This study aims to explore the medication rules and mechanisms of treating chronic renal failure(CRF) by Jinling medical school based on data mining, network pharmacology, and experimental validation systematically and deeply. Firstly, the study selected the papers published by the inherited clinicians in Jinling medical school in Chinese journals using the subject headings named "traditional Chinese medicine(TCM) + chronic renal failure", "TCM + chronic renal inefficiency", or "TCM + consumptive disease" in China National Knowledge Infrastructure, Wanfang, and VIP Chinese Science and Technology Periodical Database and screened TCM formulas for treating CRF according to inclusion and exclusion criteria. The study analyzed the frequency of use of single TCM and the four properties, five tastes, channel tropism, and efficacy of TCM used with high frequency and performed association rule and clustering analysis, respectively. As a result, a total of 215 TCM formulas and 235 different single TCM were screened, respectively. The TCM used with high frequency included Astragali Radix, Rhei Radix et Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma, Poria, and Atractylodis Macrocephalae Rhizoma(top 5). The single TCM characterized by "cold properties, sweet flavor, and restoring spleen channel" and the TCM with the efficacy of tonifying deficiency had the highest frequency of use, respectively. Then, the TCM with the rules of "blood-activating and stasis-removing" and "diuretic and dampness-penetrating" appeared. In addition, the core combination of TCM [(Hexin Formula, HXF)] included "Astragali Radix, Rhei Radix et Rhizoma, Poria, Salviae Miltiorrhizae Radix, and Angelicae Sinensis Radix". The network pharmacology analysis showed that HXF had 91 active compounds and 250 corresponding protein targets including prostaglandin-endoperoxide synthase 2(PTGS2), PTGS1, sodium voltage-gated channel alpha subunit 5(SCN5A), cholinergic receptor muscarinic 1(CHRM1), and heat shock protein 90 alpha family class A member 1(HSP90AA1)(top 5). Gene Ontology(GO) function analysis revealed that the core targets of HXF predominantly affected biological processes, cellular components, and molecular functions such as positive regulation of transcription by ribonucleic acid polymerase Ⅱ and DNA template transcription, formation of cytosol, nucleus, and plasma membrane, and identical protein binding and enzyme binding. Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis revealed that CRF-related genes were involved in a variety of signaling pathways and cellular metabolic pathways, primarily involving "phosphatidylinositol 3-kinase(PI3K)-protein kinase B(Akt) pathway" and "advanced glycation end products-receptor for advanced glycation end products". Molecular docking results showed that the active components in HXF such as isomucronulatol 7-O-glucoside, betulinic acid, sitosterol, and przewaquinone B might be crucial in the treatment of CRF. Finally, a modified rat model with renal failure induced by adenine was used, and the in vivo experimental confirmation was performed based on the above-mentioned predictions. The results verify that HXF can regulate mitochondrial autophagy in the kidneys and the PI3K-Akt-mammalian target of rapamycin(mTOR) signaling pathway activation at upstream, so as to alleviate renal tubulointerstitial fibrosis and then delay the progression of CRF.
Data Mining ; Drugs, Chinese Herbal/chemistry* ; Network Pharmacology ; Humans ; Kidney Failure, Chronic/metabolism* ; Medicine, Chinese Traditional ; China

This study explored the prescription pattern of traditional Chinese medicine(TCM) in the treatment of hypertensive left ventricular hypertrophy(LVH), so as to provide a relevant theoretical basis for the clinical diagnosis and treatment of hypertensive LVH. The study systematically searched the databases of CNKI, Wanfang, VIP, and SinoMed to screen out the qualified literature on TCM treatment of hypertensive LVH and used Microsoft Excel 2021 to establish the relevant prescription database. It also counted the frequency, property, flavor, and meridian affiliation of TCM in the prescriptions and classified their efficacy. The study used Lantern 5.0 and Rstudio software to analyze the hidden structural models and association rules of the high-frequency TCM with a frequency of >3.50% and adopted Origin 2024 software to visualize the data, so as to explore the prescription pattern of TCM in treating hypertensive LVH. The results showed that a total of 128 TCM prescriptions were included, involving 163 TCM with a total frequency of 1 242. The high-frequency TCM included Salviae Miltiorrhizae Radix et Rhizoma, Uncariae Ramulus Cum Uncis, Gastrodiae Rhizoma, Poria, and Chuanxiong Rhizoma, with the main efficacy from blood-activating and stasis-resolving herbs, tonic herbs, and liver-calming and wind-extinguishing herbs. The latent structure analysis(LSA) identified 10 latent variables, 20 latent classes, 7 comprehensive clustering models, and 23 core prescriptions. It was speculated that the common syndromes of hypertensive LVH included blood stasis obstructing the collaterals, ascending hyperactivity of liver Yang, Yin deficiency with Yang hyperactivity, and intermingled phlegm and blood stasis. The association rule analysis yielded 33 strong association rules, with the highest comprehensive association rule being Gastrodiae Rhizoma→Uncariae Ramulus Cum Uncis. Hypertensive LVH is characterized by asthenia in origin and asthenia in superficiality, with Yin deficiency and Qi deficiency as the origin and blood stasis and phlegm as the superficiality. Clinical treatment focuses on activating blood circulation, resolving stasis, tonifying Qi, and nourishing Yin, combined with syndrome-specific therapies such as calming wind and stopping convulsions, clearing heat, eliminating dampness and resolving phlegm, and promoting diuresis and reducing swelling.
Drugs, Chinese Herbal/therapeutic use* ; Data Mining ; Humans ; Hypertension/complications* ; Hypertrophy, Left Ventricular/physiopathology* ; Medicine, Chinese Traditional ; Drug Prescriptions

Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing important semantic information. A Transformer encoder was used for cross-modal semantic learning. By introducing manifold similarity constraints, balance constraints, and a linear classification network constraint, the algorithm enhanced the discriminability of the hash codes. Experimental results demonstrated that the MSACH algorithm improved the mean average precision (MAP) by 11.8% and 12.8% on two datasets compared to traditional methods. The algorithm exhibits outstanding performance in enhancing retrieval accuracy and handling large-scale medical data, showing promising potential for practical applications.
Algorithms ; Semantics ; Humans ; Ultrasonography ; Information Storage and Retrieval/methods* ; Image Processing, Computer-Assisted/methods*

Online hashing methods are receiving increasing attention in cross modal medical image retrieval research. However, existing online methods often lack the learning ability to maintain semantic correlation between new and existing data. To this end, we proposed online semantic similarity cross-modal hashing (OSCMH) learning framework to incrementally learn compact binary hash codes of medical stream data. Within it, a sparse representation of existing data based on online anchor datasets was designed to avoid semantic forgetting of the data and adaptively update hash codes, which effectively maintained semantic correlation between existing and arriving data and reduced information loss as well as improved training efficiency. Besides, an online discrete optimization method was proposed to solve the binary optimization problem of hash code by incrementally updating hash function and optimizing hash code on medical stream data. Compared with existing online or offline hashing methods, the proposed algorithm achieved average retrieval accuracy improvements of 12.5% and 14.3% on two datasets, respectively, effectively enhancing the retrieval efficiency in the field of medical images.
Semantics ; Humans ; Algorithms ; Information Storage and Retrieval/methods* ; Diagnostic Imaging ; Image Processing, Computer-Assisted/methods*

Data space, as an innovative data management and sharing model, is emerging in the medical and health sectors. This study expounds on the conceptual connotation of data space and delineates its key technologies, including distributed data storage, standardization and interoperability of data sharing, data security and privacy protection, data analysis and mining, and data space assessment. By analyzing the real-world cases of data spaces within medicine and health, this study compares the similarities and differences across various dimensions such as purpose, architecture, data interoperability, and privacy protection. Meanwhile, data spaces in these fields are challenged by the limited computing resources, the complexities of data integration, and the need for optimized algorithms. Additionally, legal and ethical issues such as unclear data ownership, undefined usage rights, risks associated with privacy protection need to be addressed. The study notes organizational and management difficulties, calling for enhancements in governance framework, data sharing mechanisms, and value assessment systems. In the future, technological innovation, sound regulations, and optimized management will help the development of the medical and health data space. These developments will enable the secure and efficient utilization of data, propelling the medical industry into an era characterized by precision, intelligence, and personalization.
Humans ; Computer Security ; Information Dissemination ; Data Management ; Information Storage and Retrieval ; Data Mining

Databases, Bibliographic ; Evidence-based Practice ; Health Services Needs And Demand

OBJECTIVE: To propose a new protocol for personalized mandibular reconstruction assisted by three-dimensional (3D) retrieval model based on fully connected neural network (FCNN) and a database of mandibles, and to verify clinical feasibility of the protocol. METHODS: A database of mandibles of 300 normal northern Chinese Han people was established. On the basis of cephalometry, the mandible landmarks with good stability were further screened. Mandibular landmarks were selected and geometric features of the mandible were extracted. A 3D retrieval algorithm was developed, which could retrieve the mandible most similar to a given mandible from the database. A FCNN was built to train the algorithm to improve accuracy of the 3D retrieval model. Using Geomagic Control 2014 software, matching accuracy of the 3D retrieval model was based on aforementioned mandible database and algorithm. From December 2019 to March 2021, a total of 5 patients underwent personalized mandibular reconstruction assisted by a 3D retrieval model based on mandible database and FCNN in the Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology. The most similar mandible was retrieved from mandible database through 3D retrieval algorithm. It was used to restore the premorbid morphology of defect area and guide mandibular reconstruction. For the 5 patients, mandible was reconstructed with iliac flap. Virtual surgical plan was transformed using individual surgical guides. RESULTS: Through screening, mandibular landmarks with high reproducibility and stability were identified and composed of mandibular landmarker protocols. After training, the average deviation between most similar mandible retrieved from the 300-case mandible database through 3D retrieval model based on FCNN and given mandible was (1.77±0.44) mm. And the root-mean-square deviation between the most similar mandible retrieved from the database and given mandible was (2.58±0.86) mm. The mandibular reconstruction surgery was successful in all the 5 patients. Their facial symmetry and occlusion were restored. All the patients were satisfied with postoperative appearance. The mean deviation between postoperative mandible and preoperative design was (0.98±0.17) mm. The area with a deviation ≤1 mm accounted for 61.34%±14. 13%, ≤2 mm accounted for 83.82%±7.35%, and ≤3 mm accounted for 93.94%± 2.87%. CONCLUSION The personalized mandibular reconstruction assisted by 3D retrieval model based on the 300-case mandible database and FCNN is feasible clinically.
Humans ; Neural Networks, Computer ; Mandibular Reconstruction/methods* ; Mandible/diagnostic imaging* ; Imaging, Three-Dimensional/methods* ; Adult ; Databases, Factual ; Female ; Male ; Algorithms ; Middle Aged ; Cephalometry

The application of artificial intelligence (AI) technology in the field of radiation protection is gradually becoming a key force driving industrial development. This paper focuses on the applications of AI technology in radiation monitoring, shielding design, and nuclear science data mining, and prospects its future development. Through real-time monitoring and predictive analysis, AI technology has significantly improved the accuracy and efficiency of radiation monitoring, optimized the selection and configuration of shielding materials, and effectively reduced radiation exposure. Additionally, AI's data mining capabilities provide powerful tools for nuclear reactor design and optimization, promoting innovation in nuclear and radiological sciences. Despite technical challenges and ethical issues such as accuracy, data processing, and algorithmic transparency, the application prospects of AI in radiation protection remain broad. This paper emphasizes the critical role of AI technology in enhancing medical safety and efficiency, and foresees more future innovations and applications in the field of radiation protection.
Radiation Protection/methods* ; Artificial Intelligence ; Radiation Monitoring ; Humans ; Data Mining ; Algorithms

OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

OBJECTIVES: Nasopharyngeal carcinoma is often diagnosed at a late stage due to its concealed location and exhibits marked regional clustering, posing a significant public health challenge in China. This study aims to analyze the disease burden of nasopharyngeal carcinoma in China using the latest 2021 Global Burden of Diseases (GBD) database, providing epidemiological evidence for precise prevention and control of nasopharyngeal carcinoma. METHODS: Age-standardized incidence rate (ASIR), mortality rate, and disability-adjusted life year (DALY) rate were used as indicators of disease burden. Stratified analyses were conducted by age, sex, socio-demographic index (SDI), and relevant risk factors. The autoregressive integrated moving average (ARIMA) model and Bayesian age-period-cohort (BAPC) model were employed to project ASIR trends through 2050. RESULTS: In 2021, China's age-standardized incidence, mortality, and DALY rates of nasopharyngeal carcinoma were 3.4/100 000, 1.5/100 000, and 48.7/100 000, respectively, all higher than the global average. Across all age groups, Chinese males exhibited higher ASIR, mortality, and DALY rates than females. From 1990 to 2021, the disease burden of nasopharyngeal carcinoma in China decreased gradually with rising SDI. The proportion of nasopharyngeal carcinoma burden attributed to alcohol consumption, smoking, and occupational formaldehyde exposure in China exceeded global levels, especially among males. Projections from both models indicate a rising trend in ASIR for males, females, and the general population in China and globally from 2022 to 2050. CONCLUSIONS Over the past 30 years, the disease burden of nasopharyngeal carcinoma in China has decreased with the increasing SDI values but remains higher than the global average. Furthermore, ASIR is projected to increase over the next 30 years. It is imperative for China to enhance healthcare resource allocation for nasopharyngeal carcinoma prevention, diagnosis, and treatment, particularly among high-risk male populations.
Humans ; China/epidemiology* ; Male ; Nasopharyngeal Carcinoma/mortality* ; Female ; Middle Aged ; Nasopharyngeal Neoplasms/mortality* ; Adult ; Incidence ; Global Burden of Disease ; Disability-Adjusted Life Years ; Aged ; Risk Factors ; Adolescent ; Databases, Factual ; Young Adult ; Cost of Illness ; Child ; Bayes Theorem