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Objective. This study is aimed at identifying stemness-related genes in pancreatic ductal adenocarcinoma (PDAC). Methods. The RNA-seq data of PADC patients were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The mRNA expression-based stemness index (mRNAsi) and epigenetically regulated mRNAsi (EREG-mRNAsi) of PADC patients were evaluated. The mRNAsi-related gene sets in PADC were identified by weighted gene coexpression network analysis (WGCNA). The key genes were further analyzed using functional enrichment analysis. The Kaplan-Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of the key genes. Prognostic hub genes were used to establish nomograms. The receiver operating characteristic (ROC) curves, concordance index ( C -index), and calibration curves were used to assess the discrimination and accuracy of the nomogram. Finally, these results were validated in the Gene Expression Omnibus (GEO) database. Results. A total of 36 key genes related to mRNAsi were identified by WGCNA. A prognostic gene signature compromising seven genes (TPX2, ZWINT, UBE2C, CCNB2, CDK1, BUB1, and BIRC5) was established to predict the overall survival (OS) of PADC patients. The Cox regression analysis revealed that the risk score was an independent prognostic factor for PADC. Patients were then divided into the high-risk and low-risk groups. The ROC curves, C -index, and calibration curves indicated good performance of the prognostic signature in the TCGA and GEO datasets. Moreover, the nomogram incorporating clinical parameters showed better sensitivity and specificity for predicting the OS of PADC patients. Conclusion. The stemness-related prognostic model successfully predicted the OS of PADC patients and could be used for the treatment of PADC.

Background Acute thyrotoxic myopathy (ATM) is a rare and potentially lethal complication of thyrotoxicosis. The typical clinical symptoms of ATM are characterized by bulbar paralysis. Reports of the successful treatment of ATM are sporadic due to its low incidence. Subacute thyroiditis (SAT) is one of the etiology of hyperthyroidism. The intrathyroidal injection of glucocorticoids is a novel administration route to treat subacute thyroiditis and reduce the resulting adverse reactions. However, no English literature has reported Chinese with ATM and SAT overlap. Here, we report a Chinese rare with ATM and SAT that recovered from a different and novel route of glucocorticoid administration. Case presentation A 23-year-old woman visited our hospital with a two-year history of progressive weakness of her bulbar muscles, hoarseness, cough when swallowing, dysphagia, and a one-month history of recurrent painful swelling of the thyroid gland. She was diagnosed with ATM, chronic thyrotoxic myopathy (CTM), Graves' ophthalmopathy (GO) due to Graves' disease (GD), and (SAT). After she was treated with a combination of low-dose glucocorticoids, antithyroid drugs (ATDs), propranolol, and ultrasound-guided percutaneous intrathyroidal injection of glucocorticoids, the bulbar paralysis, proximal myopathy, and neck pain simultaneously improved without recurrence during follow-up. To the best of our knowledge, this is the first case report of a patient with ATM, CTM, GD, and GO treated by administering a combination of low-dose glucocorticoids and antithyroid agents. Conclusions Clinicians should consider ATM and intervene with aggressive glucocorticoid therapy was the key to reversing the progression of ATM when a patient has bulbar paralysis and thyrotoxic symptoms. Ultrasound-guided percutaneous intrathyroidal injection of glucocorticoids is a feasible and operable method of curing SAT. Our case report references the clinical diagnosis and treatment of such cases.

Objective. The aim of this study is to explore the potential pathogenesis of juvenile dermatomyositis by bioinformatics analysis of gene chips, which would screen the hub genes, identify potential biomarkers, and reveal the development mechanism of juvenile dermatomyositis. Material and Methods. We retrieved juvenile dermatomyositis’s original expression microarray data of message RNAs (mRNAs) and microRNAs (miRNAs) from NCBI’s Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/); through the R package of limma in Bioconductor, we can screen the differentially expressed miRNAs and mRNAs, and then we further analyzed the predicted target genes by the methods such as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and miRNA-mRNA regulatory network construction and protein-protein interaction (PPI) network using Cytoscape 3.6.1. Results. Compared with normal juvenile skin tissues, 6 upregulated microRNAs and 5 downregulated microRNAs were identified from 166 downregulated microRNAs and 58 upregulated microRNAs in juvenile dermatomyositis tissues. The enrichment pathways of differentially expressed microRNAs include cell adhesion molecules (CAMs), autoimmune thyroid disease, Type I diabetes mellitus, antigen and presentation, viral myocardium, graft-versus-host disease, and Kaposi sarcoma-associated herpes virus infection. By screening of microRNA-messenger RNA regulatory network and construction of PPI network map, three target miRNAs were identified, namely, miR-193b, miR-199b-5p, and miR-665. Conclusion. We identified mir-193b, mir-199b-5p, and mir-6653 target miRNAs by exploring the miRNA-mRNA regulation network mechanism related to the pathogenesis of juvenile dermatomyositis, which will be of great significance for further study on the pathogenesis and targeted therapy of juvenile dermatomyositis.

The Dy3+/Eu3+ doped CaBi2Ta2O9 phosphors had been obtained via the sintering processes at 1200 °C for 3 h. The phase and luminescence performance of the prepared phosphors had been researched. The X-ray diffraction results indicate the pure orthorhombic phase of the prepared phosphors. When the phosphors are excited at 355 nm, the Dy3+/Eu3+ single doped CaBi2Ta2O9 phosphors exhibit the characteristic emission bands corresponding to Dy3+ and Eu3+, and the Dy3+/Eu3+ codoped CaBi2Ta2O9 phosphors exhibit tunable luminescence on account of the Dy3+ → Eu3+ energy transfers. In this process, the dipole-dipole interaction is dominated.

Objective: Aim of this study was to identify the stemness-related genes in Pancreatic ductal adenocarcinoma (PDAC). Methods: The RNA-seq data of PADC were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. mRNA expression base-index (mRNAsi) and epigenetically regulated mRNAsi (EREG-mRNAsi) of PADC were evaluated. The mRNAsi-based gene sets in PADC were identified by Weighted gene co-expression network analysis (WGCNA). Functional Enrichment Analyses were performed with key genes. Kaplan–Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of the key genes. Prognosis-associated hub genes were applied to establish nomograms. The receiver operating characteristic curves (ROC) and concordance index (C-index) were utilized to assess the discrimination and accuracy of the nomogram. Finally, these results were validated in the Gene Expression Omnibus (GEO) database and immunohistochemistry (IHC). Results: 36 key genes associate with mRNAsi were screened via WGCNA. Next a five-gene signature compromised TPX2, NCAPH, UBE2C, CCNB2, CEP55. Based on the expression of the signature, the PADC patients were classify patients into high- and low-risk groups. Cox regression analysis revealed that the high-risk group was significantly positive with overall survival (OS). Moreover, the nomogram has better sensitivity and specificity for predicting the OS. And the ROC, C-index indicated good performance of the prognostic signature in the TCGA and GEO dataset. Conclusion: Prognostic model associated with cancer stem cells (CSCs) reliably predict OS in PADC. this might be beneficial for the treatment of PADC patients.

Hyperspectral remote sensing images have brought abundant spectral information for terrain classification. But the terrain classification of hyperspectral remote sensing images is confronted with the problems of high dimensionality and nonlinear separability, which lead to unsatisfied terrain classification rate. In order to raise the terrain classification recognition rate of hyperspectral remote sensing images, a new terrain classification method is presented based on kernel maximum margin criterion (KMMC), i.e., KMMC subspace method. Firstly, the original data are mapped to a high-dimensional kernel space by kernel method, and then the maximum margin criterion (MMC) is used to extract the nonlinear discriminant features of original data in the kernel space. Finally, the minimum Euclidean distance classifier is used to classify in the resulting KMMC feature subspace. Recognition results on account of an airborne visible / infrared imaging spectrometer (AVIRIS) hyperspectral remote sensing image show that, compared with the original space method, linear discriminant analysis (LDA) subspace method, MMC subspace method and kernel linear discriminant analysis (KLDA) subspace method, the proposed KMMC subspace method can significantly raise the recognition rate while reducing the dimensionality of the data.