ObjectiveTo investigate the mechanism of Xiaozhi Qinggan decoction （XQD） in preventing and treating metabolic dysfunction-associated steatotic liver disease （MASLD） by regulating ferroptosis， network pharmacology， in vitro and in vivo experiments. MethodsIn the in vivo experiment， mouse MASLD models were established by high-fat diet （HFD） induction. The model mice were randomly assigned to a positive control group （silybin， 50 mg·kg^-1）， low-， medium- and high-dose XQD groups （4.725， 9.45， 18.9 g·kg^-1）， with a normal control group. After 4 weeks of modeling， mice except the normal group were administered intragastrically for 8 consecutive weeks. Liver function， serum lipid levels， hepatic histopathology， as well as the levels of malondialdehyde （MDA）， superoxide dismutase （SOD）， reduced glutathione （GSH） and oxidized glutathione （GSSG） and Fe²⁺ were detected. The mRNA and protein expression of p53， SLC7A11 and GPX4 were determined by quantitative Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot. In the network pharmacology analysis， active components and potential targets of XQD for MASLD were screened， followed by functional and pathway enrichment analyses， and molecular docking was performed to verify the target binding activity. In the in vitro experiment， the optimal concentration of XQD-containing serum was screened by cytotoxicity assay. HepG2 cells were transfected with ov-NC or ov-p53 plasmid， and a lipid accumulation model was induced by free fatty acid （FFA， 1.0 mmol·L^-1）. Cells were divided into a normal group， FFA model group， ov-NC+XQD （15%） group and ov-p53+XQD （15%） group. Intracellular Fe²⁺ level and lipid accumulation were evaluated， and the protein expression of p53， SLC7A11 and GPX4 was measured by Western blot. ResultsCompared with the normal group， the model group exhibited markedly elevated body weight， liver weight， liver index， fasting blood glucose， AUC of glucose tolerance test， serum liver function and blood lipid levels at week 12 （P<0.01）. Hepatic steatosis and inflammatory infiltration were observed by pathological staining. Additionally， hepatic levels of MDA， SOD and Fe²⁺ were increased （P<0.01）， while GSH， GSSG and the GSH/GSSG ratio were decreased （P<0.01）. The mRNA and protein expression of hepatic p53 was upregulated （P<0.01）， whereas the expression of SLC7A11 and GPX4 was downregulated （P<0.01）. Compared with the model group， the low- and medium-dose XQD groups showed significantly decreased body weight at week 12 （P<0.05）. The silybin group， together with the medium- and high-dose XQD groups， presented reduced liver weight and liver index （P<0.05）. Fasting blood glucose and the AUC of glucose tolerance test were lowered in all four treatment groups （P<0.05， P<0.01）. Pathological staining revealed alleviated hepatic steatosis and inflammation， accompanied by decreased serum liver function and blood lipid levels （P<0.05， P<0.01）. Moreover， hepatic MDA and SOD levels were markedly reduced， while GSH， GSSG and the GSH/GSSG ratio were significantly elevated （P<0.05， P<0.01）. Hepatic Fe²⁺ level was decreased （P<0.01）. The mRNA and protein expression of hepatic p53 was downregulated， and the expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. Network pharmacology analysis identified quercetin， kaempferol， luteolin， tanshinone IIA and isorhamnetin as the core active components of XQD， with p53 serving as the key target. Stable binding was verified between these active components and the p53 protein. The optimal concentration of XQD-containing serum in vitro was determined to be 15%. Compared with the normal group， the model group showed increased intracellular Fe²⁺ and lipid accumulation， significantly upregulated p53 protein expression （P<0.01）， and markedly downregulated SLC7A11 and GPX4 protein expression （P<0.01）. Compared with the model group， the ov-NC group exhibited reduced Fe²⁺ and lipid accumulation， downregulated p53 expression， and upregulated SLC7A11 and GPX4 expression. In the ov-p53 group， p53 expression was upregulated （P<0.01）， while SLC7A11 and GPX4 expression was downregulated （P<0.01）. ConclusionXQD inhibits ferroptosis by downregulating p53 and upregulating SLC7A11 and GPX4， thereby alleviating oxidative stress and lipid peroxidation in hepatocytes and improving MASLD.

ObjectiveTo explore the effect of oral sodium butyrate on skeletal muscle atrophy in CT26 tumor mice through the gut microbiota-skeletal muscle axis and its potential mechanism. MethodsSixty SPF BALB/c male mice aged 8 weeks were randomly divided into a normal control group (NC, n=18) and a ABX-depleted group (ABX, n=42). The ABX mice were pretreated with a quadruple antibiotic cocktail via oral gavage (0.2 ml per administration, once daily, 6 d per week, for 2 weeks), whereas NC received an equal volume of sterile water. The quadruple antibiotic cocktail consisted of metronidazole (1 g/L), vancomycin (0.5 g/L), ampicillin (1 g/L), and gentamicin (1 g/L). Following successful pretreatment, six mice from each group were randomly selected for gut microbiota sequencing analysis and designated as the Abx group and the NC0 group, respectively. Theremaining mice in ABX were subcutaneously inoculated in the dorsum with 0.2 ml of CT26 cell suspension (at a cell density of 1×10⁷/ml). Then these mice were randomly allocated into three subgroups: a control tumor bearing model group (0_NaB, n=12), a tumor-bearing model group receiving low-dose oral sodium butyrate (L_NaB, n=12), a tumor-bearing model group receiving high-dose oral sodium butyrate (H_NaB, n=12). And mice in NC were inoculated at the same site with 0.2 ml of normal saline. The administration dose for L_NaB was 0.3 g/(kg·d), that for H_NaB was 0.5 g/(kg·d), while NC and 0_NaB were given the same volume of normal saline (0.2ml per time, once daily, 6 d per week, for 4 weeks). The general condition of mice was monitored, and forelimb grip strength gastrocnemius muscle mass and its muscle fiber cross-sectional area were measured for each group. The structural changes in gut microbiota were assessed by 16S rRNA sequencing of cecal contents. Pathological alterations in the intestinal wall were examined via HE staining. Serum and gastrocnemius muscle levels of TNF‑α, IL-6, IL-1β, and LPS were quantified using ELISA. The protein expression of ZO-1 and occludin in the small intestine, as well as proteins associated with the TLR4/MyD88/NF-κB signaling pathway in the gastrocnemius muscle, were detected by Western blot analysis. Results(1) The alpha-diversity in Abx was significantly lower than that in NC0 (P<0.01), a significant decrease of the mass and muscle fiber cross-sectional area of the gastrocnemius (P<0.01), with the majority of gut microbiota being effectively depleted. (2) Compared with NC, the subcutaneous tumors of mice in 0_NaB were prominent, a significant increase of the mass and muscle fiber cross-sectional area of the gastrocnemius, accompanied by a significant decrease in body weight at the end of the 3th and 4th week (P<0.05), and a significant weakening of the forelimb grasping strength at the 5th and 6th week (P<0.01). Compared with 0_NaB, the tumor mass of mice in L_NaB and H_NaB showed a significant decreasing trend, and the grip strength of the forelimbs significantly increased at the 5th and 6th week (P<0.05, P<0.01). (3) Compared with 0_NaB, the Shannon and Observed species indices in α diversity of L_NaB and H_NaB were significantly increased (P<0.05). At the genus level, compared with 0_NaB, L_NaB exhibited a significant decrease in the relative abundance of Parasutterella (P< 0.01), while H_NaB showed significant reductions in the relative abundances of both Escherichia-Shigella and Parasutterella (P < 0.01). (4) Compared with 0_NaB, the small intestinal tissue structure in L_NaB and H_NaB was more intact, the infiltration of inflammatory cells was significantly reduced, and the capillaries were slightly dilated. The expression levels of ZO-1 and occludin proteins in L_NaB were significantly increased (P<0.01). (5) The LPS concentration in the gastrocnemius muscle and the protein expression levels of TLR4, MyD88, p-IκBα, and p-NF‑κB p65 in L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05). The serum TNF‑α concentration in H_NaB and TNF-α concentration in the gastrocnemius muscle of the L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05, P<0.01, P<0.01). ConclusionOral administration of NaB can improve gut microbiota α diversity, adjusting its composition, improving intestinal mucosal barrier function, reducing the LPS-induced pro-inflammatory response, and delaying skeletal muscle atrophy. The underlying mechanism may involve down regulation of TLR4/MyD88/NF-κB signaling in skeletal muscle.

Objective To comprehensively analyze the current epidemic characteristics and disease burden of brucellosis in Tongliao City, and to provide a basis for the prevention and control strategy of brucellosis in Tongliao City. Methods The report data of brucellosis in Tongliao City from 2018 to 2023 were collected. Descriptive methods were used for data analysis, and the disability-adjusted life years and indirect economic losses were calculated. Results From 2018 to 2023, a total of 22 034 cases were reported in Tongliao City, with an average annual incidence of 136.17/100 000. The incidence was statistically different between men and women ( χ²=12.23, P=0.032). The majority of cases were farmers (94.25%), followed by herdsmen (1.67%). The age group was concentrated between 30-60 years old (79.30%), among which the majority of cases were in the 40-50 years group (6 883/22 034). The onset time had seasonal characteristics, and the peak period was from March to August (the seasonal index was between 115.40%-151.29%). In terms of regional distribution, cases were reported in all counties (banners). The average annual incidence was highest in Kulun Banner (233.85/100 000) and Zalut Banner (210.13/100 000), and lowest in Keerqin District (42.28/100 000) and Holingol City (31.87/100 000). The analysis of disease burden showed that a total of 677.55 person-years (YLD) were lost from 2018 to 2023, with an average annual loss of 112.92 person-years. The total indirect economic loss was 59.3576 million yuan, with an average annual loss of 9.892 9 million yuan, and the people over 60 years old had the lowest annual loss. Conclusion The overall brucellosis epidemic in Tongliao City has shown a fluctuating downward trend. The epidemic prevention and control should be strengthened in farmers, people aged 40-50 years old, and areas such as Zalut Banner and Kulun Banner to further control the epidemic of brucellosis.

By reviewing the physical biological research on the activation of acupoint effects by acupuncture， this paper explains the activation mechanism from the perspective of the generation and transmission of mechanical signals caused by acupuncture， and reveals the physical-chemical coupling processes in the acupoint microenvironment. Future research should focus on locally mechanosensitive cells， further exploring how acupuncture mechanical signals trigger dynamic changes in cells and molecules in the acupoints， and the physical-chemical information transduction mechanism， which will provide scientific evidence for the acupoint activation during acupuncture. Related studies will contribute to a deeper understanding of the scientific principles behind acupuncture and promote its clinical application and development.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Microplastics are plastic fibers, particles, or films with a particle size of less than 5 mm. They are widely found in water, soil, and atmospheric environments. Because of their small particle size, large surface area, strong adsorptive capacity and other characteristics, they can adsorb heavy metals, persistent organic pollutants, environmental endocrine disruptors and other substances. When humans are exposed to microplastics, the particles can not only have toxic effects on the contact sites, but also penetrate tissue barriers and acess other organs, potentially causing systemic toxic effects. Existing epidemiological and toxicological studies have shown that microplastics can cause damage to the digestive, respiratory, nervous and reproductive systems. However, their bio-distribution, metabolic characteristics and toxic mechanisms have not been fully clarified. This study provides a systematic review of the absorption, distribution, metabolism and excretion characteristics of microplastics in living organisms. By integrating factors such as particle size and chemical composition, this study also investigates the toxic effects of microplastics on multiple organ systems (e.g., digestive and nervous systems) and key organs (e.g., intestine and liver), as well as the underlying molecular mechanisms. The aim is to provide a scientific basis for a comprehensive assessment of the health risks of microplastics and to offer theoretical support for the development of relevant prevention and control strategies.

Objective: To explore whether digital facial and tongue diagnostic technologies can support the assessment of coronary heart disease (CHD) patients for coronary artery stenosis severity, and examine potential associations between digital tongue diagnosis features and myocardial biomarkers. Methods: The TFDA-1 face and tongue diagnosis instrument and the TDAS analysis system were used to perform intelligent visual examination and analysis of the facial and tongue in CHD patients who attended the Department of Cardiology at Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine between October 2, 2023 and July 31, 2024. Variables were screened using principal component analysis (PCA) and multicollinearity analysis to construct four machine learning models, including random forest, LightGBM, decision tree, and naive Bayes, for the early prediction of coronary artery stenosis severity. Model performance metrics, including sensitivity, specificity, precision, F1 score, accuracy, and the area under the receiver operating characteristic (ROC) curve (AUC), were evaluated. Visual analyses were performed using the SHapley Additive exPlanations (SHAP) interpreter and decision curve analysis. For patients after percutaneous coronary intervention (PCI), a conceptual model linking cardiac biomarkers and tongue diagnosis was constructed using the partial least squares structural equation modeling (PLS-SEM), and its validity was assessed. Results: A total of 459 CHD patients were enrolled and assigned to a PCI group and a non-PCI group (which comprised two subgroups: mild stenosis or less group, moderate stenosis or greater group). For sublingual vein (SV) features, the PCI group had lower SV-a and SV-b than the other groups (P < 0.01 and P < 0.05, respectively). For tongue surface features, the PCI group had significantly higher tongue body (TB)-L, TB-a, and TB-b (P < 0.05, P < 0.01, and P < 0.001, respectively), as well as higher tongue coating (TC)-a and TC-b (P < 0.01 and P < 0.001, respectively). Age, SV-a, SV-b, creatine kinase-myocardial band (CK-MB), CK, TC-a, lip-L, and lip-b were incorporated in the machine learning models. The random forest model performed best, with an AUC of 0.924, an F1 score of 0.839, precision of 0.807, accuracy of 0.864, sensitivity of 0.873, and specificity of 0.839. Decision curve analysis indicated that both LightGBM and random forest had clinical utility. PLS-SEM confirmed the pathway relationships: myocardial biomarkers → TB and myocardial biomarkers → TC (coefficient = – 0.238, t = 2.239, P = 0.025, and coefficient = – 0.270, t = 2.522, P = 0.012, respectively). Conclusion This study developed a noninvasive early warning model for coronary artery stenosis in patients with CHD. It applied PLS-SEM to investigate the association between post-PCI cardiac biomarkers and tongue diagnosis, and validated the proposed association chain. These findings suggest that intelligent traditional Chinese medicine (TCM) visual diagnosis integrated with modern digital technology may support CHD risk assessment and comprehensive health management.

BACKGROUND: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC death. However, the current understanding of the targeting agents and mechanisms of RIPK3 in the treatment of glaucoma remains limited. Notably, artificial intelligence (AI) technologies have significantly advanced drug discovery. This study aimed to discover RIPK3 inhibitor with AI assistance. METHODS: An acute ocular hypertension model was used to simulate pathological ocular hypertension in vivo . We employed a series of AI methods, including large language and graph neural network models, to identify the target compounds of RIPK3. Subsequently, these target candidates were validated using molecular simulations (molecular docking, absorption, distribution, metabolism, excretion, and toxicity [ADMET] prediction, and molecular dynamics simulations) and biological experiments (Western blotting and fluorescence staining) in vitro and in vivo . RESULTS: AI-driven drug screening techniques have the potential to greatly accelerate drug development. A compound called HG9-91-01, identified using AI methods, exerted neuroprotective effects in acute glaucoma. Our research indicates that all five candidates recommended by AI were able to protect the morphological integrity of RGC cells when exposed to hypoxia and glucose deficiency, and HG9-91-01 showed a higher cell survival rate compared to the other candidates. Furthermore, HG9-91-01 was found to protect the retinal structure and reduce the loss of retinal layers in an acute glaucoma model. It was also observed that the neuroprotective effects of HG9-91-01 were highly correlated with the inhibition of PANoptosis (apoptosis, pyroptosis, and necroptosis). Finally, we found that HG9-91-01 can regulate key proteins related to PANoptosis, indicating that this compound exerts neuroprotective effects in the retina by inhibiting the expression of proteins related to apoptosis, pyroptosis, and necroptosis. CONCLUSION AI-enabled drug discovery revealed that HG9-91-01 could serve as a potential treatment for acute glaucoma.
Animals ; Glaucoma/metabolism* ; Neuroprotective Agents/pharmacology* ; Mice ; Receptor-Interacting Protein Serine-Threonine Kinases/metabolism* ; Artificial Intelligence ; Retinal Ganglion Cells/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation ; Mice, Inbred C57BL ; Male