Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Radiochemotherapy-induced oral mucositis (OM) is a common oral complication in patients with tumors following head and neck radiotherapy or chemotherapy. Erosion and ulcers are the main features of OM that seriously affect the quality of life of patients and even the progress of tumor treatment. To date, differences in clinical prevention and treatment plans for OM have been noted among doctors of various specialties, which has increased the uncertainty of treatment effects. On the basis of current research evidence, this expert consensus outlines risk factors, clinical manifestations, clinical grading, ancillary examinations, diagnostic basis, prevention and treatment strategies and efficacy indicators for OM. In addition to strategies such as basic oral care, anti-inflammatory and analgesic agents, anti-infective agents, pro-healing agents, and photobiotherapy recommended in previous guidelines, we also emphasize the role of traditional Chinese medicine in OM prevention and treatment. This expert consensus aims to provide references and guidance for dental physicians and oncologists in formulating strategies for OM prevention, diagnosis, and treatment, standardizing clinical practice, reducing OM occurrence, promoting healing, and improving the quality of life of patients.
Humans ; Chemoradiotherapy/adverse effects* ; Consensus ; Risk Factors ; Stomatitis/etiology*

OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment

The success of chimeric antigen receptor T (CAR-T) cells therapy for hematologic malignancies has sparked interest in potential applications for solid tumors. However, unlike the homogeneous, dynamic, and nutrient-rich hematologic environment, CAR-T cells must overcome the complex tumor microenvironment. Ensuring efficient contact with tumor cells remains a primary challenge to enhance the efficacy of CAR-T cell therapy. Abnormal tumor angiogenesis, disordered chemokine production, dense extracellular matrix, and stromal cells all act as biological barriers that hinder contact of CAR-T cells with tumor cells. This review summarizes specific strategies to promote vascular normalization, modulate chemokine production, target physical barriers, combine different therapeutic approaches, and innovative cell delivery methods to enhance infiltration of CAR-T cells into solid tumors. These strategies will help to overcome current limitations and enhance the effectiveness of CAR-T cell therapy for solid tumors.

Objective:To evaluate the efficacy of lamb′s tripe extract and vitamin B 12 capsule (LTEVB 12C) on chronic atrophic gastritis (CAG) at different locations (antrum lesser curvature, antrum greater curvature, gastric angle, corpus lesser curvature, and corpus greater curvature). Methods:From August 2011 to January 2013, 715 patients with CAG in a multicenter, randomized, double-blind, placebo-controlled trial were enrolled from 16 tertiary first-class hospitals across the country, including the First Affiliated Hospital of Air Force Medical University, Nanfang Hospital of Southern Medical University, the First Hospital of Jilin University, West China Hospital of Sichuan University, etc., there were 476 cases in the LTEVB 12C group and 239 cases in the placebo group. The patients of the LTEVB 12C group received LTEVB 12C, and the patients of placebo group received LTEVB 12C mimetic, all the medications were taken 3 capsules each time and 3 times a day after meals, and the treatment course of 2 groups were both 6 months. The efficacy evaluation criteria included the effective rate (a decrease of ≥1 in histopathological score compared with baseline after 6 months of treatment) and the reversal rate (a decrease of ≥ 2 in histopathological score compared with baseline after 6 months of treatment in the patients with moderate to severe CAG). The impact of lesion sites on the therapeutic effects of LTEVB 12C was analyzed by logistic regression analysis. The two-way unordered Cochran-Mantel-Haenszel chi-square test considering the center effect and Pearson chi-square test were used for statistical analysis. Results:The effective rates of chronic inflammation at the antrum greater curvature and corpus greater curvature (23.3%, 110/473 vs. 13.0%, 31/239; 20.3%, 96/472 vs. 12.6%, 30/239), the effective rates of atrophy at the antrum lesser curvature, antrum greater curvature, gastric angle, corpus lesser curvature, and the corpus greater curvature (27.0%, 118/437 vs. 15.7%, 34/216; 29.2%, 126/432 vs. 18.5%, 38/205; 27.8%, 121/435 vs. 16.7%, 36/216; 32.5%, 127/391 vs. 19.8%, 37/187; 33.0%, 119/361 vs. 21.8%, 39/179), and the effective rates of intestinal metaplasia at the antrum lesser curvature, antrum greater curvature, gastric angle, and the corpus lesser curvature (45.0%, 112/249 vs. 29.8%, 31/104; 53.8%, 86/160 vs. 33.9%, 21/62; 45.8%, 103/225 vs. 24.0%, 25/104; 51.9%, 83/160 vs. 28.3%, 17/60) of the LTEVB 12C group were all higher than those of the placebo group, and the differences were statistically significant ( χ2=10.76, 6.39, 9.69, 7.91, 11.05, 9.62, 8.57, 5.20, 7.11, 12.45, and 6.73; all P<0.05). The reversal rates of chronic inflammation at the corpus lesser curvature and corpus greater curvature (5.2%, 12/231 vs. 0, 0/123; 4.7%, 8/170 vs. 0, 0/88), the reversal rates of atrophy at the antrum lesser curvature, antrum greater curvature, corpus lesser curvature, and the corpus greater curvature (6.8%, 22/323 vs. 1.3%, 2/151; 9.2%, 29/315 vs. 1.4%, 2/144; 14.2%, 38/267 vs. 2.5%, 3/121; 20.8%, 35/168 vs. 5.8%, 4/69), and the reversal rates of intestinal metaplasia at the antrum lesser curvature, antrum greater curvature, gastric angle, and the corpus lesser curvature (29.8%, 39/131 vs. 9.1%, 4/44; 41.0%, 32/78 vs. 12.5%, 3/24; 33.3%, 44/132 vs. 4.8%, 3/63; 50.0%, 37/74 vs. 8.7%, 2/23) of the LTEVB 12C group were all higher than those of the placebo group, and the differences were statistically significant ( χ2=6.58, 5.12, 5.60, 8.61, 11.43, 6.59, 7.30, 4.95, 15.92, 7.62; all P<0.05). There were no statistically significant differences in the effective rates and reversal rates of active inflammation at different locations between the LTEVB 12C group and the placebo group (all P>0.05). The results of logistic regression analysis (taking the antrum lesser curvature as the reference) further confirmed that the reversal rates of chronic inflammation ( OR=0.22, 95% confidence interval (95% CI): 0.07 to 0.67; OR=0.24, 95% CI: 0.07 to 0.80), atrophy ( OR=0.28, 95% CI: 0.16 to 0.49; OR=0.28, 95% CI: 0.16 to 0.49), and intestinal metaplasia ( OR=0.42, 95% CI: 0.24 to 0.77; OR=0.20, 95% CI: 0.08 to 0.52) at the corpus lesser curvature and corpus greater curvature were all higher than those at the antrum lesser curvature, and the differences were statistically significant (all P<0.05). There were no statistically siginificant differences in the reversal rates of the aforementioned pathological features between the antrum greater curvature, gastric angle, and the antrum lesser curvature (all P>0.05). Conclusion:LTEVB 12C can achieve good efficacy in the treatment of CAG, and the chronic inflammation, atrophy, and intestinal metaplasia at multiple locations are improved, especially at the corpus lesser curvature and the corpus greater curvature.

Objective:To explore the influencing factors of the use of intravenous therapy specialist nurses and construct a theoretical framework, so as to provide reference for developing intervention measures and improving the use of intravenous therapy specialist nurses.Methods:The grounded theory research method was used. From July to August 2024, 17 intravenous therapy managers/specialist nurses from six ClassⅢ Grade A hospitals in Beijing City and Hebei Province were selected through purposive and theoretical sampling for semi-structured interviews. NVivo 12.0 was used for data analysis, including open, axial, and selective coding.Results:A total of 79 initial concepts were extracted and summarized into 25 domains, which were consolidated into five main domains, including organizational management and support, personal characteristics and professional identity, team collaboration and communication, work performance and incentive mechanisms, and external environment and opportunities. On this basis, a theoretical framework for factors influencing the use of intravenous therapy specialist nurses was constructed.Conclusions:This study constructs a theoretical framework for factors influencing the use of intravenous therapy specialist nurses. Managers can leverage this theoretical framework to develop targeted intervention strategies that enhance the effectiveness of intravenous therapy specialist nurses and optimize the allocation of nursing human resources.

The number of patients with eye diseases in China is enormous,and the negative effects of these conditions,such as impaired visual function,psychological burdens,and restricted social participation,are becoming increasingly severe.Due to the limited and unevenly distributed ophthalmic resources,and the significant limitations of traditional diagnostic and therapeutic approaches in terms of accuracy and efficiency,there is an urgent need for more sensitive and efficient modalities.With the rapid advancement of artificial intelligence technology,ophthalmic diagnosis has entered a new stage of intelligent transformation.Facial photos,as a noninvasive and convenient medium,show unique advantages in eye disease diagnosis.Artificial intelligence systems based on facial photo analysis have been applied to the screening and diagnosis of conditions such as myopia,strabismus,ptosis,and thyroid eye disease,showing promising results.This review introduces the workflow of intelligent diagnosis for ocular diseases based on facial photographs,with a focus on recapitulating relevant research findings both domestically and internationally in recent years.It summarizes the innovative features and application advantages of intelligent diagnosis systems for eye diseases based on facial photos,analyzes the current technical bottlenecks and challenges in application,proposes corresponding countermeasures,and discusses future development directions,aiming to provide references and new insights for the intelligent screening and diagnosis of eye diseases.

Objective To establish an efficient,sensitive,and accurate ion chromatography method for the simultaneous determination of three impurity ions—bromide(Br-),nitrite(NO2-),and oxalate(C2 O42-)—in oral rehydration salts powder(Ⅲ).These impurity ions may pose potential toxic side effects on children's health;therefore,ensuring their content within safe limits is crucial for safeguarding pediatric medication safety.Methods A Metrosep A Supp 5 column(250 mm×4.0 mm,5 μm),packed with quaternary ammonium-bonded polyvinyl alcohol was used.The eluent consisted of carbonate buffer:Mobile phase A was a mixture of 3.2 mmol·L-1 sodium carbonate and 1.0 mmol·L-1 sodium bicarbonate(50∶50,V∶V),and mobile phase B was a mixture of 32 mmol·L-1 sodium carbonate and 10 mmol·L-1 sodium bicarbonate(50∶50,V∶V),with gradient elution.The column temperature was set at 35℃,and the flow rate was 0.7 mL·min-1.Limits for the three impurity ions were set according to the International Council for Harmonisation guidelines(ICH M7(R1)and ICH Q3B),and the method was validated by testing six actual samples.Results Within the concentration range of 0.02-0.50 μg·mL-1,the linear correlation coefficients(R2)for the three impurity ions were all greater than 0.999.The detection limits ranged from 1.2 to 3.4 ng·mL-1,and the spiked recovery rates were between 92.0%and 102.0%.Results from the six actual samples demonstrated that the method effectively controlled the content of impurity ions.Conclusion This study successfully established a gradient elution ion chromatography method for the simultaneous determination of three impurity ions in Oral rehydration salts powder(Ⅲ).The method is highly sensitive,specific,and accurate.