Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade

Oral bacteriome and mycobiome of patients with idiopathic membranous nephropathy with different tongue coatings treated with a Chinese herbal formula

ETHNOPHARMACOLOGICAL RELEVANCE

Moshen Fuyuan Formula (MSFY) is one of the representative Chinese medicine compound for Idiopathic membranous nephropathy (IMN), that originate from Fang Ji Huang Qi decoction in the Han dynasty. IMN is usually accompanied by different tongue coatings in traditional Chinese medicine (TCM), and tongue microorganisms are important factors affecting the formation of the tongue coating. Recently, oral microbiomes, including bacteria and fungi, have been identified as pivotal factors that contribute to disease development. However, the regulation of oral microbiomes by MSFY has not been defined.

AIM OF THE STUDY

In this work, we explore the characteristics of oral bacteria and fungi in IMN patients with different tongue coatings, and clarify the therapeutic effect of MSFY based on oral microbiome.

MATERIALS AND METHODS

We enrolled 24 patients with IMN, including 11 with white tongue (IMN-W) and 13 with yellow tongue (IMN-Y), and recruited an additional 10 healthy individuals. Patients with IMN were treated with the MSFY. The oral bacteriome and fungi before and after treatment were detected using full-length 16S rRNA and internal transcribed spacer gene sequencing.

RESULTS

The therapeutic effect of MSFY on patients with yellow tongue coating was more significant than that on patients with white tongue coating. In terms of oral bacteriome, Campylobacter bacteria were enriched in patients with yellow tongue and could be a promising biomarker for yellow coating. Enrichment of Veillonella parvula_A may partially account for the therapeutic effect of MSFY. As for oral fungi, Malassezia globosa was enhanced in patients with IMN-W and reduced in patients with IMN-Y. Notably, it was reduced by MSFY. We also found that mycobiome-bacteriome interactions were highly complex and dynamic in patients with IMN.

CONCLUSION

The regulation of the dynamic balance between oral fungi and bacteria by MSFY contributes to the treatment of IMN. This study determined the oral bacteriome and mycobiome of patients with IMN with different tongue coatings before and after MSFY treatment, which aids in promoting personalized treatment in clinical TCM and provides direction for investigating the mechanism of Chinese herbal medicines.

Bacteroides fragilis in saliva: investigating links with ulcerative colitis

BACKGROUND

Ulcerative colitis (UC) is a long-term bowel inflammation of unknown cause. Recent research points to gut microbiota, especially Enterotoxigenic Bacteroides fragilis (ETBF), in UC's development. This study examined the presence of Bacteroides fragilis (B. fragilis) and ETBF in the saliva of UC patients and Healthy Controls (HCs) in Iran.

METHODS

A total of 40 UC patients and 40 healthy controls were included in the study. Saliva samples were collected and analyzed for the presence of B. fragilis and ETBF using real-time polymerase chain reaction (PCR).

RESULTS

B. fragilis was more prevalent in HCs (70%) than UC patients (67.5%), but not significantly (p = 0.809). ETBF was significantly more prevalent in UC patients (50%) than HCs (10%) (p < 0.0001). The mean count of B. fragilis was higher in UC patients, but not significantly (p = 0.47). However, the mean count of ETBF was significantly higher in UC patients (p = 0.000089). In terms of gender, the number of B. fragilis in women was not significant (p = 0.16), but the number of ETBF was significantly higher in women with UC (p = 0.000458). For men, no significant differences were observed.

CONCLUSIONS

The present study suggest a higher prevalence of B. fragilis observed in UC patients compared to HCs. Further research is needed to confirm these findings and explore potential mechanisms underlying this association.

Oral microbiota and gastric cancer: recent highlights and knowledge gaps

Gastric cancer is one of the most common malignant tumors worldwide and has a high mortality rate. However, tests for the early screening and diagnosis of gastric cancer are limited and invasive. Certain oral microorganisms are over-expressed in gastric cancer, but there is heterogeneity among different studies. Notably, each oral ecological niche harbors specific microorganisms. Among them, tongue coating, saliva, and dental plaque are important and unique ecological niches in the oral cavity. The colonization environment in different oral niches may be a source of heterogeneity. In this paper, we systematically discuss the latest developments in the field of the oral microbiota and gastric cancer and elucidate the enrichment of microorganisms in the oral ecological niches of the tongue coatings, saliva, and dental plaque in gastric cancer patients. The various potential mechanisms by which the oral microbiota induces gastric cancer (activation of an excessive inflammatory response; promotion of proliferation, migration, invasion, and metastasis; and secretion of carcinogens, leading to imbalance in gastric microbial communities) are explored. In this paper, we also highlight the applications of the rapeutics targeting the oral microbiota in gastric cancer and suggests future research directions related to the relationship between the oral microbiota and gastric cancer.

The metabolites mainly composed of lipids in tongue coating are non-invasive potential biomarkers for chronic gastritis

The changes in tongue coating metabolites in patients with chronic gastritis (CG) under different gastroscopy indicators were analyzed, and these metabolites were screened for potential non-invasive biomarkers to assist in the diagnosis of chronic gastritis. The technology of gas chromatography and liquid chromatography combined with mass spectrometry has been used to more comprehensively detect tongue coating metabolites of 350 CG patients. Spearman correlation analysis and random forest algorithm were used to screen metabolites that can serve as potential biomarkers. Compared with healthy individuals, CG group showed significant changes in the content of 101 metabolites, with an increase in the content of 54 metabolites and a decrease in the content of 47 metabolites. These differential metabolites are mainly composed of 47 lipids and lipid like substances. 1 metabolite was associated with bile reflux, 1 metabolite was associated with gastric mucosal erosion, 10 metabolites were associated with atrophy, 10 metabolites were associated with intestinal metaplasia, and 3 metabolites were associated with Helicobacter pylori infection. The ROC model composed of 5 metabolites can distinguish between CG group and healthy individuals, with an accuracy of 95.4%. The ROC model composed of 5,6-Dihydroxyindole can distinguish between chronic superficial gastritis group and chronic atrophic gastritis group, with an accuracy of 75.3%. The lipids and lipid like metabolites were the main abnormal metabolites in patients with chronic gastritis. It was worth noting that the content of Sphinganine 1-phase, 4-Ipomenol, and Nervonic acid in tongue coating increased, and the content of 1-Methyladenosine and 3-Hydroxycapric acid decreased, which helped to identify CG patients. The decrease in the content of 5,6-dihydroxyindole reminded patients that the development trend of CG was shifting from superficial to atrophic or even intestinal metaplasia. The detection of these metabolic markers of tongue coating was expected to be developed as a non-invasive and convenient technology in the future to assist us in monitoring and diagnosing the occurrence and development of CG.

S5Utis: Structured State-Space Sequence SegNeXt UNet-like Tongue Image Segmentation in Traditional Chinese Medicine

Intelligent Traditional Chinese Medicine can provide people with a convenient way to participate in daily health care. The ease of acceptance of Traditional Chinese Medicine is also a major advantage in promoting health management. In Traditional Chinese Medicine, tongue imaging is an important step in the examination process. The segmentation and processing of the tongue image directly affects the results of intelligent Traditional Chinese Medicine diagnosis. As intelligent Traditional Chinese Medicine continues to develop, remote diagnosis and patient participation will play important roles. Smartphone sensor cameras can provide irreplaceable data collection capabilities in enhancing interaction in smart Traditional Chinese Medicine. However, these factors lead to differences in the size and quality of the captured images due to factors such as differences in shooting equipment, professionalism of the photographer, and the subject's cooperation. Most current tongue image segmentation algorithms are based on data collected by professional tongue diagnosis instruments in standard environments, and are not able to demonstrate the tongue image segmentation effect in complex environments. Therefore, we propose a segmentation algorithm for tongue images collected in complex multi-device and multi-user environments. We use convolutional attention and extend state space models to the 2D environment in the encoder. Then, cross-layer connection fusion is used in the decoder part to fuse shallow texture and deep semantic features. Through segmentation experiments on tongue image datasets collected by patients and doctors in real-world settings, our algorithm significantly improves segmentation performance and accuracy.

The oral microbiome and oral and upper gastrointestinal diseases

Background

Microbiomes are essential components of the human body, and their populations are substantial. Under normal circumstances, microbiomes coexist harmoniously with the human body, but disturbances in this equilibrium can lead to various diseases. The oral microbiome is involved in the occurrence and development of many oral and gastrointestinal diseases. This review focuses on the relationship between oral microbiomes and oral and upper gastrointestinal diseases, and therapeutic strategies aiming to provide valuable insights for clinical prevention and treatment.

Methods

To identify relevant studies, we conducted searches in PubMed, Google Scholar, and Web of Science using keywords such as "oral microbiome," "oral flora, " "gastrointestinal disease, " without any date restrictions. Subsequently, the retrieved publications were subject to a narrative review.

Results

In this review, we found that oral microbiomes are closely related to oral and gastrointestinal diseases such as periodontitis, dental caries, reflux esophagitis, gastritis, and upper gastrointestinal tumors (mainly the malignant ones). Oral samples like saliva and buccal mucosa are not only easy to collect, but also display superior sample stability compared to gastrointestinal tissues. Consequently, analysis of the oral microbiome could potentially serve as an efficient preliminary screening method for high-risk groups before undergoing endoscopic examination. Besides, treatments based on the oral microbiomes could aid early diagnosis and treatment of these diseases.

Conclusions

Oral microbiomes are essential to oral and gastrointestinal diseases. Therapies centered on the oral microbiomes could facilitate the early detection and management of these conditions.

Exploration of the intestinal flora to reveal the important contribution of Radix Astragali to Huangqi Jianzhong Tang in treating chronic atrophic gastritis rats

Radix Astragali (Huangqi in Chinese, HQ) is a commonly used Chinese herbal medicine for thousands of years. In this study, A classic prescription Huangqi Jianzhong tang (HQJZ) was selected to evaluate the important effect of HQ on rats with chronic atrophic gastritis (CAG) from the perspective of intestinal flora in cecal contents samples. Traditional pharmacological indicators, including weight change, pathological examination and biochemical indicators showed that HQ exerted favorable contribution to HQJZ against CAG, where the efficiencies of HQ and HQJZ were better than HY (HQJZ prepared without HQ). An accurate strategy was adopted to screen out the differential metabolites in the metabolomis analysis of intestinal flora in cecal contents samples based on the optimal screening factors, including VIP (importance of variables in projection), FC (fold change), AUROC (area under the receiver operating characteristic curve) and -ln(p-value), which were evaluated based on their interpreting, grouping, and predicting abilities of the performed orthogonal partial least-squares-discriminate analysis (OPLS-DA) models. Ten altered differential metabolites were obtained and associated with the intestinal flora, which HQ exerted the important metabolic contributions to HQJZ. The efficacy on the diversity of intestinal flora and their correlations with the altered metabolites further showed the important role of HQ in HQJZ composition. This work provided valuable approach for looking for potential biomarkers associated with metabolomics research with more accuracy, and provided new insights into the mechanisms to explain the efficacy of HQ contributing to HQJZ formula.

Application of intelligent tongue image analysis in Conjunction with microbiomes in the diagnosis of MAFLD

Background

Metabolic associated fatty liver disease (MAFLD) is a widespread liver disease that can lead to liver fibrosis and cirrhosis. Therefore, it is essential to develop early diagnosic and screening methods.

Methods

We performed a cross-sectional observational study. In this study, based on data from 92 patients with MAFLD and 74 healthy individuals, we observed the characteristics of tongue images, tongue coating and intestinal flora. A generative adversarial network was used to extract tongue image features, and 16S rRNA sequencing was performed using the tongue coating and intestinal flora. We then applied tongue image analysis technology combined with microbiome technology to obtain an MAFLD early screening model with higher accuracy. In addition, we compared different modelling methods, including Extreme Gradient Boosting (XGBoost), random forest, neural networks(MLP), stochastic gradient descent(SGD), and support vector machine(SVM).

Results

The results show that tongue-coating Streptococcus and Rothia, intestinal Blautia, and Streptococcus are potential biomarkers for MAFLD. The diagnostic model jointly incorporating tongue image features, basic information (gender, age, BMI), and tongue coating marker flora (Streptococcus, Rothia), can have an accuracy of 96.39%, higher than the accuracy value except for bacteria.

Conclusion

Combining computer-intelligent tongue diagnosis with microbiome technology enhances MAFLD diagnostic accuracy and provides a convenient early screening reference.

Distinct microbiome of tongue coating and gut in type 2 diabetes with yellow tongue coating

The gut microbiome plays a critical role in the pathogenesis of type 2 diabetes mellitus (T2DM). However, the inconvenience of obtaining fecal samples hinders the clinical application of gut microbiome analysis. In this study, we hypothesized that tongue coating color is associated with the severity of T2DM. Therefore, we aimed to compare tongue coating, gut microbiomes, and various clinical parameters between patients with T2DM with yellow (YC) and non-yellow tongue coatings (NYC). Tongue coating and gut microbiomes of 27 patients with T2DM (13 with YC and 14 with NYC) were analyzed using 16S rDNA gene sequencing technology. Additionally, we measured glycated hemoglobin (HbA1c), random blood glucose (RBG), fasting blood glucose (FBG), postprandial blood glucose (PBG), insulin (INS), glucagon (GC), body mass index (BMI), and homeostasis model assessment of β-cell function (HOMA-β) levels for each patient. The correlation between tongue coating and the gut microbiomes was also analyzed. Our findings provide evidence that the levels of Lactobacillus spp. are significantly higher in both the tongue coating and the gut microbiomes of patients with YC. Additionally, we observed that elevated INS and GC levels, along with decreased BMI and HOMA-β levels, were indicative of a more severe condition in patients with T2DM with YC. Moreover, our results suggest that the composition of the tongue coating may reflect the presence of Lactobacillus spp. in the gut. These results provide insights regarding the potential relationship between tongue coating color, the gut microbiome, and T2DM.

Investigation of Campylobacter concisus gastric epithelial pathogenicity using AGS cells

Campylobacter concisus is an oral bacterium. Recent studies suggest that C. concisus may be involved in human gastric diseases. The mechanisms, however, by which C. concisus causes human gastric diseases have not been investigated. Here we examined the gastric epithelial pathogenicity of C. concisus using a cell culture model. Six C. concisus strains and the human gastric epithelial cell line AGS cells were used. IL-8 produced by AGS cells after incubation with C. concisus was measured using enzyme-linked immunosorbent assay (ELISA), and AGS cell apoptosis was determined by caspase 3/7 activities. The effects of C. concisus on actin arrangement in AGS cells was determined using fluorescence staining. The effects of C. concisus on global gene expression in AGS cells was determined by transcriptomic analysis and quantitative real-time PCR (qRT-PCR). The role of the upregulated CYP1A1 gene in gastric cancer survival was assessed using the Kaplan-Meier method. C. concisus induced production of IL-8 by AGS cells with strain variation. Significantly increased caspase 3/7 activities were observed in AGS cells incubated with C. concisus strains when compared to AGS cells without bacteria. C. concisus induced actin re-arrangement in AGS cells. C. concisus upregulated 30 genes in AGS cells and the upregulation of CYP1A1 gene was confirmed by qRT-PCR. The Kaplan-Meier analysis showed that upregulation of CYP1A1 gene is associated with worse survival in gastric cancer patients. Our findings suggest that C. concisus may play a role in gastric inflammation and the progression of gastric cancer. Further investigation in clinical studies is warranted.

In-depth metaproteomics analysis of tongue coating for gastric cancer: a multicenter diagnostic research study

BACKGROUND

Our previous study revealed marked differences in tongue images between individuals with gastric cancer and those without gastric cancer. However, the biological mechanism of tongue images as a disease indicator remains unclear. Tongue coating, a major factor in tongue appearance, is the visible layer on the tongue dorsum that provides a vital environment for oral microorganisms. While oral microorganisms are associated with gastric and intestinal diseases, the comprehensive function profiles of oral microbiota remain incompletely understood. Metaproteomics has unique strength in revealing functional profiles of microbiota that aid in comprehending the mechanism behind specific tongue coating formation and its role as an indicator of gastric cancer.

METHODS

We employed pressure cycling technology and data-independent acquisition (PCT-DIA) mass spectrometry to extract and identify tongue-coating proteins from 180 gastric cancer patients and 185 non-gastric cancer patients across 5 independent research centers in China. Additionally, we investigated the temporal stability of tongue-coating proteins based on a time-series cohort. Finally, we constructed a machine learning model using the stochastic gradient boosting algorithm to identify individuals at high risk of gastric cancer based on tongue-coating microbial proteins.

RESULTS

We measured 1432 human-derived proteins and 13,780 microbial proteins from 345 tongue-coating samples. The abundance of tongue-coating proteins exhibited high temporal stability within an individual. Notably, we observed the downregulation of human keratins KRT2 and KRT9 on the tongue surface, as well as the downregulation of ABC transporter COG1136 in microbiota, in gastric cancer patients. This suggests a decline in the defense capacity of the lingual mucosa. Finally, we established a machine learning model that employs 50 microbial proteins of tongue coating to identify individuals at a high risk of gastric cancer, achieving an area under the curve (AUC) of 0.91 in the independent validation cohort.

CONCLUSIONS

We characterized the alterations in tongue-coating proteins among gastric cancer patients and constructed a gastric cancer screening model based on microbial-derived tongue-coating proteins. Tongue-coating proteins are shown as a promising indicator for identifying high-risk groups for gastric cancer. Video Abstract.

Establishment of a Standard Tongue Coating Collection Method for Microbiome Studies

Objective: Recently, researchers have been focusing on characterizing the tongue coating microbiome from patients with digestive tract disease. However, to the best of our knowledge, the tongue coating collection methods have not been standardized until now. This article focuses on bridging this gap by exploring and validating the conditions suitable for the collection of tongue coating samples. Methods: One hundred forty-one healthy subjects were involved in the standardization of the tongue coating collection method. We conducted our standardization experiment by comparing different sampling tools, different preservation solutions, different scraping times, and different storage days with preservation at room temperature. The tongue coating samples from 59 normal individuals were analyzed using 16S ribosomal RNA (rRNA) gene-sequencing technology. The assessment of the quality of extracted DNA was used to verify our established method. We separated the 59 subjects into two groups (aged and younger), and the sequencing results were used to explore the age-related changes in microbiome. Results: Sterile oral swab B is suitable for the collection of tongue coating samples. To obtain a sufficient amount of DNA from a tongue coating sample, we recommend 30 times of tongue coating scraping. Normal saline, phosphate-buffered saline, and commercial preservation solution are all suitable for short-term sample storage (<1 hour). The commercial long-term preservation solution, which stores samples at room temperature (0 hour to 7 days) and can provide for fast commercial transportation, ensures the integrity of the sample DNA as well as the stability of the DNA quality. By using the established method, extracted DNA from all the 59 normal individuals' tongue coating samples passed an appropriate quality bar for microbiome studies. The average value of OD 260/280 is 1.72 ± 0.10; the average total DNA amount is 334.92 ng (±183.81 ng). The bacterial diversity of the tongue coating is increased and the bacterial community composition changes greatly in the NC group (aged normal subjects). Fusobacteriota is found as the dominant bacteria phyla in aged normal subjects with the 16S rRNA gene-sequencing technology. At the genus level, the relative abundance of Fusobacterium, Haemophilus, and Leptotrichia are significantly higher in aged individuals (all p < 0.05), and Neisseria, Streptococcus, and Porphyromonas are significantly higher in younger individuals (all p < 0.05). Conclusion: A participant-friendly tongue coating collection method for microbiome analyses can be established with good reliability and reproducibility. By taking advantage of our established method and 16S rRNA gene sequencing, significant differences were found in diversity and composition of tongue coating microbiota between aged and younger individuals, which contributes to a better understanding of the age-related composition of tongue coating microbiota.

Oral microbiota disorder in GC patients revealed by 2b-RAD-M

BACKGROUND

Microbiota alterations are linked with gastric cancer (GC). However, the relationship between the oral microbiota (especially oral fungi) and GC is not known. In this study, we aimed to apply 2b-RAD sequencing for Microbiome (2b-RAD-M) to characterize the oral microbiota in patients with GC.

METHODS

We performed 2b-RAD-M analysis on the saliva and tongue coating of GC patients and healthy controls. We carried out diversity, relative abundance, and composition analyses of saliva and tongue coating bacteria and fungi in the two groups. In addition, indicator analysis, the Gini index, and the mean decrease accuracy were used to identify oral fungal indicators of GC.

RESULTS

In this study, fungal imbalance in the saliva and tongue coating was observed in the GC group. At the species level, enriched Malassezia globosa (M. globosa) and decreased Saccharomyces cerevisiae (S. cerevisiae) were observed in saliva and tongue coating samples of the GC group. Random forest analysis indicated that M. globosa in saliva and tongue coating samples could serve as biomarkers to diagnose GC. The Gini index and mean decreases in accuracy for M. globosa in saliva and tongue coating samples were the largest. In addition, M. globosa in saliva and tongue coating samples classified GC from the control with areas under the receiver operating curve (AUCs) of 0.976 and 0.846, respectively. Further ecological analysis revealed correlations between oral bacteria and fungi.

CONCLUSION

For the first time, our data suggested that changes in oral fungi between GC patients and controls may help deepen our understanding of the complex spectrum of the different microbiotas involved in GC development. Although the cohort size was small, this study is the first to use 2b-RAD-M to reveal that oral M. globosa can be a fungal biomarker for detecting GC.

Oral Microbiota as a Diagnostic Biomarker of Digestive Cancer: A Systematic Review

AIM

This article aimed to review the association of oral microbiota with digestive cancer (DC).

BACKGROUND

Oral microbiota is one of the most complex ecosystems in our body. The mouth, from which the digestive system starts, may be a source of an abundant taxonomic group of microbiotas that travel to the digestive system followed by growth, reproduction, and settlement, forming a complex microecological environment causing systemic and gastrointestinal (GI) disease.

REVIEW RESULTS

A total of 14 articles were chosen for review. Most studies were case-control. Both positive and negative associations were seen between oral microbiome and DC.

CONCLUSION

Digestive cancer may be associated with distinctive oral microbial character.

CLINICAL SIGNIFICANCE

The present systematic review enlightens the risk of digestive carcinoma with oral microbiota that may act as a biomarker for early diagnosis of DC in a more comfortable, acceptable, and noninvasive way. How to cite this article: Ikbal SKA, Yadav SK, Mehrotra R, et al. Oral Microbiota as a Diagnostic Biomarker of Digestive Cancer: A Systematic Review. J Contemp Dent Pract 2023;24(11):902-911.

Oral Microbiota: The Influences and Interactions of Saliva, IgA, and Dietary Factors in Health and Disease

Recent advances in metagenomic analyses have made it easier to analyze microbiota. The microbiota, a symbiotic community of microorganisms including bacteria, archaea, fungi, and viruses within a specific environment in tissues such as the digestive tract and skin, has a complex relationship with the host. Recent studies have revealed that microbiota composition and balance particularly affect the health of the host and the onset of disease. Influences such as diet, food preferences, and sanitation play crucial roles in microbiota composition. The oral cavity is where the digestive tract directly communicates with the outside. Stable temperature and humidity provide optimal growth environments for many bacteria. However, the oral cavity is a unique environment that is susceptible to pH changes, salinity, food nutrients, and external pathogens. Recent studies have emphasized the importance of the oral microbiota, as changes in bacterial composition and balance could contribute to the development of systemic diseases. This review focuses on saliva, IgA, and fermented foods because they play critical roles in maintaining the oral bacterial environment by regulating its composition and balance. More attention should be paid to the oral microbiota and its regulatory factors in oral and systemic health.

Oral microbiome as a co-mediator of halitosis and periodontitis: a narrative review

Objective

Halitosis or oral malodor is an unpleasant odor from the oral cavity. However, although patients with periodontitis often complain of halitosis, their relationship has not been fully elucidated. We reviewed previous literature based on the hypothesis that the relationship between halitosis and periodontitis is mediated by the oral microbiome.

Materials and methods

This narrative review sought to provide insight into the causative role of the oral microbiome in influencing halitosis and periodontitis. In addition, we tried to deepen knowledge related to the relationship between halitosis and periodontitis generated by the oral microbiome accumulated over the past 40 years.

Results

From 1984 to 2023, a total of 106 papers that carefully and scientifically dealt with halitosis and periodontitis were included in this narrative review. Based on previous results, halitosis and periodontitis were closely related. For decades, researchers have taken an intriguing approach to the question of whether there is a relationship between halitosis and periodontitis. Central factors in the relationship between halitosis and periodontitis include volatile sulfur compounds (VSCs), the oral microbiota that produce VSCs, and the inflammatory response.

Conclusions

Taken together, the more severe periodontitis, the higher the level of VSC in halitosis, which may be mediated by oral microbiome. However, the relationship between the occurrence, maintenance, and exacerbation of periodontitis and halitosis is not a necessary and sufficient condition for each other because they are complex interplay even in one individual.

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

Gastric cancer (GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development; therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

Progress in traditional Chinese medicine against chronic gastritis: From chronic non-atrophic gastritis to gastric precancerous lesions

Chronic gastritis (CG) is a persistent inflammation of the gastric mucosa that can cause uncomfortable symptoms in patients. Traditional Chinese medicine (TCM) has been widely used to treat CG due to its precise efficacy, minimal side effects, and holistic approach. Clinical studies have confirmed the effectiveness of TCM in treating CG, although the mechanisms underlying this treatment have not yet been fully elucidated. In this review, we summarized the clinical research and mechanisms of TCM used to treat CG. Studies have shown that TCM mechanisms for CG treatment include H. pylori eradication, anti-inflammatory effects, immune modulation, regulation of gastric mucosal cell proliferation, apoptosis, and autophagy levels.

Physiology of the tongue with emphasis on taste transduction

The tongue is a complex multifunctional organ that interacts and senses both interoceptively and exteroceptively. Although it is easily visible to almost all of us, it is relatively understudied and what is in the literature is often contradictory or is not comprehensively reported. The tongue is both a motor and a sensory organ: motor in that it is required for speech and mastication, and sensory in that it receives information to be relayed to the central nervous system pertaining to the safety and quality of the contents of the oral cavity. Additionally, the tongue and its taste apparatus form part of an innate immune surveillance system. For example, loss or alteration in taste perception can be an early indication of infection as became evident during the present global SARS-CoV-2 pandemic. Here, we particularly emphasize the latest updates in the mechanisms of taste perception, taste bud formation and adult taste bud renewal, and the presence and effects of hormones on taste perception, review the understudied lingual immune system with specific reference to SARS-CoV-2, discuss nascent work on tongue microbiome, as well as address the effect of systemic disease on tongue structure and function, especially in relation to taste.

Alterations in bacterial community dynamics from noncancerous to Gastric cancer

Gastric microbiome has been shown to contribute to gastric carcinogenesis, understanding how alterations in gastric microbiome is helpful to the prevention and treatment of gastric cancer (GC). However, few studies have focused on the change of microbiome during the gastric carcinogenesis. In this study, the microbiome of gastric juice samples from healthy control (HC), gastric precancerous lesions (GPL) and gastric cancer (GC) was investigated by 16S rRNA gene sequencing. Our results showed that the alpha diversity of patients with GC was significantly lower than other groups. Compared to other groups, some genera in GC group were shown to be up-regulated (e.g., Lautropia and Lactobacillus) and down-regulated (e.g., Peptostreptococcus and Parvimonas). More importantly, the emergence of Lactobacillus was closely related to the occurrence and development of GC. Moreover, the microbial interactions and networks in GPL exhibited higher connectivity, complexity and lower clustering property, while GC showed the opposite trend. Taken together, we suggest that changes in the gastric microbiome are associated with GC and perform a key function in maintaining the tumor microenvironment. Therefore, our findings will provide new ideas and references for the treatment of GC.

Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study

BACKGROUND

Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC).

METHODS

From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362.

FINDINGS

For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88-0.92 in the internal verification and 0.83-0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers.

INTERPRETATION

Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG).

FUNDING

The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).

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.

Helicobacter pylori and Gastric Cancer: Pathogenetic Mechanisms

Gastric cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer death worldwide. Helicobacter pylori (H. pylori) is one of the main risk factors for this type of neoplasia. Carcinogenetic mechanisms associated with H. pylori are based, on the one hand, on the onset of chronic inflammation and, on the other hand, on bacterial-specific virulence factors that can damage the DNA of gastric epithelial cells and promote genomic instability. Here, we review and discuss the major pathogenetic mechanisms by which H. pylori infection contributes to the onset and development of gastric cancer.

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.

Confocal Laser Endomicroscopy for Detection of Early Upper Gastrointestinal Cancer

Esophageal and gastric cancers are common diseases with high morbidity and mortality; thus, early detection and treatment are beneficial to improve prognosis. Confocal laser endomicroscopy (CLE) is a novel imaging technique that permits the histological analysis of tissues during endoscopy. CLE has been shown to uniquely affect the diagnosis of early upper gastrointestinal cancers. Relevant literature was searched using PubMed and Google Scholar databases. Despite inherent flaws, CLE can reduce tissue damage and improve diagnostic accuracy to a certain extent. CLE in combination with other imaging methods can help enhance the detection rate and avoid unnecessary biopsies in the management of esophageal or gastric cancer and precancerous lesions. CLE is of great significance in the diagnosis and surveillance of early cancers of the upper gastrointestinal tract. Further technical innovations and the standardisation of CLE will make it more responsive to the needs of routine clinical applications.

A new model for predicting the occurrence of polycystic ovary syndrome: Based on data of tongue and pulse

Background and objective

Polycystic ovary syndrome is one of the most common types of endocrine and metabolic diseases in women of reproductive age that needs to be screened early and assessed non-invasively. The objective of the current study was to develop prediction models for polycystic ovary syndrome based on data of tongue and pulse using machine learning techniques.

Methods

A dataset of 285 polycystic ovary syndrome patients and 201 healthy women were investigated to identify the significant tongue and pulse parameters for predicting polycystic ovary syndrome. In this study, feature selection was performed using least absolute shrinkage and selection operator regression. Several machine learning algorithms (multilayer perceptron classifier, eXtreme gradient boosting classifier, and support vector machine) were used to construct the classification models to predict the presence of polycystic ovary syndrome.

Results

TB-L, TB-a, TB-b, TC-L, TC-a, h3, and h4/h1 in tongue and pulse parameters were statistically associated with polycystic ovary syndrome presence. Among the several machine learning techniques, the support vector machine model was optimal for the comprehensive evaluation of this dataset and deduced the area under the receiver operating characteristic curve, DeLong test, calibration curve, and decision curve analysis.

Conclusion

The machine learning model with tongue and pulse factors can predict the existence of polycystic ovary syndrome precisely.

Gastric Cancer: The Microbiome Beyond Helicobacter pylori

Gastric cancer remains an important global health burden. Helicobacter pylori is the major etiological factor in gastric cancer, infecting the stomach of almost half of the population worldwide. Recent progress in microbiome research offered a new perspective on the complexity of the microbial communities of the stomach. Still, the role of the microbiome of the stomach beyond H. pylori in gastric carcinogenesis is not well understood and requires deeper investigation. The gastric bacterial communities of gastric cancer patients are distinct from those of patients without cancer, but the microbial alterations that occur along the process of gastric carcinogenesis, and the mechanisms through which microorganisms influence cancer progression still need to be clarified. Except for Epstein-Barr virus, the potential significance of the virome and of the mycobiome in gastric cancer have received less attention. This chapter updates the current knowledge regarding the gastric microbiome, including bacteria, viruses, and fungi, within the context of H. pylori-mediated carcinogenesis. It also reviews the possible roles of the local gastric microbiota, as well as the microbial communities of the oral and gut ecosystems, as biomarkers for gastric cancer detection. Finally, it discusses future perspectives and acknowledges limitations in the area of microbiome research in the gastric cancer setting, to which further research efforts should be directed. These will be fundamental not only to increase our current understanding of host-microbial interactions but also to facilitate translation of the findings into innovative preventive, diagnostic, and therapeutic strategies to decrease the global burden of gastric cancer.

A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation

The rapid development of artificial intelligence technology has gradually extended from the general field to all walks of life, and intelligent tongue diagnosis is the product of a miraculous connection between this new discipline and traditional disciplines. We reviewed the deep learning methods and machine learning applied in tongue image analysis that have been studied in the last 5 years, focusing on tongue image calibration, detection, segmentation, and classification of diseases, syndromes, and symptoms/signs. Introducing technical evolutions or emerging technologies were applied in tongue image analysis; as we have noticed, attention mechanism, multiscale features, and prior knowledge were successfully applied in it, and we emphasized the value of combining deep learning with traditional methods. We also pointed out two major problems concerned with data set construction and the low reliability of performance evaluation that exist in this field based on the basic essence of tongue diagnosis in traditional Chinese medicine. Finally, a perspective on the future of intelligent tongue diagnosis was presented; we believe that the self-supervised method, multimodal information fusion, and the study of tongue pathology will have great research significance.

A Framework to Predict Gastric Cancer Based on Tongue Features and Deep Learning

Gastric cancer has become a global health issue, severely disrupting daily life. Early detection in gastric cancer patients and immediate treatment contribute significantly to the protection of human health. However, routine gastric cancer examinations carry the risk of complications and are time-consuming. We proposed a framework to predict gastric cancer non-invasively and conveniently. A total of 703 tongue images were acquired using a bespoke tongue image capture instrument, then a dataset containing subjects with and without gastric cancer was created. As the images acquired by this instrument contain non-tongue areas, the Deeplabv3+ network was applied for tongue segmentation to reduce the interference in feature extraction. Nine tongue features were extracted, relationships between tongue features and gastric cancer were explored by using statistical methods and deep learning, finally a prediction framework for gastric cancer was designed. The experimental results showed that the proposed framework had a strong detection ability, with an accuracy of 93.6%. The gastric cancer prediction framework created by combining statistical methods and deep learning proposes a scheme for exploring the relationships between gastric cancer and tongue features. This framework contributes to the effective early diagnosis of patients with gastric cancer.

The oral microbiota and cardiometabolic health: A comprehensive review and emerging insights

There is mounting evidence demonstrating that oral dysbiosis causes periodontal disease and promotes the development of cardiovascular disease. The advancement of omics techniques has driven the optimization of oral microbiota species analysis and has provided a deeper understanding of oral pathogenic bacteria. A bi-directional relationship exists between the oral microbiota and the host, and oral-gut microbiota transfer is known to alter the composition of the gut microbiota and may cause local metabolic disorders. Furthermore, cardiovascular health can also be highly affected by oral microbiota functions and metabolites, including short-chain fatty acids (SCFAs), nitric oxide (NO), hydrogen sulfide (H2S), and some lipid metabolites. Studies have found that trimethylamine oxide (TMAO) may have adverse effects on cardiovascular health, whereas SCFAs, NO, and H2S have cardioprotective effects. SCFAs and H2S exert varying oral and cardiovascular effects, however reports on this specific topic remain controversial. Previous evidences are accustomed to summarizing the functions of oral microbiota in the context of periodontitis. The direct relationship between oral microbiota and cardiovascular diseases is insufficient. By systematically summarizing the methods associated with oral microbiota transplantation (OMT), this review facilitates an investigation into the causal links between oral microbiota and cardiovascular disease. The concomitant development of omics, bioinformatics, bacterial culture techniques, and microbiota transplantation techniques is required to gain a deeper understanding of the relationship between oral microbiota and cardiovascular disease occurrence.

Weifuchun alters tongue flora and decreases serum trefoil factor I levels in gastric intestinal metaplasia: A CONSORT-compliant article

OBJECTIVE

To explore the molecular mechanisms of Weifuchun in the treatment of gastric intestinal metaplasia (GIM), we designed a preclinical pilot study to examine potential markers of disease progression based on alterations in the tongue flora.

METHODS

Total 27 patients with GIM were treated with Weifuchun for 4 weeks and 26 volunteers as controls. Tongue coating bacteria were profiled using 16S rDNA high-throughput sequencing. Serum pepsinogen I and II levels were detected using the latex immunoturbidimetric assay. The levels of serum trefoil factor I was detected by ELISA. Microplate-based quantification was used to detect serum total bile acid (TBA).

RESULTS

After treatment, the relative abundance of 4 dominant tongue coating genera (Granulicatella, Gemella, Lachnoanaerobaculum, and Neisseria) increased significantly wheras Alloprevotella, [Eubacterium] nodatum group, Prevotell, and Ruminococcaceae UCG-014 decreased (P < .05). The results showed that Alloprevotella and 3 rare tongue coating genera (Lautropia, Treponema 2, and Aliihoeflea) might be potential markers or target flora for the treatment of GIM. Kyoto encyclopedia of genes and genomes (KEGG) function prediction analysis showed that Weifuchun may regulate bile secretion and folate biosynthesis in patients with GIM. The level of serum trefoil factor I decreased significantly in response to Weifuchun treatment, which was consistent with the decrease in folate biosynthesis predicted by KEGG.

CONCLUSION

Weifuchun may restore the balance of tongue flora by decreasing the levels of serum trefoil factor I, thereby providing a new way to measuring the underlying effectiveness and potential mechanisms of action of this traditional Chinese medicinal compound in the treatment of GIM.

Oral Microbiota and Tumor-A New Perspective of Tumor Pathogenesis

Microorganisms have long been known to play key roles in the initiation and development of tumors. The oral microbiota and tumorigenesis have been linked in epidemiological research relating to molecular pathology. Notably, some bacteria can impact distal tumors by their gastrointestinal or blood-borne transmission under pathological circumstances. Certain bacteria drive tumorigenesis and progression through direct or indirect immune system actions. This review systemically discusses the recent advances in the field of oral microecology and tumor, including the oncogenic role of oral microbial abnormalities and various potential carcinogenesis mechanisms (excessive inflammatory response, host immunosuppression, anti-apoptotic activity, and carcinogen secretion) to introduce future directions for effective tumor prevention.

Differences in the microbiota of oral rinse, lesion, and normal site samples from patients with mucosal abnormalities on the tongue

The oral microbiota associated with mucosal diseases, including oral squamous cell carcinoma and oral potentially malignant disorders, have been extensively analyzed at the phylum and genus levels. However, the details of the oral microbiota remain unclear at the species and operational taxonomic unit (OTU) levels. We aimed to determine differences in the microbiota of oral rinse, lesion and normal site swab samples of patients with mucosal abnormalities on the tongues. Oral samples were obtained from 10 patients with oral mucosal abnormalities. Alpha and beta diversity at the OTU and genus levels of the microbiota samples were analyzed using OTUs clustered with 99.6% similarity based on 16S rRNA gene sequences obtained using the Sanger method. At the OTU level, the microbiota of the lesions were the least diverse but were different from those of the normal site and oral rinse samples. The OTUs corresponding to Streptococcus infantis and Haemophilus parainfluenzae were suggested to contribute to the differences between the microbiota of the lesions and normal sites. At the genus level, no significant differences between these microbiota were observed. In conclusion, strict OTU-level microbiota analysis might be able to discriminate lesions from normal sites of patients with mucosal abnormalities.

From Anti-HER-2 to Anti-HER-2-CAR-T Cells: An Evolutionary Immunotherapy Approach for Gastric Cancer

Current Therapeutic modalities provide no survival advantage to gastric cancer (GC) patients. Targeting the human epidermal growth factor receptor-2 (HER-2) is a viable therapeutic strategy against advanced HER-2 positive GC. Antibody-drug conjugates, small-molecule tyrosine kinase inhibitors (TKIs), and bispecific antibodies are emerging as novel drug forms that may abrogate the resistance to HER-2-specific drugs and monoclonal antibodies. Chimeric antigen receptor-modified T cells (CAR-T) targeting HER-2 have shown considerable therapeutic potential in GC and other solid tumors. However, due to the high heterogeneity along with the complex tumor microenvironment (TME) of GC that often leads to immune escape, the immunological treatment of GC still faces many challenges. Here, we reviewed and discussed the current progress in the research of anti-HER-2-CAR-T cell immunotherapy against GC.

Oral-Gut Microbiome Analysis in Patients With Metabolic-Associated Fatty Liver Disease Having Different Tongue Image Feature

Objective

The objective of this study was to identify the biological correlation between the tongue coating color and oral and gut micro-characteristics in metabolic-associated fatty liver disease (MAFLD) patients.

Method

The characteristics of the tongue coating were examined using an automatic tongue diagnosis system. Tongue coating and stool samples were collected from 38 MAFLD patients, and 16S rDNA full-length assembly sequencing technology (16S-FAST) was used for bioinformatic analysis.

Results

Twenty-two and 16 subjects were included in two distinct clusters according to the white/yellow color of the tongue coating, which was assessed by the L*a*b* values of the image. Upon analyzing the microorganisms in the tongue coating, 66 and 62 pathognomonic bacterial genera were found in the White and Yellow Coating Groups, respectively. The abundance of Stomatobaculumis positively correlated with the a* values of the tongue coating in the White Coating Group, while Fusobacterium, Leptotrichia, and Tannerella abundance was significantly correlated with the b* values in the Yellow Coating Group. Function prediction mainly showed the involvement of protein families related to BRITE hierarchies and metabolism. The MHR (MONO%/high-density lipoprotein cholesterol) of the Yellow Coating Group was higher than that of the White Coating Group.

Conclusion

In MAFLD patients, lower a* values and higher b* values are indicators of a yellow tongue coating. There were also significant differences in the flora of different tongue coatings, with corresponding changes in the intestinal flora, indicating a correlation between carbohydrate metabolism disorders and inflammation in the oral microbiome.

Microbial Characteristics of Common Tongue Coatings in Patients with Precancerous Lesions of the Upper Gastrointestinal Tract

The tongue coating (TC) microbiota, a crucial component of the tongue coating, illustrates a huge microbial percentage of the body that mostly includes actinobacteria, bacteroides, firmicutes, and fusobacteria. The TC microbiota is closely related to the development of upper gastrointestinal malignancies, such as oral, gastric, and esophageal cancer. Nonetheless, the microbiological characteristics of common TCs in individuals with precancerous lesions of the upper gastrointestinal tract are still unclear. Herein, we designed a case-control study, recruiting 153 PLUGT patients with four different types of TCs, including 47 white-thin, 19 white-thick, 47 yellow-thin, and 40 yellow-thick, as well as 47 volunteers as controls. To analyze microbial characteristics, 16S rRNA microbiome approaches were used. An enzyme-linked immunosorbent assay (ELISA) was employed to assess serum IL-17A and total bile acid (TBA). According to the obtained results, Leptotrichia was found to be a promising biomarker for thin as well as thick yellow coatings. In comparison to the control TC microbiota, 39 different genera developed commensal networks in common TCs. Lachnoanaerobaculum and pseudonocardia were the most striking core bacteria. Lachnoanaerobaculum positively correlated with Leptotrichia in W-thin and Y-thick coatings, with actinomyces and methylobacterium in Y-thin coatings, with Campylobacter in Y-thick coatings, and with Bradyrhizobium in W-thick and Y-thick coatings. Serum IL-17A levels were greater in cases with W-thin coating than in controls, and serum IL-17A was positively linked with Parvimonas in patients with W-thick or Y-thin coating. In Y-thin coating, the oral dominating bacteria Streptococcus was negatively linked with serum TBA. Taken together, the promoted bacteria were found to be synergistically proliferative in the TCs of PLUGT patients. The diverse TCs had distinct bacterial commensal networks, whereas the common TCs were linked by specific bacteria to serum IL-17A and TBA.

Campylobacter concisus gastritis masquerading as Helicobacter pylori on gastric biopsy

OBJECTIVE

Campylobacter concisus is a Gram-negative rod closely related to Helicobacter pylori. We sought to identify gastric biopsies positive for C. concisus that had been misdiagnosed as H. pylori gastritis in our routine surgical pathology practice.

MATERIALS AND METHODS

We performed a retrospective review of gastric biopsies in our regional microbiology and pathology electronic records to identify cases that were submitted for H. pylori testing in which C. consicus was identified on culture and how many had concurrent biopsies sent to pathology for histologic assessment over a two-year period (2017-2018). Pathologic findings in the gastric biopsies were reviewed and immunohistochemical staining for H. pylori was performed.

RESULTS

50 of 2191 gastric biopsy specimens submitted to microbiology in 2017-18 grew C. concisus (2.3%), compared to 168 in which H. pylori was identified (7.7%). Twenty-eight cases had concurrent histology. A total of four cases (three from 2017 and one from 2018) demonstrated organisms morphologically identical to H. pylori in the H&E sections, of which all were H. pylori immunoreactive.

CONCLUSIONS

Our case series is the first to demonstrate that C. concisus can mimic H. pylori gastritis in routine biopsy pathology.

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

BACKGROUND

In traditional Chinese medicine, it is believed that the "tongue coating is produced by fumigation of stomach gas", and that tongue coating can reflect the health status of humans, especially stomach health. Therefore, studying the relationship between the microbiome of the tongue coating and the gastric fluid is of great significance for understanding the biological basis of tongue diagnosis.

METHODS

This paper detected the microbiomes of the tongue coating and the gastric fluid in 35 gastritis patients using metagenomic sequencing technology, systematically constructed the microbial atlas of tongue coating and gastric juice, and first described the similar characteristics between the two sites.

RESULTS

There was a significant correlation between tongue coating and gastric juice in terms of microbial species composition and overall diversity. In terms of species composition, it was found that the two sites were dominated by five phyla, namely, Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria and Proteobacteria, and that most of the gastric microbial species could be detected from the patient's own tongue coating. In terms of overall diversity, a significant correlation was found between the alpha diversity of the tongue coating microbiome and the gastric juice microbiome. Furthermore, in terms of abundance, 4 classes, 2 orders, 4 families, 18 genera and 46 species were found to significantly correlate between the tongue coating and the gastric fluid.

CONCLUSIONS

The results provide microbiome-based scientific evidence for tongue diagnosis, and offer a new perspective for understanding the biological basis of tongue diagnosis.

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.

Metagenomic Analysis Reveals a Changing Microbiome Associated With the Depth of Invasion of Oral Squamous Cell Carcinoma

The relationship between oral squamous cell carcinoma (OSCC) development and the microbiome has attracted increasing attention. The depth of invasion (DOI) is an important indicator of tumor progression, staging and prognosis, and the change in the oral microbiome based on the DOI is unclear. This report describes the use of metagenomic analyses to investigate the relationship between the oral microbiome and the DOI. Forty patients in different DOI categories were recruited; 10 healthy people served as the control group. Swab samples collected from the participants were subjected to metagenomic analyses, and the oral microbial communities and their functions were investigated. The abundances of Fusobacterium nucleatum, Capnocytophaga sputigena, Porphyromonas endodontalis, and Gemella haemolysans were significantly increased in the patients compared with the controls. The abundances of some bacteria exhibited a stage-related trend. The abundances of P. endodontalis, Gemella morbillorum and G. haemolysans increased with increasing DOI. In contrast, the abundances of Prevotella melaninogenica, Haemophilus parainfluenzae and Neisseria flavescens decreased with increasing DOI. Based on receiver operating characteristic (ROC) curve analysis, eight species were found to have predictive value: Rothia mucilaginosa, P. melaninogenica, H. parainfluenzae, and N. flavescens in the healthy control group and P. endodontalis, G. morbillorum, G. haemolysans and Fusobacterium periodonticum in the high DOI group. In the functional analysis, several metabolic pathways were decreased, whereas flagellar assembly and bacterial chemotaxis showed an increasing trend as the disease progressed. Biofilm formation, flagella, lipopolysaccharide (LPS) and other virulence factors exhibited staging-related changes. These pathogenic pathways and factors had a clear correlation with specific pathogens. In particular, when OSCC progressed to the late stage, microbial diversity and functional potential changed greatly.

The Association Between the Gut Microbiome, Nutritional Habits, Antibiotics, and Gastric Cancer: a Scoping Review

 PURPOSE OF REVIEW: Gastric cancer (GC) represents one of the leading causes of cancer-related deaths worldwide. The prevalence of GC among the younger population has been increasing in recent years, and the latter is associated with late detection and advanced disease status. The factors involved in the development of GC have been the focus of investigation in the past few years; yet no consistent conclusions or preventative solutions have been suggested. This scoping review aims to explore and report on research studies conducted to investigate the association between GC, the gut microbiome, and nutritional habits. RECENT FINDINGS : Using a predefined protocol in compliance with the PRISMA guidelines, a search was conducted on four separate databases including Google Scholar, Cochrane Library, ProQuest, and PubMed to investigate the association between GC, microbiome, and nutrition. A total of 1219 articles were identified through this process. Forty-three articles met the initial screening criteria and following full-article analysis, and 10 articles met the full inclusion criteria and were included in the current review. The results of the study support that there are differences in the gut microbiota between GC patients and healthy controls and that GC patients may have increased microbiota richness and lower diversity compared to healthy controls. In addition, the detection of pre/early GC may be possible through the analysis of the microbiota using fecal sampling. Nutritional habits, probiotics, and antibiotics may also play an important role in affecting GC development. Preliminary studies support a role for the gut microbiota in developing GC. Yet, the lack of sufficient randomized controlled studies investigating the association between GC, the gut microbiota, and nutritional habits demonstrates the need for further clinical research to develop preventative strategies that will aim to reduce the increased incidence of GC among all age groups including younger populations.

Alterations in Gastric Mucosal Microbiota in Gastric Carcinogenesis: A Systematic Review and Meta-Analysis

Background: The gastric microbiota profile alters during gastric carcinogenesis. We aimed to identify the alterations in the alpha diversity and relative abundance of bacterial phyla and genera of gastric microbiota in the development of gastric cancer (GC). Methods: The systematic review was performed based on a published protocol with the registration number CRD42020206973. We searched through PubMed, EMBASE and Cochrane databases, as well as conference proceedings and references of review articles (May 2021) for observational studies reporting either the relative abundance of bacterial phyla or genera, or alpha diversity indexes in both GC and non-cancer groups. Selection of studies and data extraction were performed independently by two researchers, with disagreements resolved through discussion. Risk of bias was assessed using the self-modified Newcastle-Ottawa Scale. Results of random-effects meta-analyses were presented as mean differences (MD). Results: Our systematic review included 751 GC patients and 792 non-cancer patients from 14 case-control studies. Gastric cancer group had fewer operational taxonomic units (OTUs) (MD = -68.52, 95%CI: -126.65 to -10.39) and a lower Simpson index (MD = -0.13, 95%CI: -0.20 to -0.07) compared with non-cancer group. At the phylum level, gastric cancer group had a higher abundance of Firmicutes (MD = 7.11, 95%CI: 1.76 to 12.46). At the genus level, Streptococcus (MD = 3.03, 95%CI: 0.07 to 6.00) and Lactobacillus (MD = 5.15, 95%CI: 1.27 to 9.04) were found to be enriched in GCgroup. The relative abundance of the rest bacterial phyla or genera analyzed in our study did not significantly differ between two groups. Subgroup analyses indicated that the source of samples was the major source of interstudy heterogeneity. Conclusion: This systematic review suggested that gastric microbiota dysbiosis occurred in gastric carcinogenesis, with alpha diversity declined and microbiota composition altered.

Compositional and genetic alterations in Graves' disease gut microbiome reveal specific diagnostic biomarkers

Graves' Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves' disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson's Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.

Tongue-coating microbiome as a cancer predictor: A scoping review

OBJECTIVE

The tongue microbiome has emerged as a non-invasive diagnostic and tracking prognostic tool in the detection of diseases mainly cancer. This scoping review aimed to identify the association between tongue microbiome and pre-cancer or cancer lesions.

DESIGN

A comprehensive electronic database search including PubMed, Web of Science, and Scopus was undertaken up to March 2021, without language or date restrictions. This review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline. All observational studies that compared microbial community on the dorsal surface of the tongue between cancer or precancerous cases and healthy controls using NGS techniques were included.

RESULTS

Of 274 records identified, nine studies were eligible to be included. Despite the inconsistent observations in terms of diversity and richness, most studies reported alteration in bacterial communities between pre-cancer or cancer cases and control groups. The bacterial profile among cases was so far correlated at the phylum level with a noticeable diverse degree at the genus level. The majority of included studies reported a higher abundance of certain kinds of microorganisms as compared to healthy participants including Firmicutes, Fusobacteria and Actinobacteria at phyla level as well as Streptococcus, Actinomyces, Leptotrichia, Campylobacter, and Fusobacterium at the genus level.

CONCLUSION

The alteration of the tongue microbial community has been associated with several diseases mainly cancer. So, the tongue microbiome may serve as a promising diagnostic tool or as a long-term monitor in precancerous or cancer cases.

Oral, Tongue-Coating Microbiota, and Metabolic Disorders: A Novel Area of Interactive Research

Interactions between colonizing microbiota and the host have been fully confirmed, among which the tongue-coating microbiota have a moderate rate of renewal and disease sensitivity and are easily obtained, making them an ideal research subject. Oral microbiota disorders are related to diabetes, obesity, cardiovascular disease, cancer, and other systemic diseases. As an important part of the oral cavity, tongue-coating microbiota can promote gastritis and digestive system tumors, affecting the occurrence and development of multiple chronic diseases. Common risk factors include diet, age, and immune status, among others. Metabolic regulatory mechanisms may be similar between the tongue and gut microbiota. Tongue-coating microbiota can be transferred to the respiratory or digestive tract and create a new balance with local microorganisms, together with the host epithelial cells forming a biological barrier. This barrier is involved in the production and circulation of nitric oxide (NO) and the function of taste receptors, forming the oral-gut-brain axis (similar to the gut-brain axis). At present, the disease model and mechanism of tongue-coating microbiota affecting metabolism have not been widely studied, but they have tremendous potential.