Species composition and overall diversity are significantly correlated between the tongue coating and gastric fluid microbiomes in gastritis patients

Characteristics of tongue images and tongue coating bacteria in patients with colorectal cancer

BACKGROUND

Tongue diagnosis can assess the physiological functions and pathological conditions of colorectal cancer (CRC).

OBJECTIVE

To investigate the characteristics of tongue images and the bacteria composition of tongue coating in patients with CRC.

METHODS

A total of 59 CRC patients were enrolled and underwent tongue image analysis using a diagnostic instrument. Third-generation sequencing technique was used to determine tongue coating bacteria. The relationships among tongue images, tongue coating bacteria and clinical information (age, gender, and location) were further analyzed. Statistical analyses were performed to investigate the potential associations between tongue coating microbiota and two key variables (tongue images and age).

RESULTS

CRC patients typically present with four distinct tongue images, including yellow greasy coating, petechiae, white greasy coating, and red tongue with little coating. Notably, the microbiota composition of tongue coatings demonstrates a statistically significant correlation with both tongue diagnostic features and patient age compared to other clinical parameters. Alloprevotella rava may be primary contributors to the formation of yellow greasy coating, while Prevotella intermedia appears to be associated with the development of white greasy coating. Furthermore, Streptococcus parasanguinis might emerged as a potential biomarker for CRC patients under 62 years of age, whereas Prevotella sp. 000163055 appears to be a predominant species in the tongue coating microbiota of CRC patients over 62 years.

CONCLUSION

Overall, this study emphasizes the variations in the community structure and diversity of tongue coating bacteria in CRC patients through different tongue images. The findings provide novel insights that could enhance the predictive capacity of tongue diagnosis for clinical progression monitoring and contribute to the development of early intervention strategies in CRC management.

Metagenomic and single-cell RNA-Seq survey of the Helicobacter pylori-infected stomach in asymptomatic individuals

Helicobacter pylori colonization of the gastric niche can persist for years in asymptomatic individuals. To deeply characterize the host-microbiota environment in H. pylori-infected (HPI) stomachs, we collected human gastric tissues and performed metagenomic sequencing, single-cell RNA-Seq (scRNA-Seq), flow cytometry, and fluorescent microscopy. HPI asymptomatic individuals had dramatic changes in the composition of gastric microbiome and immune cells compared with noninfected individuals. Metagenomic analysis uncovered pathway alterations related to metabolism and immune response. scRNA-Seq and flow cytometry data revealed that, in contrast to murine stomachs, ILC2s are virtually absent in the human gastric mucosa, whereas ILC3s are the dominant population. Specifically, proportion of NKp44+ ILC3s out of total ILCs were highly increased in the gastric mucosa of asymptomatic HPI individuals, and correlated with the abundance of selected microbial taxa. In addition, CD11c+ myeloid cells and activated CD4+ T cells and B cells were expanded in HPI individuals. B cells of HPI individuals acquired an activated phenotype and progressed into a highly proliferating germinal-center stage and plasmablast maturation, which correlated with the presence of tertiary lymphoid structures within the gastric lamina propria. Our study provides a comprehensive atlas of the gastric mucosa-associated microbiome and immune cell landscape when comparing asymptomatic HPI and uninfected individuals.

Construction of Tongue Image-Based Machine Learning Model for Screening Patients with Gastric Precancerous Lesions

Screening patients with precancerous lesions of gastric cancer (PLGC) is important for gastric cancer prevention. The accuracy and convenience of PLGC screening could be improved with the use of machine learning methodologies to uncover and integrate valuable characteristics of noninvasive medical images related to PLGC. In this study, we therefore focused on tongue images and for the first time constructed a tongue image-based PLGC screening deep learning model (AITongue). The AITongue model uncovered potential associations between tongue image characteristics and PLGC, and integrated canonical risk factors, including age, sex, and Hp infection. Five-fold cross validation analysis on an independent cohort of 1995 patients revealed the AITongue model could screen PLGC individuals with an AUC of 0.75, 10.3% higher than that of the model with only including canonical risk factors. Of note, we investigated the value of the AITongue model in predicting PLGC risk by establishing a prospective PLGC follow-up cohort, reaching an AUC of 0.71. In addition, we developed a smartphone-based app screening system to enhance the application convenience of the AITongue model in the natural population from high-risk areas of gastric cancer in China. Collectively, our study has demonstrated the value of tongue image characteristics in PLGC screening and risk prediction.

Study on syndrome rules of stagnated heat in liver and stomach of non-erosive reflux disease based on microecology of tongue coating

INTRODUCTION

At present, the pathogenesis of non-erosive reflux disease (NERD) is still unclear, and proton pump inhibitors are the main treatment drug. However, the effect is limited. Traditional Chinese medicine treatment of NERD has advantages. Stagnated heat in liver and stomach syndrome is the most important traditional Chinese medicine syndrome type of this disease. Tongue diagnosis is an important basis for the diagnosis of stagnated heat in liver and stomach syndrome. The microecology of tongue coating suggests the occurrence and development of disease. The purpose of this study aims to clarify the regular changes of tongue coating microecology in stagnated heat in liver and stomach syndrome of NERD.

METHODS AND ANALYSIS

This is a cross-sectional clinical trial. This study is divided into NERD stagnated heat in liver and stomach syndrome group, qi stagnation, and phlegm obstruction syndrome control group and normal control group, with 20 cases in each group. Tongue coating samples will be collected from 3 groups, and 16SrRNA gene sequencing technology will be used to detect the genome of tongue coating flora in patients with NERD with stagnated heat in liver and stomach syndrome, control group with qi stagnation and phlegm obstruction syndrome and normal control group. The main outcome measures are the distribution, diversity, and richness of the tongue flora in patients and healthy controls.

DISCUSSION

The results of this study will clarify the internal relationship between NERD stagnated heat in liver and stomach syndrome and the microecological changes in tongue coating.