This study aimed to assess the predictive ability of 18F-FDG PET/CT radiomic features for MYCN, 1p and 11q abnormalities in NB.One hundred and twenty-two pediatric patients (median age 3. 2 years, range, 0.2-9.8 years) with NB were retrospectively enrolled. Significant features by multivariable logistic regression were retained to establish a clinical model (C_model), which included clinical characteristics. 18F-FDG PET/CT radiomic features were extracted by Computational Environment for Radiological Research. The least absolute shrinkage and selection operator (LASSO) regression was used to select radiomic features and build models (R-model). The predictive performance of models constructed by clinical characteristic (C_model), radiomic signature (R_model), and their combinations (CR_model) were compared using receiver operating curves (ROCs). Nomograms based on the radiomic score (rad-score) and clinical parameters were developed.The patients were classified into a training set (n = 86) and a test set (n = 36). Accordingly, 6, 8, and 7 radiomic features were selected to establish R_models for predicting MYCN, 1p and 11q status. The R_models showed a strong power for identifying these aberrations, with area under ROC curves (AUCs) of 0.96, 0.89, and 0.89 in the training set and 0.92, 0.85, and 0.84 in the test set. When combining clinical characteristics and radiomic signature, the AUCs increased to 0.98, 0.91, and 0.93 in the training set and 0.96, 0.88, and 0.89 in the test set. The CR_models had the greatest performance for MYCN, 1p and 11q predictions (P < 0.05).The pre-therapy 18F-FDG PET/CT radiomics is able to predict MYCN amplification and 1p and 11 aberrations in pediatric NB, thus aiding tumor stage, risk stratification and disease management in the clinical practice.
Safety is vital for people and emergency management helps keep people safe. Emergency management includes four stages: Planning and Mitigation, Preparedness, Response and Recovery. Geospatial applications (including GIS) have been extensively used in each stage of emergency management. Nowadays, on the technical side, artificial intelligence tools like deep learning could be put to good use. For example, one of the main benefits of deep learning over various machine learning algorithms is its ability to generate new features from limited series of features located in the training dataset. Therefore, deep learning algorithms can create new tasks to solve current ones. Decision-makers can utilize the geospatial information to develop planning and mitigation strategies with such advanced techniques. GIS models and simulation capabilities are used to exercise response and recovery plans during non-disaster times. They help the decision-makers sense the near real-time possibilities during an event. Once disaster occurs, GIS will take effect in real time response and recovery activities.
Abstract Context Follicular thyroid carcinoma (FTC) is the second most common type of thyroid carcinoma and must be pathologically distinguished from benign follicular adenoma (FA). Additionally, the clinical assessment of thyroid tumors with uncertain malignant potential (TT-UMP) demands effective indicators. Objective We aimed to identify discriminating DNA methylation markers between FA and FTC. Methods DNA methylation patterns were investigated in 33 FTC and 33 FA samples using reduced representation bisulfite sequencing and methylation haplotype block–based analysis. A prediction model was constructed and validated in an independent cohort of 13 FTC and 13 FA samples. Moreover, 36 TT-UMP samples were assessed using this model. Results A total of 70 DNA methylation markers, approximately half of which were located within promoters, were identified to be significantly different between the FTC and FA samples. All the Gene Ontology terms enriched among the marker-associated genes were related to “DNA binding,” implying that the inactivation of DNA binding played a role in FTC development. A random forest model with an area under the curve of 0.994 was constructed using those markers for discriminating FTC from FA in the validation cohort. When the TT-UMP samples were scored using this model, those with fewer driver mutations also exhibited lower scores. Conclusion An FTC-predicting model was constructed using DNA methylation markers, which distinguished between FA and FTC tissues with a high degree of accuracy. This model can also be used to help determine the potential of malignancy in TT-UMP.
Pancreatic ductal adenocarcinoma (PDAC) remains treatment refractory. Immunotherapy has achieved success in the treatment of multiple malignancies. However, the efficacy of immunotherapy in PDAC is limited by a lack of promising biomarkers. In this research, we aimed to identify robust immune molecular subtypes of PDAC to facilitate prognosis prediction and patient selection for immunotherapy.
The regulation of dopamine levels is important in a variety of diseases including addiction. Here we find a novel role for the CLOCK protein as a transcriptional repressor at the TH promoter which is mediated by its interaction with the metabolic sensing protein, SIRT1. Moreover, we demonstrate that TH transcription is modulated by the redox state of neurons, and daily rhythms in cellular redox balance in the VTA, and that TH transcription, is largely disrupted following chronic cocaine administration. Furthermore, interactions between CLOCK/SIRT1 are important in the regulation of cocaine reward and dopaminergic activity with interesting differences depending upon whether dopaminergic activity is in a heightened state and if there is a functional circadian clock. Taken together, we find that rhythms in cellular metabolism and circadian proteins work together to regulate dopamine synthesis and the reward value for drugs of abuse.
The monodispersed BaTiO3 nanocrystals have been synthesized by one-step solvothermal method. The average particle size of BaTiO3 powders is as small as 5 nm with a narrow size distribution. Using this powder, 5nm bulk dense Nano ceramics have been prepared by pressureless two-step sintering method. The microstructure, properties, phase transition and size effect of BaTiO3 ceramics have been investigated systematically by using TEM, HRTEM, XRD and Raman spectra. The Raman Spectra revealed successive transitions from rhombohedral to orthorhombic, tetragonal and cubic with the temperature increased from −190°C to 500°C. Piezoelectric loop measurement results are also shown that ferroelelctricity could still retained in BaTiO3 ceramics with grain size down to 5 nm.
Surface rupture of carotid plaque can cause severe cerebrovascular disease, including transient ischemic attack and stroke. The aim of this study was to elucidate the molecular mechanism governing carotid plaque progression and to provide candidate treatment targets for carotid atherosclerosis.The microarray dataset GSE28829 and the RNA-seq dataset GSE104140, which contain advanced plaque and early plaque samples, were utilized in our analysis. Differentially expressed genes (DEGs) were screened using the "limma" R package. Gene modules for both early and advanced plaques were identified based on co-expression networks constructed by weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were employed in each module. In addition, hub genes for each module were identified. Crucial genes were identified by molecular complex detection (MCODE) based on the DEG co-expression network and were validated by the GSE43292 dataset. Gene set enrichment analysis (GSEA) for crucial genes was performed. Sensitivity analysis was performed to evaluate the robustness of the networks that we constructed.A total of 436 DEGs were screened, of which 335 were up-regulated and 81 were down-regulated. The pathways related to inflammation and immune response were determined to be concentrated in the black module of the advanced plaques. The hub gene of the black module was ARHGAP18 (Rho GTPase activating protein 18). NCF2 (neutrophil cytosolic factor 2), IQGAP2 (IQ motif containing GTPase activating protein 2) and CD86 (CD86 molecule) had the highest connectivity among the crucial genes. All crucial genes were validated successfully, and sensitivity analysis demonstrated that our results were reliable.To the best of our knowledge, this study is the first to combine DEGs and WGCNA to establish a DEG co-expression network in carotid plaques, and it proposes potential therapeutic targets for carotid atherosclerosis.
To explore the effects of seven kinds of hemoglobin variants on two HbA1c detection methods.Twenty-five hemoglobin variant samples (Hb D, S, Q, G, J, E & F) and 40 control samples were from February 2012 to April 2013 collected. All samples were tested by ion exchange-high performance liquid chromatography system (IE-HPLC) and affinity chromatograghy high performance liquid chromatography (AC-HPLC) respectively.We compared the coincidence between HbA1c results of two instruments and blood glucose and observed the difference between variant and control groups for two methods using statistic software SPSS 19.0.A high consistency existed between IE-HPLC and AC-HPLC in the control group with no hemoglobin variants (6.68% ± 1.87% vs 6.64% ± 1.99%, P > 0.05) . For the hemoglobin variants group, the results of HbA1c via IE-HPLC were interfered by hemoglobin variants (3.57% ± 3.51% than 4.95% ± 0.57%, P < 0.05). However, HbA1c detection of AC-HPLC had no interference with hemoglobin variants and it demonstrated an excellent correlation with blood glucose.The results of HbA1c in blood samples containing common hemoglobin variants may be interfered on IE-HPLC to be falsely lower or higher.Only detecting glycated hemoglobin with strong specificity,AC-HPLC is well-correlated with blood glucose and its results are not interfered by common variant hemoglobin.
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