Concurrent Control of Two Aphid-Borne Potyviruses in Cucurbits by Two-in-One Vaccine.

The application of attenuated viruses has been widely practiced for protecting crops from infection by related severe strains of the same species. Papaya ringspot virus W-type (PRSV W) and zucchini yellow mosaic virus (ZYMV) devastate cucurbits worldwide. However, the prevailing of these two viruses in cucurbits cannot be prevented by a single protective virus. In this study, we disclosed that co-infection of horn melon plants by two mild strains, PRSV P-type (PRSV P) HA5-1 and ZYMV-ZAC (a previously developed mild mutant of ZYMV) confers concurrent protection against PRSV P and ZYMV. Consequently, mild mutants of PRSV W were created by site-directed mutagenesis through modifications of the pathogenicity motifs FRNK and PD in helper component-protease (HC-Pro). A stable PRSV W mutant WAC (PRSV-WAC) with R181I and D397N mutations in HC-Pro was generated, inducing mild mottling, followed by symptomless recovery in cucurbits. Horn melon plants pre-infected by PRSV-WAC and ZYMV-ZAC showed no apparent interference on viral accumulation with no synergistic effects on symptoms. An agroinfiltration assay of mixed HC-Pros of WACHC-Pro + ZACHC-Pro revealed no additive effect of RNA silencing suppression. PRSV-WAC or ZYMV-ZAC alone only antagonized a severe strain of homologous virus, while co-infection with these two mild strains provided complete protection against both PRSV W and ZYMV. Similar results were reproduced in muskmelon and watermelon plants, indicating the feasibility of a two-in-one vaccine for concurrent control of PRSV W and ZYMV in cucurbits.

Rapid selection of potyviral cross-protection effective mutants from the local lesion host after nitrous acid mutagenesis.

Zucchini yellow mosaic virus (ZYMV) seriously damages cucurbits worldwide. Control of ZYMV by cross-protection has been practised for decades, but selecting useful mild viruses is time-consuming and laborious. Most attenuated potyviruses used for cross-protection do not induce hypersensitive reaction (HR) in Chenopodium quinoa, a local lesion host Chenopodium quinoa. Here, severe ZYMV TW-TN3 tagged with green fluorescent protein (GFP), designated ZG, was used for nitrous acid mutagenesis. From three trials, 11 mutants were identified from fluorescent spots without HR in inoculated C. quinoa leaves. Five mutants caused attenuated symptoms in squash plants. The genomic sequences of these five mutants revealed that most of the nonsynonymous changes were located in the HC-Pro gene. The replacement of individual mutated HC-Pros in the ZG backbone and an RNA silencing suppression (RSS) assay indicated that each mutated HC-Pro is defective in RSS function and responsible for reduced virulence. Four mutants provided high degrees of protection (84%-100%) against severe virus TW-TN3 in zucchini squash plants, with ZG 4-10 being selected for removal of the GFP tag. After removal of the GFP gene, Z 4-10 induced symptoms similar to ZG 4-10 and still provided 100% protection against TW-TN3 in squash, thus is considered not a genetically engineered mutant. Therefore, using a GFP reporter to select non-HR mutants of ZYMV from C. quinoa leaves is an efficient way to obtain beneficial mild viruses for cross-protection. This novel approach is being applied to other potyviruses.

Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy.

This study aimed to assess the feasibility of using magnetic resonance imaging (MRI)-based Delta radiomics characteristics extrapolated from the Ax LAVA + C series to identify intermediary- and high-risk factors in patients with cervical cancer undergoing surgery following neoadjuvant chemoradiotherapy. A total of 157 patients were divided into two groups: those without any intermediary- or high-risk factors and those with one intermediary-risk factor (negative group; n = 75). Those with any high-risk factor or more than one intermediary-risk factor (positive group; n = 82). Radiomics characteristics were extracted using Ax-LAVA + C MRI sequences. The data was divided into training (n = 126) and test (n = 31) sets in an 8:2 ratio. The training set data features were selected using the Mann-Whitney U test and the Least Absolute Shrinkage and Selection Operator (LASSO) test. The best radiomics features were then analyzed to build a preoperative predictive radiomics model for predicting intermediary- and high-risk factors in cervical cancer. Three models-the clinical model, the radiomics model, and the combined clinic and radiomics model-were developed in this study utilizing the random forest Algorithm. The receiver operating characteristic (ROC) curve, decision curve analysis (DCA), accuracy, sensitivity, and specificity were used to assess the predictive efficacy and clinical benefits of each model. Three models were developed in this study to predict intermediary- and high-risk variables associated with postoperative pathology for patients who underwent surgery after receiving neoadjuvant radiation. In the training and test sets, the AUC values assessed using the clinical model, radiomics model, and combined clinical and radiomics models were 0.76 and 0.70, 0.88 and 0.86, and 0.91 and 0.89, respectively. The use of machine learning algorithms to analyze Delta Ax LAVA + C MRI radiomics features can aid in the prediction of intermediary- and high-risk factors in patients with cervical cancer receiving neoadjuvant therapy.