Traditional Chinese Medicine Syndrome Differentiation of Delta and Omicron Variants of SARS-CoV-2 Carriers in Changsha,Hunan.

Objective: To summarize and compare the main traditional Chinese medicineTCMsyndromes of Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2SARS-CoV-2 carriers to provide references for the syndrome evolution and syndrome differentiation of SARS-CoV-2 infection. Method(s):The TCM medical records of imported and local cases of infection with Delta and Omicron variants of SARS-CoV-2 in Changsha since September 23,2021 to March 27,2022 were collected,including 18 Delta variant cases and 36 Omicron variant cases. Their TCM diagnosis information and TCM pathogenesis were analyzed and compared. Result(s): The common manifestations in Delta variant cases were cough,fever,chest distress/shortness of breath,sore muscles,nausea,dry mouth,dry or sore throat,thick and greasy tongue coating,and rapid and slippery pulse. The predominant pathogenesis was dampness-heat in the upper-energizer and heat stagnation in the lesser Yang combined with dampness. The occurrence of chest distress/shortness of breath,greasy tongue coating,slippery pulse,and the proportion of dampness-heat in the upper-energizer syndrome were higher in Delta variant cases than in Omicron variant cases P<0.05. The common manifestations in Omicron variant cases were itchy and sore throat,nasal congestion,running nose,fever,mild aversion to cold,dry mouth,dizziness,slightly reddish tongue with thin white coating,and rapid or wiry pulse. The predominant pathogenesis was wind-dryness invading defensive exterior,and heat stagnation in the lesser Yang. The occurrence of white-coated tongue and the proportion of wind-dryness invading defensive exterior syndrome were higher in Omicron variant cases than in Delta variant casesP<0.05. Conclusion(s): There are certain differences in TCM syndromes and the corresponding pathogenesis between Delta variant and Omicron variant cases in Changsha,Hunan. The Delta variant of SARS-COV-2 tends to induce dampness-heat syndrome, whereas Omicron variant infection tends to elicit wind-dampness syndrome,which is expected to provide a reference for the pathogenesis evolution of SARS-COV-2 infection.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

Microbiological characteristics of different tongue coatings in adults.

BACKGROUND: Tongue coating is an important health indicator in traditional Chinese medicine (TCM). The tongue coating microbiome can distinguish disease patients from healthy controls. To study the relationship between different types of tongue coatings and health, we analyzed the species composition of different types of tongue coatings and the co-occurrence relationships between microorganisms in Chinese adults. From June 2019 to October 2020, 158 adults from Hangzhou and Shaoxing City, Zhejiang Province, were enrolled. We classified the TCM tongue coatings into four different types: thin white tongue fur (TWF), thin yellow tongue fur (TYF), white greasy tongue fur (WGF), and yellow greasy tongue fur (YGF). Tongue coating specimens were collected and used for 16S rRNA gene sequencing using the Illumina MiSeq system. Wilcoxon rank-sum and permutational multivariate analysis of variance tests were used to analyze the data. The microbial networks in the four types of tongue coatings were inferred independently using sparse inverse covariance estimation for ecological association inference. RESULTS: The microbial composition was similar among the different tongue coatings; however, the abundance of microorganisms differed. TWF had a higher abundance of Fusobacterium periodonticum and Neisseria mucosa, the highest α-diversity, and a highly connected community (average degree = 3.59, average closeness centrality = 0.33). TYF had the lowest α-diversity, but the most species in the co-occurrence network diagram (number of nodes = 88). The platelet-to-lymphocyte ratio (PLR) was associated with tongue coating (P = 0.035), and the YGF and TYF groups had higher PLR values. In the co-occurrence network, Aggregatibacter segnis was the "driver species" of the TWF and TYF groups and correlated with C-reactive protein (P < 0.05). Streptococcus anginosus was the "driver species" in the YGF and TWF groups and was positively correlated with body mass index and weight (P < 0.05). CONCLUSION: Different tongue coatings have similar microbial compositions but different abundances of certain bacteria. The co-occurrence of microorganisms in the different tongue coatings also varies. The significance of different tongue coatings in TCM theory is consistent with the characteristics and roles of the corresponding tongue-coating microbes. This further supports considering tongue coating as a risk factor for disease.

Constructing tongue coating recognition model using deep transfer learning to assist syndrome diagnosis and its potential in noninvasive ethnopharmacological evaluation.

ETHNOPHARMACOLOGICAL RELEVANCE: Tongue coating has been used as an effective signature of health in traditional Chinese medicine (TCM). The level of greasy coating closely relates to the strength of dampness or pathogenic qi in TCM theory. Previous empirical studies and our systematic review have shown the relation between greasy coating and various diseases, including gastroenteropathy, coronary heart disease, and coronavirus disease 2019 (COVID-19). However, the objective and intelligent greasy coating and related diseases recognition methods are still lacking. The construction of the artificial intelligent tongue recognition models may provide important syndrome diagnosis and efficacy evaluation methods, and contribute to the understanding of ethnopharmacological mechanisms based on TCM theory. AIM OF THE STUDY: The present study aimed to develop an artificial intelligent model for greasy tongue coating recognition and explore its application in COVID-19. MATERIALS AND METHODS: Herein, we developed greasy tongue coating recognition networks (GreasyCoatNet) using convolutional neural network technique and a relatively large (N = 1486) set of tongue images from standard devices. Tests were performed using both cross-validation procedures and a new dataset (N = 50) captured by common cameras. Besides, the accuracy and time efficiency comparisons between the GreasyCoatNet and doctors were also conducted. Finally, the model was transferred to recognize the greasy coating level of COVID-19. RESULTS: The overall accuracy in 3-level greasy coating classification with cross-validation was 88.8% and accuracy on new dataset was 82.0%, indicating that GreasyCoatNet can obtain robust greasy coating estimates from diverse datasets. In addition, we conducted user study to confirm that our GreasyCoatNet outperforms TCM practitioners, yet only consuming roughly 1% of doctors' examination time. Critically, we demonstrated that GreasyCoatNet, along with transfer learning, can construct more proper classifier of COVID-19, compared to directly training classifier on patient versus control datasets. We, therefore, derived a disease-specific deep learning network by finetuning the generic GreasyCoatNet. CONCLUSIONS: Our framework may provide an important research paradigm for differentiating tongue characteristics, diagnosing TCM syndrome, tracking disease progression, and evaluating intervention efficacy, exhibiting its unique potential in clinical applications.

Existence of SARS-CoV-2 Entry Molecules in the Oral Cavity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor, angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2 (TMPRSS2), and furin, which promote entry of the virus into the host cell, have been identified as determinants of SARS-CoV-2 infection. Dorsal tongue and gingiva, saliva, and tongue coating samples were examined to determine the presence of these molecules in the oral cavity. Immunohistochemical analyses showed that ACE2 was expressed in the stratified squamous epithelium of the dorsal tongue and gingiva. TMPRSS2 was strongly expressed in stratified squamous epithelium in the keratinized surface layer and detected in the saliva and tongue coating samples via Western blot. Furin was localized mainly in the lower layer of stratified squamous epithelium and detected in the saliva but not tongue coating. ACE2, TMPRSS2, and furin mRNA expression was observed in taste bud-derived cultured cells, which was similar to the immunofluorescence observations. These data showed that essential molecules for SARS-CoV-2 infection were abundant in the oral cavity. However, the database analysis showed that saliva also contains many protease inhibitors. Therefore, although the oral cavity may be the entry route for SARS-CoV-2, other factors including protease inhibitors in the saliva that inhibit viral entry should be considered.