Lactiplantibacillus plantarum AR113 alleviates microbiota dysbiosis of tongue coating and cerebral ischemia/reperfusion injury in rat

Stroke is one of the leading causes of death and disability worldwide.However,information on stroke-related tongue coating microbiome(TCM)is limited,and whether TCM modulation could benefit for stroke prevention and rehabilitation is unknown.Here,TCM from stroke patients(SP)was characterized using molecular techniques.The occurrence of stroke resulted in TCM dysbiosis with significantly reduced species richness and diversity.The abundance of Prevotella,Leptotrichia,Actinomyces,Alloprevotella,Haemophilus,and TM7_[G-1]were greatly reduced,but common infection Streptococcus and Pseudomonas were remarkably increased.Furthermore,an antioxidative probiotic Lactiplantibacillus plantarum AR113 was used for TCM intervention in stroke rats with cerebral ischemia/reperfusion(I/R).AR113 partly restored I/R induced change of TCM and gut microbiota with significantly improved neurological deficit,relieved histopathologic change,increased activities of antioxidant enzymes,and decreased contents of oxidative stress biomarkers.Moreover,the gene expression of antioxidant-related proteins and apoptosis-related factors heme oxygenase-1(HO-1),superoxide dismutase(SOD),glutathione peroxidase(GSH-Px),nuclear factor erythroid 2-related factor 2(Nrf2),NAD(P)H:quinone oxidoreductase-1(NQO-1),and Bcl-2 was significantly increased,but cytochrome C,cleaved caspase-3,and Bax were markedly decreased in the brain by AR113 treatment.The results suggested that AR113 could ameliorate cerebral I/R injury through antioxidation and anti-apoptosis pathways,and AR113 intervention of TCM may have the application potential for stroke prevention and control.

Application value of tongue coating microflora in integration of traditional Chinese medicine and modern medicine

Observation of tongue coating is the characteristic content of traditional Chinese medicine syndrome differentiation and treatment. The microflora is the important component of tongue coating besides the desquamated epithelial cells. Tongue coating microflora might be an important linkage between the modern medical research and the classic traditional Chinese medicine theory. Therefore, the present paper summarised the application value of tongue coating microflora in health and disease to enrich the scienti fic connotation of traditional Chinese medicine tongue diagnosis and promote the development of integration of traditional Chinese medicine and modern medicine.

Study on Tongue Coating Microbiota in Patients with Atrophic Gastritis

Aims: To explore the tongue coating microbiota composition in patients with atrophic gastritis by using the 16S rRNA gene sequencing technology. Methods: The study included 29 atrophic gastritis patients and 29 age and gender-matched non-atrophic gastritis controls. By sequencing the V3-V4 region of the 16S rRNA, we investigated the microbial community structure and diversity on the tongue coating. Results: There was no significant difference in the microbial diversity on the tongue coating between the two groups. However, compared with the control, the atrophic gastritis group had a smaller number of operational taxonomic units (OTUs). At the class level, patients with atrophic gastritis had lower relative abundances of Betaproteobacteria and Spirochaetia than the control group. At the gene level, the abundance of Neisseria and Aggregatibacter in atrophic gastritis group had significantly decreased compared with control ones. Furthermore, functional prediction revealed that 24 metabolic pathways significantly differed between the two groups. Conclusions: Our findings provide novel evidence that tongue coating microbiota may be a biomarker for characterizing patient with atrophic gastritis, but its mechanism needs to be further elaborated.

Thick tongue coating: diagnostic markers for metastatic colorectal cancer?

Background:According to World Health Organization,colorectal cancer is the third most common cancer in the world.The prognosis assessment and condition judgment of the colorectal cancer remains a challenge clinically.Therefore,identification of diagnostic markers to evaluate the prognosis of colorectal cancer clinically should be urgently developed.We have observed that a lot of cancer patients had thick tongue clinically,but what is the relationship between tongue coating and the tumor?Methods:Seventy-four patients with colorectal carcinoma were collected through the outpatients of Tianjin Medical University Cancer Institute and Hospital from May 2010 to September 2011,in which there were 49 patients confirmed with recurrence or metastasis.All photos of patients’tongue were taken with a SONY camera in the same room and under constant conditions such as brightness or distance.Regression equation predicting thickness of tongue coating was constructed using binary logistic regression analysis.The optimal cut off of probabilities to diagnosis thick tongue coating was determined by receiver operating curve analysis.χ2 test for paired data and kappa test were used to determine the diagnostic value for recurrence and/or metastasis in colorectal cancer patients.Kolmogorov-Smirnov test was used to determine the distribution of ALT,AST,ALP ALB,TP,GLO,TBIL,DBIL,GGT,LDH,GLU,UA,CA724,CA199,CA242 and CEA.Data with the skewed distribution were presented as median(quartile interval).The association between the thickness of tongue coating and clinical-pathological character was evaluated by chi square test and two-independent-sample test.The two-independent-samplesχ2 was used to determine whether there were significant differences in the thin coating and thick coating between patients with recurrence and/or metastasis and patients without recurrence and/or metastasis.Kaplan-Meier method was used to analyze survival time.Statistical analysis was performed by SPSS(version 16.0).Results:Through retrospective clinical study we found that overall survival of colorectal cancer patients with thick greasy tongue coating is less than the patients with less tongue coating.What’s more,the risk for recurrence or/and metastasis overall survival in thick coating group was higher than thin coating group.In addition,the histological staining of the tongue slices of rats showed that EGFR receptors in the tongue root were the most among whole tongue surface.Tongue thick coating may be due to tumor patients with high levels of serum EGF which results in significantly increasing tongue coating.This finding suggested that the tongue coating of cancer patients may reflect the level of serum EGF levels in patients which may be related to shorter survival time.In addition,another study showed that serum lactic dehydrogenase level in patients with thick tongue coating is higher than patients with thin tongue coating.Conclusions:These studies suggest that tongue coating is likely to reflect some of the growth factor and enzyme levels.By observing the tongue coating we could predict the prognosis of patients and the characteristics of tongue coating may be used as new diagnostic markers to patients with colorectal carcinoma.

Deep learning-based recognition of stained tongue coating images

Objective To build a dataset encompassing a large number of stained tongue coating images and process it using deep learning to automatically recognize stained tongue coating images.Methods A total of 1001 images of stained tongue coating from healthy students at Hunan University of Chinese Medicine and 1007 images of pathological(non-stained)tongue coat-ing from hospitalized patients at The First Hospital of Hunan University of Chinese Medicine withlungcancer;diabetes;andhypertensionwerecollected.Thetongueimageswererandomi-zed into the training;validation;and testing datasets in a 7:2:1 ratio.A deep learning model was constructed using the ResNet50 for recognizing stained tongue coating in the training and validation datasets.The training period was 90 epochs.The model’s performance was evaluated by its accuracy;loss curve;recall;F1 score;confusion matrix;receiver operating characteristic(ROC)curve;and precision-recall(PR)curve in the tasks of predicting stained tongue coating images in the testing dataset.The accuracy of the deep learning model was compared with that of attending physicians of traditional Chinese medicine(TCM).Results The training results showed that after 90 epochs;the model presented an excellent classification performance.The loss curve and accuracy were stable;showing no signs of overfitting.The model achieved an accuracy;recall;and F1 score of 92%;91%;and 92%;re-spectively.The confusion matrix revealed an accuracy of 92%for the model and 69%for TCM practitioners.The areas under the ROC and PR curves were 0.97 and 0.95;respectively.Conclusion The deep learning model constructed using ResNet50 can effectively recognize stained coating images with greater accuracy than visual inspection of TCM practitioners.This model has the potential to assist doctors in identifying false tongue coating and prevent-ing misdiagnosis.

Automatic Extraction of Tongue Coatings from Digital Images:A Traditional Chinese Medicine Diagnostic Tool

In traditional Chinese medicine, the coating on the tongue is considered to be a reflection of various pathologic factors. However, the conventional method to examine the tongue lacks an acceptable standard and does not provide the means for sharing information. This paper describes a segmentation method to extract tongue coatings. First, the tongue body was extracted from the original image using the watershed transform. Then, a threshold method was applied to the image to eliminate the light from the camera flash. Finally, a threshold method using the Otsu model in combination with a splitting-merging method was used in the red, green, and blue （RGB） space to extract the thin coating. The combination of the above two methods is applied in the hue, saturation, and value （HSV） space to extract the thick coating. The feasibility of this method is tested by experiments, and the accuracy of segmentation is 95.9%.

Potential Role of EGF and EGFR in Tongue Coating Formation

Tongue coating, as a sensitive index of the physiological and pathological changes of human organs, is an important basis for the Traditional Chinese Medicine(TCM) syndrome differentiation and treatment. Mechanism of the formation and change of tongue coating is an important scientific problem. In recent years, researches indicated that in addition to apoptosis related genes, epidermal growth factor(EGF) and epidermal growth factor receptor(EGFR) also contribute to tongue coating formation. In this paper, we summarized recent studies on the potential role of EGF and EGFR in regulating the formation of tongue coating to provide some reference for the further investigations on tongue coating formation mechanisms.