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

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Objective To investigate the screening results and factors affecting abnormal detection rates among high-risk groups of esophageal cancer and to explore effective intervention measures. Methods We investigated and collected the information on gender, education level, age, marital status, symptoms of reflux esophagitis (heartburn, acid reflux, belching, hiccup, foreign body sensation in the pharynx, and difficulty swallowing), consumption of pickled vegetables, salt use, and esophageal cancer incidence of villagers in a natural village in Wenfeng District, Anyang City, Henan Province. Changes in reflux esophagitis symptoms in the high-incidence area of esophageal cancer before and after 16 years were observed, and the relationship of such changes with esophageal cancer was analyzed. Results In 2008, 711 cases were epidemiologically investigated, including 213 cases with one of the symptoms of reflux esophagitis such as heartburn, acid reflux, belching, hiccups, foreign body sensation in the pharynx, and difficulty swallowing (sorted in accordance with the abovementioned symptoms; if there are multiple symptoms, then the former is taken); 55 cases with at least two related symptoms, among which the most symptom was heartburn in 108 cases (15.1%); followed by acid reflux, belching, etc. In 2024, the same group of people was investigated, and eight people were missing because of relocation. A total of 703 people were successfully investigated, of which 189 cases (26.8%) had one of the symptoms of reflux esophagitis, such as heartburn (sorted in accordance with relevant symptoms, if there are multiple symptoms, then the former will be selected); 167 cases (23.7%) had at least two related symptoms, among which the most symptom was heartburn in 139 cases (19.7%); followed by acid reflux. Over 16 years, among the 703 people investigated, 45 cases had esophageal cancer and they had one or more of the abovementioned symptoms. No significant differences in the reflux esophagitis-like symptoms were found between 2008 and 2024 (P=0.26); no significant differences in the composition of reflux esophagitis-like symptoms were found between 2008 and 2024 (P=0.299). Conclusion The detection rate of reflux esophagitis-related symptoms in the population in a high-risk area of esophageal cancer has not decreased in the past 16 years, and the high-risk factors still exist. Esophageal cancer is closely related to reflux esophagitis, and clinical practice can provide early diagnosis and treatment for high-risk population.

With the rapid development of deep learning(DL)technology,its potential applications in the medical field have become increasingly prominent.As a refractory disease,osteonecrosis of the femoral head(ONFH)has certain limitations in traditional diagnostic and therapeutic approaches.The application of DL technology is expected to overcome these limitations and improve diagnosis and treatment outcomes.At present,the applications of DL models-including enhancing image clarity,improving diagnostic accuracy and efficiency,conducting prognostic evaluations,optimizing preoperative planning,assisting intraoperative imaging,and customizing personalized treatment plans-have fully demonstrated their tremendous potential in the diagnosis and treatment of ONFH.This review summarizes the current application status of DL in ONFH diagnosis and treatment,aiming to provide references and insights for future related research.

Objective To investigate the status of population dynamics and distribution changes of Aedes aegypti in Guangdong Province.Methods Continuous monitoring was conducted from May 2018 to July 2024 in Wushi Town and Qishui Town,Leizhou City,Zhanjiang City,Guangdong Province.Additionally,a survey of the distribution of Ae.aegypti along the Leizhou Peninsula coast was carried out.Results The density of Ae.aegypti in Zhanjiang showed a gradual decline from 2018 to 2024.The last detection of adult Ae.aegypti in Wushi Town was in September 2021,and the last larva was found in October 2023.No Ae.aegypti was detected in Qishui Town during surveys from 2021 to 2024.A survey of 18 coastal villages in the Leizhou Peninsula revealed no detections of Ae.aegypti.Conclusions This study provides a basis for understanding the distribution and population density fluctuations of Ae.aegypti,assessing its invasion risk,and scientifically conducting relevant prevention and control efforts.

Prolonged disorders of consciousness(pDoC)are complex and prolonged conditions that severely impact patient prognosis and remain a clinical treatment challenge.In recent years,neural regulation-based awakening therapies have been widely applied in the assessment and treatment of pDoC patients.Repetitive transcranial magnetic stimulation(rTMS)technology can regulate neural activity and improve patients'consciousness states,demonstrating positive awakening effects for pDoC patients.However,the optimal stimulation parameters and awakening mechanisms of rTMS remain unclear.This article reviews the pathological mechanisms of pDoC,clinical applications of rTMS at different targeting sites and stimulation frequencies,and focuses on exploring how rTMS promotes consciousness recovery through neural mechanisms such as altering neural pathways,reshaping brain networks,promoting synaptic plasticity and neurotransmitter release,regulating neurotrophic factor expression,and modulating cerebral hemodynamics.Based on artificial intelligence,the article also prospects the future clinical research applications of rTMS.

Objective To establish a portable gas chromatography-mass spectrometry (GC-MS) method for determining carbon disulfide in workplace air. Methods Samples were collected using the built-in Tenax GR adsorption tube in the portable GC-MS, followed by thermal desorption. The analytes were separated on a DB-1 chromatographic column and detected by a 3D ion trap mass spectrometer, with 1,3,5-tris(trifluoromethyl)benzene used as the internal standard. Qualitative analysis was based on retention time and characteristic ions, and quantitative analysis was performed using the internal standard method. Results The method showed a linear range of 0.034-0.340 mg/m³ with a correlation coefficient of 0.999 4 using the adsorption tube enrichment mode. The detection limit was 0.007 mg/m³, and the lower limit of quantification was 0.022 mg/m³. The average recovery ranged from 97.5% to 104.0%. The within-run and between-run relative standard deviation was 2.7%-10.4% and 8.8%-14.8%, respectively. Conclusion A rapid, green, highly sensitive, and interference-resistant on-site detection method was established. As a supplement to existing national standard methods, this method is suitable for real-time monitoring of carbon disulfide in workplace air and for occupational exposure risk assessment.

Protein tyrosine phosphatase nonreceptor type 2 (PTPN2) is a promising target for sensitizing solid tumors to immune checkpoint blockades. However, the highly polar active sites of PTPN2 hinder drug discovery efforts. Leveraging small interfering RNA (siRNA) technology, we developed a novel glutathione-responsive nano-platform HPssPT (HA/PEIss@siPtpn2) to silence PTPN2 and enhance immunotherapy efficacy in hepatocellular carcinoma (HCC). HPssPT showed potent transfection and favorable safety profiles. PTPN2 deficiency induced by HPssPT amplified the interferon γ signaling in HCC cells by increasing the phosphorylation of Janus-activated kinase 1 and signal transducer and activator of transcription 1, resulting in enhanced antigen presentation and T cell activation. The nano-platform was also able to promote the M1-like polarization of macrophages in vitro. The unique tropism of HPssPT towards tumor-associated macrophages, facilitated by hyaluronic acid coating and CD44 receptor targeting, allowed for simultaneous reprogramming of both tumor cells and tumor-associated macrophages, thereby synergistically reshaping tumor microenvironment to an immunostimulatory state. In HCC, colorectal cancer, and melanoma animal models, HPssPT monotherapy provoked robust antitumor immunity, thereby sensitizing tumors to PD-1 blockade, which provided new inspiration for siRNA-based drug discovery and tumor immunotherapy.

Uric acid (UA) is the final metabolite of purines in the human body. An imbalance in UA production and excretion that disrupts homeostasis leads to elevated blood UA levels and the development of hyperuricemia (HUA). Approximately one-third of UA is excreted through the intestinal tract. As a crucial component of the intestinal microenvironment, the gut microbiota plays a pivotal role in regulating blood UA levels. Alterations or imbalances in gut microbiota composition are linked to the onset of HUA, which implies the potential of gut microbiota as a novel target for the prevention and treatment of HUA. This review introduces the occurrence mechanism and damage of hyperuricemia, examines the association between HUA and the gut microbiota and their metabolites, and explores the molecular mechanisms underlying gut microbiota-targeted therapies for HUA. Furthermore, it discusses the potential applications of probiotics, prebiotics, and traditional Chinese medicine (including both single herbs and compound formulas) with UA-lowering effects, along with cutting-edge technologies such as fecal microbiota transplantation and machine learning in HUA treatment. This review provides valuable perspectives and strategies for improving the prevention and treatment of HUA.
Hyperuricemia/microbiology* ; Humans ; Gastrointestinal Microbiome/physiology* ; Probiotics/therapeutic use* ; Uric Acid/blood* ; Fecal Microbiota Transplantation ; Prebiotics ; Medicine, Chinese Traditional