Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram

Abstract Background Cervical cancer patients receiving radiotherapy and chemotherapy require accurate survival prediction methods. The objective of this study was to develop a prognostic analysis model based on a radiomics score to predict overall survival (OS) in cervical cancer patients. Methods Predictive models were developed using data from 62 cervical cancer patients who underwent radical hysterectomy between June 2020 and June 2021. Radiological features were extracted from T2-weighted (T2W), T1-weighted (T1W), and diffusion-weighted (DW) magnetic resonance images prior to treatment. We obtained the radiomics score (rad-score) using least absolute shrinkage and selection operator (LASSO) regression and Cox’s proportional hazard model. We divided the patients into low- and high-risk groups according to the critical rad-score value, and generated a nomogram incorporating radiological features. We evaluated the model’s prediction performance using area under the receiver operating characteristic (ROC) curve (AUC) and classified the participants into high- and low-risk groups based on radiological characteristics. Results The 62 patients were divided into high-risk (n = 43) and low-risk (n = 19) groups based on the rad-score. Four feature parameters were selected via dimensionality reduction, and the scores were calculated after modeling. The AUC values of ROC curves for prediction of 3- and 5-year OS using the model were 0.84 and 0.93, respectively. Conclusion Our nomogram incorporating a combination of radiological features demonstrated good performance in predicting cervical cancer OS. This study highlights the potential of radiomics analysis in improving survival prediction for cervical cancer patients. However, further studies on a larger scale and external validation cohorts are necessary to validate its potential clinical utility

The Antifungal Effects of Citral on <i>Magnaporthe oryzae</i> Occur via Modulation of Chitin Content as Revealed by RNA-Seq Analysis

The natural product citral has previously been demonstrated to possess antifungal activity against Magnaporthe oryzae. The purpose of this study was to screen and annotate genes that were differentially expressed (DEGs) in M. oryzae after treatment with citral using RNA sequencing (RNA-seq). Thereafter, samples were reprepared for quantitative real-time PCR (RT-qPCR) analysis verification of RNA-seq data. The results showed that 649 DEGs in M. oryzae were significantly affected after treatment with citral (100 μg/mL) for 24 h. Kyoto Encyclopedia of Genes and Genomes (KEGG) and a gene ontology (GO) analysis showed that DEGs were mainly enriched in amino sugar and nucleotide sugar metabolic pathways, including the chitin synthesis pathway and UDP sugar synthesis pathway. The results of the RT-qPCR analysis also showed that the chitin present in M. oryzae might be degraded to chitosan, chitobiose, N-acetyl-D-glucosamine, and β-D-fructose-6-phosphate following treatment with citral. Chitin degradation was indicated by damaged cell-wall integrity. Moreover, the UDP glucose synthesis pathway was involved in glycolysis and gluconeogenesis, providing precursors for the synthesis of polysaccharides. Galactose-1-phosphate uridylyltransferase, which is involved in the regulation of UDP-α-D-galactose and α-D-galactose-1-phosphate, was downregulated. This would result in the inhibition of UDP glucose (UDP-Glc) synthesis, a reduction in cell-wall glucan content, and the destruction of cell-wall integrity