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.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

The transcription factor HOXB13 plays crucial roles in cancer development. HOXB13 is abnormally expressed in most cancers, which makes it a valuable therapeutic target for cancer therapy. The level of HOXB13 differs significantly between healthy and cancer tissues, which indicates that the level of HOXB13 is closely related to carcinogenesis. The regulatory network mediated by HOXB13 in cancer proliferation, metastasis, and invasion has been systematically investigated. Moreover, HOXB13 variants play distinct roles in different cancers and populations. By understanding the molecular mechanisms and mutation features of HOXB13, we provide a comprehensive overview of carcinogenesis networks dependent on HOXB13. Finally, we discuss advancements in anticancer therapy targeting HOXB13 and the roles of HOXB13 in drug resistance to molecular-targeted therapies, which serves as a foundation for developing HOXB13-targeted drugs for clinical diagnosis and cancer therapies.
Humans ; Neoplasms/metabolism* ; Homeodomain Proteins/metabolism* ; Carcinogenesis/genetics* ; Mutation ; Gene Expression Regulation, Neoplastic ; Molecular Targeted Therapy ; Drug Resistance, Neoplasm/genetics*

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective To propose a precise suctioning scheme for intravenous drug dispensing based on the vial dispensing robot to enhance the quality of finished infusion.Methods Six kinds of typical representative vial drugs were selected as the research objects,including pantoprazole sodium for injection,papaverine hydrochloride for injection,cefuroxime sodium for injection,Bozhi Glycopeptide Injection,Esomeprazole Sodium for Injection and Methylprednisolone Sodium Succinate for injection.The optimal suction speed was determined by studying the relationship between the size parameters of vials and the suction speed of robot dispensing,which was used to carry out drug dispensing with the vial dispensing robot to verify whether the minimum drug residue could be obtained with the speed.The drug residue was compared with that by manual dispensing.SPSS 24.0 and Excel 2021 were applied to statistical analysis.Results The optimal suction efficiency and minimized drug residue could be got with the depth of the syringe needle hole into the rubber plug(X)less than the height of the rubber plug(H)and the optimal suction speed(Vs)of 7.48 mm/s;the suction efficiency could be ensured without air drawn in when X not less than H and Vs ranging from 10.64 to 39.31 mm/s.The mean values of the drug residue by the robot were all lower than those by manual dispensing,with the differences being statistically significant(P<0.05).Conclusion The proposed scheme can be used for optimizing the parameters of the vial vial dispensing robot to obtain infusion solution with high stability and reliability,which promotes standardization and normalization of intravenous infusion dispensing process.[Chinese Medical Equipment Journal,2025,46(9):45-51]

The etiology of nervous system diseases is complicated, posing significant harm to patients and often resulting in poor prognoses. In recent years, the role of dopaminergic system in nervous system diseases has attracted much attention, and its complex regulatory mechanism and therapeutic potential have been gradually revealed. This paper reviews the role of dopaminergic neurons, the neurotransmitter dopamine, dopamine receptors and dopamine transporters in neurological diseases (including Alzheimer's disease, Parkinson's disease and schizophrenia), with a view to further elucidating the disease mechanism and providing new insights and strategies for the treatment of neurological diseases.
Humans ; Dopamine/metabolism* ; Nervous System Diseases/physiopathology* ; Parkinson Disease/physiopathology* ; Receptors, Dopamine/metabolism* ; Dopaminergic Neurons/physiology* ; Dopamine Plasma Membrane Transport Proteins/metabolism* ; Alzheimer Disease/physiopathology* ; Schizophrenia/physiopathology* ; Animals

This study aimed to explore the pharmacological mechanism of Yourenji Capsules(YRJ) in improving osteoporosis by combining network pharmacology and proteomics technologies. The SD rats were randomly divided into a blank control group and a 700 mg·kg~(-1) YRJ group. The rats were subjected to gavage administration with the corresponding drugs, and the blank serum, drug-containing serum, and YRJ samples were compared using ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) to analyze the main components absorbed into blood. Network pharmacology analysis was conducted based on the YRJ components absorbed into blood to obtain related targets of the components and target genes involved in osteoporosis, and Venn diagrams were used to identify the intersection of drug action targets and disease targets. The STRING database was used for protein-protein interaction(PPI) network analysis of potential target proteins to construct a PPI network. Gene Ontology(GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment were performed using Enrichr to investigate the potential mechanism of action of YRJ. Ovariectomy(OVX) was performed to establish a rat model of osteoporosis, and the rats were divided into a sham group, a model group, and a 700 mg·kg~(-1) YRJ group. The rats were given the corresponding drugs by gavage. The femurs of the rats were subjected to label-free proteomics analysis to detect differentially expressed proteins, and GO functional enrichment and KEGG pathway enrichment analyses were performed on the differentially expressed proteins. With the help of network pharmacology and proteomics results, the mechanism by which YRJ improves osteoporosis was predicted. The analysis of the YRJ components absorbed into blood revealed 23 bioactive components of YRJ, and network pharmacology results indicated that key targets involved include tumor necrosis factor(TNF), tumor protein p53(TP53), protein kinase(AKT1), and matrix metalloproteinase 9(MMP9). These targets are mainly involved in osteoclast differentiation, estrogen signaling pathways, and nuclear factor-kappa B(NF-κB) signaling pathways. Additionally, the proteomics analysis highlighted important pathways such as peroxisome proliferator-activated receptor(PPAR) signaling pathways, mitogen-activated protein kinase(MAPK) signaling pathways, and β-alanine metabolism. The combined approaches of network pharmacology and proteomics have revealed that the mechanism by which YRJ improves osteoporosis may be closely related to the regulation of inflammation, osteoblast, and osteoclast metabolic pathways. The main pathways involved include the NF-κB signaling pathways, MAPK signaling pathways, and PPAR signaling pathways, among others.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Osteoporosis/metabolism* ; Proteomics ; Rats ; Rats, Sprague-Dawley ; Network Pharmacology ; Female ; Protein Interaction Maps/drug effects* ; Capsules ; Humans ; Signal Transduction/drug effects*

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.