Chronic atrophic gastritis （CAG） is a digestive system disease characterized by the reduction and atrophy of the intrinsic glands of the gastric mucosa. This disease is closely related to risk factors such as Helicobacter pylori （Hp） infection，long-term unhealthy eating habits and lifestyle. As CAG is a key link in the development of gastric cancer，effectively preventing its deterioration is of great significance for the prevention of gastric cancer. At present，Western medicine mainly uses symptomatic treatments such as eradicating Hp，protecting gastric mucosa， and promoting gastrointestinal motility. However， long-term use is prone to drug resistance and cannot reverse limitations such as gland atrophy， making it urgent to explore new intervention strategies. In recent years，with the deepening of CAG mechanism research，the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway，as one of the classic signaling pathways，plays a significant role in the occurrence and development of CAG，while its systematic summary is still blank. Based on the regulatory advantages of "multi-target，multi-pathway，and low toxicity"，traditional Chinese medicine can improve the pathological process of CAG by intervening in key nodes of the PI3K/Akt pathway. In this paper，the research progress of traditional Chinese medicine regulating PI3K/Akt pathway to improve CAG was systematically reviewed for the first time. The expression of PI3K/Akt signaling pathway in CAG was discussed，including the regulation of inflammation and oxidative stress，cell proliferation and apoptosis，and autophagy. The traditional Chinese medicine flavonoids，alkaloids，terpenoids and other compounds that regulate this pathway were summarized. The traditional Chinese medicine compounds mainly include classic famous prescriptions such as Xiaochaihu Tang，Banxia Xiexin Tang，Morodan concentrated pills，Elian granules and other traditional Chinese patent medicines，as well as empirical prescriptions such as modified Leweiyin formula，and Qiling prescription. This study aims to give full play to the advantages of traditional Chinese medicine and lay a solid foundation for the wide application and further development of CAG treatment，and provide new ideas for clinical research and drug research on CAG.

AIM:To investigate the associations of triglyceride glucose(TyG)index, triglyceride glucose-body mass index(TyG-BMI), and homeostatic model assessment of insulin resistance(HOMA-IR)with diabetic retinopathy(DR), and to evaluate their diagnostic value.METHODS: This study was a single-center retrospective study. Patients with type 2 diabetes mellitus(T2DM)who were hospitalized in the endocrinology department of 3201 Hospital from January 1, 2023 to March 1, 2025 were included. According to the diagnostic criteria for DR, participants were classified into DR group and non-DR(NDR)group. Then the association of TyG index, TyG-BMI, and HOMA-IR index with DR of the two groups of patients were alalyzed.RESULTS:A total of 969 patients with T2DM were enrolled in this study, including 816 patients in the DR group. Among DR group, 271 were males(33.2%)and 545 were females(66.8%), with a mean age of 56.78±11.88 years. The NDR group consisted of 153 patients, including 41 males(26.8%)and 112 females(73.2%), with a mean age of 59.40±10.52 years. Statistically significant differences were observed between the DR group and the NDR group in terms of age, BMI, TyG index, TyG-BMI, HOMA-IR index, fasting blood glucose(FBG), 2-h postprandial blood glucose(2 hPBG), fasting insulin(FINS), 2-h postprandial insulin(2 hPINS), fasting C-peptide(FCP), 2-h postprandial C-peptide(2 hPCP), total cholesterol(CHO), triglyceride(TG), low-density lipoprotein(LDL-C), blood urea nitrogen(BUN), uric acid(UA), direct bilirubin(DBIL), glycated hemoglobin(HbA1c), milligrams per total protein(M-TP), microalbuminuria(MALB), urinary albumin to creatinine ratio(UACR), 24-hour urine protein, white blood cell(WBC), neutrophil(N), and platelets(PLT; all P<0.05), while no significant differences were found in the remaining indicators(all P>0.05). In multivariable Logistic regression, both TyG index(aOR=198.65, 95% CI: 66.73-591.41, P<0.001)and TyG-BMI(aOR=1.03, 95% CI: 1.02-1.04, P<0.001)remained independently positive associated with DR. Quartile analysis indicated a progressive increase in DR risk with ascending quartiles of TyG index and TyG-BMI(all Ptrend<0.001). In contrast, HOMA-IR was not significantly associated with DR. Restricted cubic spline analysis, fully adjusted for confounders, showed a nonlinear upward trend in DR risk with increasing TyG index(Pnonlinearity<0.001), whereas TyG-BMI exhibited a U-shaped association(Pnonlinearity<0.05). No significant association was found between HOMA-IR and DR after propensity score matching. Receiver operating characteristic(ROC)curve demonstrated area under curve(AUC)values of 0.870(95% CI: 0.839-0.901)for TyG index, 0.710(95% CI: 0.665-0.755)for TyG-BMI, and 0.657(95% CI: 0.608-0.706)for HOMA-IR.CONCLUSION:The TyG index and TyG-BMI are risk factors for DR. A dose-dependent increase in DR risk was associated with elevated TyG index values. TyG-BMI exhibited an inverted U-shaped relationship with DR risk. The TyG index had better diagnostic efficiency for DR compared to both TyG-BMI and HOMA-IR index.

Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

Hepatocellular carcinoma（HCC）， as one of the common malignant tumours， has seen a continuous rise in incidence and mortality worldwide， posing a serious threat to human health. However， traditional treatments have certain limitations， therefore， the exploration of new therapeutic strategies is particularly urgent. In recent years， with in-depth research on the regulatory mechanisms of microRNA（miRNA） in tumour occurrence and development， it has become new targets for HCC diagnosis and treatment. As a traditional treatment method， Chinese medicine， due to its multi-component， multi-pathway， and multi-target overall regulatory characteristics， shows broad prospects in treating HCC by regulating miRNAs. Accordingly， this paper reviews recent studies on the role of miRNAs in HCC and research advances in traditional Chinese medicine interventions， finding that various miRNAs play key roles in HCC cell cycle regulation， proliferation and apoptosis， invasion and metastasis， immune microenvironment， and drug resistance. It summarises how active ingredients， extracts， medicinal pairs， and formulas of Chinese medicine act on specific miRNAs to regulate their downstream target gene expression， affecting the malignant behaviour of HCC cells and exerting anti-cancer effects. This study aims to provide a theoretical basis for miRNAs as potential biomarkers and therapeutic targets for HCC， as well as to offer new ideas for developing miRNA-based targeted Chinese medicine therapies.

Non-alcoholic fatty liver disease （NAFLD） is a chronic liver disease closely related to metabolism， which is mainly characterized by abnormal lipid deposition in hepatocytes. In recent years， with the increasing prevalence of obesity and metabolic syndrome， NAFLD has become one of the most common chronic diseases in the world. The pathogenesis of NAFLD is complex and varied， involving the cross-regulation of multiple signaling pathways such as glucose-lipid metabolism， oxidative stress， and inflammation. The TLR4 signaling pathway plays a key role in the development and progression of NAFLD， and abnormal activation of this pathway accelerates the deterioration of NAFLD by promoting the release of pro-inflammatory cytokines， inducing oxidative stress， and exacerbating insulin resistance. Studies have shown that traditional Chinese medicine （TCM） can regulate the TLR4 signaling pathway to alleviate the symptoms and pathological features of NAFLD. The present review summarizes the experimental research progress in the TCM regulation of the TLR4 signaling pathway in treating NAFLD in the past 5 years， covering a wide range of TCM active ingredients （such as polysaccharides， terpenoids， alkaloids， flavonoids） and compound prescriptions. The active ingredients and compound prescriptions of TCM can effectively ameliorate lipid metabolism disorders， reduce insulin resistance， regulate intestinal flora， and inhibit inflammation and oxidative stress by regulating the TLR4 signaling pathway via multiple targets and pathways， thus slowing down the progression of NAFLD. Through in-depth analysis of the pathological mechanisms of NAFLD and exploration of the potential of TLR4 signaling pathway as a therapeutic target， we can provide theoretical support for the application of TCM in the treatment of NAFLD， as well as new perspectives and directions for future clinical research and new drug development， thereby promoting the innovation and development of therapeutic strategies for NAFLD.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

Objective To analyze the detection rate and risk factors of pulmonary infection in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods A total of 308 patients with AECOPD hospitalized at the Second Affiliated Hospital of Chengdu Medical College were selected from October 2020 to October 2023 as the research subjects. The incidence of pulmonary infections was analyzed, and univariate and logistic multivariate regression analyses were conducted to identify the risk factors of pulmonary infections. Results Among the 308 patients with AECOPD, 155 cases (50.32%) had pulmonary infection and were selected as the infected group, and 153 cases without pulmonary infection were included in the uninfected group. There were no obvious differences in gender, body mass index, education level, drinking history, hypertension, heart failure and malnutrition between the two groups (P>0.05). There were significant differences between the two groups in age, hospitalization time, mechanical ventilation history, smoking history, glucocorticoid use time, and diabetes mellitus (P<0.05). Logistic analysis showed that the ORs of pulmonary infection risk in AECOPD patients with age ≥ 60 years old, hospitalization time ≥ 14 days, mechanical ventilation history, glucocorticoid use time ≥ 7 days, diabetes mellitus, and smoking history were 2.740 (1.024-7.330), 4.586 (2.318-9.071), 3.971 (1.806-8.731), 3.264 (1.419-7.508), 2.680 (1.012-7.100), and 2.826 (1.156-6.909), respectively. Conclusion The risk of pulmonary infection is high in AECOPD patients, which is influenced by factors such as age, hospitalization time, mechanical ventilation history, smoking history, and glucocorticoid use time. Clinical screening should be focused on the above indicators and active prevention and treatment measures should be taken to reduce the occurrence of pulmonary infection.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.