This study, designed as a retrospective study, aims to investigate the clinical efficacy of Longgu Muli Decoction plus additions in treating chronic atrophic gastritis (CAG) and the changes in traditional Chinese medicine (TCM) syndromes. Sixty patients with CAG were enrolled and divided into the observation group and control group according to different treatment methods, with 30 patients in each group. The observation group received Longgu Muli Decoction plus additions, while the control group received conventional treatment. The treatment duration was 4 weeks. Clinical efficacy, TCM syndrome scores, gastrointestinal hormone levels, serum inflammatory factor levels, and sleep quality of the 2 groups were evaluated before and after treatment. Data were analyzed using SPSS 22.0 statistical software. The total effective rate in the observation group was 96.67%, significantly higher than 86.67% in the control group (P < .05). After treatment, the TCM syndrome scores, gastrointestinal hormone levels (endothelin [ET], calcitonin gene-related peptide [CGRP], epidermal growth factor [EGF]), and serum inflammatory factor levels (tumor necrosis factor-α [TNF-α], interleukin-6 [IL-6], C-reactive protein [CRP]) in the observation group were significantly better than those in the control group (P < .05). Moreover, the Pittsburgh Sleep Quality Index (PSQI) total score and various subscale scores in the observation group were significantly lower than those in the control group (P < .05). Longgu Muli Decoction plus additions has significant clinical efficacy in treating CAG. It can effectively improve gastrointestinal function, reduce inflammatory reactions, and enhance sleep quality, thus demonstrating high clinical application value.

Chronic atrophic gastritis (CAG) is an important stage of precancerous lesions of gastric cancer. Effective treatment and regulation of CAG are essential to prevent its progression to malignancy. Traditional Chinese medicine (TCM) has shown multi-targeted efficacy in CAG treatment, with advantages in enhancing gastric mucosal barrier defense, improving microcirculation, modulating inflammatory and immune responses, and promoting lesion healing, etc. Clinical studies and meta-analyses indicate that TCM provides significant benefits, with specific Chinese herbal compounds and monomers demonstrating protective effects on the gastric mucosa through mechanisms including anti-inflammation, anti-oxidation, and regulation of cellular proliferation and apoptosis, etc. Finally, it is pointed out that the efficacy of TCM in the treatment of CAG requires standardized research and unified standards, and constantly clarifies and improves the evaluation criteria of each dimension of gastric mucosal barrier function.

Chronic atrophic gastritis (CAG), precancerous lesions of gastric cancer (PLGC), and gastric cancer (GC), seriously threaten human health. Traditional Chinese medicine (TCM) has been employed in the treatment of chronic diseases for a long time and has shown remarkable efficacy.

Recently, there has been an increasing use of TCM in treating CAG, PLGC, and GC. The objective of this study is to compile a comprehensive overview of the existing research on the effects and molecular mechanisms of TCM, including formulas, single herbs, and active components.

To obtain a comprehensive understanding of traditional use of TCM in treating these diseases, we reviewed ancient books and Chinese literature. In addition, keywords such as "TCM", "CAG", "PLGC", "GC", and "active ingredients" were used to collect modern research on TCM published in databases such as CNKI, Web of Science, and Pubmed up to April 2024. All collected information was then summarized and analyzed.

This study analyzed 174 articles, which covered the research progress of 20 TCM formulas, 14 single herbs, and 50 active ingredients in treating CAG, PLGC, and GC. Sources, effects, and molecular mechanisms of the TCM were summarized.

This article reviews the progress of TCM in the management of CAG, PLGC, and GC, which will provide a foundation for the clinical application and further development of TCM.

Background: Yeokwisan (YWS) is a standardised herbal formula for relieving functional dyspepsia symptoms. Methods: We explored the therapeutic value of YWS and its potential effects on gastritis. Its inhibitory effect on gastric mucosal damage and anti-inflammatory activity in animal models of alcohol- and restraint stress-induced gastritis were also examined. Gastric tissues of ICR mice treated with YWS (150 and 300 mg/kg) or famotidine (5 mg/kg) for 10 days were collected, and gastric lesions were quantified. The stomachs of C57BL/6 mice treated with YWS (150 and 300 mg/kg) or famotidine (5 mg/kg) for 23 days were collected, and gastric lesions were quantified. Blood samples were analysed for inflammation related factors and gastroprotective effects. Results: YWS (300 mg/kg) inhibited gastric damage by 42.33% in the EtOH-induced gastritis model and 75% in the restraint stress-induced gastritis model (compared to the control group). Pretreatment with YWS led to decreased levels of inflammatory factors (IL-1β, IL-6, and COX-2). YWS showed gastroprotective effects through histamine downregulation, while prostaglandin E2 (PGE2) and mucin were upregulated. The mRNA levels of H2R, M3R, CCK2R, and H+/K+ ATPase were significantly decreased following treatment with YWS. Conclusions: YWS provides gastric protection through its anti-inflammatory properties, reduced histamine secretion, and enhanced release of mucosal defensive factors.

Chronic gastritis (CG) is a common gastrointestinal disorder characterized by inflammation of the stomach lining. Liver-stomach disharmony (LSD) syndrome is believed to contribute to CG symptoms.

To evaluate the efficacy and safety of microcosmic syndrome differentiation and Chinese herbal medicine (CHM) treatment in patients with CG and LSD syndrome.

Sixty-four patients with CG and LSD syndrome were randomly divided into two groups: The treatment group received CHM based on microcosmic syndrome differentiation and the control group received conventional Western medicine. The treatment course lasted 12 wk. The primary outcome was improvement in dyspeptic symptoms, measured using the Nepean Dyspepsia Index. The secondary outcomes included the improvement rate of endoscopic findings, histopathological findings, and microcosmic syndrome scores and the incidence of adverse events.

After 12 wk of treatment, the treatment group showed significantly greater improvement in dyspeptic symptoms than the control group (93.75% vs 65.63%, P < 0.01). The treatment group also showed a significantly higher improvement rate in endoscopic findings than the control group (81.25% vs 53.13%, P < 0.05). The improvement rates of histopathological findings and microcosmic syndrome scores were not significantly different between the two groups (P > 0.05). No serious adverse events were observed in either group.

Microcosmic syndrome differentiation and CHM treatment can effectively improve dyspeptic symptoms and endoscopic findings in patients with CG and LSD syndrome and have a good safety profile. Further studies with larger sample sizes and longer follow-up periods are required to confirm the long-term efficacy and mechanism of action of this treatment.

Current tongue segmentation methods often struggle with extracting global features and performing selective filtering, particularly in complex environments where background objects resemble the tongue. These challenges significantly reduce segmentation efficiency. To address these issues, this article proposes a novel model for tongue segmentation in complex environments, combining Mamba and U-Net. By leveraging Mamba's global feature selection capabilities, this model assists U-Net in accurately excluding tongue-like objects from the background, thereby enhancing segmentation accuracy and efficiency.

To improved the segmentation accuracy of the U-Net backbone model, we incorporated the Mamba attention module along with a multi-stage feature fusion module. The Mamba attention module serially connects spatial and channel attention mechanisms at the U-Net 's skip connections, selectively filtering the feature maps passed into the deep network. Additionally, the multi-stage feature fusion module integrates feature maps from different stages, further improving segmentation performance.

Compared with state-of-the-art semantic segmentation and tongue segmentation models, our model improved the mean intersection over union by 1.17%. Ablation experiments further demonstrated that each module proposed in this study contributes to enhancing the model's segmentation efficiency.

This study constructs a Tongue segmentation model based on U-Net and Mamba (TUMamba). The model effectively extracted global spatial and channel features using the Mamba attention module, captured local detail features through U-Net, and enhanced image features via multi-stage feature fusion. The results demonstrate that the model performs exceptionally well in tongue segmentation tasks, proving its value in handling complex environments.