Prediction of IDH1 gene mutation by a nomogram based on multiparametric and multiregional MR images.

OBJECTIVE: To investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma. DATA AND METHODS: The authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness. RESULTS: Age was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values. CONCLUSION: A nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.

Prediction of IDH1 gene mutation by a nomogram based on multiparametric and multiregional MR images

Abstract Objective To investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma. Data and methods The authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness. Results Age was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values. Conclusion A nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.

Cloning and functional analysis of glutathione peroxidase gene in red swamp crayfish Procambarus clarkii.

Glutathione peroxidases (GPxs) are key enzymes in the antioxidant defense systems of living organisms, including crustaceans. The red swamp crayfish Procambarus clarkii is the most commonly farmed freshwater crayfish in Chinese inland nowadays due to its commercial value. However, high stocking density has resulted in adverse effects in growth performance and health. To investigate the function of GPxs in immune defense of the crayfish, we cloned and characterized a full length GPx (PcGPx) from P. clarkii by a reverse-transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends (RACE). The 931 bp PcGPx cDNA contains a 38 bp 5'-untranslated region (UTR), a 519 bp coding sequence (CDS) and a 375 bp 3'-UTR with a selenocysteine insertion sequence (SECIS). The PcGPx was predicted to encode 172 amino acids, and its putative molecular mass was 20.9 kDa with a pI of 4.37. A selenocysteine (Sec) encoded by the unusual stop codon, TGA, was in the protein coding region. Phylogenetic analysis showed that PcGPx clustered with the GPxs from the penaeid shrimp Metapenaeus ensis and Caenorhabditis elegans, sharing much higher similarity with vertebrate GPx1 and GPx2 than with GPx3 and GPx5. Quantitative RT-PCR revealed that PcGPx was extremely highly expressed in ovary and early embryos. In addition, the levels of PcGPx mRNA and reactive oxygen species (ROS) significantly increased after challenge with gram-negative Vibrio harveyi, gram-positive Staphyloccocus aureus or white spot syndrome virus (WSSV). These results suggest that PcGPx may play important roles not only in immune defense, but also in oogenesis in the crayfish.