The RALF2-FERONIA-MYB63 module orchestrates growth and defense in tomato roots.

Plant secreted peptides RAPID ALKALINISATION FACTORs (RALFs), which act through the receptor FERONIA (FER), play important roles in plant growth. However, it remains unclear whether and how RALF-FER contributes to the trade-off of plant growth-defense. Here, we used a variety of techniques such as CRISPR/Cas9, protein-protein interaction and transcriptional regulation methods to investigate the role of RALF2 and its receptor FER in regulating lignin deposition, root growth, and defense against Fusarium oxysporum f. sp. lycopersici (Fol) in tomato (Solanum lycopersicum). The ralf2 and fer mutants show reduced primary root length, elevated lignin accumulation, and enhanced resistance against Fol than the wild-type. FER interacts with and phosphorylates MYB63 to promote its degradation. MYB63 serves as an activator of lignin deposition by regulating the transcription of dirigent protein gene DIR19. Mutation of DIR19 suppresses lignin accumulation, and reverses the short root phenotype and Fol resistance in ralf2 or fer mutant. Collectively, our results demonstrate that the RALF2-FER-MYB63 module fine-tunes root growth and resistance against Fol through regulating the deposition of lignin in tomato roots. The study sheds new light on how plants maintain the growth-defense balance via RALF-FER.

Radiomic Analysis of Contrast-Enhanced CT Predicts Glypican 3-Positive Hepatocellular Carcinoma.

BACKGROUND: The Glypican 3 (GPC3)-positive expression in Hepatocellular Carcinoma (HCC) is associated with a worse prognosis. Moreover, GPC3 has emerged as an immunotherapeutic target in advanced unresectable HCC systemic therapy. It is significant to diagnose GPC3-positive HCCs before therapy. Regarding imaging diagnosis of HCC, dynamic contrast-enhanced CT is more common than MRI in many regions. OBJECTIVE: The aim of this study was to construct and validate a radiomics model based on contrast-enhanced CT to predict the GPC3 expression in hepatocellular carcinoma. METHODS: This retrospective study included 141 (training cohort: n = 100; validation cohort: n = 41) pathologically confirmed HCC patients. Radiomics features were extracted from the Artery Phase (AP) images of contrast-enhanced CT. Logistic regression with the Least Absolute Shrinkage and Selection Operator (LASSO) regularization was used to select features to construct radiomics score (Rad-score). A final combined model, including the Rad-score of the selected features and clinical risk factors, was established. Receiver Operating Characteristic (ROC) curve analysis, Delong test, and Decision Curve Analysis (DCA) were used to assess the predictive performance of the clinical and radiomics models. RESULTS: 5 features were selected to construct the AP radiomics model of contrast-enhanced CT. The radiomics model of AP from contrast-enhanced CT was superior to the clinical model of AFP in training cohorts (P < 0.001), but not superior to the clinical model in validation cohorts (P = 0.151). The combined model (AUC = 0.867 vs. 0.895), including AP Rad-score and serum Alpha-Fetoprotein (AFP) levels, improved the predictive performance more than the AFP model (AUC = 0.651 vs. 0.718) in the training and validation cohorts. The combined model, with a higher decision curve indicating more net benefit, exhibited a better predictive performance than the AP radiomics model. DCA revealed that at a range threshold probability approximately above 60%, the combined model added more net benefit compared to the AP radiomics model of contrastenhanced CT. CONCLUSION: A combined model including AP Rad-score and serum AFP levels based on contrast-enhanced CT could preoperatively predict GPC3-positive expression in HCC.

The MYC2-PUB22-JAZ4 module plays a crucial role in jasmonate signaling in tomato.

Jasmonates (JAs), a class of lipid-derived stress hormones, play a crucial role across an array of plant physiological processes and stress responses. Although JA signaling is thought to rely predominantly on the degradation of specific JAZ proteins by SCFCOI1, it remains unclear whether other pathways are involved in the regulation of JAZ protein stability. Here, we report that PUB22, a plant U-box type E3 ubiquitin ligase, plays a critical role in the regulation of plant resistance against Helicoverpa armigera and other JA responses in tomato. Whereas COI1 physically interacts with JAZ1/2/5/7, PUB22 physically interacts with JAZ1/3/4/6. PUB22 ubiquitinates JAZ4 to promote its degradation via the 26S proteasome pathway. Importantly, we observed that pub22 mutants showreduced resistance to H. armigera, whereas jaz4 single mutants and jaz1 jaz3 jaz4 jaz6 quadruple mutants have enhanced resistance. The hypersensitivity of pub22 mutants to herbivores could be partially rescued by JAZ4 mutation. Moreover, we found that expression of PUB22 can be transcriptionally activated by MYC2, thus forming a positive feedback circuit in JA signaling. We noticed that the PUB22-JAZ4 module also regulates other JA responses, including defense against B. cinerea, inhibition of root elongation, and anthocyanin accumulation. Taken together, these results indicate that PUB22 plays a crucial role in plant growth and defense responses, together with COI1-regulated JA signaling, by targeting specific JAZs.

Preoperative Diagnosis of Dual-Phenotype Hepatocellular Carcinoma Using Enhanced MRI Radiomics Models.

BACKGROUND: Dual-phenotype hepatocellular carcinoma (DPHCC) is highly aggressive and difficult to distinguish from hepatocellular carcinoma (HCC). PURPOSE: To develop and validate clinical and radiomics models based on contrast-enhanced MRI for the preoperative diagnosis of DPHCC. STUDY TYPE: Retrospective. POPULATION: A total of 87 patients with DPHCC and 92 patients with non-DPHCC randomly divided into a training cohort (n = 125: 64 non-DPHCC; 61 DPHCC) and a validation cohort (n = 54: 28 non-DPHCC; 26 DPHCC). FIELD STRENGTH/SEQUENCE: A 3.0 T; dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging sequence. ASSESSMENT: In the clinical model, the maximum tumor diameter and hepatitis B virus (HBV) were independent risk factors of DPHCC. In the radiomics model, a total of 1781 radiomics features were extracted from tumor volumes of interest (VOIs) in the arterial phase (AP) and portal venous phase (PP) images. For feature reduction and selection, Pearson correlation coefficient (PCC) and recursive feature elimination (RFE) were used. Clinical, AP, PP, and combined radiomics models were established using machine learning algorithms (support vector machine [SVM], logistic regression [LR], and logistic regression-least absolute shrinkage and selection operator [LR-LASSO]) and their discriminatory efficacy assessed and compared. STATISTICAL TESTS: The independent sample t test, Mann-Whitney U test, Chi-square test, regression analysis, receiver operating characteristic curve (ROC) analysis, Pearson correlation analysis, the Delong test. A P value < 0.05 was considered statistically significant. RESULTS: In the validation cohort, the combined radiomics model (area under the curve [AUC] = 0.908, 95% confidence interval [CI]: 0.831-0.985) showed the highest diagnostic performance. The AUCs of the PP (AUC = 0.879, 95% CI: 0.779-0.979) and combined radiomics models were significantly higher than that of clinical model (AUC = 0.685, 95% CI: 0.526-0.844). There were no significant differences in AUC between AP or PP radiomics model and combined radiomics model (P = 0.286, 0.180 and 0.543). CONCLUSION: MRI radiomics models may be useful for discriminating DPHCC from non-DPHCC before surgery. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma.

OBJECTIVES: The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for preoperative prediction of VETC and patient prognosis in hepatocellular cancer (HCC). METHODS: The study included 182 (training cohort: 128; validation cohort: 54) HCC patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Volumes of interest including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase images, from which 1316 radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the useful features. Clinical, intratumoral, peritumoral, combined radiomics, and clinical radiomics models were established using machine learning algorithms. The Kaplan-Meier survival analysis was used to assess early recurrence and progression-free survival (PFS) in the VETC + and VETC- patients. RESULTS: In the validation cohort, the area under the curves (AUCs) of radiomics models were higher than that of the clinical model using random forest (all p < 0.05). The peritumoral radiomics model (AUC = 0.972;95% confidence interval [CI]:0.887-0.998) had significantly higher AUC than intratumoral model (AUC = 0.919; 95% CI: 0.811-0.976) (p = 0.044). There were no significant differences in AUC between intratumoral or peritumoral radiomics model (PR) and combined radiomics model (p > 0.05). Early recurrence and PFS were significantly different between the PR-predicted VETC + and VETC- HCC patients (p < 0.05). PR-predicted VETC was independent predictor of early recurrence (hazard ratio [HR]: 2.08[1.31-3.28]; p = 0.002) and PFS (HR: 1.95[1.20-3.17]; p = 0.007). CONCLUSIONS: The intratumoral or peritumoral radiomics model may be useful in predicting VETC and patient prognosis preoperatively. The peritumoral radiomics model may yield an incremental value over intratumoral model. KEY POINTS: • Radiomics models are useful for predicting vessels encapsulating tumor clusters (VETC) and patient prognosis preoperatively. • Peritumoral radiomics model may yield an incremental value over intratumoral model in prediction of VETC. • Peritumoral radiomics-model-predicted VETC was an independent predictor of early recurrence and progression-free survival.

Radiomic analysis of Gd-EOB-DTPA-enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma.

BACKGROUND: Nuclear protein Ki-67 indicates the status of cell proliferation and has been regarded as an attractive biomarker for the prognosis of HCC. The aim of this study is to investigate which radiomics model derived from different sequences and phases of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI was superior to predict Ki-67 expression in hepatocellular carcinoma (HCC), then further to validate the optimal model for preoperative prediction of Ki-67 expression in HCC. METHODS: This retrospective study included 151 (training cohort: n = 103; validation cohort: n = 48) pathologically confirmed HCC patients. Radiomics features were extracted from the artery phase (AP), portal venous phase (PVP), hepatobiliary phase (HBP), and T2-weighted (T2W) images. A logistic regression with the least absolute shrinkage and selection operator (LASSO) regularization was used to select features to build a radiomics score (Rad-score). A final combined model including the optimal Rad-score and clinical risk factors was established. Receiver operating characteristic (ROC) curve analysis, Delong test and calibration curve were used to assess the predictive performance of the combined model. Decision cure analysis (DCA) was used to evaluate the clinical utility. RESULTS: The AP radiomics model with higher decision curve indicating added more net benefit, gave a better predictive performance than the HBP and T2W radiomic models. The combined model (AUC = 0.922 vs. 0.863) including AP Rad-score and serum AFP levels improved the predictive performance more than the AP radiomics model (AUC = 0.873 vs. 0.813) in the training and validation cohort. Calibration curve of the combined model showed a good agreement between the predicted and the actual probability. DCA of the validation cohort revealed that at a range threshold probability of 30-60%, the combined model added more net benefit compared with the AP radiomics model. CONCLUSIONS: A combined model including AP Rad-score and serum AFP levels based on enhanced MRI can preoperatively predict Ki-67 expression in HCC.

Texture Analysis Based on Gd-EOB-DTPA-Enhanced MRI for Identifying Vessels Encapsulating Tumor Clusters (VETC)-Positive Hepatocellular Carcinoma.

PURPOSE: To determine the potential findings associated with vessels encapsulating tumor clusters (VETC)-positive hepatocellular carcinoma (HCC), with particular emphasis on texture analysis based on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI. METHODS: Eighty-one patients with VETC-negative HCC and 52 patients with VETC-positive HCC who underwent Gd-EOB-DTPA-enhanced MRI before curative partial hepatectomy were retrospectively evaluated in our institution. MRI texture analysis was performed on arterial phase (AP) and hepatobiliary phase (HBP) images. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to select texture features most useful for identifying VETC-positive HCC. Univariate and multivariate analyses were used to determine significant variables for identifying the VETC-positive HCC in clinical factors and the texture features of MRI. Receiver operating characteristic (ROC) analysis and DeLong test were performed to compare the identified performances of significant variables for identifying VETC-positive HCC. RESULTS: LASSO logistic regression selected 3 features in AP and HBP images, respectively. In multivariate analysis, the Log-sigma-4.0-mm-3D first-order Kurtosis derived from AP images (odds ratio [OR] = 4.128, P = 0.001) and the Wavelet-LHL-GLDM Dependence Non Uniformity Normalized derived from HBP images (OR = 2.280, P = 0.004) were independent significant variables associated with VETC-positive HCC. The combination of the two texture features for identifying VETC-positive HCC achieved an AUC value of 0.844 (95% confidence interval CI, 0.777, 0.910) with a sensitivity of 80.8% (95% CI, 70.1%, 91.5%) and specificity of 74.1% (95% CI, 64.5%, 83.6%). CONCLUSION: Texture analysis based on Gd-EOB-DTPA-enhanced MRI can help identify VETC-positive HCC.

Imaging features based on Gd-EOB-DTPA-enhanced MRI for predicting vessels encapsulating tumor clusters (VETC) in patients with hepatocellular carcinoma.

OBJECTIVE: To investigate the non-invasive prediction of hepatocellular carcinoma (HCC) with vessels encapsulating tumor clusters (VETC) based on qualitative and quantitative imaging features of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI. METHODS: 109 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA enhanced MRI and immunochemical staining for CD34 were retrospectively evaluated in our institution (the first affiliated hospital of Soochow university). Pre-operative imaging features of Gd-EOB-DTPA-enhanced MRI were qualitatively and quantitatively reviewed by radiologists. Significant variables for differentiating the VETC-positive and VETC-negative HCCs were identified in univariate and multivariate analyses. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off values for quantitative variables. The nomogram based on the coefficient of multivariate analysis was constructed to evaluate the probability of VETC-positive HCCs. RESULTS: The multivariate analysis showed that the serum AST level >40 U l-1 (p = 0.007), non-rim diffuse and heterogeneous arterial phase hyperenhancement (p = 0.035), tumor-to-liver SI ratio of 1.135 or more on AP images (p = 0.001), and tumor-to-liver SI ratio of 0.585 or less on HBP images (p = 0.002) were significant predictors for predicting VETC-positive HCCs. Combing all four significant variables provided a diagnostic accuracy of 82.6%, sensitivity of 83.9%, specificity of 80.9% for identifying VETC status. The area under the receiver operating characteristics curve value of the logistical regression coefficient-based nomogram was 0.885 (95% confidence intervals, 0.824-0.946). CONCLUSION: Qualitative and quantitative imaging features of Gd-EOB-DTPA-enhanced MRI integrating laboratory examination can provide good diagnostic performance. ADVANCES IN KNOWLEDGE: VETC is a novel identified microvascular pattern; associations between imaging features and VETC status have not been investigated. Pre-operative diagnosis of VETC status in HCC is essential to help predict the outcome of patients and make a decision for the therapeutic schedule.

Correction to: Titanium Ions Inhibit the Bacteria in Vase Solutions of Freshly Cut Gerbera jamesonii and Extend the Flower Longevity.

We request that the following corrections be made in our article.

Titanium Ions Inhibit the Bacteria in Vase Solutions of Freshly Cut Gerbera jamesonii and Extend the Flower Longevity.

Titanium ions significantly promote plant growth, but the mechanism is still unclear. Cut flowers are ideal materials for the study of plant growth and senescence. In this study, freshly cut Gerbera jamesonii were used to study the effects of titanium ions (8 mg/L) on the flower longevity. Flowering observation showed that the gerbera vase life was significantly prolonged in the presence of titanium ions. Plate colony counts showed that the amounts of bacteria in the vase solution of the control group were approximately 1700 times more than that of titanium ion treatment group. High-throughput sequencing was used to determine the sequences of 16S rRNA gene V3-V4 variable regions of the vase solutions to analyze bacterial species, their average proportions, and absolute abundance. The results showed that the titanium ions reduced the entire bacterial counts as well as altered the absolute abundance of different bacterial species in the vase solution. The most prevalent bacteria were mainly Enterobacteriaceae, Pseudomonas veronii, Pseudomonas sp., Delftia sp., Agrobacterium sp., Sphingobacterium multivorum, Acinetobacter johnsonii, and Clostridiaceae. In combination with plate colony counts, we demonstrated that all the bacterial growths were significantly inhibited by titanium ions, regardless of their average proportions increased or decreased. These results showed that titanium ions could extend effectively the longevity of gerberas and possess the broad-spectrum antibacterial properties. This study provides a basis for further mechanism exploration of titanium ions action and its applications in cut flower preservation and agricultural production.

Identification and Expression Profile of CYPome in Perennial Ryegrass and Tall Fescue in Response to Temperature Stress.

Plant cytochrome P450s are involved in a wide range of biosynthetic reactions that generate various biomolecules, including a variety of defensive compounds. Perennial ryegrass (Lolium perenne) and tall fescue (Festuca arundinacea) are two major species of turf and forage grasses that usually experience low temperature below -10°C and high temperature over 38°C around the world. In this study, we re-analyzed transcriptome of perennial ryegrass and tall fescue treated with heat and cold stress. Thus, we can evaluate P450 composition in these species and confirm whether P450 genes response to temperature stress. We identified 277 and 319 P450 transcripts with open reading frames larger than 300 bp, respectively. These P450 transcripts were mainly classed in the CYP71, 51, 94, 89, 72, and 734 families. In perennial ryegrass and tall fescue, a total of 66 and 62 P450 transcripts were up-regulated, and 65 and 117 transcripts were down-regulated when subjected to heat stress, respectively. When exposed to cold stress, 60 and 73 transcripts were up-regulated, and 59 and 77 transcripts were down-regulated in perennial ryegrass and tall fescue. Among these differentially expressed transcripts, 64 and 87 of them showed expression level changes that followed the same trend, and these temperature-responsive genes primarily belong to the CYP71, 72 and 99 families. Besides, heat and cold stress altered phenylalanine and brassinosteroid involved P450 transcripts in perennial ryegrass and tall fescue. P450 transcripts involved in the metabolism of these compounds showed a strong response to heat and/or cold stress, indicating that they likely play important roles in temperature acclimation in these two species. The CYPome provide a genetic base for the future functional studies, as well as genetic studies that may improve stress tolerance for perennial ryegrass and tall fescue to extreme temperature.

Genomic profiling of exogenous abscisic acid-responsive microRNAs in tomato (Solanum lycopersicum).

BACKGROUND: Plant microRNAs (miRNAs) are involved in various biological pathways and stress responses as negative regulators at the posttranscriptional level. Abscisic acid (ABA) is a key signaling molecule that mediates plant stress response by activating many stress-related genes. Although some miRNAs in plants are previously identified to respond to ABA, a comprehensive profile of ABA-responsive miRNAs has not yet been elucidated. RESULTS: Here, we identified miRNAs responding to exogenous application of ABA, and their predicted target genes in the model plant organism tomato (Solanum lycopersicum). Deep sequencing of small RNAs from ABA-treated and untreated tomatoes revealed that miRNAs can be up- or down-regulated upon treatment with ABA. A total of 1067 miRNAs were detected (including 365 known and 702 candidate novel miRNAs), of those, 416 miRNAs which had an abundance over two TPM (transcripts per million) were selected for differential expression analysis. We identified 269 (180 known and 89 novel) miRNAs that respond to exogenous ABA treatment with a change in expression level of |log2FC|≥0.25. 136 of these miRNAs (90 known and 46 novel) were expressed at significantly different levels |log2FC|≥1 between treatments. Furthermore, stem-loop RT-PCR was applied to validate the RNA-seq data. Target prediction and analysis of the corresponding ABA-responsive transcriptome data uncovered that differentially expressed miRNAs are involved in condition stress and pathogen resistance, growth and development. Among them, approximately 90 miRNAs were predicted to target transcription factors and pathogen resistance genes. Some miRNAs had functional overlap in biotic and abiotic stress. Most of these miRNAs were down-regulated following exposure to exogenous ABA, while their related target genes were inversely up-regulated, which is consistent with their negative regulatory role in gene expression. CONCLUSIONS: Exogenous ABA application influences the composition and expression level of tomato miRNAs. ABA mainly down-regulates miRNAs that their target genes involve in abiotic stress adaption and disease resistance. ABA might increase expression of stress-related genes via miRNA-mediated posttranscriptional regulation, and our results indicate that ABA treatment has the potential to improve both abiotic stress tolerance and pathogen resistance. This study presents a comprehensive profile of ABA-regulated miRNAs in the tomato, and provides a robust database for further investigation of ABA regulatory mechanisms.