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.

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.

Discovery of hCES2A inhibitors from Glycyrrhiza inflata via combination of docking-based virtual screening and fluorescence-based inhibition assays.

Human carboxylesterase 2 (hCES2A) is a key target to ameliorate the intestinal toxicity triggered by irinotecan that causes severe diarrhea in 50%-80% of patients receiving this anticancer agent. Herbal medicines are frequently used for the prevention and treatment of the intestinal toxicity of irinotecan, but it is very hard to find strong hCES2A inhibitors from herbal medicines in an efficient way. Herein, an integrated strategy via combination of chemical profiling, docking-based virtual screening and fluorescence-based high-throughput inhibitor screening assays was utilized. Following the screening of a total of 73 herbal products, licorice (the dried root of Glycyrrhiza species) was found with the most potent hCES2A inhibition activity. Further investigation revealed that the chalcones and several flavonols in licorice displayed strong hCES2A inhibition activities, while isoliquiritigenin, echinatin, naringenin, gancaonin I and glycycoumarin exhibited moderate inhibition of hCES2A. Inhibition kinetic analysis demonstrated that licochalcone A, licochalcone C, licochalcone D and isolicoflavonol potently inhibited hCES2A-mediated fluorescein diacetate hydrolysis in a reversible and mixed inhibition manner, with Ki values less than 1.0 µM. Further investigations demonstrated that licochalcone C, the most potent hCES2A inhibitor identified from licorice, dose-dependently inhibited intracellular hCES2A in living HepG2 cells. In summary, this study proposed an integrated strategy to find hCES2A inhibitors from herbal medicines, and our findings suggested that the chalcones and isolicoflavonol in licorice were the key ingredients responsible for hCES2A inhibition, which would be very helpful to develop new herbal remedies or drugs for ameliorating hCES2A-associated drug toxicity.

[Analysis on pulse diagram characteristics of subjects with subhealth state].

OBJECTIVE: To study the pulse diagram parameters of subjects with subhealth state and to find the pulse parameters for subhealth state evaluation. METHODS: A total of 1 275 subjects without diagnosed diseases were recruited and their health conditions were assessed with Health Evaluating Questionnaire H20 V2009. The subjects were assigned to health group or subhealth group according to the scale score. Subjects' syndrome in the subhealth group was differentiated using score of "subhealth state of syndrome differentiation V2010". Another 121 patients with cardiovascular diseases were enrolled as a control. The pulse information was collected with YJJ-101 subhealth pulse monitoring system and the parameters include amplitude of main wave (h1), amplitude of repeat wave (h5) and its front wave (h3), 1/3 or 1/5 width of main wave (w1) or (w2), time of rapid ejection phase (t2), period of pulse (t), pulse pressure (Pp), square (S), area in systole (As) and area in diastole (Ad) of pulse diagram and ratios of h3/h1, h5/h1, w1/t, w2/t and h1/t1. RESULTS: Pulse diagram analysis showed significant differences among health, subhealth and disease group in Pp, h1, S and As and ratios of h5/h1 and w2/t. Compared with the health group, the values of w1/t and w2/t of the subhealth group increased (P<0.05), and Pp, h1, h5, h5/h1, S, As and Ad decreased (P<0.05). Compared with health group, the parameters of pulse of the subhealth group were increased in Pp and h5/h1 (P<0.05) and decreased in h1, w2/t, S and As (P<0.05). Compared with health group, pulse parameters h3/h1, w1, w1/t, w2/t of excess and deficiency syndrome group increased, and h1, h5, h1/t 1and h5/h1 decreased. Among different syndromes of subhealth state, pulse diagram parameters h1, h5, h3/h1, h5/h1 and w1/t of yin deficiency, qi deficiency, liver stagnation and excess heat group were significantly different (P<0.05) from the health group, for example, pulse parameters h1 and h5 of stagnation, yin deficiency, qi deficiency and excess heat group declined in order, and pulse parameters h3/h1 and w1/t of liver stagnation, excess heat, yin deficiency and qi deficiency group increased in order. Pulse index h1 in the kidney deficiency group was higher than that in the health group and the other syndrome groups. CONCLUSION: Results of analyzing sphygmogram parameters showed different characteristics among different health status and the subhealth state due to different syndromes. Sphygmogram parameters may be used for objective evaluation of health status or subhealth syndrome differentiation.

[Continuous bio-hydrogen production by mesophilic and thermophilic cultures].

Anaerobic biological hydrogen productions were achieved successfully in two lab-scale anaerobic hydrogen production reactors under mesophilic (37 degrees C) and thermophilic (55 degrees C) conditions, respectively. The mesophilic reactor, a CSTR, was operated over 4 months by seeding with river sediments and feeding with glucose solution, in which the highest hydrogen production rate was 8.6 L/(L x d) and the substrate hydrogen production molar ratio (H2/glucose) was 1.98. After seeded with anaerobic methanogenic granules, a UASB reactor was thermophilically operated by feeding with sucrose solution and during its steady operation period, the hydrogen production rate was 6.8 L/(L x d) and the substrate hydrogen production molar ratio (H2/sucrose) was 3.6. Within the produced gas, the H2 percentages were about 43% and others were CO2, no methane could be detected. Thermophilic hydrogen-producing granules were successfully cultivated in the UASB reactor, which were grey-white in color, the diameters were about 0.8 - 1.2 mm, and typical settling velocities were about 30 - 40 m/h. Through SEM a great number of bacilli could be found on the surface of the granules which made the surface rough. Total DNA of these two hydrogen production sludges were extracted and purified, and the PCR and DGGE process were conducted, the results indicate that most of the eubacteria in two sludges are the same, but the dominant species are obviously different with each other.