ABSTRACT
OBJECTIVE To comprehensively evaluate the quality of Eriobotrya japonica leaves from different producing areas. METHODS The contents of alcohol-soluble extracts were determined by hot-dipping method using 30 batches of E. japonica leaves from different producing areas as samples. The contents of total flavonoids and total triterpene acids were determined by ultraviolet spectrophotometry. The contents of five kinds of triterpenic acids （euscaphic acid，crataegolic acid，corosolic acid，oleanolic acid and ursolic acid） were determined by HPLC. The quality of E. japonica leaves from different producing areas was comprehensively evaluated by using entropy weight technique for order preference by similarity to an ideal solution （TOPSIS）. The bivariate correlation analysis of E. japonica leaves was conducted by SPSS 22.0 software in terms of weight， comprehensive evaluation value， the content of alcohol-soluble extract， the contents of total flavonoids， total triterpene acids and five triterpenic acids. RESULTS The contents of alcohol-soluble extract in 30 batches of E. japonica leaves were （24.56±0.08）%-（34.85±0.13）%； the contents of total flavonoids were （4.69±0.11）-（14.23±0.27） mg/g； the contents of total triterpene acid were （27.58±0.59）- （63.95±1.27） mg/g； the contents of euscaphic acid， crataegolic acid， corosolic acid， oleanolic acid and ursolic acid were （0.728± 0.011）-（6.064±0.063）， （0.526±0.013）-（3.245±0.022）， （1.222±0.025）-（8.807±0.094）， （0.856±0.021）-（2.931±0.075）， （4.704±0.087）-（11.806±0.283） mg/g， respectively. The analysis result of entropy weight TOPSIS method showed that the top three samples with comprehensive evaluation values （No.Kjcx-5） were S14 （Huotian Town， Yunxiao County， Zhangzhou，Fujian）， S19 （Qinnan District， Qinzhou， Guangxi） and S29 （Guoyang County， Bozhou， Anhui）. Comprehensive evaluation 0596-2559522。E-mail：jxrcwxp@163.com of E. japonica leaves was positively correlated with the contents of five kinds of triterpenic acids， such as euscaphic acid， crataegolic acid， corosolic acid， oleanolic acid and ursolic acid （P＜0.01）. The weight of E. japonica leaves was positively correlated with the comprehensive evaluation value （P＜0.01）. CONCLUSIONS The qualities of E. japonica leaves from different producing areas are very different. Among them， the qualities of E. japonica leaves from Huotian Town， Yunxiao County， Zhangzhou of Fujian， Qinzhou Qinnan District of Guangxi， and Bozhou Guoyang County of Anhui are relatively better. The weight of E. japonica leaves is positively correlated with their quality.
ABSTRACT
ObjectiveBy comparing the differences in composition and content of volatile components between Atractylodis Macrocephalae Rhizoma（AMR）and bleaching AMR， bran-fried AMR and bran-fried bleaching AMR， the effect of processing with rice-washed water on the volatile components in AMR and bran-fried AMR were investigated. MethodHeadspace gas chromatography-mass spectrometry（HS-GC-MS）was used to determine the volatile components in raw products， bran-fried products and their processed products with rice-washed water. GC conditions were programmed temperature（starting temperature of 50 ℃， rising to 140 ℃ at 10 ℃·min-1， maintained for 5 min， then rising to 210 ℃ at 4 ℃·min-1）， splitting ratio of 10∶1， high purity helium as the carrier gas and a solvent delay time of 3 min. MS conditions were an electron bombardment ion source（EI） with an electron collision energy of 70 eV， ion source temperature of 230 ℃， and the detection range of m/z 20-650. The relative contents of the components were determined by the peak area normalization method， the obtained sample data were subjected to principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） by SIMCA 14.1 software， and the differential components of AMR and bleaching AMR， and bran-fried AMR and bran-fried bleaching AMR were screened according to variable importance in the projection（VIP） value>1 and P<0.05. ResultA total of 71 volatile components were identified， including 53 in AMR， 50 in bleaching AMR， 51 in bran-fried AMR， and 44 in bran-fried bleaching AMR. OPLS-DA results showed that there were significant differences between AMR and bleaching AMR， bran-fried AMR and bran-fried bleaching AMR， but not between AMR samples from different origins. The compound composition of AMR and bleaching AMR， bran-fried AMR and bran-fried bleaching AMR did not change， but the contents of monoterpenes and sesquiterpenes changed significantly. ConclusionSignificant changes in the contents of volatile components were observed in AMR and bleaching AMR， bran-fried AMR and bran-fried bleaching AMR， among them， 1，2-dimethyl-4-methylidenecyclopentene， 9，10-dehydro-isolongifolene， γ-elemene， zingiberene， atractylone， silphinene， modhephene and （1S，4S，4aS）-1-isopropyl-4，7-dimethyl-1，2，3，4，4a，5-hexahydronaphthalene can be used as candidate differential markers of volatile components of AMR before and after processing with rice-washed water.
ABSTRACT
High-frequency steady-state asymmetric visual evoked potential (SSaVEP) provides a new paradigm for designing comfortable and practical brain-computer interface (BCI) systems. However, due to the weak amplitude and strong noise of high-frequency signals, it is of great significance to study how to enhance their signal features. In this study, a 30 Hz high-frequency visual stimulus was used, and the peripheral visual field was equally divided into eight annular sectors. Eight kinds of annular sector pairs were selected based on the mapping relationship of visual space onto the primary visual cortex (V1), and three phases (in-phase[0º, 0º], anti-phase [0º, 180º], and anti-phase [180º, 0º]) were designed for each annular sector pair to explore response intensity and signal-to-noise ratio under phase modulation. A total of 8 healthy subjects were recruited in the experiment. The results showed that three annular sector pairs exhibited significant differences in SSaVEP features under phase modulation at 30 Hz high-frequency stimulation. And the spatial feature analysis showed that the two types of features of the annular sector pair in the lower visual field were significantly higher than those in the upper visual field. This study further used the filter bank and ensemble task-related component analysis to calculate the classification accuracy of annular sector pairs under three-phase modulations, and the average accuracy was up to 91.5%, which proved that the phase-modulated SSaVEP features could be used to encode high- frequency SSaVEP. In summary, the results of this study provide new ideas for enhancing the features of high-frequency SSaVEP signals and expanding the instruction set of the traditional steady state visual evoked potential paradigm.
Subject(s)
Humans , Evoked Potentials, Visual , Brain-Computer Interfaces , Healthy Volunteers , Signal-To-Noise RatioABSTRACT
Steady-state visual evoked potential (SSVEP) has been widely used in the research of brain-computer interface (BCI) system in recent years. The advantages of SSVEP-BCI system include high classification accuracy, fast information transform rate and strong anti-interference ability. Most of the traditional researches induce SSVEP responses in low and middle frequency bands as control signals. However, SSVEP in this frequency band may cause visual fatigue and even induce epilepsy in subjects. In contrast, high-frequency SSVEP-BCI provides a more comfortable and natural interaction despite its lower amplitude and weaker response. Therefore, it has been widely concerned by researchers in recent years. This paper summarized and analyzed the related research of high-frequency SSVEP-BCI in the past ten years from the aspects of paradigm and algorithm. Finally, the application prospect and development direction of high-frequency SSVEP were discussed and prospected.
Subject(s)
Humans , Brain-Computer Interfaces , Evoked Potentials, Visual , AlgorithmsABSTRACT
OBJECTIV E To study composition an d content changes of volatile components during the bleaching process of Atractylodis macrocephala with the water of washing rice. METHODS The raw products of A. macrocephala and bleached products of 5 different bleaching stages were prepared （in the first and second stages ，raw products were bleached with 9-fold volumn of the water of washing rice for 12 h and 24 h，respectively；in the third ，fourth and fifth stages ，the raw products were firstly bleached with 9-fold volumn of the water of washing rice for 24 h，and then bleached with 9-fold volumn of clean water for 12，24 and 48 h，respectively）；the bleaching temperature was set at 26 ℃. The volatile components of raw products of A. macrocephala and its bleached products of 5 different bleaching stages were qualitatively analyzed by using headspace gas chromatography-mass spectrometry. The relative percentage of each component was calculated by peak area normalization method. RESULTS A total of 49 volatile components were identified from raw products of A. macrocephala and its bleached products of 5 different bleaching stages，including 20 common volatile components such as terpinolene ，cyperene and atractylon ，etc. Among them ，33，31，28， 30，28 and 29 volatile components were identified from the raw products of A. macrocephala and the bleached products of the first to fifth stages ，the relative percentages of which were 66.218％ ，64.711％ ，79.410％ ，65.419％ ，67.101％ ，66.818％ ， respectively；among them ，the relative percentage of atractylon in bleached products was the highest in the fourth stage （41.206％），but was the lowest in the third stage （35.926％）. Compared with the raw product ，16 volatile components such as pethylbrene and β-vetivenen were added in the bleaching process ，while 8 volatile components such as ethyl palmitate and β-maaliene were not detected. However ，5 volatile components including 11-rotundene and （－）-valeranone in the bleaching process showed a trend of disappearance-emergence and disappearance-emergence-disappearance. CONCLUSIONS In the third stage，the total relative percentage of each volatile component and the relative percentage of representative dry component as ， atractylone are the lowest in bleached products of A. ； macrocephala，i.e. the bleaching technology of relieving the dry property of A. macrocephala e with the water of washing rice is bleaching with 9-fold volumn of the water of washing rice for 24 h，and then bleaching with 9-fold volumn of clean water for 12 h.
ABSTRACT
ObjectiveTo identify the chemical constituents of Alismatis Rhizoma before and after processing with salt-water by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry （UPLC-Q-TOF-MS）， and to investigate the changes of terpenoids in Alismatis Rhizoma before and after processing with salt-water. MethodUPLC-Q-TOF-MS was used to detect with 0.1% formic acid aqueous solution （A）-acetonitrile （B）as mobile phase for gradient elution （0-0.01 min， 20%B； 0.01-5 min， 20%-40%B； 5-40 min， 40%-95%B； 40-42 min， 95%B； 42-42.1 min， 95%-20%B； 42.1-45 min， 20%B）， electrospray ionization （ESI） was selected for collection and detection in positive ion mode with the scanning range of m/z 100-1 250 and ion source temperature at 500 ℃. The data were analyzed by PeakView 1.2.0.3， the components were identified according to the primary and secondary MS data， and combined with the reference substance and literature. After normalized treatment by MarkerView 1.2.1， the MS data were analyzed by principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA）， and then the differential components before and after processing were screened. The content changes of differential components were analyzed according to the relative peak area. ResultA total of 30 components were identified under positive ion mode， including 28 prototerpene triterpenes and 2 sesquiterpenes. The results of PCA and OPLS-DA showed that there were significant differences in components from Alismatis Rhizoma before and after processing with salt-water， and 10 differential components （alisol B 23-acetate， alisol I， alismol， 11-deoxy-alisol B 23-acetate， alisol B， alisol C， 11-deoxy-alisol B， alisol G， 11-deoxy-alisol C and alisol A） were screened， and the contents of alisol G and alisol A decreased significantly after processing. ConclusionUPLC-Q-TOF-MS can comprehensively and accurately identify the chemical constituents in raw and salt-processed products of Alismatis Rhizoma. It takes a great difference in the contents of chemical constituents before and after processing， and the difference of substituents is the main reason for this differences， which can provide reference for determining the material basis of efficacy changes of Alismatis Rhizoma before and after processing with salt-water.
ABSTRACT
ObjectiveTo identify the chemical constituents of Alismatis Rhizoma before and after processing with salt-water by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry （UPLC-Q-TOF-MS）， and to investigate the changes of terpenoids in Alismatis Rhizoma before and after processing with salt-water. MethodUPLC-Q-TOF-MS was used to detect with 0.1% formic acid aqueous solution （A）-acetonitrile （B）as mobile phase for gradient elution （0-0.01 min， 20%B； 0.01-5 min， 20%-40%B； 5-40 min， 40%-95%B； 40-42 min， 95%B； 42-42.1 min， 95%-20%B； 42.1-45 min， 20%B）， electrospray ionization （ESI） was selected for collection and detection in positive ion mode with the scanning range of m/z 100-1 250 and ion source temperature at 500 ℃. The data were analyzed by PeakView 1.2.0.3， the components were identified according to the primary and secondary MS data， and combined with the reference substance and literature. After normalized treatment by MarkerView 1.2.1， the MS data were analyzed by principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA）， and then the differential components before and after processing were screened. The content changes of differential components were analyzed according to the relative peak area. ResultA total of 30 components were identified under positive ion mode， including 28 prototerpene triterpenes and 2 sesquiterpenes. The results of PCA and OPLS-DA showed that there were significant differences in components from Alismatis Rhizoma before and after processing with salt-water， and 10 differential components （alisol B 23-acetate， alisol I， alismol， 11-deoxy-alisol B 23-acetate， alisol B， alisol C， 11-deoxy-alisol B， alisol G， 11-deoxy-alisol C and alisol A） were screened， and the contents of alisol G and alisol A decreased significantly after processing. ConclusionUPLC-Q-TOF-MS can comprehensively and accurately identify the chemical constituents in raw and salt-processed products of Alismatis Rhizoma. It takes a great difference in the contents of chemical constituents before and after processing， and the difference of substituents is the main reason for this differences， which can provide reference for determining the material basis of efficacy changes of Alismatis Rhizoma before and after processing with salt-water.
ABSTRACT
Objective:To analyze the distribution characteristics of traditional Chinese medicine (TCM) syndromes in patients with coronavirus disease 2019 (COVID-19) in plateau areas, and to provide theoretical basis for further clinical treatment of patients with COVID-19.Methods:From August 9 to August 24, 2022, patients with COVID-19 admitted to the Third People's Hospital of Tibet Autonomous Region (designated hospital for COVID-19) were included, and their baseline characteristics (age, gender, source), clinical classification and distribution of TCM syndrome types were collected and analyzed. Data analysis was performed using SPSS 26.0 statistical software.Results:A total of 161 COVID-19 patients were enrolled with ethnic distribution: 124 (77.02%) Tibetans, 35 (21.74%) Han, and 2 (1.24%) Hui, 68 males and 93 females. The male-to-female ratio was 0.73∶1. Aged 1 to 94 years, the average age was (39.06±23.64) years old, of which 4 patients were under 1 year old (excluded because the information was missing). A total of 157 patients were enrolled, and 124 patients (78.9%) were under 60 years old, including 120 cases of common type, 4 cases of severe type, 0 cases of critical type, 7 cases over 80 years old, 1 case over 90 years old, and 32 cases under 18 years old. The clinical manifestations of the patient are mainly cough, expectoration, fever, aversion to cold, dry throat, headache, fatigue, running nose, dry mouth, bitter mouth, etc. Most of the tongue is pale, red, and white greasy moss or thin white coating. In TCM, the most common syndrome was cold-dampness blocking lung syndrome (99 cases, 63.06%), followed by cold-dampness stagnant lung syndrome (22 cases, 14.01%), damp-heat accumulating lung syndrome (22 cases, 14.01%), and humidity stagnant lung syndrome (11 cases, 7.01%). Syndromes of epidemic (2 cases, 1.27%), epidemic toxins blocking the lung pattern (1 cases, 0.64%), toxins with dryness intense heat in both qi and ying phases pattern (0 cases) accounted for less than 2%, and the distribution of various syndrome types in COVID-19 patients was uneven ( χ2 = 0.48, P < 0.05). Conclusion:The most common TCM syndromes of COVID-19 patients in Lhasa are cold-dampness blocking lung syndrome, followed by cold-dampness stagnant lung syndrome, damp-heat accumulating lung syndrome, and humidity stagnant lung syndrome.
ABSTRACT
Error self-detection based on error-related potentials (ErrP) is promising to improve the practicability of brain-computer interface systems. But the single trial recognition of ErrP is still a challenge that hinters the development of this technology. To assess the performance of different algorithms on decoding ErrP, this paper test four kinds of linear discriminant analysis algorithms, two kinds of support vector machines, logistic regression, and discriminative canonical pattern matching (DCPM) on two open accessed datasets. All algorithms were evaluated by their classification accuracies and their generalization ability on different sizes of training sets. The study results show that DCPM has the best performance. This study shows a comprehensive comparison of different algorithms on ErrP classification, which could give guidance for the selection of ErrP algorithm.
Subject(s)
Algorithms , Brain , Brain-Computer Interfaces , Discriminant Analysis , Electroencephalography , Support Vector MachineABSTRACT
Brain-computer interface (BCI) provides a direct communicating and controlling approach between the brain and surrounding environment, which attracts a wide range of interest in the fields of brain science and artificial intelligence. It is a core to decode the electroencephalogram (EEG) feature in the BCI system. The decoding efficiency highly depends on the feature extraction and feature classification algorithms. In this paper, we first introduce the commonly-used EEG features in the BCI system. Then we introduce the basic classical algorithms and their advanced versions used in the BCI system. Finally, we present some new BCI algorithms proposed in recent years. We hope this paper can spark fresh thinking for the research and development of high-performance BCI system.