Epigenetic modification of a pectin methylesterase gene activates apoplastic iron reutilization in tomato roots.

Iron (Fe) distribution and reutilization are crucial for maintaining Fe homeostasis in plants. Here, we demonstrate that the tomato (Solanum lycopersicum) Colorless nonripening (Cnr) epimutant exhibits increased Fe retention in cell wall pectin due to an increase in pectin methylesterase (PME) activity. This ultimately leads to Fe deficiency responses even under Fe-sufficient conditions when compared to the wild type (WT). Whole-genome bisulfite sequencing revealed that modifications to cell wall-related genes, especially CG hypermethylation in the intron region of PECTIN METHYLESTERASE53 (SlPME53), are involved in the Cnr response to Fe deficiency. When this intron hypermethylation of SlPME53 was artificially induced in WT, we found that elevated SlPME53 expression was accompanied by increased PME activity and increased pectin-Fe retention. The manipulation of SlPME53, either through overexpression in WT or knockdown in Cnr, influenced levels of pectin methylesterification and accumulation of apoplast Fe in roots. Moreover, CG hypermethylation mediated by METHYLTRANSFERASE1 (SlMET1) increased SlPME53 transcript abundance, resulting in greater PME activity and higher Fe retention in cell wall pectin. Therefore, we conclude that the Cnr mutation epigenetically modulates SlPME53 expression by SlMET1-mediated CG hypermethylation, and thus the capacity of the apoplastic Fe pool, creating opportunities for genetic improvement of crop mineral nutrition.

Tetrad stage transient cold stress skews auxin-mediated energy metabolism balance in Chinese cabbage pollen.

Changing ambient temperature often impairs plant development and sexual reproduction, particularly pollen ontogenesis. However, mechanisms underlying cold stress-induced male sterility are not well understood. Here, we exposed Chinese cabbage (Brassica campestris) to different cold conditions during flowering and demonstrated that the tetrad stage was the most sensitive. After completion of pollen development at optimal conditions, transient cold stress at the tetrad stage still impacted auxin levels, starch and lipid accumulation, and pollen germination, ultimately resulting in partial male sterility. Transcriptome and metabolome analyses and histochemical staining indicated that the reduced pollen germination rate was due to the imbalance of energy metabolism during pollen maturation. The investigation of ß-glucuronidase (GUS)-overexpressing transgenic plants driven by the promoter of DR5 (DR5::GUS report system) combined with cell tissue staining and metabolome analysis further validated that cold stress during the tetrad stage reduced auxin levels in mature pollen grains. Low-concentration auxin treatment on floral buds at the tetrad stage before cold exposure improved the cold tolerance of mature pollen grains. Artificially changing the content of endogenous auxin during pollen maturation by spraying chemical reagents and loss-of-function investigation of the auxin biosynthesis gene YUCCA6 by artificial microRNA technology showed that starch overaccumulation severely reduced the pollen germination rate. In summary, we revealed that transient cold stress at the tetrad stage of pollen development in Chinese cabbage causes auxin-mediated starch-related energy metabolism imbalance that contributes to the decline in pollen germination rate and ultimately seed set.

Integrated metabolome and transcriptome analyses reveal the molecular mechanism underlying dynamic metabolic processes during taproot development of Panax notoginseng.

BACKGROUND: Panax notoginseng (Burk) F. H. Chen is one of the most famous Chinese traditional medicinal plants. The taproot is the main organ producing triterpenoid saponins, and its development is directly linked to the quality and yield of the harvested P. notoginseng. However, the mechanisms underlying the dynamic metabolic changes occurring during taproot development of P. notoginseng are unknown. RESULTS: We carried out metabolomic and transcriptomic analyses to investigate metabolites and gene expression during the development of P. notoginseng taproots. The differentially accumulated metabolites included amino acids and derivatives, nucleotides and derivatives, and lipids in 1-year-old taproots, flavonoids and terpenoids in 2- and 3-year-old taproots, and phenolic acids in 3-year-old taproots. The differentially expressed genes (DEGs) are related to phenylpropanoid biosynthesis, metabolic pathway and biosynthesis of secondary metabolites at all three developmental stages. Integrative analysis revealed that the phenylpropanoid biosynthesis pathway was involved in not only the development of but also metabolic changes in P. notoginseng taproots. Moreover, significant accumulation of triterpenoid saponins in 2- and 3-year-old taproots was highly correlated with the up-regulated expression of cytochrome P450s and uridine diphosphate-dependent glycosyltransferases genes. Additionally, a gene encoding RNase-like major storage protein was identified to play a dual role in the development of P. notoginseng taproots and their triterpenoid saponins synthesis. CONCLUSIONS: These results elucidate the molecular mechanism underlying the accumulation of and change relationship between primary and secondary metabolites in P. notoginseng taproots, and provide a basis for the quality control and genetic improvement of P. notoginseng.

Development of a stable genetic transformation system in Erigeron breviscapus: a case study with EbYUC2 in relation to leaf number and flowering time.

MAIN CONCLUSION: A stable genetic transformation system for Erigeron breviscapus was developed. We cloned the EbYUC2 gene and genetically transformed it into Arabidopsis thaliana and E. breviscapus. The leaf number, YUC2 gene expression, and the endogenous auxin content in transgenic plants were significantly increased. Erigeron breviscapus is a prescription drug for the clinical treatment of cardiovascular and cerebrovascular diseases. The rosette leaves have the highest content of the major active compound scutellarin and are an important component in the yield of E. breviscapus. However, little is known about the genes related to the leaf number and flowering time of E. breviscapus. In our previous study, we identified three candidate genes related to the leaf number and flowering of E. breviscapus by combining resequencing data and genome-wide association study (GWAS). However, their specific functions remain to be characterized. In this study, we cloned and transformed the previously identified full-length EbYUC2 gene into Arabidopsis thaliana, developed the first stable genetic transformation system for E. breviscapus, and obtained the transgenic plants overexpressing EbYUC2. Compared with wild-type plants, the transgenic plants showed a significant increase in the number of leaves, which was correlated with the increased expression of EbYUC2. Consistently, the endogenous auxin content, particularly indole-3-acetic acid, in transgenic plants was also significantly increased. These results suggest that EbYUC2 may control the leaf number by regulating auxin biosynthesis, thereby laying a foundation for revealing the molecular mechanism governing the leaf number and flowering time of E. breviscapus.

Comparison of Neutralizing Antibody Response Kinetics in Patients with Hand, Foot, and Mouth Disease Caused by Coxsackievirus A16 or Enterovirus A71: A Longitudinal Cohort Study of Chinese Children, 2017-2019.

Hand, foot, and mouth disease (HFMD), which is mainly caused by coxsackievirus A16 (CVA16) or enterovirus A71 (EV-A71), poses a serious threat to children's health. However, the long-term dynamics of the neutralizing Ab (NAb) response and ideal paired-serum sampling time for serological diagnosis of CVA16-infected HFMD patients were unclear. In this study, 336 CVA16 and 253 EV-A71 PCR-positive HFMD inpatients were enrolled and provided 452 and 495 sera, respectively, for NAb detection. Random-intercept modeling with B-spline was conducted to characterize NAb response kinetics. The NAb titer of CVA16 infection patients was estimated to increase from negative (2.1, 95% confidence interval [CI]: 1.4-3.3) on the day of onset to a peak of 304.8 (95% CI: 233.4-398.3) on day 21 and then remained >64 until 26 mo after onset. However, the NAb response level of EV-A71-infected HFMD patients was much higher than that of CVA16-infected HFMD patients throughout. The geometric mean titer was significantly higher in severe EV-A71-infected patients than in mild patients, with a 2.0-fold (95% CI: 1.4-3.2) increase. When a 4-fold rise in titer was used as the criterion for serological diagnosis of CVA16 and EV-A71 infection, acute-phase serum needs to be collected at 0-5 d, and the corresponding convalescent serum should be respectively collected at 17.4 (95% CI: 9.6-27.4) and 24.4 d (95% CI: 15.3-38.3) after onset, respectively. In conclusion, both CVA16 and EV-A71 infection induce a persistent humoral immune response but have different NAb response levels and paired-serum sampling times for serological diagnosis. Clinical severity can affect the anti-EV-A71 NAb response.

Influence of the COVID-19 pandemic on the vitamin D status of children: A cross-sectional study.

Coronavirus disease 2019 (COVID-19), as well as its prevention and control measures, seriously affected people's livehood, which may have affected the body's level of vitamin D (VD). This study aimed to investigate the effect of the COVID-19 pandemic on the VD status of children in Zhengzhou, China. In this study, we included 12 272 children in 2019 (before the COVID-19 pandemic) and 16 495 children in 2020 (during the COVID-19 pandemic) to examine the changes in VD levels and deficiency rates among children before and during the COVID-19 pandemic. Total VD levels in 2020 were significantly higher than those in 2019 (26.56 [18.15, 41.40] vs. 25.98 [17.92, 40.09] ng/ml, p < 0.001). Further analysis revealed that during the COVID-19 pandemic control period in 2020, the VD levels in February, March, and April were lower than those in the same months of 2019, while the VD deficiency rates were significantly higher. Additionally, our data revealed that VD levels decreased significantly with age. Among children older than 6 years, the VD deficiency rate exceeded 50%. These results indicate that we should pay close attention to VD supplementation during the COVID-19 pandemic control period and in children older than 6 years of age.

High-efficiency FBG array sensor interrogation system via a neural network working with sparse data.

FBG array sensors have been widely used in the multi-point monitoring of large structures due to their excellent optical multiplexing capability. This paper proposes a cost-effective demodulation system for FBG array sensors based on a Neural Network (NN). The stress variations applied to the FBG array sensor are encoded by the array waveguide grating (AWG) as transmitted intensities under different channels and fed to an end-to-end NN model, which receives them and simultaneously establishes a complex nonlinear relationship between the transmitted intensity and the actual wavelength to achieve absolute interrogation of the peak wavelength. In addition, a low-cost data augmentation strategy is introduced to break the data size bottleneck common in data-driven methods so that the NN can still achieve superior performance with small-scale data. In summary, the demodulation system provides an efficient and reliable solution for multi-point monitoring of large structures based on FBG array sensors.

Depression Detection Based on Analysis of EEG Signals in Multi Brain Regions.

BACKGROUND: As an objective method to detect the neural electrical activity of the brain, electroencephalography (EEG) has been successfully applied to detect major depressive disorder (MDD). However, the performance of the detection algorithm is directly affected by the selection of EEG channels and brain regions. METHODS: To solve the aforementioned problems, nonlinear feature Lempel-Ziv complexity (LZC) and frequency domain feature power spectral density (PSD) were extracted to analyze the EEG signals. Additionally, effects of different brain regions and region combinations on detecting MDD were studied with eyes closed and opened in a resting state. RESULTS: The mean LZC of patients with MDD was higher than that of the control group, and the mean PSD of patients with MDD was generally lower than that of the control group. The temporal region is the best brain region for MDD detection with a detection accuracy of 87.4%. The best multi brain regions combination had a detection accuracy of 92.4% and was made up of the frontal, temporal, and central brain regions. CONCLUSIONS: This paper validates the effectiveness of multiple brain regions in detecting MDD. It provides new ideas for exploring the pathology of MDD and innovative methods of diagnosis and treatment.

Characteristics of heavy metal accumulation and risk assessment in understory Panax notoginseng planting system.

Yunnan Province is the main planting area of the precious Chinese herbal medicines (CHM) Panax notoginseng; however, it locates the geological area with high soil heavy metals in China. The frequent land replacement due to continuous cropping obstacles and excessive application of chemicals makes P. notoginseng prone to be contaminated by heavy metals under the farmland P. notoginseng (FPn) planting. To overcome farmland shortage, understory P. notoginseng (UPn) was developed as a new ecological planting model featured by no chemicals input. However, this newly developed planting system requires urgently the soil-plant heavy metal characteristics and risk assessment. This study aimed to evaluate the pollution status of eight heavy metals in the tillage layer (0-20 cm), subsoil layer (20-40 cm) and the plants of UPn in Lancang County, Yunnan Province. Pollution index (Pi) showed that the contamination degree of heavy metals in the tillage layer and subsoil layer was Cd > Pb > Ni > Cu > Zn > Cr > Hg > As and Pb > Cd > Cu > Ni > Cr > Hg > Zn > As, respectively. Potential ecological risk index (PERI) for the tillage layer and subsoil layer was slight and middle, respectively. The exceeding standard rate of Cd, As, Pb, Hg, Cu in the UPn roots was 5.33%, 5.33%, 13.33%, 26.67% and 1.33%, respectively, while only Cd and Hg in the UPn leaves exceeded the standard 10% and 14%, respectively. The enrichment abilities of Cd and Hg in the roots and leaves of UPn were the strongest, while that of Pb was the weakest. The Hazard index (HI) and target hazard quotient (THQ) of eight heavy metals in the roots and leaves of UPn were less than 1.Therefore, our results prove that Upn has no human health risk and provide a scientific basis for the safety evaluation and extension of UPn.

Fabry-Perot interferometric sensor demodulation system utilizing multi-peak wavelength tracking and neural network algorithm.

For FPI sensor demodulation systems to be used in actual engineering measurement, they must have high performance, low cost, stability, and scalability. Excellent performance, however, necessitates expensive equipment and advanced algorithms. This research provides a new absolute demodulation system for FPI sensors that is high-performance and cost-effective. The reflected light from the sensor was demultiplexed into distinct channels using an array waveguide grating (AWG), with the interference spectrum features change translated as the variation of the transmitted intensity in each AWG channel. This data was fed into an end-to-end neural network model, which was utilized to interrogate multiple interference peaks' absolute peak wavelengths simultaneously. This architecturally simple network model can achieve remarkable generalization capabilities without training large-scale datasets using an appropriate data augmentation strategy. Experiments show that in simultaneous multi-wavelength and cavity length interrogations, the proposed system has the precision of up to ± 14 pm and ± 0.07 µm, respectively. The interrogation resolution can theoretically reach the pm level benefit from the neural network method. Furthermore, the system's outstanding demodulation repeatability and suitability were demonstrated. The system is expected to provide a high-performance and cost-effective, reliable solution for practical engineering applications.

Long Non-coding RNAs: Pivotal Epigenetic Regulators in Diabetic Retinopathy.

Diabetic retinopathy (DR) is a severe complication of diabetes; however, its mechanism is not fully understood. Evidence has recently revealed that long non-coding RNAs (lncRNAs) are abnormally expressed in DR, and lncRNAs may function as pivotal regulators. LncRNAs are able to modulate gene expression at the epigenetic level by acting as scaffolds of histone modification complexes and sponges of binding with microRNAs (miRNAs). LncRNAs are believed to be important epigenetic regulators, which may become beneficial in the diagnosis and therapy of DR. However, the mechanisms of lncRNAs in DR are still unclear. In this review, we summarize the possible functions and mechanisms of lncRNAs in epigenetic regulation to target genes in the progression of DR.

Efficient calculation of optical properties of suspended-core fiber via a machine learning algorithm.

Growing nonlinearity demands in mid-infrared applications place more outstanding requirements on fiber structure design. Chalcogenide suspended-core fibers (SCFs) are considered excellent candidates for mid-infrared applications due to their significant advantages in nonlinearity and dispersion management. However, traditional numerical methods for accurate modeling and optimization of SCFs often rely on the performance of computing devices and have many limitations when dealing with complex models. A machine learning algorithm is applied to calculate the optical properties of chalcogenide SCFs, including effective mode area, nonlinear coefficient, and dispersion. The established artificial neural network (ANN) model enables accurate prediction of the above optical properties of As2S3 SCF, for which in the wavelength range of 1.0 to 4.0 µm, the radius of the fiber core is 0.4 to 0.6 µm, and width of the cantilever is 0.06 to 0.09 µm. We demonstrate that this simple ANN model has considerable advantages over the traditional numerical calculation model in computational speed and resource utilization. In summary, the proposed model can quickly provide more accurate optical property predictions, providing a cost-effective solution for precise modeling and optimization of chalcogenide SCFs.

Research Advances in the Mutual Mechanisms Regulating Response of Plant Roots to Phosphate Deficiency and Aluminum Toxicity.

Low phosphate (Pi) availability and high aluminum (Al) toxicity constitute two major plant mineral nutritional stressors that limit plant productivity on acidic soils. Advances toward the identification of genes and signaling networks that are involved in both stresses in model plants such as Arabidopsis thaliana and rice (Oryza sativa), and in other plants as well have revealed that some factors such as organic acids (OAs), cell wall properties, phytohormones, and iron (Fe) homeostasis are interconnected with each other. Moreover, OAs are involved in recruiting of many plant-growth-promoting bacteria that are able to secrete both OAs and phosphatases to increase Pi availability and decrease Al toxicity. In this review paper, we summarize these mutual mechanisms by which plants deal with both Al toxicity and P starvation, with emphasis on OA secretion regulation, plant-growth-promoting bacteria, transcription factors, transporters, hormones, and cell wall-related kinases in the context of root development and root system architecture remodeling that plays a determinant role in improving P use efficiency and Al resistance on acidic soils.

The miR157-SPL-CNR module acts upstream of bHLH101 to negatively regulate iron deficiency responses in tomato.

Iron (Fe) homeostasis is critical for plant growth, development, and stress responses. Fe levels are tightly controlled by intricate regulatory networks in which transcription factors (TFs) play a central role. A series of basic helix-loop-helix (bHLH) TFs have been shown to contribute to Fe homeostasis, but the regulatory layers beyond bHLH TFs remain largely unclear. Here, we demonstrate that the SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE (SPL) TF SlSPL-CNR negatively regulates Fe-deficiency responses in tomato (Solanum lycopersicum) roots. Fe deficiency rapidly repressed the expression of SlSPL-CNR, and Fe deficiency responses were intensified in two clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein 9-generated SlSPL-CNR knock-out lines compared to the wild-type. Comparative transcriptome analysis identified 47 Fe deficiency-responsive genes the expression of which is negatively regulated by SlSPL-CNR, one of which, SlbHLH101, helps regulate Fe uptake genes. SlSPL-CNR localizes the nucleus and interacts with the GTAC and BOX 4 (ATTAAT) motifs in the SlbHLH101 promoter to repress its expression. Inhibition of SlSPL-CNR expression in response to Fe deficiency was well correlated with the expression of the microRNA SlymiR157. SlymiR157-overexpressing tomato lines displayed enhanced Fe deficiency responses, as did SlSPL-CNR loss-of-function mutants. We propose that the SlymiR157-SlSPL-CNR module represents a novel pathway that acts upstream of SlbHLH101 to regulate Fe homeostasis in tomato roots.

[ST segment morphological classification based on support vector machine multi feature fusion].

ST segment morphology is closely related to cardiovascular disease. It is used not only for characterizing different diseases, but also for predicting the severity of the disease. However, the short duration, low energy, variable morphology and interference from various noises make ST segment morphology classification a difficult task. In this paper, we address the problems of single feature extraction and low classification accuracy of ST segment morphology classification, and use the gradient of ST surface to improve the accuracy of ST segment morphology multi-classification. In this paper, we identify five ST segment morphologies: normal, upward-sloping elevation, arch-back elevation, horizontal depression, and arch-back depression. Firstly, we select an ST segment candidate segment according to the QRS wave group location and medical statistical law. Secondly, we extract ST segment area, mean value, difference with reference baseline, slope, and mean squared error features. In addition, the ST segment is converted into a surface, the gradient features of the ST surface are extracted, and the morphological features are formed into a feature vector. Finally, the support vector machine is used to classify the ST segment, and then the ST segment morphology is multi-classified. The MIT-Beth Israel Hospital Database (MITDB) and the European ST-T database (EDB) were used as data sources to validate the algorithm in this paper, and the results showed that the algorithm in this paper achieved an average recognition rate of 97.79% and 95.60%, respectively, in the process of ST segment recognition. Based on the results of this paper, it is expected that this method can be introduced in the clinical setting in the future to provide morphological guidance for the diagnosis of cardiovascular diseases in the clinic and improve the diagnostic efficiency.

Relationship between emotional intelligence and job well-being in Chinese clinical nurses: multiple mediating effects of empathy and communication satisfaction.

BACKGROUND: Nursing work is associated with great pressure, and nurses are often overwhelmed. Therefore, correct emotional regulation is essential to improve nurses' job well-being and promote better engagement in nursing work. The purpose of this study was to establish a structural model to estimate the impact of Chinese clinical nurses' emotional intelligence on job well-being, using multiple intermediaries to explain the internal mechanisms underlying the relationship. METHODS: This was a cross-sectional study of 1475 registered nurses from a Chinese hospital who provided responses to emotional intelligence, empathy, communication satisfaction, and job well-being scales. Path analysis using a multiple mediation model was performed using AMOS 23.0. RESULTS: Among all clinical nurses who participated in the survey, 1475 (98.33 %) completed the questionnaire. The nurses' job well-being score was 83.61 ± 12.63. There was a significant positive correlation between job well-being and communication satisfaction, emotional intelligence, and empathy ability (r = 0.346-0.570, P < 0.001). Empathy and communication satisfaction partially mediated the relationship between emotional intelligence and job well-being, with effect sizes of 0.047 and 0.227, respectively. The chain mediating effect of empathy and communication satisfaction had a value of 0.045. CONCLUSIONS: It is recommended that hospital managers take actions to improve nurses' emotional intelligence level, and conduct professional psychological training to improve nurses' empathy and communication satisfaction, and ultimately improve their job well-being.

[An automatic pulmonary nodules detection algorithm with multi-scale information fusion].

Lung nodules are the main manifestation of early lung cancer. So accurate detection of lung nodules is of great significance for early diagnosis and treatment of lung cancer. However, the rapid and accurate detection of pulmonary nodules is a challenging task due to the complex background, large detection range of pulmonary computed tomography (CT) images and the different sizes and shapes of pulmonary nodules. Therefore, this paper proposes a multi-scale feature fusion algorithm for the automatic detection of pulmonary nodules to achieve accurate detection of pulmonary nodules. Firstly, a three-layer modular lung nodule detection model was designed on the deep convolutional network (VGG16) for large-scale image recognition. The first-tier module of the network is used to extract the features of pulmonary nodules in CT images and roughly estimate the location of pulmonary nodules. Then the second-tier module of the network is used to fuse multi-scale image features to further enhance the details of pulmonary nodules. The third-tier module of the network was fused to analyze the features of the first-tier and the second-tier module of the network, and the candidate box of pulmonary nodules in multi-scale was obtained. Finally, the candidate box of pulmonary nodules under multi-scale was analyzed with the method of non-maximum suppression, and the final location of pulmonary nodules was obtained. The algorithm is validated by the data of pulmonary nodules on LIDC-IDRI common data set. The average detection accuracy is 90.9%.

Comparative transcriptome and metabolome analyses provide new insights into the molecular mechanisms underlying taproot thickening in Panax notoginseng.

BACKGROUND: Taproot thickening is a complex biological process that is dependent on the coordinated expression of genes controlled by both environmental and developmental factors. Panax notoginseng is an important Chinese medicinal herb that is characterized by an enlarged taproot as the main organ of saponin accumulation. However, the molecular mechanisms of taproot enlargement are poorly understood. RESULTS: A total of 29,957 differentially expressed genes (DEGs) were identified during the thickening process in the taproots of P. notoginseng. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment revealed that DEGs associated with "plant hormone signal transduction," "starch and sucrose metabolism," and "phenylpropanoid biosynthesis" were predominantly enriched. Further analysis identified some critical genes (e.g., RNase-like major storage protein, DA1-related protein, and Starch branching enzyme I) and metabolites (e.g., sucrose, glucose, fructose, malate, and arginine) that potentially control taproot thickening. Several aspects including hormone crosstalk, transcriptional regulation, homeostatic regulation between sugar and starch, and cell wall metabolism, were identified as important for the thickening process in the taproot of P. notoginseng. CONCLUSION: The results provide a molecular regulatory network of taproot thickening in P. notoginseng and facilitate the further characterization of the genes responsible for taproot formation in root medicinal plants or crops.

[Coronary vessel intimal sequence extraction based on prior boundary constraints in optical coherence tomography image].

Optical coherence tomography (OCT) is a new technique applied in cardiovascular system. It can detect vessel intimal, small structure of plaque surface and discover small lesions with its high axial resolution and quantification character. Especially with the application of OCT in characterization of coronary atherosclerotic plaque, diagnosis and treatment strategy making, optimizing percutaneous coronary intervention therapy and assessment after stent planting make the OCT become an efficient tool for cardiovascular disease diagnosis and treatment. This paper presents a novel coronary vessel intimal sequence extraction method based on prior boundary constraints in OCT image. On the basis of conventional Chan-Vese model, we modified the evolutionary weight function to control the evolutionary rate of boundary by adding local information of boundary curve. At the same time, we added the gradient energy term and intimal boundary constraint term based on priori boundary condition to further control the evolutionary of boundary curve. At last, coronary vessel intimal is extracted in a sequence way. The comparison with vessel intimal, manual segmented by clinical scientists (golden standard), indicates that our coronary vessel intimal extraction method is robust to intimal boundary blur, distortion, guide wire shadow and plaque disturbs. The results of this study can be applied to clinical aid diagnosis and precise diagnosis and treatment.