Objective To investigate the current distribution of radiotherapy resources in Gansu Province, evaluate the equity of resource allocation, and provide a scientific basis for optimizing regional resource allocation. Methods A questionnaire survey was carried out to assess radiotherapy resources in medical institutions across Gansu Province, China. The equity of radiotherapy resource distribution and associated disparities were assessed using the Gini coefficient, Lorenz curve, and Theil index. Results A total of 23 medical institutions in Gansu Province provided radiotherapy services, comprising 39 radiotherapy devices and 438 professionals, of whom medical physicists accounted for 16.9%. The radiotherapy frequency was 0.47 cases per thousand population. The Gini coefficients for radiotherapy resource distribution ranged from 0.38 to 0.56 by population and from 0.52 to 0.70 by geography. The Theil index for radiotherapy resources ranged from 1.36 to 3.67. Conclusion Radiotherapy resources in Gansu Province were insufficient, and the capacity of radiotherapy service was suboptimal. The equity of radiotherapy resource allocation by geography was worse than that by population. Therefore, it is imperative to address the shortage of radiotherapy resources, strengthen the professional workforce, enhance the capacity radiotherapy service and resource utilization, optimize resource allocation, and promote regional equity in radiotherapy provision in Gansu Province.

BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

BACKGROUND:Spondylolisthesis is a common disease,and there is a lack of effective drugs to treat it.There is still a need to further define the pathogenesis and screen out more suitable therapeutic targets for spondylolisthesis.Mendelian randomization analysis can be used to explore the drugable genes associated with spondylolisthesis and provide valuable guidance for the development of more effective and targeted therapeutic drugs.OBJECTIVE:To explore potential therapeutic targets and effective drugs for spondylolisthesis by means of pharmaceutically available genome-wide Mendelian randomization analysis.METHODS:Using the Finnish database,eQTLGen consortium,drug signature database,drug-gene interaction database,protein-protein interaction database,organic small molecule biological activity database and protein structure database,which contains genome and health information of half a million Finns,data on druggable genes were subjected to two-sample Mendelian randomization analysis and co-localization analysis with data from genome-wide association studies of spondylolisthesis to identify genes highly associated with spondylolisthesis.In addition,GO and KEGG enrichment analysis,protein network construction,drug prediction and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic agents.RESULTS AND CONCLUSION:In this study,we identified 34 potential drug target genes that were significantly associated with spondylolisthesis,particularly the gene APOBEC3G.This gene showed a significant association with spondylolisthesis outcomes through Mendelian analysis and co-localization analysis,suggesting that APOBEC3G may be a priority therapeutic target.As for other potential mechanisms and drugs,we still need to conduct more in-depth research to determine their roles.This study used a database from a European population,which can be used as a reference for the study of population genetics in China.

Objective To address the current blind spots in quality control and the risk of data distortion in radiological health technical service institutions, overcome the limitations of low efficiency and insufficient anomaly identification in manual verification, establish an automatic anomaly early warning mechanism based on AI algorithms, provide accurate clues for health supervision and law enforcement, and significantly enhance the efficiency of industry supervision. Methods On-site inspection data were collected via photographic imaging. Advanced image processing and object detection algorithms were employed to automatically extract and analyze key information from the images. Through data analysis, the system was used to calculate and assess the inspection results. A dynamic early warning engine was developed to automatically trigger alerts upon detection of deviations from standard thresholds or regulatory violations in radiological health technical services. These alerts were delivered through a regulatory information system. Results Following AI model training, the accuracy of the image processing and object detection algorithms reached 99% and the early warning accuracy reached 93%. Compared with the traditional supervision mode, the efficiency of anomaly detection was improved and the average response time was shortened. Conclusion The full-process supervision information system constructed in this study has realized the triple mechanism of pre-event standardization, in-event monitoring, and post-event traceability for radiological health technical services. In particular, the system has established a four-level quality control chain of “institutional self-inspection, intelligent recheck, expert judgment, and administrative action”, providing a technological innovation path for ensuring the radiation protection and safety of medical staff, patients, and the public.

AIM:To investigate the role of serum high-sensitivity C-reactive protein(hsCRP)in the pathogenesis and progression of diabetic retinopathy(DR)in patients with type 2 diabetes mellitus(T2DM).METHODS:A nested case-control study was conducted involving 187 T2DM patients(187 eyes)who attended at Eye Center, Beijing Tongren Hospital, Capital Medical University from June 2017 to October 2024. Patients were categorized into three groups: the diabetes mellitus(DM)group, non-proliferative DR(NPDR)group, and proliferative DR(PDR)group. Baseline information was collected, including age, sex, duration of DM, and duration of hypertension. All patients underwent fasting biochemical tests and comprehensive ophthalmic examinations.RESULTS: A positive correlation was observed between hsCRP and fasting blood glucose(FBG; P=0.004)and glycated hemoglobin A1c(HbA1c; P=0.048)by Spearman's rank correlation coefficient analysis. After adjusting for confounding factors, multivariable Logistic regression identified hsCRP as a significant risk factor for DR(OR=2.67, 95% CI: 1.19-5.96, P=0.017). CONCLUSION:Serum hsCRP is positively correlated with FBG and HbA1c and can serve as an important predictor of the severity of DR.

Chemotherapy is an important treatment for tumors， but most patients experience varying degrees of chemotherapy- induced myelosuppression. Four properties theory of traditional Chinese medicine （TCM） has unique advantages in improving chemotherapy-induced myelosuppression. The monomers from TCM with different properties and flavors， such as cold-natured （e.g. Scutellaria baicalensis， Rhus chinensis）， cool-natured （e.g. Ligustrum lucidum， Ophiopogon japonicus）， warm-natured （e.g. Panax ginseng， Epimedium brevicornu， Curcuma longa， Angelica sinensis）， hot-natured （e.g. Cinnamomum cassia， Aconitum carmichaeli）， and neutral-natured （e. g. donkey-hide gelatin， Lycium barbarum， Rhodiola rosea， fungi）， can exert anti- myelosuppressive effects by reducing damage to hematopoietic stem/progenitor cells， improving the bone marrow hematopoietic microenvironment， inhibiting the oxidative stress response， regulating signaling pathways， so as to ultimately repaire inflammatory damage and improve hematopoietic function， thereby playing an anti-myelosuppressive role.

AIM: To review and summarize the current research and achievements in the field of diabetic cataract, with the aim of better identifying research hotspots and trends in this area.METHODS: Based on the relevant literature retrieved from the China National Knowledge Infrastructure, Web of Science databases, and Pubmed, a bibliometric analysis of the diabetic cataract was conducted by means of Microsoft Office Excel 2017 and CiteSpace 6.3R2. Research hotspots were subsequently synthesized after visualizations of author/country collaborations, co-citation networks of highly cited literature, keyword clustering, and emergence.RESULTS: A total of 815 Chinese and 572 English publications were finally included. Overall, this field had maintained substantial scholarly attention globally, though publications had progressively decreased since 2018. While inter-institutional collaboration in this area remained limited, a multinational collaborative network had emerged with the People's Republic of China, the United States of America, the United Kingdom, and the Kingdom of Spain as central hubs. Core research priorities in diabetic cataract consistently encompassed surgical and pharmacological interventions, pathogenesis, associated ocular/systemic complications; while international and domestic research contents aligned fundamentally in these domains, but the domestic research was unique in nursing interventions and herbal medicine-based interventions. Recent analytical trends revealed that Chinese investigations prioritized the pathogenic mechanisms of diabetic cataract, whereas international efforts concentrated on clinical therapeutics.CONCLUSION: This bibliometric analysis of diabetic cataract research literature(2000-2024)synthesizes the current advancements, research priorities, and scholarly contributions in the field, and intuitively demonstrates significant academic merit and clinical relevance, which can provide evidence-based guidance for the future research trajectories.

Necroptosis, a form of programmed cell death, initiates a series of biological responses and further culminates in necroinflammatory processes, consequently limiting the efficacy of cytokine antagonists in treating inflammatory diseases. To address this issue, DNAzyme R3-Dz specifically targeting receptor-interacting protein kinase 3 (RIP3) mRNA, a necrosome component, has been successfully developed and studied to elucidate the mechanism in cleaving its target mRNA. Then a polyamidoamine (PAMAM) derivative was constructed through the modification of nucleobase analog (termed AP) to achieve the R3-Dz delivery to macrophages. The AP/R3-Dz nanoparticles effectively downregulated the RIP3 expression, leading to subsequent decrease in the levels of reactive oxygen species (ROS) and damage-associated molecular patterns (DAMPs), ultimately inhibiting the necroinflammatory processes mediated by the NOD-like receptor family pyrin domain-containing 3 (NLRP3). Finally, AP/R3-Dz nanoparticles and their combination with the NLRP3 inhibitor MCC950 suppressed the necrotic phenotype and ameliorated the disease progression in diverse models, including gouty arthritis, autoimmune hepatitis and rheumatoid arthritis. In summary, the AP/R3-Dz nanoparticles in combination with MCC950 have been demonstrated to achieve the intervention in necroptosis and inflammation by dual disruption of the intricate feedback loop of necroinflammation and thus have promising potential in the treatment of inflammatory diseases.

OBJECTIVES: We propose a Contrastive Regional Attention and Prior Knowledge-Infused U-Transformer model (CRAKUT) to address the challenges of imbalanced text distribution, lack of contextual clinical knowledge, and cross-modal information transformation to enhance the quality of generated radiology reports. METHODS: The CRAKUT model comprises 3 key components, including an image encoder that utilizes common normal images from the dataset for extracting enhanced visual features, an external knowledge infuser that incorporates clinical prior knowledge, and a U-Transformer that facilitates cross-modal information conversion from vision to language. The contrastive regional attention in the image encoder was introduced to enhance the features of abnormal regions by emphasizing the difference between normal and abnormal semantic features. Additionally, the clinical prior knowledge infuser within the text encoder integrates clinical history and knowledge graphs generated by ChatGPT. Finally, the U-Transformer was utilized to connect the multi-modal encoder and the report decoder in a U-connection schema, and multiple types of information were used to fuse and obtain the final report. RESULTS: We evaluated the proposed CRAKUT model on two publicly available CXR datasets (IU-Xray and MIMIC-CXR). The experimental results showed that the CRAKUT model achieved a state-of-the-art performance on report generation with a BLEU-4 score of 0.159, a ROUGE-L score of 0.353, and a CIDEr score of 0.500 in MIMIC-CXR dataset; the model also had a METEOR score of 0.258 in IU-Xray dataset, outperforming all the comparison models. CONCLUSIONS The proposed method has great potential for application in clinical disease diagnoses and report generation.
Humans ; Radiology Information Systems ; Radiology