Study of cabbage antioxidant system response on early infection stage of Xanthomonas campestris pv. campestris.

Black rot, caused by Xanthomonas campestris pv. campestris (Xcc) significantly affects the production of cabbage and other cruciferous vegetables. Plant antioxidant system plays an important role in pathogen invasion and is one of the main mechanisms underlying resistance to biological stress. Therefore, it is important to study the resistance mechanisms of the cabbage antioxidant system during the early stages of Xcc. In this study, 108 CFU/mL (OD600 = 0.1) Xcc race1 was inoculated on "zhonggan 11" cabbage using the spraying method. The effects of Xcc infection on the antioxidant system before and after Xcc inoculation (0, 1, 3, and 5 d) were studied by physiological indexes determination, transcriptome and metabolome analyses. We concluded that early Xcc infection can destroy the balance of the active oxygen metabolism system, increase the generation of free radicals, and decrease the scavenging ability, leading to membrane lipid peroxidation, resulting in the destruction of the biofilm system and metabolic disorders. In response to Xcc infection, cabbage clears a series of reactive oxygen species (ROS) produced during Xcc infection via various antioxidant pathways. The activities of antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) increased after Xcc infection, and the ROS scavenging rate increased. The biosynthesis of non-obligate antioxidants, such as ascorbic acid (AsA) and glutathione (GSH), is also enhanced after Xcc infection. Moreover, the alkaloid and vitamin contents increased significantly after Xcc infection. We concluded that cabbage could resist Xcc invasion by maintaining the stability of the cell membrane system and improving the biosynthesis of antioxidant substances and enzymes after infection by Xcc. Our results provide theoretical basis and data support for subsequent research on the cruciferous vegetables resistance mechanism and breeding to Xcc.

Comparative study of the quality indices, antioxidant substances, and mineral elements in different forms of cabbage.

BACKGROUND: As the second largest leafy vegetable, cabbage (Brassica oleracea L. var. capitata) is grown globally, and the characteristics of the different varieties, forms, and colors of cabbage may differ. In this study, five analysis methods-variance analysis, correlation analysis, cluster analysis, principal component analysis, and comprehensive ranking-were used to evaluate the quality indices (soluble protein, soluble sugar, and nitrate), antioxidant content (vitamin C, polyphenols, and flavonoids), and mineral (K, Ca, Mg, Cu, Fe, Mn, and Zn) content of 159 varieties of four forms (green spherical, green oblate, purple spherical, and green cow heart) of cabbage. RESULTS: The results showed that there are significant differences among different forms and varieties of cabbage. Compared to the other three forms, the purple spherical cabbage had the highest flavonoid, K, Mg, Cu, Mn, and Zn content. A scatter plot of the principal component analysis showed that the purple spherical and green cow heart cabbage varieties were distributed to the same quadrant, indicating that their quality indices and mineral contents were highly consistent, while those of the green spherical and oblate varieties were irregularly distributed. Overall, the green spherical cabbage ranked first, followed by the green cow heart, green oblate, and purple spherical varieties. CONCLUSIONS: Our results provide a theoretical basis for the cultivation and high-quality breeding of cabbage.

Effect of hydrogen sulfide on cabbage photosynthesis under black rot stress.

Hydrogen sulfide (H2S), as a potential gaseous signaling molecule, is involved in mediating biotic and abiotic stress in plants. Currently, there are no studies investigating the mechanism by which H2S improves photosynthesis under black rot (BR) stress caused by Xanthomonas campestris pv. Campestris (Xcc). In this study, we investigated the effect of exogenous H2S on Xcc induced photosynthetic impairment in cabbage seedlings. BR has an inhibitory effect on the photosynthetic ability of cabbage seedlings. Xcc infection can significantly reduce the chlorophyll content, photosynthetic characteristics, chlorophyll fluorescence, Calvin cycle related enzyme activity and gene expression in cabbage leaves. The use of H2S can alleviate this inhibitory effect, reduce chlorophyll decomposition, improve gas exchange, enhance the activity of Calvin cycle related enzymes, and increase the expression of related genes. Transcriptome analysis showed that all differential genes related to photosynthesis were up regulated under H2S treatment compared to normal inoculation. Therefore, spraying exogenous H2S can improve the photosynthetic capacity of cabbage seedlings, reduce Xcc induced photoinhibition, and improve plant resistance.

Potential Antihuman Epidermal Growth Factor Receptor 2 Target Therapy Beneficiaries: The Role of MRI-Based Radiomics in Distinguishing Human Epidermal Growth Factor Receptor 2-Low Status of Breast Cancer.

BACKGROUND: Multiparametric MRI radiomics could distinguish human epidermal growth factor receptor 2 (HER2)-positive from HER2-negative breast cancers. However, its value for further distinguishing HER2-low from HER2-negative breast cancers has not been investigated. PURPOSE: To investigate whether multiparametric MRI-based radiomics can distinguish HER2-positive from HER2-negative breast cancers (task 1) and HER2-low from HER2-negative breast cancers (task 2). STUDY TYPE: Retrospective. POPULATION: Task 1: 310 operable breast cancer patients from center 1 (97 HER2-positive and 213 HER2-negative); task 2: 213 HER2-negative patients (108 HER2-low and 105 HER2-zero); 59 patients from center 2 (16 HER2-positive, 27 HER2-low and 16 HER2-zero) for external validation. FIELD STRENGTH/SEQUENCE: A 3.0 T/T1-weighted contrast-enhanced imaging (T1CE), diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC). ASSESSMENT: Patients in center 1 were assigned to a training and internal validation cohort at a 2:1 ratio. Intratumoral and peritumoral features were extracted from T1CE and ADC. After dimensionality reduction, the radiomics signatures (RS) of two tasks were developed using features from T1CE (RS-T1CE), ADC (RS-ADC) alone and T1CE + ADC combination (RS-Com). STATISTICAL TESTS: Mann-Whitney U tests, the least absolute shrinkage and selection operator, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: For task 1, RS-ADC yielded higher area under the ROC curve (AUC) in the training, internal, and external validation of 0.767/0.725/0.746 than RS-T1CE (AUC = 0.733/0.674/0.641). For task 2, RS-T1CE yielded higher AUC of 0.765/0.755/0.678 than RS-ADC (AUC = 0.706/0.608/0.630). For both of task 1 and task 2, RS-Com achieved the best performance with AUC of 0.793/0.778/0.760 and 0.820/0.776/0.711, respectively, and obtained higher clinical benefit in DCA compared with RS-T1CE and RS-ADC. The calibration curves of all RS demonstrated a good fitness. DATA CONCLUSION: Multiparametric MRI radiomics could noninvasively and robustly distinguish HER2-positive from HER2-negative breast cancers and further distinguish HER2-low from HER2-negative breast cancers. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

A contrast-enhanced MRI-based nomogram to identify lung metastasis in soft-tissue sarcoma: A multi-centre study.

BACKGROUND: Lung metastasis (LM) status is critical for making treatment decisions in soft-tissue sarcoma (STS) patients, yet magnetic resonance imaging (MRI)-based prediction of LM in STSs has not been thoroughly investigated. PURPOSE: This study aimed to develop MRI-based radiomics models for identifying LM in STSs. METHODS: We enrolled 122 STS patients from our hospital to form a primary cohort. Thirty-two patients from another hospital were included as an external validation cohort. All patients underwent T1-weighted contrast-enhanced (T1-CE) MRI scans before treatment. Radiomics features were extracted from T1-CE MRI sequence and selected by least absolute shrinkage and selection operator (LASSO) to build the radiomics signature. Clinical factors were evaluated using the univariate and multivariate analyses. Multivariable logistic regression analysis was used to construct a clinical-radiomics nomogram incorporating the radiomics signature with margin. Receiver operating characteristic (ROC), calibration and decision curve analysis (DCA) curves were plotted and area under the ROC curves (AUCs) were calculated to assess the predictive performance of nomogram, radiomics signature and margin. RESULTS: A total of five features was finally identified highly related to the LM status to develop the radiomics signature. The nomogram integrating the radiomics signature and margin achieved the best prediction performance in the training (AUCs, nomogram vs. radiomics signature vs. margin, 0.918 vs. 0.894 vs. 0.609), internal validation (AUCs, nomogram vs. radiomics signature vs. margin, 0.864 vs. 0.841 vs. 0.666) and external validation (AUCs, nomogram vs. radiomics signature vs. margin, 0.843 vs. 0.800 vs. 0.643) sets. CONCLUSIONS: The developed nomogram was a promising tool to help make preoperative treatment strategies for STSs.

Physical, chemical, and biological control of black rot of brassicaceae vegetables: A review.

As one of the important sources of human nutrition, Brassicaceae vegetables are widely grown worldwide. Black rot caused by Xanthomonas campestris pv. campestris (Xcc) seriously affects the quality and yield of Brassicaceae vegetables. Therefore, it is important to study control methods of Xcc for Brassicaceae vegetable production. This paper reviews the physical, chemical, and biological control methods of Xcc in Brassicaceae vegetables developed in recent years, and the underlying mechanisms of control methods are also discussed. Based on our current knowledge, future research directions for Xcc control are also proposed. This review also provides a reference basis for the control of Xcc in the field cultivation of Brassicaceae vegetables.

Application of Exogenous Silicon for Alleviating Photosynthetic Inhibition in Tomato Seedlings under Low-Calcium Stress.

To address the low Ca-induced growth inhibition of tomato plants, the mitigation effect of exogenous Si on tomato seedlings under low-Ca stress was investigated using different application methods. We specifically analyzed the effects of root application or foliar spraying of 1 mM Si on growth conditions, leaf photosynthetic properties, stomatal status, chlorophyll content, chlorophyll fluorescence, ATP activity and content, Calvin cycle-related enzymatic activity, and gene expression in tomato seedlings under low vs. adequate calcium conditions. We found that the low-Ca environment significantly affected (reduced) these parameters, resulting in growth limitation. Surprisingly, the application of 1 mM Si significantly increased plant height, stem diameter, and biomass accumulation, protected photosynthetic pigments, improved gas exchange, promoted ATP production, enhanced the activity of Calvin cycle key enzymes and expression of related genes, and ensured efficient photosynthesis to occur in plants under low-Ca conditions. Interestingly, when the same amount of Si was applied, the beneficial effects of Si were more pronounced under low-Ca conditions that under adequate Ca. We speculate that Si might promote the absorption and transport of calcium in plants. The effects of Si also differed depending on the application method; foliar spraying was better in alleviating photosynthetic inhibition in plants under low-Ca stress, whereas root application of Si significantly promoted root growth and development. Enhancing the photosynthetic capacity by foliar Si application is an effective strategy for ameliorating the growth inhibition of plants under low-Ca stress.

Clinical-Radiomics Nomogram from T1W, T1CE, and T2FS MRI for Improving Diagnosis of Soft-Tissue Sarcoma.

PURPOSE: To compare values of multiparametric magnetic resonance imaging (MRI) sequences and propose clinical-radiomics nomogram for diagnosis of soft-tissue sarcoma (STS). PROCEDURES: This study enrolled 148 patients from Dec. 2017 to Feb. 2021. All patients underwent T1-weighted (T1W), contrast-enhanced T1-weighted (T1CE), and T2-weighted fat-suppressed (T2FS) MRI scans. A total of 1967 radiomic features were extracted from the segmented regions of interest (ROIs) in each MRI sequence. Highly diagnostic radiomic features were selected with Mann-Whitney U test, elastic net, and Akaike's information criterion (AIC) based on MRI images. Logistical regression was used to build Rad scores. Clinical factors were analyzed using the chi-square test or Mann-Whitney U test. The performance of the Rad scores was judged using the area under the receiver operating characteristic area under the curve (ROC AUC), sensitivity, specificity, and accuracy. The nomogram was developed by integrating the Rad score and the most important clinical factor. RESULTS: By combining the three MRI sequences, the Rad-Com was developed consisting of twelve features selected by with Mann-Whitney U test, elastic net, and AIC: four from T1W, three from TICE, and five from T2FS MRI. The margin (P < 0.05) demonstrated a statistically significant difference between patients with benign and malignant soft-tissue tumors (STT). The nomogram was constructed by integrating the Rad-Com and margin, which yielded favorable diagnostic AUCs of 0.919 (sensitivity (Sen) = 0.784, specificity (Spe) = 0.936) and 0.913 (Sen = 0.923, Spe = 0.792) in the training and validation cohort. CONCLUSION: The proposed nomogram may have potential as a noninvasive marker for STS diagnosis.

Organocatalytic formal [3 + 3] cyclization of α-(6-indolyl) propargylic alcohols.

With the aid of acetic acid, a 1,10-conjugate addition-mediated formal [3 + 3] cyclization of alkynyl indole imine methides formed in situ from α-(6-indolyl) propargylic alcohols with 1,3-dicarbonyl compounds such as 4-hydroxycoumarins and cyclohexane-1,3-diones was developed, which provided robust access to a wide range of pyranocoumarin and pyran derivatives containing an indole skeleton with high efficiency under mild conditions.

Multi-parametric MRI-based radiomics for the diagnosis of malignant soft-tissue tumor.

PURPOSE: To develop and validate a multiparametric magnetic resonance imaging-based radiomics nomogram for differentiating malignant and benign soft-tissue tumors. METHODS: A total of 91 patients with pathologically confirmed soft-tissue tumors were enrolled between January 2017 and October 2020. Forty-eight patients were consecutively enrolled between November 2020 and March 2022, as a time-independent cohort. All patients underwent contrast-enhanced T1-weighted and T2-weighted fat-suppression magnetic resonance scans at 3.0 T. Radiomics features were extracted and selected from the two modalities to develop the radiomics signature. Significant clinical/morphological characteristics were identified using a multivariate logistic regression analysis. The least absolute shrinkage and selection operator regression were applied to identify discriminative features. A clinical-radiomics nomogram was constructed based on clinical/morphological characteristics and radiomics features. Finally, the performance of the nomogram was validated using the receiver operating characteristic and decision curve analysis (DCA). RESULTS: Six features were selected to establish the combined RS. Size, margin, and peritumoral edema were identified as the most important clinical and morphological factors, respectively. The radiomics signature outperformed the clinical model in terms of AUC and sensitivity. The nomogram integrating the combined RS, size, margin, and peritumoral edema achieved favorable predictive efficacy, generating AUCs of 0.954 (95% confidence interval [CI]: 0.907-1.000, Sen = 0.861, Spe = 0.917), 0.962 (95% CI: 0.901-1.000, Sen = 0.944, Spe = 0.923), and 0.935 (95% CI: 0.871-0.998, Sen = 0.815, Spe = 0.952) in the training (n = 60), validation (n = 31) and time-independent (n = 48) cohorts, respectively. The DCA curve indicated good clinical usefulness of the nomogram. CONCLUSIONS: Our study demonstrated the clinical potential of multiparametric MRI-based radiomics in distinguishing malignant from benign soft-tissue tumors, which can be considered as a noninvasive tool for individual treatment management.

Radiomics evaluates the EGFR mutation status from the brain metastasis: a multi-center study.

Objective.To develop and externally validate habitat-based MRI radiomics for preoperative prediction of the EGFR mutation status based on brain metastasis (BM) from primary lung adenocarcinoma (LA).Approach.We retrospectively reviewed 150 and 38 patients from hospital 1 and hospital 2 between January 2017 and December 2021 to form a primary and an external validation cohort, respectively. Radiomics features were calculated from the whole tumor (W), tumor active area (TAA) and peritumoral oedema area (POA) in the contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI image. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures (RSs) based on W (RS-W), TAA (RS-TAA), POA (RS-POA) and in combination (RS-Com). The area under receiver operating characteristic curve (AUC) and accuracy analysis were performed to assess the performance of radiomics models.Main results.RS-TAA and RS-POA outperformed RS-W in terms of AUC, ACC and sensitivity. The multi-region combined RS-Com showed the best prediction performance in the primary validation (AUCs, RS-Com versus RS-W versus RS-TAA versus RS-POA, 0.901 versus 0.699 versus 0.812 versus 0.883) and external validation (AUCs, RS-Com versus RS-W versus RS-TAA versus RS-POA, 0.900 versus 0.637 versus 0.814 versus 0.842) cohort.Significance.The developed habitat-based radiomics models can accurately detect the EGFR mutation in patients with BM from primary LA, and may provide a preoperative basis for personal treatment planning.

Intratumoral analysis of digital breast tomosynthesis for predicting the Ki-67 level in breast cancer: A multi-center radiomics study.

PURPOSE: To non-invasively evaluate the Ki-67 level in digital breast tomosynthesis (DBT) images of breast cancer (BC) patients based on subregional radiomics. METHODS: A total of 266 patients who underwent DBT scans were consecutively enrolled at two centers, between September 2017 and September 2021. The whole tumor region was partitioned into various intratumoral subregions, based on individual- and population-level clustering. Handcrafted radiomics and deep learning-based features were extracted from the subregions and from the whole tumor region, and were selected by least absolute shrinkage and selection operator (LASSO) regression, yielding radiomics signatures (RSs). The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the developed RSs. RESULTS: Each breast tumor region was partitioned into an inner subregion (S1) and a marginal subregion (S2). The RSs derived from S1 always generated higher AUCs compared with those from S2 or from the whole tumor region (W), for the external validation cohort (AUCs, S1 vs. W, handcrafted RSs: 0.583 [95% CI, 0.429-0.727] vs. 0.559 [95% CI, 0.405-0.705], p-value: 0.920; deep RSs: 0.670 [95% CI, 0.516-0.802] vs. 0.551 [95% CI, 0.397-0.698], p-value: 0.776). The fusion RSs, combining handcrafted and deep learning-based features derived from S1, yielded the highest AUCs of 0.820 (95% CI, 0.714-0.900) and 0.792 (95% CI, 0.647-0.897) for the internal and external validation cohorts, respectively. CONCLUSIONS: The subregional radiomics approach can accurately predict the Ki-67 level based on DBT data; thus, it may be used as a potential non-invasive tool for preoperative treatment planning in BC.