Objective Evaluation of Pulse Width Using an Array Pulse Diagram.

BACKGROUND: Pulse width, which can reflect qi, blood excess, and deficiency, has been used for diagnosing diseases and determining the prognosis in traditional Chinese medicine (TCM). This study aimed to devise an objective method to measure the pulse width based on an array pulse diagram for objective diagnosis. METHODS: The channel 6, the region wherein the pulse wave signal is the strongest, is located in the middle of the pulse sensor array and at the guan position of cunkou during data collection. Therefore, the main wave (h1) time of the pulse wave was collected from the channel 6 through calculation. The left h1 time was collected from the remaining 11 channels. The amplitudes at these time points were extracted as the h1 amplitudes for each channel. However, the pulse width could not be calculated accurately at 12 points. Consequently, a bioharmonic spline interpolation algorithm was used to interpolate the h1 amplitude data obtained from the horizontal and vertical points, yielding 651 (31 × 21) h1 amplitude data. The 651 data points were converted into a heat map to intuitively calculate the pulse width. The pulse width was calculated by multiplying the number of grids on the vertical axis with the unit length of the grid. The pulse width was determined by TCM doctors to verify the pulse width measurement accuracy. Meanwhile, a color Doppler ultrasound examination of the volunteers' radial arteries was performed and the intravascular meridian widths of the radial artery compared with the calculated pulse widths to determine the reliability. RESULTS: The pulse width determined using the maximal h1 amplitude method was comparable with the radial artery intravascular meridian widths measured using color Doppler ultrasound. The h1 amplitude was higher in the high blood pressure group and the pulse width was greater. CONCLUSIONS: The pulse width determined using the maximal h1 amplitude was objective and accurate. Comparison between the pulse widths of the normal and high blood pressure groups verified the reliability of the method.

Distribution characteristics of oral microbiota and its relationship with intestinal microbiota in patients with type 2 diabetes mellitus.

Introduction: Type 2 diabetes mellitus (T2DM) has a high incidence rate globally, increasing the burden of death, disability, and the economy worldwide. Previous studies have found that the compositions of oral and intestinal microbiota changed respectively in T2DM; whether the changes were associated or interacted between the two sites and whether there were some associations between T2DM and the ectopic colonization of oral microbiota in the gut still need to be identified. Research design and methods: We performed a cross-sectional observational study; 183 diabetes and 74 controls were enrolled. We used high-throughput sequencing technology to detect the V3-V4 region of 16S rRNA in oral and stool samples. The Source Tracker method was used to identify the proportion of the intestinal microbiota that ectopic colonized from the oral cavity. Results: The oral marker bacteria of T2DM were found, such as Actinobacteria, Streptococcus, Rothia, and the intestinal marker bacteria were Bifidobacterium, Streptococcus, and Blautia at the genus level. Among them, Actinobacteria and Blautia played a vital role in different symbiotic relationships of oral and intestinal microbiota. The commonly distributed bacteria, such as Firmicutes, Bacteroidetes, and Actinobacteria, were found in both oral and intestine. Moreover, the relative abundance and composition of bacteria were different between the two sites. The glycine betaine degradation I pathway was the significantly up-regulated pathway in the oral and intestinal flora of T2DM. The main serum indexes related to oral and intestinal flora were inflammatory. The relative abundance of Proteobacteria in the intestine and the Spirochete in oral was positively correlated, and the correlation coefficient was the highest, was 0.240 (P<0.01). The proportion of ectopic colonization of oral flora in the gut of T2DM was 2.36%. Conclusion: The dysbacteriosis exited in the oral and intestine simultaneously, and there were differences and connections in the flora composition at the two sites in T2DM. Ectopic colonization of oral flora in the intestine might relate to T2DM. Further, clarifying the oral-gut-transmitting bacteria can provide an essential reference for diagnosing and treating T2DM in the future.

Relationships Between Diurnal Changes of Tongue Coating Microbiota and Intestinal Microbiota.

The oral cavity and the intestine are the main distribution locations of human digestive bacteria. Exploring the relationships between the tongue coating and gut microbiota, the influence of the diurnal variations of the tongue coating microbiota on the intestinal microbiota can provide a reference for the development of the disease diagnosis and monitoring, as well as the medication time. In this work, a total of 39 healthy college students were recruited. We collected their tongue coating microbiota which was collected before and after sleep and fecal microbiota. The diurnal variations of tongue coating microbiota are mainly manifested on the changes in diversity and relative abundance. There are commensal bacteria in the tongue coating and intestines, especially Prevotella which has the higher proportion in both sites. The relative abundance of Prevotella in the tongue coating before sleep has a positive correlation with intestinal Prevotella; the r is 0.322 (p < 0.05). Bacteroides in the intestine had the most bacteria associated with the tongue coating and had the highest correlation coefficient with Veillonella in the oral cavity, which was 0.468 (p < 0.01). These results suggest that the abundance of the same flora in the two sites may have a common change trend. The SourceTracker results show that the proportion of intestinal bacteria sourced from tongue coating is less than 1%. It indicates that oral flora is difficult to colonize in the intestine in healthy people. This will provide a reference for the study on the oral and intestinal microbiota in diseases.

A Study of Logistic Regression for Fatigue Classification Based on Data of Tongue and Pulse.

Methods: The Tongue and Face Diagnosis Analysis-1 instrument and Pulse Diagnosis Analysis-1 instrument were used to collect the tongue image and sphygmogram of the subhealth fatigue population (n = 252) and disease fatigue population (n = 1160), and we mainly analyzed the tongue and pulse characteristics and constructed the classification model by using the logistic regression method. Results: The results showed that subhealth fatigue people and disease fatigue people had different characteristics of tongue and pulse, and the logistic regression model based on tongue and pulse data had a good classification effect. The accuracies of models of healthy controls and subhealth fatigue, subhealth fatigue and disease fatigue, and healthy controls and disease fatigue were 68.29%, 81.18%, and 84.73%, and the AUC was 0.698, 0.882, and 0.924, respectively. Conclusion: This study provided a new noninvasive method for the fatigue diagnosis from the perspective of objective tongue and pulse data, and the modern tongue diagnosis and pulse diagnosis have good application prospects.

Assessment Parameters for Arrayed Pulse Wave Analysis and Application in Hypertensive Disorders.

Study on the objectivity of pulse diagnosis is inseparable from the instruments to obtain the pulse waves. The single-pulse diagnostic instrument is relatively mature in acquiring and analysing pulse waves, but the pulse information captured by single-pulse diagnostic instrument is limited. The sensor arrays can simulate rich sense of the doctor's fingers and catch multipoint and multiparameter array signals. How to analyse the acquired array signals is still a major problem in the objective research of pulse diagnosis. The goal of this study was to establish methods for analysing arrayed pulse waves and preliminarily apply them in hypertensive disorders. While a sensor array can be used for the real-time monitoring of twelve pulse wave channels, for each subject in this study, only the pulse wave signals of the left hand at the "guan" location were obtained. We calculated the average pulse wave (APW) per channel over a thirty-second interval. The most representative pulse wave (MRPW) and the APW were matched by their correlation coefficient (CC). The features of the MRPW and the features that corresponded to the array pulse volume (APV) parameters were identified manually. Finally, a clinical trial was conducted to detect these feature performance indicators in patients with hypertensive disorders. The independent-samples t-tests and the Mann-Whitney U-tests were performed to assess the differences in these pulse parameters between the healthy and hypertensive groups. We found that the radial passage (RP) APV h1, APV h3, APV h4, APV h3/h1 (P < 0.01), and APV h4/h1 (P < 0.05) were significantly higher in the hypertensive group than in the healthy group; the intermediate passage (IP) APV h4, APV h3/h1 (P < 0.05), and APV h4/h1 (P < 0.01) and the mean APV h3, APV h3/h1 (P < 0.05), and APV h4/h1 (P < 0.01) were significantly higher in the hypertensive group than in the healthy group, and the ulnar passage (UP) APV h4/h1 (P < 0.05) was clearly elevated in the hypertensive group. These results provide a preliminary validation of this novel approach for determining the APV by arrayed pulse wave analysis. In conclusion, we identified effective indicators of hypertensive vascular function. Traditional Chinese medicine (TCM) pulses comprise multidimensional information, and a sensor array could provide a better indication of TCM pulse characteristics. In this study, the validation of the arrayed pulse wave analysis demonstrates that the APV can reliably mirror TCM pulse characteristics.

Correlation of myopia onset and progression with corneal biomechanical parameters in children.

BACKGROUND: Recent epidemiological studies have shown that general eye measurement parameters and corneal biomechanical properties can predict the speed of myopic progression in children. AIM: To investigate the correlation between the onset and progression of myopia and corneal biomechanical parameters in children. METHODS: The study included 102 cases in the emmetropia group, 207 cases in the myopic group, and 109 cases in the hyperopic group. The correlation between the change in corneal biomechanical indexes and the change in general ocular measurement parameters was analyzed. A one-way ANOVA test compared general ocular measurement and corneal biomechanical parameters. Pearson's correlation coefficient was analyzed to correlate corneal biomechanical and general ocular measurement parameters. RESULTS: The general ophthalmometric parameters: Spherical equivalent (SE), intraocular pressure (IOP), and axial length (AL), differed significantly among subjects in myopia, emmetropia, and hyperopic groups. Children's SE positively correlated with corneal biomechanical parameters: Second velocity of applanation (A2V), peak distance (PD), and deformation amplitude (DA) (P < 0.05), and second applanation length (A2L) (P < 0.05). But it was negatively correlated with PD, DA and integral radius (IR) (P < 0.05). Also, IOP was negatively correlated with A2L and IR (P < 0.05). AL positively correlated with A2V and negatively correlated with second applanation time (A2T), highest concavity, and PD. Central corneal thickness positively correlated with first applanation length, first applanation time, first applanation deformation amplitude, A2V, A2L, A2T, second applanation deformation amplitude, central curvature radius at highest concavity (HCR), PD, DA, IR, ambrosia relational thickness-horizontal, first applanation stiffness parameter, corvis biomechanical index, topographic and biomechanics index and the first velocity of applanation. The general ocular Km in children positively correlated with corneal biomechanical parameters DA and IR and negatively correlated with A2L, HCR, and PD. There was a positive correlation between the general ocular measurement parameters ΔSE and corneal biomechanical parameters ΔA2V and ΔA2L, and a negative correlation with ΔIR. The increase in general ocular measurement parameter ΔKm positively correlated with changes in corneal biomechanical parameters, ΔDA and ΔIR, and negatively correlated with ΔHCR and ΔPD. CONCLUSION: Myopia development in children was associated with multiple corneal biomechanical parameters.

A New Method for Syndrome Classification of Non-Small-Cell Lung Cancer Based on Data of Tongue and Pulse with Machine Learning.

OBJECTIVE: To explore the data characteristics of tongue and pulse of non-small-cell lung cancer with Qi deficiency syndrome and Yin deficiency syndrome, establish syndrome classification model based on data of tongue and pulse by using machine learning methods, and evaluate the feasibility of syndrome classification based on data of tongue and pulse. METHODS: We collected tongue and pulse of non-small-cell lung cancer patients with Qi deficiency syndrome (n = 163), patients with Yin deficiency syndrome (n = 174), and healthy controls (n = 185) using intelligent tongue diagnosis analysis instrument and pulse diagnosis analysis instrument, respectively. We described the characteristics and examined the correlation of data of tongue and pulse. Four machine learning methods, namely, random forest, logistic regression, support vector machine, and neural network, were used to establish the classification models based on symptom, tongue and pulse, and symptom and tongue and pulse, respectively. RESULTS: Significant difference indices of tongue diagnosis between Qi deficiency syndrome and Yin deficiency syndrome were TB-a, TB-S, TB-Cr, TC-a, TC-S, TC-Cr, perAll, and the tongue coating texture indices including TC-CON, TC-ASM, TC-MEAN, and TC-ENT. Significant difference indices of pulse diagnosis were t4 and t5. The classification performance of each model based on different datasets was as follows: tongue and pulse < symptom < symptom and tongue and pulse. The neural network model had a better classification performance for symptom and tongue and pulse datasets, with an area under the ROC curves and accuracy rate which were 0.9401 and 0.8806. CONCLUSIONS: It was feasible to use tongue data and pulse data as one of the objective diagnostic basis in Qi deficiency syndrome and Yin deficiency syndrome of non-small-cell lung cancer.

Application of computer tongue image analysis technology in the diagnosis of NAFLD.

Nonalcoholic fatty liver disease (NAFLD), a leading cause of chronic hepatic disease, can progress to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Therefore, it is extremely important to explore early diagnosis and screening methods. In this study, we developed models based on computer tongue image analysis technology to observe the tongue characteristics of 1778 participants (831 cases of NAFLD and 947 cases of non-NAFLD). Combining quantitative tongue image features, basic information, and serological indexes, including the hepatic steatosis index (HSI) and fatty liver index (FLI), we utilized machine learning methods, including Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Adaptive Boosting Algorithm (AdaBoost), Naïve Bayes, and Neural Network for NAFLD diagnosis. The best fusion model for diagnosing NAFLD by Logistic Regression, which contained the tongue image parameters, waist circumference, BMI, GGT, TG, and ALT/AST, achieved an AUC of 0.897 (95% CI, 0.882-0.911), an accuracy of 81.70% with a sensitivity of 77.62% and a specificity of 85.22%; in addition, the positive likelihood ratio and negative likelihood ratio were 5.25 and 0.26, respectively. The application of computer intelligent tongue diagnosis technology can improve the accuracy of NAFLD diagnosis and may provide a convenient technical reference for the establishment of early screening methods for NAFLD, which is worth further research and verification.

Acupuncture combined with western medicine for the treatment of hypertension: A protocol for an updated systematic review and meta-analysis.

BACKGROUND: Hypertension is a kind of cardiovascular syndrome with the main clinical manifestation of continuous increase of systemic arterial blood pressure. Hypertension coexists with other cardiovascular risk factors and is an important risk factor for cardiovascular and cerebrovascular diseases. Acupuncture is an important part of Traditional Chinese Medicine intervention. The antihypertensive effect of acupuncture on hypertension is based on the neuroendocrine system, characterized by multichannel and multitarget. This study aims to provide latest and updated proof of systematic review to assess the effectiveness and safety of acupuncture for hypertension. METHODS: We will systematically search 9 databases from their inceptions to February 2021. Only randomized controlled trials of acupuncture combined with western medicine in the treatment of hypertension will meet the inclusion criteria. The main outcome measures we focus on include clinical efficacy, syndrome efficacy, Traditional Chinese Medicine syndrome score, diastolic and systolic blood pressure changes, blood pressure variability, heart rate variability, pulse rate variability, and adverse reactions. The research screening, data extraction, and risk of bias assessment will be employed by 2 reviewers independently, and disagreement will be decided by a third senior reviewer. The Revman 5.3 software will be used for meta-analysis. The confidence of proof will be rated adopting grading of recommendations assessment, development and evaluation tool and methodological quality of this research will be assessed using assessment of multiple systematic reviews-2 and risk of bias in systematic reviews. The publication quality will be evaluated by preferred reporting items for systematic reviews and meta-analyses (PRISMA). RESULTS: This systematic review (SR) will provide evidence-based medical evidence for hypertension therapy by acupuncture combined with western medicine and we will submit the findings of this SR for peer-review publication. CONCLUSIONS: This SR will provide latest and updated summary proof for assessing the effectiveness and safety of acupuncture for hypertension. REGISTRATION NUMBER: INPLASY 202150047.

Tongue image quality assessment based on a deep convolutional neural network.

BACKGROUND: Tongue diagnosis is an important research field of TCM diagnostic technology modernization. The quality of tongue images is the basis for constructing a standard dataset in the field of tongue diagnosis. To establish a standard tongue image database in the TCM industry, we need to evaluate the quality of a massive number of tongue images and add qualified images to the database. Therefore, an automatic, efficient and accurate quality control model is of significance to the development of intelligent tongue diagnosis technology for TCM. METHODS: Machine learning methods, including Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Adaptive Boosting Algorithm (Adaboost), Naïve Bayes, Decision Tree (DT), Residual Neural Network (ResNet), Convolution Neural Network developed by Visual Geometry Group at University of Oxford (VGG), and Densely Connected Convolutional Networks (DenseNet), were utilized to identify good-quality and poor-quality tongue images. Their performances were made comparisons by using metrics such as accuracy, precision, recall, and F1-Score. RESULTS: The experimental results showed that the accuracy of the three deep learning models was more than 96%, and the accuracy of ResNet-152 and DenseNet-169 was more than 98%. The model ResNet-152 obtained accuracy of 99.04%, precision of 99.05%, recall of 99.04%, and F1-score of 99.05%. The performances were better than performances of other eight models. The eight models are VGG-16, DenseNet-169, SVM, RF, GBDT, Adaboost, Naïve Bayes, and DT. ResNet-152 was selected as quality-screening model for tongue IQA. CONCLUSIONS: Our research findings demonstrate various CNN models in the decision-making process for the selection of tongue image quality assessment and indicate that applying deep learning methods, specifically deep CNNs, to evaluate poor-quality tongue images is feasible.

Two new xanthones, a new lignin, and twenty phenolic compounds from Smilax china and their NO production inhibitory activities.

Two new xanthones smilone A (1), smilone B (2), and a new lignin smilgnin A (3) were isolated from the rhizomes of Smilax china L., together with three known xanthones (4-6), four lignins (7-10), two flavones (11, 12), two stilbenoids (13, 14), and ten organic phenoloids (15-24). Of them, compounds 4-6 were isolated from the genus Smilax for the first time. The structures of 1-24 were elucidated by the extensive analysis of spectral data and compared with the literature. All compounds were evaluated for their inhibitory effects against LPS-induced NO production in RAW264.7 macrophages. Among them, compound 24 exhibited significant inhibitory activity against NO production (IC50 = 1.26 µM), while compounds 3, 6, and 7 showed weak activities at the concentration of 50 µM.[Formula: see text].

Tongue color clustering and visual application based on 2D information.

PURPOSE: Studies have shown the association between tongue color and diseases. To help clinicians make more objective and accurate decisions quickly, we take unsupervised learning to deal with the basic clustering of tongue color in a 2D way. METHODS: A total of 595 typical tongue images were analyzed. The 3D information extracted from the image was transformed into 2D information by principal component analysis (PCA). K-Means was applied for clustering into four diagnostic groups. The results were evaluated by clustering accuracy (CA), Jaccard similarity coefficient (JSC), and adjusted rand index (ARI). RESULTS: The new 2D information totally retained 89.63% original information in the L*a*b* color space. And our methods successfully classified tongue images into four clusters and the CA, ARI, and JSC were 89.04%, 0.721, and 0.890, respectively. CONCLUSIONS: The 2D information of tongue color can be used for clustering and to improve the visualization. K-Means combined with PCA could be used for tongue color classification and diagnosis. Methods in the paper might provide reference for the other research based on image diagnosis technology.

Algicidal bacterium CZBC1 inhibits the growth of Oscillatoria chlorina, Oscillatoria tenuis, and Oscillatoria planctonica.

Frequent harmful cyanobacteria blooms limit the sustainable development of aquaculture. Algicidal bacteria can efficiently control harmful algae without secondary pollution. The algicidal bacteria CZBC1 can lyse Oscillatoria spp. and other harmful cyanobacteria, but its effector mechanism and algicidal threshold are unknown. In this study, we examined the algicidal effect of CZBC1 on O. chlorina, O. tenuis, and O. planctonica by microscopic enumeration and scanning electron microscopy observation. Then, we examined the alginolytic effects of CZBC1 (concentrations 103-106 colony forming units (cfu)/mL) on these three species (concentrations 103-106 cells/mL) to determine the effective concentrations of CZBC1 for Oscillatoria spp. alginolysis. Results showed that CZBC1 can directly lyse O. chlorina and O. tenuis but indirectly lyse O. planctonica. When the initial concentration of CZBC1 was 106 cfu/mL, alginolytic effects were high for all three species at all concentrations, and the alginolytic rate could reach 100% in 3-9 days. When the initial concentration of CZBC1 was lower (103 cfu/mL), its inhibitory effects were delayed by 2-5 days, but the cell counts were significantly decreased compared with the control, evidencing significant alginolysis. In addition, the higher the concentration of the algicidal bacteria suspension, the more significant the alginolytic effects. Our results indicate that CZBC1 has different alginolytic mechanisms for O. chlorina, O. tenuis, and O. planctonica, and that different initial concentrations of CZBC1 have different alginolytic effects on these algal species.

Chest physiotherapy for the prevention of ventilator-associated pneumonia: A meta-analysis.

BACKGROUND: Ventilator-associated pneumonia (VAP) remains a frequent and severe complication in mechanically ventilated patients. We undertook a meta-analysis to evaluate the efficacy of chest physiotherapy (CPT) for the prevention of VAP. METHODS: A systematic literature search of PubMed and Embase databases were searched up until November 25, 2018 for published studies of mechanically ventilated patients comparing CPT with controls and reporting on the occurrence of VAP. Two authors independently selected studies and abstracted data on study quality and outcomes. We pooled data using random-effects models. RESULTS: A total of 6 randomized (n = 704) controlled trials were identified. CPT did not significantly reduce the incidence of VAP (risk ratio = 1.02; 95% confidence interval, 0.82-1.26; P = .87), but reduced hospital mortality (risk ratio = 0.68; 95% confidence interval, 0.48-0.95; P = .02). No significant differences were observed regarding intensive care unit mortality, length of intensive care unit stay, and duration of mechanical ventilation. CONCLUSIONS: CPT may not significantly reduce the incidence of VAP and alter other important clinical outcomes in adult patients receiving mechanical ventilation. However, the results should be interpreted cautiously owing to the heterogeneity and the limited trials. Further large-scale, well-designed randomized controlled trials are needed.

A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave.

OBJECTIVE: In this study, machine learning was utilized to classify and predict pulse wave of hypertensive group and healthy group and assess the risk of hypertension by observing the dynamic change of the pulse wave and provide an objective reference for clinical application of pulse diagnosis in traditional Chinese medicine (TCM). METHOD: The basic information from 450 hypertensive cases and 479 healthy cases was collected by self-developed H20 questionnaires and pulse wave information was acquired by self-developed pulse diagnostic instrument (PDA-1). H20 questionnaires and pulse wave information were used as input variables to obtain different machine learning classification models of hypertension. This method was aimed at analyzing the influence of pulse wave on the accuracy and stability of machine learning model, as well as the feature contribution of hypertension model after removing noise by K-means. RESULT: Compared with the classification results before removing noise, the accuracy and the area under the curve (AUC) had been improved. The accuracy rates of AdaBoost, Gradient Boosting, and Random Forest (RF) were 86.41%, 86.41%, and 85.33%, respectively. AUC were 0.86, 0.86, and 0.85, respectively. The maximum accuracy of SVM increased from 79.57% to 83.15%, and the AUC stability increased from 0.79 to 0.83. In addition, the features of importance on traditional statistics and machine learning were consistent. After removing noise, the features with large changes were h1/t1, w1/t, t, w2, h2, t1, and t5 in AdaBoost and Gradient Boosting (top10). The common variables for machine learning and traditional statistics were h1/t1, h5, t, Ad, BMI, and t2. CONCLUSION: Pulse wave-based diagnostic method of hypertension has significant value in reference. In view of the feasibility of digital-pulse-wave diagnosis and dynamically evaluating hypertension, it provides the research direction and foundation for Chinese medicine in the dynamic evaluation of modern disease diagnosis and curative effect.

Tongue Image Database Construction Based on the Expert Opinions: Assessment for Individual Agreement and Methods for Expert Selection.

This study aims at introducing a method for individual agreement evaluation to identify the discordant raters from the experts' group. We exclude those experts and decide the best experts selection method, so as to improve the reliability of the constructed tongue image database based on experts' opinions. Fifty experienced experts from the TCM diagnostic field all over China were invited to give ratings for 300 randomly selected tongue images. Gwet's AC1 (first-order agreement coefficient) was used to calculate the interrater and intrarater agreement. The optimization of the interrater agreement and the disagreement score were put forward to evaluate the external consistency for individual expert. The proposed method could successfully optimize the interrater agreement. By comparing three experts' selection methods, the interrater agreement was, respectively, increased from 0.53 [0.32-0.75] for original one to 0.64 [0.39-0.80] using method A (inclusion of experts whose intrarater agreement>0.6), 0.69 [0.63-0.81] using method B (inclusion of experts whose disagreement score="0"), and 0.76 [0.67-0.83] using method C (inclusion of experts whose intrarater agreement>0.6& disagreement score="0"). In this study, we provide an estimate of external consistency for individual expert, and the comprehensive consideration of both the internal consistency and the external consistency for each expert would be superior to either one in the tongue image construction based on expert opinions.

Pulse Wave Cycle Features Analysis of Different Blood Pressure Grades in the Elderly.

BACKGROUND AND OBJECTIVE: The same range of blood pressure values may reflect different vascular functions, especially in the elderly. Therefore, a single blood pressure value may not comprehensively reveal cardiovascular function. This study focused on identifying pulse wave features in the elderly that can be used to show functional differences when blood pressure values are in the same range. METHODS: First, pulse data were preprocessed and pulse cycles were segmented. Second, time domain, higher-order statistics, and energy features of wavelet packet decomposition coefficients were extracted. Finally, useful pulse wave features were evaluated using a feature selection and classifier design. RESULTS: A total of 6,075 pulse wave cycles were grouped into 3 types according to different blood pressure levels and each group was divided into 2 categories according to a history of hypertension. The classification accuracy of feature selection in the 3 groups was 97.91%, 95.24%, and 92.28%, respectively. CONCLUSION: Selected features could be appropriately used to analyze cardiovascular function in the elderly and can serve as the basis for research on a cardiovascular risk assessment model based on Traditional Chinese Medicine pulse diagnosis.

Genistein Promotes Proliferation of Human Cervical Cancer Cells Through Estrogen Receptor-Mediated PI3K/Akt-NF-κB Pathway.

Phytoestrogens are polyphenol compounds which have similar structure to 17ß-estradiol (E2), a kind of main estrogen in women. Thus, phytoestrogens may affect the reproductive and endocrine systems, leading to the development of estrogen-related cancers. The effect of genistein (Gen), one of the most studied phytoestrogens, on human cervical cancer cells (HeLa) was investigated in this study. It was found that Gen at concentrations of 0.001, 0.01, 0.1 and 1 µmol·L-1 promoted the proliferation of HeLa cells in a dose-dependent manner. Gen increased the portion of HeLa cells in S phase and decreased the portion of the cells in G1 phase. Besides, apoptosis rate of the cells was significantly lower when treated with Gen compared with the control group. It was also found that the expression of ERα, Akt or nuclear NF-κB p65 protein was activated by Gen. The correlation between these three proteins may be as following: ERα was the upstream, followed by Akt, and then nuclear NF-κB p65 protein. In addition, the downstream genes of activated nuclear NF-κB p65 were found to be associated with cell cycle and apoptosis of cancer cells. Our results suggested that Gen may stimulate cell proliferation partially through the estrogen receptor-mediated PI3K/Akt-NF-κB pathway and the further activation of the downstream genes of nuclear NF-κB p65.

The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.

Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods. Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L*a*b* of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results. The L*a*b* values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions. At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible.

Inhibitory Effects of Enterolactone on Growth and Metastasis in Human Breast Cancer.

A lignan-rich diet is associated with a lower risk of human breast cancer. Enterolactone, an active polyphenol metabolites of lignan, was reported to have an antitumor effect. We investigated the mechanism for the effect of enterolactone against human breast cancer. Cellular changes, and associated genes induced by enterolactone, were investigated in MDA-MB-231 cells. Enterolactone showed an antiproliferative effect, and its IC50 was 261.9 ± 10.5 µM for a treatment period of 48 hr. The mRNA levels of the genes related to cell proliferation, Ki67, PCNA, and FoxM1, were reduced. Enterolactone induced accumulation of cells in the S phase, and a lower expression of Cyclin E1, Cyclin A2, Cyclin B1, and Cyclin B2 genes. There were almost no changes in the transcription levels of the genes that participate in G0/G1 phase regulation, CDK4, CDK6, and Cyclin D1. Furthermore, enterolactone interfered with the cytoskeleton by downregulating phosphorylation of the FAK/paxillin pathway, inhibiting migration and invasion of cells. The results suggest that enterolactone exerts an antitumor effect by regulating the expression of genes associated with cell proliferation and the cell cycle and by blocking the FAK/paxillin signaling pathway. These findings provide new insights into the molecular mechanisms behind the antitumor effect of enterolactone.