2,4-Dihydroxybenzoic Acid, a Novel SA Derivative, Controls Plant Immunity via UGT95B17-Mediated Glucosylation: A Case Study in Camellia Sinensis.

The plant hormone salicylic acid (SA) plays critical roles in plant innate immunity. Several SA derivatives and associated modification are identified, whereas the range and modes of action of SA-related metabolites remain elusive. Here, the study discovered 2,4-dihydroxybenzoic acid (2,4-DHBA) and its glycosylated form as native SA derivatives in plants whose accumulation is largely induced by SA application and Ps. camelliae-sinensis (Pcs) infection. CsSH1, a 4/5-hydroxylase, catalyzes the hydroxylation of SA to 2,4-DHBA, and UDP-glucosyltransferase UGT95B17 catalyzes the formation of 2,4-DHBA glucoside. Down-regulation reduced the accumulation of 2,4-DHBA glucosides and enhanced the sensitivity of tea plants to Pcs. Conversely, overexpression of UGT95B17 increased plant disease resistance. The exogenous application of 2,4-DHBA and 2,5-DHBA, as well as the accumulation of DHBA and plant resistance comparison, indicate that 2,4-DHBA functions as a potentially bioactive molecule and is stored mainly as a glucose conjugate in tea plants, differs from the mechanism described in Arabidopsis. When 2,4-DHBA is applied exogenously, UGT95B17-silenced tea plants accumulated more 2,4-DHBA than SA and showed induced resistance to Pcs infection. These results indicate that 2,4-DHBA glucosylation positively regulates disease resistance and highlight the role of 2,4-DHBA as potentially bioactive molecule in the establishment of basal resistance in tea plants.

A geraniol synthase regulates plant defense via alternative splicing in tea plants.

Geraniol is an important contributor to the pleasant floral scent of tea products and one of the most abundant aroma compounds in tea plants; however, its biosynthesis and physiological function in response to stress in tea plants remain unclear. The proteins encoded by the full-length terpene synthase (CsTPS1) and its alternative splicing isoform (CsTPS1-AS) could catalyze the formation of geraniol when GPP was used as a substrate in vitro, whereas the expression of CsTPS1-AS was only significantly induced by Colletotrichum gloeosporioides and Neopestalotiopsis sp. infection. Silencing of CsTPS1 and CsTPS1-AS resulted in a significant decrease of geraniol content in tea plants. The geraniol content and disease resistance of tea plants were compared when CsTPS1 and CsTPS1-AS were silenced. Down-regulation of the expression of CsTPS1-AS reduced the accumulation of geraniol, and the silenced tea plants exhibited greater susceptibility to pathogen infection than control plants. However, there was no significant difference observed in the geraniol content and pathogen resistance between CsTPS1-silenced plants and control plants in the tea plants infected with two pathogens. Further analysis showed that silencing of CsTPS1-AS led to a decrease in the expression of the defense-related genes PR1 and PR2 and SA pathway-related genes in tea plants, which increased the susceptibility of tea plants to pathogens infections. Both in vitro and in vivo results indicated that CsTPS1 is involved in the regulation of geraniol formation and plant defense via alternative splicing in tea plants. The results of this study provide new insights into geraniol biosynthesis and highlight the role of monoterpene synthases in modulating plant disease resistance via alternative splicing.

Volatile compound-mediated plant-plant interactions under stress with the tea plant as a model.

Plants respond to environmental stimuli via the release of volatile organic compounds (VOCs), and neighboring plants constantly monitor and respond to these VOCs with great sensitivity and discrimination. This sensing can trigger increased plant fitness and reduce future plant damage through the priming of their own defenses. The defense mechanism in neighboring plants can either be induced by activation of the regulatory or transcriptional machinery, or it can be delayed by the absorption and storage of VOCs for the generation of an appropriate response later. Despite much research, many key questions remain on the role of VOCs in interplant communication and plant fitness. Here we review recent research on the VOCs induced by biotic (i.e. insects and pathogens) and abiotic (i.e. cold, drought, and salt) stresses, and elucidate the biosynthesis of stress-induced VOCs in tea plants. Our focus is on the role of stress-induced VOCs in complex ecological environments. Particularly, the roles of VOCs under abiotic stress are highlighted. Finally, we discuss pertinent questions and future research directions for advancing our understanding of plant interactions via VOCs.

An Optimal Prognostic Model Based on Multiparameter Ultrasound for Acute-on-Chronic Liver Failure.

OBJECTIVE: Acute-on-chronic liver failure (ACLF) is associated with a considerably high mortality, and accurate prognosis prediction is critical to navigate intervention decisions and improve clinical outcomes. The objective of this study was to establish a better prognostic model for ACLF based on multiparameter ultrasound in combination with clinical features. METHODS: A total of 149 patients with ACLF were prospectively enrolled and underwent conventional ultrasound, 2-D shear wave elastography (SWE), attenuation imaging, color Doppler sonography, superb microvascular imaging and contrast-enhanced ultrasound (CEUS). Univariate and multivariate analyses were performed to identify independent ultrasound signatures for the prognosis of ACLF, which, when integrated with clinical characteristics, were used to establish a prognostic model. RESULTS: Hepatic perfusion features of CEUS differed significantly between the poor and good prognosis groups, among which the time interval (TI) between peak portal vein (PV) velocity and liver parenchyma (LP) enhancement, TI(PV, LP), was independently associated with the prognosis of ACLF. A prediction model comprising TI(PV, LP) and the international normalized ratio was established, and the area under the curve (AUC) was 0.851, which is greater than those of the Model for End-stage Liver Disease (0.785), fall time of LP model (0.754), 2-D SWE nomogram (0.708) and TI(PV, LP) (0.352). Furthermore, the performance of the model was verified in an independent validation cohort (AUC = 0.920). CONCLUSION: The newly developed model performs better than existing tested models; thus, it has potential as a better non-invasive model for predicting the prognosis of patients with ACLF. A future multicenter, large-sample study is required to validate the performance of this model.

Sonographic features of thoracoabdominal wall metastases of liver cancer after liver transplantation.

Objective: Sonographic features are not well-defined in thoracoabdominal wall metastases (TAWM) of liver cancer after liver transplantation (LT), which is one of the most important reasons affecting the long-term survival of transplant recipients. The purpose of this study was to analyze the sonographic features of TAWM from liver cancer after LT and to identify the role of ultrasound (US) in the differential diagnosis between TAWM and benign lesions of the thoracoabdominal wall after LT. Methods: This retrospective study included 1,999 LT recipients between January 2008 and July 2021. Clinical characteristics and sonographic features of 32 patients with thoracoabdominal wall lesions were analyzed. The types of thoracoabdominal wall lesions were studied, and the US findings of benign and malignant lesions were compared. Whether TAWM from liver cancer after LT exhibited any distinctive sonographic appearance was evaluated. Results: All seven malignant cases were metastases from liver cancer. The benign group included 13 cases of thoracoabdominal wallencapsulated effusion/hematoma, nine of abdominal incisional hernia, and three of thoracoabdominal wall inflammatory mass. Sonographic features were significantly different between two groups. Compared with the benign group, metastases lesions were frequently located in the parietal peritoneum/pleura (4/7 vs 1/25, p = 0.009), fewer lesions were located at abdominal incisions (3/7 vs 23/25, p = 0.012), all metastatic lesions were hypoechoic (7/7 vs 5/25, p = 0.001), and most lesions had blood flow signals (4/7 vs 3/25, p = 0.026). Additionally, most metastatic cases had intrahepatic lesions (4/7 vs 1/25, p = 0.004) and multiple extrahepatic solid lesions in the abdomen (6/7 vs 0/25, p = 0.000). Conclusions: Compared with benign lesions, TAWM of liver cancer after LT exhibited unique sonographic features.

(Z)-3-Hexenol integrates drought and cold stress signaling by activating abscisic acid glucosylation in tea plants.

Cold and drought stresses severely limit crop production and can occur simultaneously. Although some transcription factors and hormones have been characterized in plants subjected each stress, the role of metabolites, especially volatiles, in response to cold and drought stress exposure is rarely studied due to lack of suitable models. Here, we established a model for studying the role of volatiles in tea (Camellia sinensis) plants experiencing cold and drought stresses simultaneously. Using this model, we showed that volatiles induced by cold stress promote drought tolerance in tea plants by mediating reactive oxygen species and stomatal conductance. Needle trap microextraction combined with GC-MS identified the volatiles involved in the crosstalk and showed that cold-induced (Z)-3-hexenol improved the drought tolerance of tea plants. In addition, silencing C. sinensis alcohol dehydrogenase 2 (CsADH2) led to reduced (Z)-3-hexenol production and significantly reduced drought tolerance in response to simultaneous cold and drought stress. Transcriptome and metabolite analyses, together with plant hormone comparison and abscisic acid (ABA) biosynthesis pathway inhibition experiments, further confirmed the roles of ABA in (Z)-3-hexenol-induced drought tolerance of tea plants. (Z)-3-Hexenol application and gene silencing results supported the hypothesis that (Z)-3-hexenol plays a role in the integration of cold and drought tolerance by stimulating the dual-function glucosyltransferase UGT85A53, thereby altering ABA homeostasis in tea plants. Overall, we present a model for studying the roles of metabolites in plants under multiple stresses and reveal the roles of volatiles in integrating cold and drought stresses in plants.

A Prognostic Nomogram with High Accuracy Based on 2D-SWE in Patients with Acute-on-chronic Liver Failure.

Background and Aims: Acute-on-chronic liver failure (ACLF) is associated with very high mortality. Accurate prediction of prognosis is critical in navigating optimal treatment decisions to improve patient survival. This study was aimed to develop a new nomogram integrating two-dimensional shear wave elastography (2D-SWE) values with other independent prognostic factors to improve the precision of predicting ACLF patient outcomes. Methods: A total of 449 consecutive patients with ACLF were recruited and randomly allocated to a training cohort (n=315) or a test cohort (n=134). 2D-SWE values, conventional ultrasound features, laboratory tests, and other clinical characteristics were included in univariate and multivariate analysis. Factors with prognostic value were then used to construct a novel prognostic nomogram. Receiver operating curves (ROCs) were generated to evaluate and compare the performance of the novel and published models including the Model for End-Stage Liver Disease (MELD), MELD combined with sodium (MELD-Na), and Jin's model. The model was validated in a prospective cohort (n=102). Results: A ACLF prognostic nomogram was developed with independent prognostic factors, including 2D-SWE, age, total bilirubin (TB), neutrophils (Neu), and the international normalized ratio (INR). The area under the ROC curve (AUC) was 0.849 for the new model in the training cohort and 0.861 in the prospective validation cohort, which were significantly greater than those for MELD (0.758), MELD-Na (0.750), and Jin's model (0.777, all p <0.05). Calibration curve analysis revealed good agreement between the predicted and observed probabilities. The new nomogram had superior overall net benefit and clinical utility. Conclusions: We established and validated a 2D-SWE-based noninvasive nomogram to predict the prognosis of ACLF patients that was more accurate than other prognostic models.

US Shear-Wave Elastography Dispersion for Characterization of Chronic Liver Disease.

Background Little is known about the benefits of the use of dispersion slope (DS) as a viscosity-related parameter derived from two-dimensional (2D) shear-wave elastography (SWE) in the stratification of hepatic pathologic stages. Purpose To evaluate whether DS as an additional parameter can improve the diagnostic performance in detecting liver necroinflammation, fibrosis, and steatosis. Materials and Methods In this prospective study, consecutive participants with chronic liver disease who underwent liver biopsy and 2D SWE were recruited between July 2019 and September 2020. DS and liver stiffness (LS) measurements were obtained with use of a 2D SWE system immediately before biopsy. The biopsy specimens were assessed to obtain the scores of fibrosis, necroinflammation, and steatosis. Differences in the area under the receiver operating characteristic curve (AUC) were used to compare the diagnostic performance of DS, LS, and a combination of DS and LS. Results There were 159 participants evaluated (among them, 79 participants with chronic hepatitis B and 11 participants with nonalcoholic fatty liver disease). The distributions of DS values among various necroinflammatory activities (P = .02) and fibrosis stages (P < .001) were different. Moreover, DS was only associated with fibrosis after subgroup analysis based on the fibrosis stages and necroinflammatory activities (P < .001). The AUCs of DS in detecting clinically significant fibrosis (fibrosis stage ≥F2), cirrhosis (fibrosis stage of F4), and moderate to severe necroinflammatory activity (necroinflammatory activity ≥A2) were 0.72 (95% CI: 0.64, 0.79), 0.71 (95% CI: 0.63, 0.78), and 0.64 (95% CI: 0.55, 0.71), respectively. The differences of AUCs were not apparent for the DS and LS combination model after excluding DS (fibrosis stage ≥F2: 0.00 [95% CI: 0.00, 0.01], fibrosis stage of F4: -0.01 [95% CI: -0.02, 0.00], and necroinflammatory activity ≥A2: 0.00 [95% CI: 0.00, 0.01]). Conclusion The addition of dispersion slope derived from two-dimensional shear-wave elastography did not improve the diagnostic performance in detecting liver fibrosis, necroinflammation, or steatosis in patients with primarily viral hepatitis. ClinicalTrials.gov registration no.: NCT03777293 © RSNA, 2022 Online supplemental material is available for this article.

Shear-Wave Dispersion Slope of the Liver: Effect of Study Protocol and Ascites on the Measurement Applicability.

This study aimed to evaluate the shear-wave dispersion (SWD) scanning protocol including the minimum number of measurements and better size of the region of interest (ROI), as well as the influence of ascites on the measurement applicability. Patients who had undergone serial SWD examinations between July 2019 and December 2020 were included. In patients with chronic liver disease (group A), two different ROI sizes were applied, and at least 10 measurements were repeated to determine the minimum number of measurements and better ROI size. In patients with liver failure (group B), failure and unreliable results were compared between patients with and without ascites. A minimum of five measurements when using a 20-mm ROI and six measurements when using a 10-mm ROI were required. Compared with using a 20-mm ROI, a 10-mm ROI showed a higher unreliable rate. The failure and unreliable rates of SWD in patients with ascites were significantly higher than those in patients without ascites. SWD examination required at least five measurements when using a 20-mm ROI and six measurements when using a 10-mm ROI. A larger ROI was associated with higher reliability, and ascites influenced the failure and reliability of the SWD measurement.

Eugenol functions as a signal mediating cold and drought tolerance via UGT71A59-mediated glucosylation in tea plants.

Cold and drought stress are the most critical stresses encountered by crops and occur simultaneously under field conditions. However, it is unclear whether volatiles contribute to both cold and drought tolerance, and if so, by what mechanisms they act. Here, we show that airborne eugenol can be taken up by the tea (Camellia sinensis) plant and metabolized into glycosides, thus enhancing cold and drought tolerance of tea plants. A uridine diphosphate (UDP)-glucosyltransferase, UGT71A59, was discovered, whose expression is strongly induced by multiple abiotic stresses. UGT71A59 specifically catalyzes glucosylation of eugenol glucoside in vitro and in vivo. Suppression of UGT71A59 expression in tea reduced the accumulation of eugenol glucoside, lowered reactive oxygen species (ROS) scavenging capacity, and ultimately impaired cold and drought stress tolerance. Exposure to airborne eugenol triggered a marked increase in UGT71A59 expression, eugenol glucoside accumulation, and cold tolerance by modulating ROS accumulation and CBF1 expression. It also promoted drought tolerance by altering abscisic acid homeostasis and stomatal closure. CBF1 and CBF3 play positive roles in eugenol-induced cold tolerance and CBF2 may be a negative regulator of eugenol-induced cold tolerance in tea plants. These results provide evidence that eugenol functions as a signal in cold and drought tolerance regulation and shed new light on the biological functions of volatiles in the response to multiple abiotic stresses in plants.

Amplification of early drought responses caused by volatile cues emitted from neighboring plants.

Plants have developed sophisticated mechanisms to survive in dynamic environments. Plants can communicate via volatile organic compounds (VOCs) to warn neighboring plants of threats. In most cases, VOCs act as positive regulators of plant defense. However, the communication and role of volatiles in response to drought stress are poorly understood. Here, we showed that tea plants release numerous VOCs. Among them, methyl salicylate (MeSA), benzyl alcohol, and phenethyl alcohol markedly increased under drought stress. Interestingly, further experiments revealed that drought-induced MeSA lowered the abscisic acid (ABA) content in neighboring plants by reducing 9-cis-epoxycarotenoid dioxygenase (NCED) gene expression, resulting in inhibition of stomatal closure and ultimately decreasing early drought tolerance in neighboring plants. Exogenous application of ABA reduced the wilting of tea plants caused by MeSA exposure. Exposure of Nicotiana benthamiana to MeSA also led to severe wilting, indicating that the ability of drought-induced MeSA to reduce early drought tolerance in neighboring plants may be conserved in other plant species. Taken together, these results provide evidence that drought-induced volatiles can reduce early drought tolerance in neighboring plants and lay a novel theoretical foundation for optimizing plant density and spacing.

APS (Age, Platelets, 2D Shear-Wave Elastography) Score Predicts Hepatocellular Carcinoma in Chronic Hepatitis B.

Background Two-dimensional (2D) shear-wave elastography (SWE) has been considered to be useful in predicting hepatocellular carcinoma (HCC) development in patients with chronic hepatitis B (CHB). Purpose To develop a risk model using 2D SWE to predict HCC in patients with CHB and to compare its predictive value with that of other models. Materials and Methods Patients with biopsy-proven CHB who underwent US and 2D SWE between April 2011 and December 2015 were enrolled in this study. After 2D SWE and biopsy were performed, the patients received regular follow-up for the detection of HCC. The scoring system was developed by dividing the parameters of the Cox proportional hazards model by the smallest parameter and simplifying the assigned points to integers. The predictive performance of the new score was compared with that of other scores. Results Among the 654 patients (mean age, 37 years; range, 30-43 years; 510 men), 26 developed HCC. The variables of age, platelet count, and liver stiffness measurement at 2D SWE were weighted to develop the so-called APS score, with a cutoff of 60 showing the best discrimination for HCC risk. The APS score (area under the receiver operating characteristic curve [AUC], 0.89) was superior to that of the Chinese University HCC prediction score constructed from age, albumin level, bilirubin level, hepatitis B virus (HBV) DNA level, and cirrhosis (AUC, 0.70; P = .005) and slightly higher than that of the guide with age, gender, HBV DNA level, core promoter mutations, and cirrhosis, or GAG-HCC score (AUC, 0.82; P = .052). In patients who underwent transient elastography, the AUC of the APS score was 0.79, compared with 0.82 for the modified risk estimation for HCC in CHB, or mREACH-B, score (P = .05). The APS score performed better in patients regardless of whether antiviral treatment was used, inflammation grade was low or high, or alanine aminotransferase levels were normal or high (all P > .05). Conclusion The APS score based on only the patient's baseline liver stiffness measurement at two-dimensional shear-wave elastography, age, and platelet count is valuable for predicting hepatocellular carcinoma in patients with chronic hepatitis B. © RSNA, 2021 Online supplemental material is available for this article.

Noninvasive, quantitative evaluation of hepatic steatosis of donor livers by reference frequency method: A preliminary study.

PURPOSE: Evaluating degree of hepatic steatosis is of great value for prognosis of liver transplantation. There is an urgent need for a non-invasive method to assess hepatic steatosis grade of donor livers. Purpose of our study was to evaluate diagnostic accuracy of attenuation coefficient estimation (ACE) by reference frequency method (RFM) in detecting hepatic steatosis of donor livers. METHOD: We retrospectively enrolled 62 potential liver donors which underwent ACE by RFM ex-vivo, in-vivo or both. We acquired raw data of B-mode images of liver parenchyma and offline-processes for attenuation estimation. Finally, we calculated and compared diagnostic performance of ACEs for steatosis grade detection and used histological results as the gold standard. RESULTS: ACEs with none, mild and moderate hepatic steatosis were 0.57, 0.73 and 0.80 dB/cm/MHz in potential donor livers. The cutoff value to diagnose mild hepatic steatosis was 0.63 dB/cm/MHz and 0.77 dB/cm/MHz for moderate hepatic steatosis, and values for the area under the receiver operating characteristic curve for diagnosis of mild and moderate hepatic steatosis were 0.92 and 0.90, respectively. CONCLUSIONS: According to our results, ACE by RFM is an accurate non-invasive method in detecting hepatic steatosis, which may be of great help for clinical evaluation of donor livers before liver transplantation.

Comparing radiomics models with different inputs for accurate diagnosis of significant fibrosis in chronic liver disease.

OBJECTIVE: The non-invasive discrimination of significant fibrosis (≥ F2) in patients with chronic liver disease (CLD) is clinically critical but technically challenging. We aimed to develop an updated deep learning radiomics model of elastography (DLRE2.0) based on our previous DLRE model to achieve significantly improved performance in ≥ F2 evaluation. METHODS: This was a retrospective multicenter study with 807 CLD patients and 4842 images from three hospitals. All of these patients have liver biopsy results as referenced standard. Multichannel deep learning radiomics models were developed. Elastography images, gray-scale images of the liver capsule, gray-scale images of the liver parenchyma, and serological results were gradually integrated to establish different diagnosis models, and the optimal model was selected for assessing ≥ F2. Its accuracy was thoroughly investigated by applying different F0-1 prevalence cohorts and independent external test cohorts. Analysis of receiver operating characteristic (ROC) curves was performed to calculate the area under the ROC curve (AUC) for significance of fibrosis (≥ F2) and cirrhosis (F4). RESULTS: The AUC of the DLRE2.0 model significantly increased to 0.91 compared with the DLRE model (AUC 0.83) when evaluating ≥ F2 (p = 0.0167). However, it did not show statistically significant differences as integrating gray-scale images and serological data into the DLRE2.0 model. AUCs of DLRE and DLRE2.0 increased, when there was higher F0-1 prevalence. All radiomics models had good robustness in the independent external test cohort. CONCLUSIONS: DLRE2.0 was the most suitable model for staging significant fibrosis while considering the balance of diagnostic accuracy and clinical practicability. KEY POINTS: • The non-invasive discrimination of significant fibrosis (≥ F2) in patients with chronic liver disease (CLD) is clinically critical but technically challenging. • We aimed to develop an updated deep learning radiomics model of elastography (DLRE2.0) based on our previous DLRE model to achieve significantly improved performance in ≥ F2 evaluation. • Our study based on 807 CLD patients and 4842 images with liver biopsy found that DLRE2.0 was the most suitable model for staging significant fibrosis while considering the balance of diagnostic accuracy and clinical practicability.

Deep learning radiomics model accurately predicts hepatocellular carcinoma occurrence in chronic hepatitis B patients: a five-year follow-up.

An early and accurate prediction of hepatocellular carcinoma (HCC) is beneficial for individualized treatment and follow-up of chronic hepatitis B (CHB) patients. We aimed to establish a prediction model for HCC by radiomics analysis in CHB patients and compare performance with liver stiffness measurement (LSM) and other clinical prognostic scores. Initially, 1215 patients were included and finally 434 CHB patients with 5-year follow-up were enrolled, 96.3% of them underwent liver biopsy. Deep learning radiomics analysis was performed on 2170 two-dimensional shear wave elastography (2D-SWE) and corresponding B-mode ultrasound (US) images. These high-throughput imaging features were also combined with low-dimensional serological clinical data by deep learning radiomics to establish different HCC prediction models and to overcome challenges of an unbalanced sample. The best model which is simple with high accuracy was selected. Prediction performance of the selected model was compared with LSM and other clinical prognostic scores. During 5-year follow-up, 32 (7.4%) of 434 patients developed HCC. The best prediction model was HCC-R, which included 2D-SWE and B-mode US images, sex and age. This model showed a high predictive value with areas under the receiver operating characteristic curve (AUCs) of 0.981, 0.942 and 0.900 in training, validation and testing cohorts for predicting 5-year prognosis of HCC. These predictive values were significantly higher than that of LSM (AUC: 0.676~0.784, p < 0.05) and better than that of other clinical prognostic scores (AUC: 0.544~0.869). HCC-R radiomics model based on 2D-SWE and B-mode US images, sex and age comprehensively reflected biomechanical and morphological information of patients and can accurately predict HCC occurrence; thus, this model has great value for treatment and follow-up of CHB patients.

Herbivore-induced DMNT catalyzed by CYP82D47 plays an important role in the induction of JA-dependent herbivore resistance of neighboring tea plants.

Herbivore-induced plant volatiles play important ecological roles in defense against stresses. However, if and which volatile(s) are involved in the plant-plant communication in response to herbivorous insects in tea plants remains unknown. Here, plant-plant communication experiments confirm that volatiles emitted from insects-attacked tea plants can trigger plant resistance and reduce the risk of herbivore damage by inducing jasmonic acid (JA) accumulation in neighboring plants. The emission of six compounds was significantly induced by geometrid Ectropis obliqua, one of the most common pests of the tea plant in China. Among them, (E)-4,8-dimethyl-1,3,7-nonatriene (DMNT) could induce the accumulation of JA and thus promotes the resistance of neighboring intact plants to herbivorous insects. CsCYP82D47 was identified for the first time as a P450 enzyme, which catalyzes the final step in the biosynthesis of DMNT from (E)-nerolidol. Down-regulation of CsCYP82D47 in tea plants resulted in a reduced accumulation of DMNT and significantly reduced the release of DMNT in response to the feeding of herbivorous insects. The first evidence for plant-plant communication in response to herbivores in tea plants will help to understand how plants respond to volatile cues in response to herbivores and provide new insight into the role(s) of DMNT in tea plants.

How does liver steatosis affect diagnostic performance of 2D-SWE.SSI: assessment from aspects of steatosis degree and pathological types.

OBJECTIVE: Two-dimensional shear wave elastography performed by SurperSonics (2D-SWE.SSI) performs well in evaluating liver fibrosis. Steatosis is one of confounding factors which might decrease accuracy, and its effect on 2D-SWE.SSI is still controversial. Our purpose is to evaluate the diagnostic performance of 2D-SWE.SSI affected by different steatosis stages and pathological types in chronic hepatitis B (CHB) patients. METHODS: 2D-SWE.SSI was performed on 1306 CHB patients. All patients were divided into mild steatosis, moderate to severe steatosis, and non-steatosis groups. Subgroup analysis was performed according to pathological type. Liver biopsy was reference standard. Propensity score matching was performed to adjust for differences in patient characteristics. The median values of different steatosis group were compared by non-parametric tests before and after propensity score matching. The area under the receiver operating characteristic curve (AUC) was analyzed to assess the diagnostic performance in different steatosis groups. RESULTS: The median values were not significantly different in different steatosis degrees expected in F0-1 patients. The AUC of 2D-SWE.SSI was not affected by different stages of liver steatosis for cirrhosis (= F4) (0.896, 0.853, 0.929, p = 0.34). The high AUCs (0.847, 0.856) were achieved in the non-steatosis and mild steatosis groups, and all were significantly higher than those of the moderate to severe steatosis group for ≥ F2. Moreover, the panacinar type had the best AUC (0.980 for F4 and 0.930 for ≥ F2). CONCLUSION: In conclusion, moderate to severe steatosis affects 2D-SWE.SSI in CHB patients. These patients had high LSM values in patients with F0-1 and lower accuracy in ≥ F2. Patients with panacinar steatosis have the highest overall diagnostic performance. KEY POINTS: • 2D-SWE.SSI was widely used in evaluating liver fibrosis and it has many confounding factors. Steatosis is one of the confounding factors and its effect on 2D-SWE.SSI was controversial. • Our study based on 1306 CHB patients with liver biopsy found that 2D-SWE.SSI might be affected by moderate to severe liver steatosis in diagnostically significant fibrosis (≥ F2) of CHB patients. • Patients with steatosis of the panacinar type have the highest overall diagnostic performance.

UGT85A53 promotes flowering via mediating abscisic acid glucosylation and FLC transcription in Camellia sinensis.

Uridine diphosphate (UDP)-dependent glycosyltransferases catalyse the glycosylation of small molecules and play important roles in maintaining cell homeostasis and regulating plant development. Glycosyltransferases are widely distributed, but their detailed roles in regulating plant growth and development are largely unknown. In this study, we identified a UDP-glycosyltransferase, UGT85A53, from Camellia sinensis, the expression of which was strongly induced by various abiotic stress factors and its protein product was distributed in both the cytoplasm and nucleus. Ectopic overexpression of CsUGT85A53 in Arabidopsis resulted in an early-flowering phenotype under both long- and short-day conditions. The transcript accumulation of the flowering repressor genes FLC and ABI5, an activator of FLC in ABA-regulated flowering signaling, were both significantly decreased in transgenic Arabidopsis compared with wild-type plants. The decreased expression level of FLC might be associated with an increased level of DNA methylation that was observed in CsUGT85A53-overexpressing (OE) plants. Biochemical analyses showed that CsUGT85A53 could glucosylate ABA to form inactive ABA-glycoside in vitro and in planta. Overexpression of CsUGT85A53 in Arabidopsis resulted in a decreased concentration of free ABA and increased concentration of ABA-glucoside. The early-flowering phenotype in the CsUGT85A53-OE transgenic lines was restored by ABA application. Furthermore, CsUGT85A53-OE plants displayed an ABA-insensitive phenotype with higher germination rates compared with controls in the presence of low concentrations of exogenous ABA. Our findings are the first to identify a UGT in tea plants that catalyses ABA glucosylation and enhance flowering transition as a positive regulator.