OBJECTIVE: To develop a user-friendly visualization application for the automatic annotation of Human Phenotype Ontology (HPO) terms based on large language models and retrieval-augmented generation (RAG) technology, and to validate its performance in an authoritative case dataset. METHODS: By integrating the domestic open-source large language model DeepSeek-V3 with RAG technology, an interactive web application was deployed on the Streamlit cloud platform. Using only the latest official HPO dataset as the data source, the lightweight sentence-embedding model BAAI/bge-small-en-v1.5 was employed to construct a FAISS vector index. During the online phase, a four-step closed-loop process is automatically completed: multilingual translation, phenotype phrase extraction, RAG candidate retrieval, term mapping, and official database validation. 121 English case reports publicly released by BMJ Case Reports and Oxford Medical Case Reports (with a gold-standard HPO set of 1 794 terms) were selected for application validation. Precision, recall, and F1 score were calculated and compared horizontally with traditional dictionary tools, standalone large language models, and the similar application "RAG-HPO". Finally, replace the model with the more advanced ChatGPT-5 and evaluate its performance on the newly extracted dataset. RESULTS: An HPO term automatic annotation visualization application named PhenoRAG, based on large language models and RAG technology, was successfully developed. Users can access it directly via a web link. Across the 112 cases, a total of 2 150 HPO terms were generated; 2,064 (96.0%) were fully validated by the official database, with a hallucination rate of 1.3% and an HPO ID-name mismatch rate of 2.7%. After deduplication, 1,906 terms remained for testing. The overall precision was 63.65%, recall was 67.34%, and F1 was 65.44%, significantly outperforming traditional annotation tools (F1: 0.45-0.49, P < 0.001). Although PhenoRAG's F1 was lower than that of RAG-HPO (F1 = 0.78, P < 0.001), which relies on a manually constructed synonym database of 54 000 entries plus the HPO dataset, it requires no additional dictionary maintenance and can be used without any background in computer programming. Moreover, after switching to the GPT-5 model, PhenoRAG exhibited no hallucination rate on the new dataset, and its F1 score significantly increased (P = 0.038). CONCLUSION Without constructing a synonym database, the PhenoRAG achieved high-accuracy automatic mapping from clinical text to standard HPO terms. It features a low usage threshold, free access, and a Chinese-language interface, and can directly serve rare disease diagnosis, genetic counseling, and research scenarios in China and worldwide, warranting further clinical promotion and multicenter validation.
Humans ; Phenotype ; Biological Ontologies ; Language ; Software ; Large Language Models

Objective:To investigate the clinical characteristics of residual dizziness（RD） after repositioning in patients with benign paroxysmal positional vertigo（BPPV）, identify its potential risk factors, and develop a predictive risk model. Methods:A total of 137 patients diagnosed with BPPV at the First Affiliated Hospital of Xi'an Jiaotong University between January 2023 and June 2023 were enrolled. Based on the presence or absence of subjective discomfort within 3 months after successful repositioning, patients were divided into the non-RD group（NRD, n=93） and the RD group（n=44）. Differences in demographic characteristics, comorbidities, and disease-related features were compared between groups. Multivariate logistic regression analysis was used to identify independent risk factors for RD, and a nomogram was constructed based on these factors. The predictive performance of the model was assessed using the area under the curve（AUC）. Results:The RD group showed significantly higher values in body mass index, prevalence of diabetes and motion sickness history, dizziness duration before repositioning, history of repositioning at external hospitals, number of treatments, and recurrence（all P<0.001）. Multivariate logistic regression revealed that diabetes（adjusted OR=8.73, P=0.039）, motion sickness history（adjusted OR=23.08, P<0.001）, dizziness duration ≥30 days before repositioning（adjusted OR=15.16, P<0.001）, and recurrence（adjusted OR=15.72, P=0.001） were independent risk factors for RD. The nomogram model based on these variables demonstrated good predictive ability, with an AUC of 0.804（95%CI 0.684-0.924）. Conclusion:Diabetes, motion sickness history, dizziness duration ≥30 days, and recurrence are independent risk factors for RD after repositioning in patients with BPPV. The nomogram model based on these variables shows good predictive performance, with recurrence having the highest predictive value. This model can aid in early identification of high-risk patients and guide individualized intervention strategies.
Humans ; Nomograms ; Benign Paroxysmal Positional Vertigo/therapy* ; Dizziness/etiology* ; Risk Factors ; Risk Assessment ; Multivariate Analysis ; Male ; Female ; Logistic Models ; Middle Aged ; Patient Positioning ; Adult

Objective:To explore the predictive value of preoperative peripheral hematological parameters combined with clinicopathological features for cervical lymph node metastasis（CLNM） in patients with laryngeal squamous cell carcinoma（LSCC）, and to construct and validate a nomogram model for CLNM. Methods:A retrospective analysis was conducted on the clinical data of 264 LSCC patients who underwent surgical treatment and were pathologically confirmed, collected from the Second Affiliated Hospital of Shandong First Medical University and Taian 88 Hospital. Specifically, 161 patients from one hospital were allocated to the training cohort, while 103 patients from another hospital constituted the validation cohort. Based on postoperative pathological results, patients were categorized into CLNM-positive and CLNM-negative groups. The general clinical data, clinicopathological features, and hematological parameters of the two groups were analyzed and compared. A preoperative predictive model for CLNM was developed using logistic regression analysis, followed by validation and sensitivity analysis to evaluate the robustness of the model's predictive performance. Results:The results showed that there were significant differences in tumor location, tumor size, tumor differentiation, neutrophil percentage, lymphocyte count, lymphocyte percentage, c-reactive protein（CRP）, fibrinogen, neutrophil-to-lymphocyte ratio（NLR）, platelet-to-lymphocyte ratio（PLR）, systemic immune-inflammation index（SII）, systemic inflammation response index（SIRI）, and prognostic inflammatory index（PIV） between the CLNM-positive and CLNM-negative groups（P<0.05）. Lasso regression identified tumor location, clinical T stage, tumor size, tumor differentiation degree, red blood cell distribution width（RDW） -coefficient of variation（RDW-CV）, CRP, FIB, D-dimer, NLR, and lymphocyte-to-monocyte ratio（LMR） were the most predictive parameters. Multivariate logistic regression revealed that tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients（P<0.05）. A nomogram was constructed based on these five factors. The model demonstrated excellent discrimination, with a C-index of 0.837（95%CI 0.766-0.908） in the training cohort and 0.809（95%CI 0.698-0.920） in the validation cohort. Calibration curves and DCA curves in both cohorts confirmed the clinical utility of the model. Sensitivity analysis further supported the robustness of the results, showing good discrimination and calibration across different age and BMI subgroups. Conclusion:Tumor location, tumor size, tumor differentiation degree, CRP, and NLR were independent risk factors for CLNM in LSCC patients. The nomogram based on these variables exhibits strong discrimination, calibration, and clinical applicability, and may serve as a valuable tool for preoperative risk assessment and individualized treatment planning.
Humans ; Nomograms ; Laryngeal Neoplasms/blood* ; Retrospective Studies ; Lymphatic Metastasis ; Carcinoma, Squamous Cell/blood* ; Lymph Nodes/pathology* ; Male ; Female ; Middle Aged ; Neck ; C-Reactive Protein ; Aged ; Logistic Models ; Neutrophils ; Prognosis

Objective:This study aims to investigate the influence of microvessel density（MVD） and microlymphatic vessel density（MLVD） on the prognosis of patients with hypopharyngeal squamous cell carcinoma（HPSCC） and to develop a nomogram prediction model for prognosis based on pathological characteristics. Methods:A retrospective analysis was conducted on clinicopathological and follow-up data from HPSCC patients who underwent surgical treatment at our institution between June 2010 and June 2020. Immunohistochemical staining was performed on tumor tissues and adjacent normal margin tissues to evaluate MVD and MLVD. The associations among MVD, MLVD, and clinicopathological features were analyzed. Univariate and multivariate Cox regression analyses were conducted to identify independent risk factors affecting overall survival（OS）. Based on these findings, a nomogram model was constructed and its predictive accuracy was assessed using C-index, receiver operating characteristic（ROC） curve, and calibration curve. Results:Both MVD and MLVD were significantly higher in HPSCC tumor tissues compared to normal tissues. Patients in the high MVD and high MLVD groups exhibited significantly lower OS rates than those in the low MVD and low MLVD groups. Multivariate Cox regression analysis revealed that N stage, recurrence, nerve invasion, lymph node capsule invasion, MVD, and MLVD were independent prognostic factors of OS. Based on these factors, a nomogram prognosis model was successfully constructed. The nomograms demonstrated superior performance in terms of C-index, area under the ROC curve, and calibration, outperforming the AJCC TNM staging system. Conclusion:Elevated MVD and MLVD levels are associated with poorer prognosis in HPSCC patients. The nomogram model based on pathological features provides valuable insights for clinical assessment and decision-making.
Humans ; Hypopharyngeal Neoplasms/blood supply* ; Prognosis ; Retrospective Studies ; Microvascular Density ; Nomograms ; Lymphatic Vessels/pathology* ; Male ; Female ; Middle Aged ; Carcinoma, Squamous Cell/blood supply* ; Microvessels/pathology* ; Lymphatic Metastasis ; Survival Rate

OBJECTIVES: To investigate the active ingredients in Hedyotis diffusa-Scutellaria barbata D. Don and the main biological processes and signaling pathways mediating their inhibitory effect on primary hepatocellular carcinoma (HCC). METHODS: The core intersecting genes of HCC and the two drugs were screened from TCMSP, Uniport, Genecards, and String databases using Cytoscape software, and GO and KEGG enrichment analyses of the intersecting genes were conducted. Molecular docking between the active ingredients of the drugs and the core genes was carried out using Pubcham, RCSB and Autoduckto to identify the active ingredients with the highest binding energy, whose inhibitory effect on HepG2 cells was verifies using CCK-8 assay, flow cytometry and Western blotting. RESULTS: TP53 and ESR1 were identified as the core genes of HCC and the two drugs. GO and KEGG analyses showed that the two genes were mainly involved in regulation of apoptotic signaling pathway, cell population proliferation, methane raft, and protein kinase activity, and participated in the signaling pathways of apoptosis, proteoglycans in cancer, PI3K Akt signaling pathway, and hepatitis B. Molecular docking studies showed that the active ingredients of the drugs could be docked with TP53 and ESR1 genes under natural conditions, and ursolic acid had the highest binding energy to ESR1 (-4.98 kcal/mol). The results of CCK-8 assay, flow cytometry and Western blotting all demonstrated significant inhibitory effect of ursolic acid on HepG2 cells. CONCLUSIONS The inhibitory effect of Hedyotis diffusa-scutellariae barbatae on HCC is mediated by multiple active ingredients in the two drugs.
Humans ; Molecular Docking Simulation ; Liver Neoplasms/drug therapy* ; Hep G2 Cells ; Network Pharmacology ; Carcinoma, Hepatocellular/drug therapy* ; Hedyotis/chemistry* ; Signal Transduction/drug effects* ; Cell Proliferation/drug effects* ; Tumor Suppressor Protein p53/metabolism* ; Apoptosis/drug effects* ; Estrogen Receptor alpha/metabolism* ; Drugs, Chinese Herbal/pharmacology*

OBJECTIVES: To evaluate the protective effect of Schistosoma japonicum cystatin (rSj-Cystatin) in a mouse mode of "two-hit" sepsis. METHODS: Sixty male C57BL/6 mice randomized equally into sham-operated group, protein group, "two-hit" modeling group, and protein intervention group. In the former two groups, the mice received an intraperitoneal injection of 100 μL PBS followed by exposure of the cecum and then by intraperitoneal injection of 100 μL PBS or 25 μg rSj-Cystatin 30 min later; In the latter two groups, 100 μL PBS containing LPS (5 mg/kg) was injected intraperitoneally 24 h before cecal ligation and puncture (CLP), and 100 μL PBS or 25 μg rSj-Cystatin were injected 30 min after CLP. At 12 h after rSj-Cystatin treatment, 6 mice from each group were sacrificed for detection of TNF-α, IL-6, IL-10, TGF-β, iNOS and Arg-1 in the serum, spleen, liver, lung and kidney tissues using ELISA, for examinations of liver, lung and kidney pathologies with HE staining, and for analysis of CD3⁺CD4⁺CD25⁺Foxp3⁺ T cell percentage in the spleen using flow cytometry. The remaining mice were observed for general condition and 72-h survival. RESULTS: The 72-h survival rates in the 4 groups were 100%, 100%, 0% and 20%, respectively, showing significant differences between the latter two groups. The mouse models of "two-hit" sepsis exhibited obvious tissue pathologies and significant elevations of TNF-α and IL-6 in both the serum and tissue homogenate, which were significantly ameliorated by rSj-Cystatin treatment. Treatment with rSj-Cystatin also increased IL-10 and TGF-β levels and spleen CD3⁺CD4⁺CD25⁺Foxp3⁺ T cell percentage. The septic mouse models also showed increased iNOS levels in all the detected tissues and a decreased Arg-1 level in the kidney, and these changes were obviously improved by rSj-Cystatin treatment. CONCLUSIONS rSj-Cystatin has a protective effect against "two-hit" sepsis in mice by regulating the inflammatory microenvironment.
Animals ; Mice ; Sepsis/drug therapy* ; Male ; Schistosoma japonicum/chemistry* ; Mice, Inbred C57BL ; Cystatins/therapeutic use* ; Interleukin-10/metabolism* ; Interleukin-6/blood* ; Tumor Necrosis Factor-alpha/blood* ; Disease Models, Animal ; Transforming Growth Factor beta/metabolism*

OBJECTIVES: To explore the mechanism by which Pulsatilla saponin D (PSD) inhibits invasion and metastasis of triple-negative breast cancer (TNBC). METHODS: The public databases were used to identify the potential targets of PSD and the invasion and metastasis targets of TNBC to obtain the intersection targets between PSD and TNBC. The "PSD-target-disease" interaction network was constructed and protein-protein interaction (PPI) analysis was performed to obtain the core targets, which were analyzed for KEGG pathway and GO functional enrichment. Molecular docking study of the core targets and PSD was performed, and the therapeutic effect and mechanism of PSD were verified using Transwell assay and Western blotting in cultured TNBC cells. RESULTS: Network pharmacology analysis identified a total of 285 potential PSD targets and 26 drug-disease intersection core targets. GO analysis yielded 175 entries related to the binding of biomolecules (protein, DNA and RNA), enzyme activities, and regulation of gene transcription. KEGG analysis yielded 46 entries involving pathways in cancer, chemical carcinogenesis-receptor activation, microRNAs in cancer, chemical carcinogenesis-reactive oxygen species, PD-L1 expression and PD-1 checkpoint pathway in cancer. Molecular docking showed high binding affinities of PSD to MTOR, HDAC2, ABL1, CDK1, TLR4, TERT, PIK3R1, NFE2L2 and PTPN1. In cultured TNBC cells, treatment with PSD significantly inhibited cell invasion and migration and lowered the expressions of MMP2, MMP9, N-cadherin and the core proteins p-mTOR, ABL1, TERT, PTPN1, HDAC2, PIK3R1, CDK1, TLR4 as well as NFE2L2 expressionin the cell nuclei. CONCLUSIONS The inhibitory effects of PSD on TNBC invasion and metastasis are mediated by multiple targets and pathways.
Humans ; Triple Negative Breast Neoplasms/metabolism* ; Saponins/pharmacology* ; Pulsatilla/chemistry* ; Female ; Molecular Docking Simulation ; Cell Line, Tumor ; Neoplasm Invasiveness ; Protein Interaction Maps ; Neoplasm Metastasis ; Signal Transduction/drug effects* ; Cell Movement/drug effects*

OBJECTIVES: To investigate the therapeutic mechanism of nodakenin for Crohn's disease (CD)-like colitis in mice. METHODS: Using a colonic organoid model with lipopolysaccharide (LPS)- and ATP-induced pyroptosis, we investigated the effects of nodakenin on pyroptosis, intestinal barrier function and inflammatory response by detecting key pyroptosis-regulating factors and assessing changes in permeability and pro-inflammatory factors. In a mouse model of 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced CD-like colitis, the therapeutic effect of nodakenin was evaluated by measuring changes in body weight, DAI score, colonic histopathologies, inflammation score, intestinal barrier function and intestinal epithelial cell pyroptosis. The mechanism of nodakenin protection against pyroptosis of intestinal epithelial cells was explored using network pharmacology analysis and in vivo and in vitro experiments. RESULTS: In LPS- and ATP-induced colonic organoids, treatment with nodakenin significantly inhibited the expressions of NLRP3, GSDMD-N, cleaved caspase-1 and caspase-11, improved intestinal FITC-dextran (FD4, 4000) permeability, and decreased the levels of IL-1β and IL-18. In the mouse model of TNBS-induced colitis, nodakenin treatment significantly alleviated weight loss, reduced DAI score, inflammatory cell infiltration and inflammation score, and decreased serum FD4 and I-FABP levels and bacteria translocation to the mesenteric lymph nodes, spleen and liver. The mice with nodakenin treatment had also lowered expressions of NLRP3, GSDMD-N, cleaved caspase-1 and caspase-11 in the intestinal mucosa. Network pharmacology analysis suggested that the inhibitory effect of nodakenin on colitis was associated with the PI3K/Akt pathway. In both the colonic organoid model and mouse models of colitis, nodakenin effectively inhibited the activation of the PI3K/Akt pathway, and the application of IGF-1, a PI3K/Akt pathway activator, strongly attenuated the protective effect of nodakenin against intestinal epithelial cell pyroptosis and intestinal barrier dysfunction. CONCLUSIONS Nodakenin protects intestinal barrier function and alleviates CD-like colitis in mice at least partly by inhibiting PI3K/Akt signaling to reduce intestinal epithelial cell pyroptosis.
Animals ; Pyroptosis/drug effects* ; Mice ; Trinitrobenzenesulfonic Acid ; Colitis/drug therapy* ; Epithelial Cells/drug effects* ; Intestinal Mucosa/cytology* ; Disease Models, Animal ; Coumarins/pharmacology* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Crohn Disease/drug therapy*

OBJECTIVES: To investigate the therapeutic mechanism of Thesium chinense Turcz. (TCT) for antibiotic-associated diarrhea (AAD). METHODS: Network pharmacology, KEGG pathway enrichment analysis and molecular docking were used to identify the shared targets and genes of TCT and AAD, the key signaling pathways and the binding between the active components in TCT and the core protein targets. In a Kunming mouse model of AAD established by intragastric administration of lincomycin hydrochloride, the effects of daily gavage of 1% carboxymethyl cellulose sodium or TCT gel solutions at 1.5 g/kg and 3 g/kg (n=10) on body weight and diarrhea were observed. HE staining, ELISA, 16S rRNA sequencing, and Western blotting were used to examine pathologies, expression levels of IL-6 and TNF-α, changes in gut microbiota, and protein expressions of EGFR, p-EGFR, PI3K, p-PI3K, Akt, and p-Akt in the colon tissues of the mice. RESULTS: We identified a total of 66 active components of TCT and 68 core targets including EGFR, STAT3 and PIK3CA. KEGG pathway enrichment analysis suggested that the therapeutic effects of TCT was mediated primarily through the PI3K/Akt signaling pathway. Molecular docking showed that EGFR had the highest binding affinity with coniferin, and the EGFR-coniferin complex maintained a stable conformation at 10 ns, whose stability was also confirmed by Gibbs free energy analysis. In the mouse models of AAD, treatment with TCT significantly improved colonic tissue morphology, decreased colonic levels of TNF-α and IL-6, increased gut microbiota diversity, and modulated the relative abundances of the key genera including Lactobacillus and Bacteroides. TCT treatment also markedly reduced protein expressions of p-EGFR, p-PI3K and p-Akt in the colon tissues of the mice. CONCLUSIONS TCT can alleviate AAD in mice by modulating gut microbiota composition, regulating the EGFR/PI3K/Akt signaling pathway, and reducing TNF‑α and IL-6 expressions.
Animals ; Gastrointestinal Microbiome/drug effects* ; Signal Transduction/drug effects* ; Mice ; ErbB Receptors/metabolism* ; Proto-Oncogene Proteins c-akt/metabolism* ; Diarrhea/drug therapy* ; Phosphatidylinositol 3-Kinases/metabolism* ; Anti-Bacterial Agents/adverse effects* ; Drugs, Chinese Herbal/therapeutic use* ; Molecular Docking Simulation

OBJECTIVES: To explore the value of serum cystatin C (CysC) levels in evaluating renal prognosis in IgA nephropathy (IgAN) patients. METHODS: We retrospectively collected the clinical data of IgAN patients diagnosed by renal biopsy at Guangdong Provincial People's Hospital from January, 2014 to December, 2018. Based on baseline serum CysC levels, the patients were divided into high serum CysC (>1.03 mg/L) group and normal serum CysC (≤1.03 mg/L) group. The composite endpoint for poor renal prognosis was defined as ≥50% decline in estimated glomerular filtration rate (eGFR) and/or progression to end-stage renal disease (ESRD). Lasso regression, multivariate Cox regression and Kaplan-Meier survival analysis were used to identify the risk factors and compare renal survival rates between the two groups. Smooth curves fitting and threshold effect analysis were used to explore the relationship between serum CysC levels and the outcomes. A nomogram model was constructed and its predictive performance was evaluated using concordance index, calibration curve, receiver operating characteristic (ROC) curve and the area under curve (AUC). RESULTS: A total of 356 IgAN patients were enrolled, who were followed up for 4.65±0.93 years. The composite endpoint occurred in 74 patients. High serum CysC was identified as an independent risk factor for poor renal prognosis in IgAN (HR=2.142, 95% CI 1.222 to 3.755), and the patients with high serum CysC levels had a lower renal survival rate (Log-rank χ²=47.970, P<0.001). In patients with serum CysC below 2.12 mg/L, a higher CysC level was associated with an increased risk of poor renal prognosis (β=3.487, 95% CI: 2.561-4.413, P<0.001), while above this level, the increase of the risk was not significant (β=0.676, 95% CI: -0.642-1.995, P=0.315). The nomogram model based on serum CysC and 3 other independent risk factors demonstrated good internal validity with a concordance index of 0.873 (95% CI: 0.839-0.907) and an AUC of 0.909 (95% CI: 0.873-0.945). CONCLUSIONS Serum CysC levels are associated with renal prognosis in IgAN patients, and high serum CysC an independent risk factor for poor renal prognosis.
Humans ; Glomerulonephritis, IGA/diagnosis* ; Cystatin C/blood* ; Prognosis ; Risk Factors ; Retrospective Studies ; Glomerular Filtration Rate ; Kidney Failure, Chronic ; Male ; Female ; Adult ; Nomograms ; Middle Aged