Objective: To develop QingNangTCM, a specialized large language model (LLM) tailored for expert-level traditional Chinese medicine (TCM) question-answering and clinical reasoning, addressing the scarcity of domain-specific corpora and specialized alignment. Methods: We constructed QnTCM_Dataset, a corpus of 100 000 entries, by integrating data from ShenNong_TCM_Dataset and SymMap v2.0, and synthesizing additional samples via retrieval-augmented generation (RAG) and persona-driven generation. The dataset comprehensively covers diagnostic inquiries, prescriptions, and herbal knowledge. Utilizing P-Tuning v2, we fine-tuned the GLM-4-9B-Chat backbone to develop QingNangTCM. A multi-dimensional evaluation framework, assessing accuracy, coverage, consistency, safety, professionalism, and fluency, was established using metrics such as bilingual evaluation understudy (BLEU), recall-oriented understudy for gisting evaluation (ROUGE), metric for evaluation of translation with explicit ordering (METEOR), and LLM-as-a-Judge with expert review. Qualitative analysis was conducted across four simulated clinical scenarios: symptom analysis, disease treatment, herb inquiry, and failure cases. Baseline models included GLM-4-9B-Chat, DeepSeek-V2, HuatuoGPT-II (7B), and GLM-4-9B-Chat (freeze-tuning). Results: QingNangTCM achieved the highest scores in BLEU-1/2/3/4 (0.425/0.298/0.137/0.064), ROUGE-1/2 (0.368/0.157), and METEOR (0.218), demonstrating a balanced and superior normalized performance profile of 0.900 across the dimensions of accuracy, coverage, and consistency. Although its ROUGE-L score (0.299) was lower than that of HuatuoGPT-II (7B) (0.351), it significantly outperformed domain-specific models in expert-validated win rates for professionalism (86%) and safety (73%). Qualitative analysis confirmed that the model strictly adheres to the “symptom-syndrome-pathogenesis-treatment” reasoning chain, though occasional misclassifications and hallucinations persisted when dealing with rare medicinal materials and uncommon syndromes. Conclusion Combining domain-specific corpus construction with parameter-efficient prompt tuning enhances the reasoning behavior and domain adaptation of LLMs for TCM-related tasks. This work provides a technical framework for the digital organization and intelligent utilization of TCM knowledge, with potential value for supporting diagnostic reasoning and medical education.

Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

Objective:To explore the occupational adaptability of psychiatric medical caregivers from the perspective of a composite ecosystem.Methods:Using purposive sampling combining with snowball sampling and based on ecosystem theory, an interview outline was set up to conduct semi-structured interviews with psychiatric medical caregivers from October to December 2023. The Colaizzi 7-step analysis method was used to extract the themes.Results:Totally 15 psychiatric medical caregivers aged 44-61 years, 4 males and 11 females. There were three themes in the study: microsystems-changes in cognition, emotion, and physical and mental health; mid-level system-support and difficulties for families, hospitals, and nursing staff institutions; the macro system-social psychological support system was lacking.Conclusions:Psychiatric medical caregivers lack professional knowledge, have more negative emotions in their emotional experiences, and have a serious lack of mental health support systems. There are biases and misunderstandings towards them in society. It is recommended that managers pay attention to the physical and mental health of psychiatric caregivers and improve their work adaptability.

Pulp regeneration is currently a hot topic in pulp disease research.With the development of regenerative medicine,pulp regeneration is transitioning from basic research to clinical applications,and stable results have been observed in some cases.However,achieving higher success rates and restoring pulp function remains a challenge in the field of pulp disease.Stem cells,growth factors,and scaffold materials are fundamental elements of tissue engineering.In recent years,dental pulp regeneration related scaffolds have received widespread attention,and new progress has been made in natural,human,and artificially synthesized scaffold materials.This article reviews the scaffold materials for pulp regeneration,aiming to provide reference for the selection of scaffold materials for dental pulp regeneration.

Objective:To develop and evaluate a medical visual question answering (VQA) model for neonatal lung ultrasound (LUS) images to enhance intelligent auxiliary diagnosis of neonatal pulmonary diseases.Methods:Using data from neonates admitted to Beijing Obstetrics and Gynecology Hospital, Capital Medical University (January 2023 to December 2024), an image-question-answer dataset comprising 251 LUS images was constructed [43 pneumonia (17.1%), 42 neonatal respiratory distress syndrome (16.7%), 83 transient tachypnea (33.1%), and 83 normal (33.1%) images] with a four-tier medical question-answer framework. Building upon the Qwen2.5-VL-7B base model and integrating LoRA fine-tuning with chain-of-thought prompting, we developed the NLUS-VQA model to enhance visual-language semantic alignment and enable stepwise clinical reasoning, achieving efficient small-sample adaptation. Model performance was comprehensively assessed through natural language generation metrics (BLEU-4, ROUGE-1/2/L), qualitative evaluation of characteristic recognition, and clinical consistency analysis.Results:(1) Quantitative evaluation demonstrated that NLUS-VQA achieved scores of 22.38 (BLEU-4), 48.26 (ROUGE-1), 22.40 (ROUGE-2), and 37.20 (ROUGE-L), representing significant improvements over baseline models. (2) Qualitatively, the model exhibited strong performance in identifying lung consolidation, coalescent B-lines, and snowflake signs, with its chain-of-thought strategy enhancing clinical interpretability and answer accuracy. (3) Clinically, NLUS-VQA achieved a Cohen's Kappa coefficient of 0.78 and diagnostic accuracy of 80.8% (21/26), indicating substantial agreement with clinical experts.Conclusion:The NLUS-VQA model demonstrates robust interpretability in recognizing key sonographic patterns (e.g. lung consolidation, confluent B-lines, and snowflake signs), providing a scalable framework for small-sample medical image analysis, though diagnostic performance on complex conditions remains limited by dataset scale and minority class representation.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis. Mesangial hyperplasia and deposition of IgA immune complex are typical pathological changes of IgAN. Animal model is an important tool to explore the pathogenesis, diagnosis and treatment plan, and evaluate the safety and efficacy of drugs. At present, there are many kinds of IgAN animal models, including humanized animal models and non-humanized animal models, and there are great differences in the modeling principle, method, time and pathological changes. The humanized animal model is closer to the pathogenesis of IgAN in humans and has gradually become a research hotspot. In this paper, common animal models of IgAN in detail from the aspects of modeling method and time, characteristics and significance of each model, and the research progress of anthropomorphic animal models are reviewed to provide reference and inspiration for the basic research of IgAN.

Objective:To construct and evaluate the predictive performance of a multiphase ultrasound radiomics model for microvascular invasion（MVI）in hepatocellular carcinoma（HCC）.Methods:A total of 126 patients with pathologically confirmed HCC were retrospectively enrolled from 4 medical centers between May 2018 and July 2025，including the First Hospital of Shanxi Medical University，Shanxi Province Third People's Hospital，Changzhi People's Hospital，and the Organ Transplant Center of the Affiliated Hospital of Qingdao University. A total of 630 ultrasound images of the lesions in different phases were collected，from which 1 561 radiomic features were extracted. The patients from medical institutions in Shanxi Province were chosen as the training set（ n=91），and the patients from the Organ Transplant Center of the Affiliated Hospital of Qingdao University were chosen as the validation set（ n=35）. In the training set，37.4%（34/91）patients presented MVI（+），whereas in the validation set，54.3%（19/35）patients presented MVI（+）. Radiomics features were extracted from ultrasound images，and features related to the MVI（+）were selected through dimensionality reduction analysis. Five multiple machine learning algorithms were used to construct predictive models，which were then evaluated using an external validation set. The Radscore was calculated，and a nomogram was constructed combining Radscore with ultrasound and clinical characteristics to predict MVI. Results:The model combining radiomics features from the portal venous phase and the delay phase showed the best predictive performance in both the training and validation sets，with area under curve（AUC）values of 0.835 and 0.727，respectively. The prediction model developed using radiomics Radscore and clinical indicators could be represented and presented as a nomogram.Conclusions:The radiomics model based on multi-phase ultrasound offers a novel approach for non-invasive preoperative prediction of MVI in liver cancer. Furthermore，its integration with clinical features aids in optimizing clinical treatment strategies.

Objective To explore the targets and mechanism of Buyang Huanwu Decoction in preventing and treating atherosclerosis through network pharmacology,molecular docking and animal experiment.Methods The main active components and related targets of Buyang Huanwu Decoction were obtained and screened through databases such as TCMSP,HERB,UniProt,PubChem,SwissADME and SwissTargetPrediction.Six disease databases such as DrugBank,GeneCards,DisGeNET,OMIM,PharmGKB and TTD were used to obtain AS related targets.R language was used to obtain common targets for the drug and disease.STRING 11.5 database was used for protein interaction network analysis,and Cytoscape 3.9.1 software was used to conduct network topology parameters and obtain core targets.GO and KEGG enrichment analysis were performed on the common targets using DAVID platform.Molecular docking of core genes with the main active components of Buyang Huanwu Decoction was conducted using AutoDock Vina 1.5.6 software.An AS mouse model was established and intervened with Buyang Huanwu Decoction.The lipid content of the mouse aortic sinus was observed using Oil Red O staining.Western blot was used to detect the expression of PI3K/AKT/p38 signaling pathway,and ELISA was used to detect the contents of TNF-α and IL-17 in mouse serum.Results A total of 104 main active components and 283 action targets of Buyang Huanwu Decoction were obtained,as well as 5 347 AS related targets and 218 common targets for drugs and disease.Buyang Huanwu Decoction may use key active components such as quercetin,kaempferol and baicalin as core targets for TP53,MAPK1,AKT1,and exert its therapeutic effect on AS through PI3K-Akt signaling pathway,TNF signaling pathway and IL-17 signaling pathway,etc.Molecular docking indicated that quercetin,luteolin,kaempferol and baicalin had good affinity with TP53,HSP90AA1,MAPK1,AKT1 and RELA targets.MAPK1 had strong binding activity with baicalin and luteolin.The experimental results showed that Buyang Huanwu Decoction could reduce the lipid content in aortic sinus of AS mice,reduce the contents of TNF-α and IL-17 in serum(P<0.01)and significantly down-regulate the expression levels of PI3K,p-AKT and p-p38 proteins(P<0.05,P<0.01).Conclusion The mechanism of Buyang Huanwu Decoction for preventing and treating AS may be related to regulating the expression of the PI3K/AKT/p38 signaling pathway,thereby reducing inflammatory response.

Objective To explore the targets and mechanism of Buyang Huanwu Decoction in preventing and treating atherosclerosis through network pharmacology,molecular docking and animal experiment.Methods The main active components and related targets of Buyang Huanwu Decoction were obtained and screened through databases such as TCMSP,HERB,UniProt,PubChem,SwissADME and SwissTargetPrediction.Six disease databases such as DrugBank,GeneCards,DisGeNET,OMIM,PharmGKB and TTD were used to obtain AS related targets.R language was used to obtain common targets for the drug and disease.STRING 11.5 database was used for protein interaction network analysis,and Cytoscape 3.9.1 software was used to conduct network topology parameters and obtain core targets.GO and KEGG enrichment analysis were performed on the common targets using DAVID platform.Molecular docking of core genes with the main active components of Buyang Huanwu Decoction was conducted using AutoDock Vina 1.5.6 software.An AS mouse model was established and intervened with Buyang Huanwu Decoction.The lipid content of the mouse aortic sinus was observed using Oil Red O staining.Western blot was used to detect the expression of PI3K/AKT/p38 signaling pathway,and ELISA was used to detect the contents of TNF-α and IL-17 in mouse serum.Results A total of 104 main active components and 283 action targets of Buyang Huanwu Decoction were obtained,as well as 5 347 AS related targets and 218 common targets for drugs and disease.Buyang Huanwu Decoction may use key active components such as quercetin,kaempferol and baicalin as core targets for TP53,MAPK1,AKT1,and exert its therapeutic effect on AS through PI3K-Akt signaling pathway,TNF signaling pathway and IL-17 signaling pathway,etc.Molecular docking indicated that quercetin,luteolin,kaempferol and baicalin had good affinity with TP53,HSP90AA1,MAPK1,AKT1 and RELA targets.MAPK1 had strong binding activity with baicalin and luteolin.The experimental results showed that Buyang Huanwu Decoction could reduce the lipid content in aortic sinus of AS mice,reduce the contents of TNF-α and IL-17 in serum(P<0.01)and significantly down-regulate the expression levels of PI3K,p-AKT and p-p38 proteins(P<0.05,P<0.01).Conclusion The mechanism of Buyang Huanwu Decoction for preventing and treating AS may be related to regulating the expression of the PI3K/AKT/p38 signaling pathway,thereby reducing inflammatory response.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis. Mesangial hyperplasia and deposition of IgA immune complex are typical pathological changes of IgAN. Animal model is an important tool to explore the pathogenesis, diagnosis and treatment plan, and evaluate the safety and efficacy of drugs. At present, there are many kinds of IgAN animal models, including humanized animal models and non-humanized animal models, and there are great differences in the modeling principle, method, time and pathological changes. The humanized animal model is closer to the pathogenesis of IgAN in humans and has gradually become a research hotspot. In this paper, common animal models of IgAN in detail from the aspects of modeling method and time, characteristics and significance of each model, and the research progress of anthropomorphic animal models are reviewed to provide reference and inspiration for the basic research of IgAN.