A 71-year-old male presented with esophageal cancer and severe aortic valve regurgitation. Treatment strategies for such patients are controversial. Considering the risks of cardiopulmonary bypass and potential esophageal cancer metastasis, we successfully performed transcatheter aortic valve implantation and minimally invasive three-incision thoracolaparoscopy combined with radical resection of esophageal cancer (McKeown) simultaneously in the elderly patient who did not require neoadjuvant treatment. This dual minimally invasive procedure took 6 hours and the patient recovered smoothly without any surgical complications.

In order to explore the possible role and molecular mechanism of the combined action of leech and bear bile in liver and gallbladder diseases, this study first used network pharmacology methods to screen the components and targets of leech and bear bile, as well as the related target genes of liver and gallbladder diseases. The selected key genes were subjected to interaction network and GO/KEGG enrichment analysis. Then, using sodium oleate induced HepG2 cell lipid deposition model and DL-ethionine induced mouse fatty liver model, the activity of leech and bear bile alone and in combination in reducing liver fat was evaluated in vitro and in vivo, and the expression of key pathway related proteins suggested by network pharmacology was detected by Western blot. The results of network pharmacology analysis showed that the active ingredients of leech and bear bile have 295 intersecting targets with liver and gallbladder related diseases, involving more than 200 signaling pathways, including the PI3K/Akt signaling pathway and phospholipase D signaling pathway closely related to glucose and lipid metabolism. The results of in vitro validation experiments showed that both leech and bear bile, alone and in combination, can significantly inhibit the lipid deposition induced by sodium oleate in human liver cells, reduce the triacylglycerol level in cell culture supernatant, and inhibit the lipid content in liver cells. The observation results of Nile red staining confocal microscopy showed that the combination of leech and bear bile had better activity in reducing lipid deposition in liver cells compared to using them alone. In a mouse fatty liver model, the combination of leech and bear bile can better reduce elevated organ indices, blood lipids, and liver lipid levels, as well as lower the levels of serum liver injury biomarkers. The animals used in this experiment and related disposal meet the requirements of animal welfare. Before the experiment, it was reviewed and approved by IACUC, Institute of Materia Medica, Chinese Academy of Medical Sciences. The Western blot experiment results showed that the combination of leech and bear bile can significantly upregulate the expression levels of p-PI3K and p-Akt proteins, and increase the p-PI3K/PI3K and p-Akt/Akt ratios, which is consistent with the predicted results of network pharmacology. The combination of leech and bear bile has great potential for treating fatty liver disease, and activating the PI3K/Akt pathway may be one of the important mechanisms for reducing lipid deposition in liver cells.

ObjectiveTo investigate the feasibility and safety of endoscopic retrograde cholangiopancreatography （ERCP） combined with oral cholangiopancreatography in the treatment of major duodenal papilla gallbladder polyps. MethodsA retrospective analysis was performed for the clinical data of eight patients with choledocholithiasis and gallbladder polyps who underwent ERCP and combined with oral cholangiopancreatography for major duodenal papilla cholecystectomy in Center of Digestive Endoscopy， Jilin People’s Hospital， from May 2022 to June 2024， and related data were collected， including the success rate of surgery， the technical success rate of gallbladder polyp removal， the superselective method of cystic duct， the time of operation， the time of gallbladder polyp removal， and surgical complications. ResultsBoth the success rate of surgery and the technical success rate of gallbladder polyp removal reached 100%， and of all eight patients， three patients used guide wire to enter the gallbladder under direct view， while five patients received oral cholangiopancreatography to directly enter the gallbladder. The time of operation was 51.88±12.34 minutes， and the time of gallbladder polyp removal was 23.13±10.94 minutes. The diameter of gallbladder polyp was 2‍ ‍—‍ ‍8 mm， and pathological examination showed inflammatory polyps in three patients， adenomatous polyps in one patient， and cholesterol polyps in four patients. There were no complications during or after surgery. The patients were followed up for 2‍ ‍—‍ ‍27 months after surgery， and no recurrence of gallbladder polyp was observed. ConclusionOral cholangiopancreatography is technically safe and feasible in endoscopic major duodenal papilla cholecystectomy.

Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease. The pathogenesis of AIH remains unclear， but it is mainly autoimmune injury caused by the breakdown of autoimmune tolerance due to the abnormal activation of the immune system， while the specific molecular mechanism remains unknown. Recent studies have shown that abnormal amino acid metabolism plays an important role in the development and progression of AIH. This article reviews the research advances in amino acid metabolic reprogramming in AIH， in order to provide a theoretical basis for amino acid metabolism as a new target for the clinical diagnosis and treatment of AIH.

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.

OBJECTIVE To investigate the mechanism of the inhibitory effect of total flavonoids from Taraxacum mongolicum on high-fat diet-induced obesity in mice through modulation of intestinal flora. METHODS Twenty-four C57BL/6J mice were randomly divided into blank group， model group and T. mongolicum total flavonoid group， with 8 mice in each group. Except for the blank group， the other 2 groups were given a high-fat diet， while T. mongolicum total flavonoid group was given T. mongolicum total flavonoid [400 mg/（kg·d）] intragastrically， once a day， for 8 consecutive weeks. During the experiment， the food intake of each group of mice was recorded. After the last medication， the body mass， fat weight， blood lipid level and pathological changes of liver and epididymal fat in mice were evaluated to observe the effect of T. mongolicum total flavonoid on the treatment of obesity in mice. The changes in abundance and structure of intestinal flora in mice were detected by amplicon sequencing； the effects of T. mongolicum total flavonoids on fat metabolism related genes were analyzed by qPCR. RESULTS Compared with model group， the body weight of mice in T. mongolicum total flavonoids group was decreased significantly （P＜0.05）； the levels of total lipid cholesterol， triglycerides， and LDL cholesterol were all decreased significantly （P＜0.01）， and the level of HDL cholesterol was increased significantly （P＜0.01）； the fat indexes of inguinal white adipose tissue and epididymal white wind_lz@hactcm.edu.cn adipose tissue were significantly reduced （P＜0.05）； significant improvement in hepatocellular steatosis and adipose cytopathy were significantly improved； mRNA expressions of COX7A1 and COX8B were significantly upregulated （P＜0.05）. The results of bacterial colony detection showed that compared with the model group， there was a rising trend in the diversity of the bacterial colony in T. mongolicum total flavonoids group， and the Sobs index characterization and β diversity were increased significantly （P＜0.05）. Relative abundances of Blautia， norank_f_Ruminococcaceae， Bilophila， Alistipes， classified_f_Ruminococcaceae， Parabacteroides， norank_f_Desulfovibrionaceae， Anaerotruncus were significantly up-regulated（P＜0.05）， while those of Faecalibaculum， Erysipelatoclostridium， GCA-900066575， Tuzzerella， Lactobacillus， norank_f_norank_o_RF39， achnospiraceae_FCS020_group were significantly down-regulated （P＜0.05）. CONCLUSIONS T. mongolicum total flavonoids can reduce body mass， fat weight and blood lipid levels， and repair the pathological damage to liver and epididymal fat in obese mice， which is related to improving intestinal flora disorders caused by high-fat diet.

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.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.

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.