strategy, and least absolute shrinkage and selection operator (LASSO) correlation were employed to select relevant radiographic features. Subsequently, eight machine learning methods (LR, SVM, KNN, RandomForest, ExtraTrees, XGBoost, LightGBM, and MLP) were employed to build a quantitative radiomic model using the selected features. A radiomic nomogram was developed through the utilization of multivariate logistic regression analysis, integrating both clinical and radiomic data. The accuracy of the nomogram was assessed using receiver operating characteristic (ROC) curve analysis, calibration, decision curve analysis (DCA), and the Hosmer-Lemeshow test. Results: To differentiate PA from AL, the radiomic model using SVM showed optimal discriminatory ability (accuracy = 0.929 and 0.857, sensitivity = 0.946 and 0.800, specificity = 0.921 and 0.897, positive predictive value = 0.854 and 0.842, and negative predictive value = 0.972 and 0.867 in the training and validation cohorts, respectively). A nomogram incorporating rad-Signature and clinical features achieved an area under the ROC curve (AUC) of 0.983 (95% confidence interval [CI]: 0.965-1) and 0.910 (95% CI: 0.830-0.990) in the training and validation cohorts, respectively. Decision curve analysis showed that the nomogram and radiomic model outperformed the clinical-factor model in terms of clinical usefulness. Conclusion: A nomogram based on grayscale ultrasonic radiomics and clinical features served as a non-invasive tool capable of differentiating PA and AL.

Relationship of Quantitative Measures of Jumping Performance with Gross Motor Development in Typically Developed Preschool Children.

Jumping is a key movement developing in the preschool period, but limited studies have reported the determinants of jumping performance and its relationship with gross motor development. This study aimed to determine the correlations among jumping performance, quantitative parameters of jumping, and gross motor development in preschool children. Twenty-one preschool children were recruited from one kindergarten, and fifteen of them with complete data were further analyzed. The quantitative parameters of standing long jump (SLJ) and standing vertical jump (SVJ) were measured using a video-based motion capture system. The gross motor development was measured using the Preschooler Gross Motor Quality Scale (PGMQ). The Spearman's rho value and a linear regression model were used to determine the relationships among the jumping performance, the quantitative measures, and the total PGMQ scores. The results indicate that the jumping performances were significantly correlated with the takeoff velocity, which was predicted by trunk inclination before takeoff in SLJ and by the ranges of trunk inclination during jumping in SVJ. Regression analysis showed that the preschool children with higher normalized jump height had better gross motor development, and that the jump performance and the gross motor development were directly or indirectly predicted by the slope of the hip-to-ankle angle plot during pre-takeoff. In conclusion, this study identifies key components of jumping in jumping performance and gross motor development in preschool children for physical education.

Sonographic Findings in Superficial Angiomyxoma of the Vulva in a Perimenopausal Female.

Superficial angiomyxoma (SAM) is an extremely rare soft tissue tumor. It is especially rare in the vulva, with only a few such cases reported in the medical literature. Here, we report a case of SAM of the vulva that was initially suspected to be a Bartholin gland cyst. The patient underwent local excision of the vulvar cyst under lumbar anesthesia. Clinical manifestations and B-scan ultrasonographic features are similar between SAM and cysts. Echoes in the mass are uneven and exhibit low echoes and punctate hyperechoic floating. Thus, increasing sonographers' awareness of the high-frequency ultrasonography findings associated with this rare tumor could broaden their knowledge base.

[Ultrasonic scores combined with blood indexes for screening and predicting compensated liver cirrhosis in chronic hepatitis B patients].

OBJECTIVE: To explore the correlation between ultrasonic scores, routine blood tests and stages of hepatic fibrosis in patients with chronic hepatitis B (CHB), and identify non-invasive indexes to establish a diagnostic model for liver cirrhosis. METHODS: A retrospective analysis of 428 patients with CHB undergoing liver biopsies was conducted. The patients' hematology, serum biochemical indexes, serum alpha fetal proteins (AFP), serum HBeAg status and ultrasonic scores were statistically analyzed. A diagnostic model was established by stepwise discriminant analysis, and aspartate aminotransferase (AST) to platelet ratio index (APRI) was used to estimate the diagnostic value. RESULTS: Partial correlation analysis indicated that platelet, serum albumin, bilirubin, AST, ratio of AST to alanine aminotransferase, prothrombin time and ultrasonic scores were correlated to the stages of liver fibrosis, and significantly differed between patients with and without liver cirrhosis. Logistic regression analysis identified ultrasonic scores, platelet, serum bilirubin, albumin and AST as indexes affecting the diagnosis of compensated cirrhosis. The area under receiver operation curve of model was 0.907. The cirrhosis index (CI) of -0.94 for this model was suitable for screening, with specificity of 85.0%, sensitivity of 81.7%, and accuracy of 84.3%. About 56.2% of the patients' CI was lower than -2.0 with the negative predictive value of 97.0% and the rate of missed diagnosis of 3.0%. About 18.2% of the patients' cirrhosis probabilities were above 0.15, with positive predictive value of 77.3%, and only 2.7% of the patients had mild fibrosis (F2), suggesting that nearly 75% of the patients did not have to receive liver biopsies. CONCLUSION: This diagnostic model integrates the ultrasonic scores, platelet, serum bilirubin, albumin and AST to enable effective screening and prediction of compensated cirrhosis, and can reduce the number of patients required to undergo liver biopsy by about 75%.

[Determination of trace arsenic and mercury in antimony concentrates by hydride generation atomic fluorescence spectrometry].

A method for the determination of trace arsenic and mercury in antimony concentrates by hydride generation atomic fluorescence spectrometry was investigated. The method of dissolving sample and the effect of concomitant ion were studied. It was found that aqua regia can be used to dissolve the sample completely, with maximum quantities of dissolved arsenic and mercury. The interference of chemical elements in antimony concentrates was avoided by adding thiourea-Vc. The matrix of antimony was vaporized with tartaric acid during sample pre-treatment. Trace arsenic and mercury were determined in real samples. The detection limits of 0.220 ng x mL(-1) and 0.002 ng x mL(-1) were obtained, the relative standard deviations(RSD% = 11) are 1.47% and 0.52%, and the recoveries are 94.0%-103.0% and 98.7%-102.8% for As and Hg respectively. This method has proved rapid, accurate and highly sensitive.

Study on the antifertility effects of the plasmid DNA vaccine expressing partial brLDH-C4'.

Partial cDNA sequence coding for Microtus brandti radde (Brandt's vole) testes-specific lactate dehydrogenase (brLDH-C4) was amplified by reverse transcription-polymerase chain reaction (RT-PCR). By inserting the product into the eukaryotic expression vector pCR3.1, pCR3.1-brLDH-C4' was obtained as the prototype of contraceptive DNA vaccine. Immunization with pCR3.1-brLDH-C4' in BALB/c mice generated antibodies specific to purified brLDH-C4' and native mouse LDH-C4 protein. The birth rate of the pCR3.1-brLDH-C4' immunized mice was found to be decreased significantly (80% lower than that of those immunized with pCR3.1). Functions of the elicited antibodies in sera from pCR3.1-brLDH-C4' inoculated mice were further explored. The results indicated that the antibodies from the mice injected with pCR3.1-brLDH-C4' could cause the agglutination of normal sperm suspension, while the ovarian structure and the development of ovarian follicles of these mice were not impaired, which gives a possible explanation for the immunocontraceptive effects of the pCR3.1-brLDH-C4' DNA vaccine.