BACKGROUND:Our previous study found that Modified Erxian Pill could alleviate inflammation in collagen-induced arthritis rats,but its mechanism needs to be further verified. OBJECTIVE:To analyze the components absorbed in the blood of Modified Erxian Pill,and observe the effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages. METHODS:(1)Analysis of components absorbed in the blood of Modified Erxian Pill:Ultra-high performance liquid chromatography-high resolution mass spectrometry was used to detect and identify Modified Erxian Pill and its components absorbed in the blood.(2)Effect of the drug-containing serum of Modified Erxian Pill on pyroptosis of J774A.1 macrophages:Molecular docking technology was used to initially verify the sesquiterpenoids and NLRP3 in components absorbed in the blood of Modified Erxian Pill.J774A.1 macrophages were randomly divided into blank control group,lipopolysaccharide+adenosine triphosphate group,and lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill with low(2.5%),medium(5%),and high(10%)dose groups.The release of lactate dehydrogenase in the cell supernatant of each group was detected according to the kit instructions.The levels of interleukin-1β and interleukin-18 in cell supernatant were detected in each group by ELISA.The cell membrane damage was detected by Hoechst/PI staining.The expression levels of NLRP3,Caspase-1,GSDMD,and GSDMD-N protein in the cells of each group were detected by western blot assay. RESULTS AND CONCLUSION:(1)A total of 32 active components of Modified Erxian Pill were identified,and 21 components entered the blood.The main components into blood included a variety of sesquiterpenoids.(2)Molecular docking results showed that 3-O-Acetyl-13-deoxyphomenone,Incensol oxide,Atractylenolide III,Rupestonic acid,and 3,7-Dihydroxy-9,11-eremophiladien-8-one had good binding activity with NLRP3.(3)Compared with the blank control group,lactate dehydrogenase activity and the expression levels of interleukin-1β and interleukin-18 were significantly increased in cell supernatant of lipopolysaccharide+adenosine triphosphate group(P<0.001).Hoechst/PI staining showed that the number of PI-positive cells was significantly increased.After the intervention of lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group,all of them showed different degrees of reduction.(4)Compared with the blank control group,NLRP3,Caspase-1,GSDMD,and GSDMD-N protein expression levels were significantly increased in the lipopolysaccharide+adenosine triphosphate group(P<0.05).Compared with lipopolysaccharide+adenosine triphosphate group,the protein expressions of NLRP3,Caspase-1,GSDMD,and GSDMD-N were significantly decreased in the lipopolysaccharide+adenosine triphosphate+Modified Erxian Pill group(P<0.05),and had a certain dose dependence.These findings verify that the drug-containing serum of Modified Erxian Pill may inhibit the pyroptosis of J774A.1 macrophages by regulating the NLRP3/Caspase-1/GSDMD pathway.

Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI. Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts. Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism. KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Immune infiltration analysis showed that the control group had more infiltration of resting natural killer cells, M2 macrophages, etc., while the HIRI group had more infiltration of M0 macrophages, neutrophils, and naive B cells. Real-time quantitative polymerase chain reaction results showed that compared with the Sham group, the relative expression of DFFB messenger RNA in liver tissue of HIRI group mice increased, and the relative expression of TNFSF10 messenger RNA decreased. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.70, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045). Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

Tumor drug resistance is an important problem in the failure of chemotherapy and targeted drug therapy, which is a complex process involving chromatin remodeling. SWI/SNF is one of the most studied ATP-dependent chromatin remodeling complexes in tumorigenesis, which plays an important role in the coordination of chromatin structural stability, gene expression, and post-translation modification. However, its mechanism in tumor drug resistance has not been systematically combed. SWI/SNF can be divided into 3 types according to its subunit composition: BAF, PBAF, and ncBAF. These 3 subtypes all contain two mutually exclusive ATPase catalytic subunits (SMARCA2 or SMARCA4), core subunits (SMARCC1 and SMARCD1), and regulatory subunits (ARID1A, PBRM1, and ACTB, etc.), which can control gene expression by regulating chromatin structure. The change of SWI/SNF complex subunits is one of the important factors of tumor drug resistance and progress. SMARCA4 and ARID1A are the most widely studied subunits in tumor drug resistance. Low expression of SMARCA4 can lead to the deletion of the transcription inhibitor of the BCL2L1 gene in mantle cell lymphoma, which will result in transcription up-regulation and significant resistance to the combination therapy of ibrutinib and venetoclax. Low expression of SMARCA4 and high expression of SMARCA2 can activate the FGFR1-pERK1/2 signaling pathway in ovarian high-grade serous carcinoma cells, which induces the overexpression of anti-apoptosis gene BCL2 and results in carboplatin resistance. SMARCA4 deletion can up-regulate epithelial-mesenchymal transition (EMT) by activating YAP1 gene expression in triple-negative breast cancer. It can also reduce the expression of Ca²⁺ channel IP3R3 in ovarian and lung cancer, resulting in the transfer of Ca²⁺ needed to induce apoptosis from endoplasmic reticulum to mitochondria damage. Thus, these two tumors are resistant to cisplatin. It has been found that verteporfin can overcome the drug resistance induced by SMARCA4 deletion. However, this inhibitor has not been applied in clinical practice. Therefore, it is a promising research direction to develop SWI/SNF ATPase targeted drugs with high oral bioavailability to treat patients with tumor resistance induced by low expression or deletion of SMARCA4. ARID1A deletion can activate the expression of ANXA1 protein in HER2+ breast cancer cells or down-regulate the expression of progesterone receptor B protein in endometrial cancer cells. The drug resistance of these two tumor cells to trastuzumab or progesterone is induced by activating AKT pathway. ARID1A deletion in ovarian cancer can increase the expression of MRP2 protein and make it resistant to carboplatin and paclitaxel. ARID1A deletion also can up-regulate the phosphorylation levels of EGFR, ErbB2, and RAF1 oncogene proteins.The ErbB and VEGF pathway are activated and EMT is increased. As a result, lung adenocarcinoma is resistant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). Although great progress has been made in the research on the mechanism of SWI/SNF complex inducing tumor drug resistance, most of the research is still at the protein level. It is necessary to comprehensively and deeply explore the detailed mechanism of drug resistance from gene, transcription, protein, and metabolite levels by using multi-omics techniques, which can provide sufficient theoretical basis for the diagnosis and treatment of poor tumor prognosis caused by mutation or abnormal expression of SWI/SNF subunits in clinical practice.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

Chronic atrophic gastritis （CAG）， a common digestive system disease， has an unclear pathogenesis. Currently， it is mostly believed to be related to Helicobacter pylori （Hp） infection， immune factors， dietary factors， bile reflux， long-term use of antibiotics and anti-inflammatory drugs， and other factors. Ferroptosis is a regulated cell death mechanism that is iron-dependent and characterized by disruption of iron metabolism and accumulation of lipid peroxides. More and more studies have found that ferroptosis is closely related to the onset of CAG. Professor LI Diangui， a master of traditional Chinese medicine， first proposed the turbid toxin theory， which holds that spleen deficiency and turbid toxin is the main pathogenic mechanism of CAG. Abnormal iron metabolism regulation is a prerequisite for the accumulation of turbid toxin in CAG， and ferroptosis is in accordance with the pathogenic mechanism （spleen deficiency and turbid toxin） of CAG. This article explores the pathological mechanism of spleen deficiency and turbid toxin in CAG from the perspectives of iron metabolism， oxidative stress， and lipid peroxidation， providing theoretical support of traditional Chinese medicine for the modern research on CAG. It enriches the modern scientific connotation of the turbid toxicity theory and provides new ideas and breakthrough points for the clinical treatment of CAG.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

Chronic atrophic gastritis （CAG）， a common digestive system disease， has an unclear pathogenesis. Currently， it is mostly believed to be related to Helicobacter pylori （Hp） infection， immune factors， dietary factors， bile reflux， long-term use of antibiotics and anti-inflammatory drugs， and other factors. Ferroptosis is a regulated cell death mechanism that is iron-dependent and characterized by disruption of iron metabolism and accumulation of lipid peroxides. More and more studies have found that ferroptosis is closely related to the onset of CAG. Professor LI Diangui， a master of traditional Chinese medicine， first proposed the turbid toxin theory， which holds that spleen deficiency and turbid toxin is the main pathogenic mechanism of CAG. Abnormal iron metabolism regulation is a prerequisite for the accumulation of turbid toxin in CAG， and ferroptosis is in accordance with the pathogenic mechanism （spleen deficiency and turbid toxin） of CAG. This article explores the pathological mechanism of spleen deficiency and turbid toxin in CAG from the perspectives of iron metabolism， oxidative stress， and lipid peroxidation， providing theoretical support of traditional Chinese medicine for the modern research on CAG. It enriches the modern scientific connotation of the turbid toxicity theory and provides new ideas and breakthrough points for the clinical treatment of CAG.

ObjectiveTo explore the therapeutic effect and mechanism of Xianglian Huazhuo prescription on chronic atrophic gastritis （CAG） in rats based on the Hedgehog signaling pathway. MethodsThe CAG rat model was established by sodium salicylate， N-methyl-N′-nitro-N-nitroguanidine （MNNG）， and irregular feeding. The successfully modeled rats were randomly divided into a model group （180 mg·L^-1）， a moradan group （1.4 g·kg^-1）， and Xianglian Huazhuo Prescription groups with high， medium， and low doses （36， 9， 18 g·kg^-1）， followed by drug intervention. Hematoxylin-eosin （HE） staining was used to observe morphological changes in the gastric mucosa. Transmission electron microscopy was used to observe the ultrastructure of gastric mucosa cells. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of Sonic Hedgehog （Shh）， Patched 1 （Ptch1）， and Glioma-associated oncogene homolog 1 （Gli1）. Western blot was used to detect the protein expression levels of Shh， Ptch1， and Gli1 in the gastric mucosa. Immunohistochemistry was used to observe the protein expression of the epithelial marker E-cadherin. ResultsCompared with the normal group， the CAG model group showed a reduction in gastric mucosal intrinsic glands and infiltration of inflammatory cells. The ultrastructure of gastric mucosal cells showed nuclear pyknosis， fewer mitochondria， and abnormal mitochondrial structure. The mRNA and protein expression of Shh， Ptch1， and Gli1 in the gastric mucosa were significantly decreased （P<0.05）， and E-cadherin protein expression was decreased. Compared with the model group， the intervention groups showed varying degrees of improvement in histopathological morphology and cellular ultrastructure. The mRNA and protein expression of Shh， Ptch1， Gli1， and E-cadherin increased to varying degrees. Xianglian Huazhuo Prescription upregulated the expression of key Hedgehog pathway factors and E-cadherin at both the mRNA and protein levels （P<0.05）. ConclusionXianglian Huazhuo prescription has a therapeutic effect on CAG in rats， and its mechanism may be related to activation of the Hedgehog signaling pathway and inhibition of epithelial-mesenchymal transition （EMT）.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.