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 Based on the visualization graph analysis of the research hotspots of Angelica sinensis, predict the future research trends, and provide references for the next step of Angelica sinensis research. Methods Chinese and English literatures on Angelica sinensis collected from CNKI, WanFang, VIP and Web of Science from 2012 to 2022 were retrieved. CiteSpace 6.1.R6 software was used to perform visualization econometrics analysis on the number of publications, authors, institutions, journals, keywords and other topics. Results 3490 Chinese literatures and 409 English literatures were included. Visual knowledge map analysis showed that Gansu University of Chinese Medicine and Nanjing University of Chinese Medicine were the research institutions with the largest number of literature publications in Chinese and English respectively. Journals published mainly include Shizhen Traditional Chinese Medicine and Materia medica, Evidence-based Complementary and Alternative Medicine. Current research hotspots include the effects of Angelica sinensis polysaccharides, volatile oils, and ferulic acid on the hematopoietic system, chronic diseases, and cognitive impairment, as well as clinical efficacy evaluations of classic prescriptions containing Angelica sinensis and their modified formulations. The research trend was characterized by a focus on the pharmacological study of Danggui Buxue Tang,employing various experimental approaches such as network pharmacology, serum pharmacology, and metabolomics to elucidate the mechanisms of Angelica sinensis. Conclusion The pharmacological effects of Angelica sinensis and its compound were extensive, which should be further researched.

Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

Objective To investigate the association between low-level ionizing radiation exposure and peripheral blood parameters in medical radiation workers, and to provide evidence for radiation protection strategies and occupational health surveillance. Methods A total of 1261 medical radiation workers from medical institutions in Heze City, Shandong Province, China, were enrolled. Individual monitoring of occupational external exposure was performed. Demographic characteristics and physical examination data were collected. According to the median annual effective dose, the subjects were stratified into a low-dose group (0.10-0.43 mSv) and a high-dose group (>0.43-5.24 mSv). Logistic regression was used to assess the association between ionizing radiation and peripheral blood parameters. Subgroup analyses were conducted by gender, age, and exposure duration. Results A total of 1261 subjects were enrolled, of whom 893 (70.82%) were male and 368 (29.18%) were female. The median age was 39.00 (32.00, 47.00) years and the median exposure duration was 11.00 (5.00, 22.00) years. No statistically significant differences in baseline characteristics were observed between the two groups. The radiation dose ranged from 0.104 to 5.239 mSv, all below the occupational exposure limit (20 mSv). Basophil count, hematocrit, and mean corpuscular volume in the high-dose group were significantly higher than those in the low-dose group, while mean corpuscular hemoglobin concentration was lower (P<0.05). Logistic regression analysis showed that ionizing radiation primarily affected erythrocyte parameters, with abnormal hematocrit (OR=1.449, 95%CI: 1.148-1.831), abnormal mean corpuscular volume (OR=1.407, 95%CI: 1.119-1.771), and abnormal mean corpuscular hemoglobin concentration (OR=1.608, 95%CI: 1.278-2.025) positively associated with ionizing radiation exposure. Subgroup analyses further revealed differences that were not observed in the total population These findings suggest that gender, age, and exposure duration may modify the effect of ionizing radiation on peripheral blood parameters. Conclusion Long-term low-level ionizing radiation exposure can affect peripheral blood parameters in medical radiation workers, particularly erythrocyte parameters. Enhanced occupational health monitoring and protection measures are warranted.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Objective:To evaluate the sample preparation proficiency and storage proficiency of 11 clinical biobanks in Beijing through simulated experiments, and to establish an assessment method for the quality comparability of biological samples.Methods:An exploratory research design was adopted. In November 2023, artificial composite serum quality control materials containing six recombinant human protein markers—recombinant human alanine aminotransferase (rhALT), recombinant human aspartate aminotransferase (rhAST), recombinant human creatine kinase (rhCK), recombinant human creatine kinase-MB (rhCK-MB), recombinant human B-type natriuretic peptide (rhBNP), and recombinant human troponin I (rhTNI)—were distributed to 11 clinical biobanks in Beijing City. Sample preparation and storage followed the standardized operating procedures. Proficiency differences were assessed through statistical analysis.Results:Three-way repeated measures ANOVA revealed all six protein markers showed a declining trend over storage time in ultra-low-temperature environments ( F values 11.68-4 179.66, all P<0.01). However, neither long-term/temporary refrigerator types ( F values 0.01-1.23, all P>0.05)nor placement locations within refrigerators significantly affected the stability of these six proteins ( F valus 0.03-1.47, all P>0.05). The biases in detection results for rhALT, rhAST, rhTNI, and rhBNP at different storage time points were within the allowable bias limits for each item, supporting their use as markers for protein stability in biobank samples. All 11 institutions passed the storage proficiency assessment. In the preparation proficiency assessment, deviations were observed in post-preparation sample results, with a notably high out-of-control rate for rhCK (36.36%). Conclusion:Sample preparation proficiency can serve as a quality control metric for clinical biobanks. Future external quality assessment systems for biobanks should focus on sample preparation rather than storage processes.

Objective To explore the risk factors of early myocardial injury in patients with acute carbon monoxide poisoning(ACOP)and the effect of myocardial injury on prognosis.Methods A total of 176 patients with ACOP who were hospitalized in Changde Hospital Affiliated to Xiangya School of Medicine,Central South University from January 2020 to November 2024 were selected.According to the highest value of MB isoenzyme of creatine kinase(CK-MB)within 72h after poisoning,the patients were divided into early myocardial injury group(CK-MB ≥ 75 U/L,32 cases)and non-early myocardial injury group(CK-MB＜75 U/L,144 cases).The clinical data of two groups were collected and compared,and independent influencing factors of early myocardial injury in patients with ACOP were explored by applying the multivariate Logistic regression model.The receiver operating characteristic(ROC)curve was drawn to analyze the predictive efficacy of its risk factors for early myocardial injury.Results The neutrophil to lymphocyte ratio,monocyte to lymphocyte ratio,alanine aminotransferase,aspartate aminotransferase(AST),blood urea nitrogen and C-reactive protein(CRP)of patients with early myocardial injury group were significantly higher than those of non-early myocardial injury group(P＜0.05).Multivariate Logistic regression analysis showed that both AST and CRP were independent risk factors for early myocardial injury in patients with ACOP(P＜0.05).The sensitivity of AST combined with CRP in predicting early myocardial injury in patients with ACOP was 78.1％,the specificity was 93.1％,and area under the curve was 0.931.The incidence of delayed encephalopathy in early myocardial injury group was significantly higher than that in non-early myocardial injury group(x2=19.055,P＜0.001).Conclusion AST and CRP are independent risk factors for early myocardial injury in ACOP patients,and AST combined with CRP has a certain predictive value for early myocardial injury in ACOP patients.The incidence of delayed encephalopathy was higher in patients with early myocardial injury,suggesting that myocardial injury is closely related to the poor prognosis of patients.

Glutathione(GSH)is a tripeptide containing sulfhydryl groups,which has the function of antioxidant,detoxifying,and immune enhancing effects,and its expression is closely associated with many diseases such as cancer,etc.Therefore,it is of great significance for clinical diagnosis by developing a highly sensitive,simple,and rapid method for detecting GSH.Herein,two-dimensional(2D)Zn-TCPP(Fe)nanosheets employing Zn2+and Fe-bound tetrakis(4-carboxyphenyl)porphyrin ligands were obtained by a surfactant-assisted synthetic method.The 2D Zn-TCPP(Fe)nanosheets exhibited excellent peroxidase-like activity,which allowed the catalysis of the H2O2-initiated oxidation of colorless 3,3',5,5'-tetramethylbenzidine(TMB)to blue oxidized TMB(ox-TMB).In the presence of GSH,GSH underwent a reduction reaction with oxTMB,resulting in the blue color of the solution fading.The proposed colorimetric sensor exhibited favorable sensitivity for GSH in the linear range of 0.1-200 μmol/L with a limit of detection(S/N=3)of 0.042 μmol/L,indicating excellent selectivity.The developed sensor was successfully applied to detect GSH level in the human serum samples with recoveries of 93.0％-107.7％,showing satisfactory results.The developed colorimetric sensor provided a new approach for detecting GSH.