Early caries confined to the enamel layer represent a critical window for achieving noninvasive intervention in caries management. Caries management has shifted from the traditional “drill-and-fill” model toward a modern paradigm centered on caries risk and lesion management. Based on contemporary concepts, this review systematically summarizes recent advances in early caries management, including caries risk assessment, early diagnosis, treatment strategy selection, and follow-up monitoring, while highlighting the major challenges currently being faced, and further reviewing and discussing the application of artificial intelligence (AI) in early caries management. In terms of risk management, conventional systems including the American Dental Association, Caries Management by Risk Assessment, Cariogram, and the Caries-Risk Assessment Tool remain mainstays in clinical practice. However, AI offers predictive capability through higher-dimensional data processing and the integration of numerous influencing factors, with the potential to improve the accuracy of risk stratification. For diagnosis, visual inspection, tactile examination, and bitewing radiography remain fundamental methods, yet their sensitivity for early caries—particularly proximal lesions—is limited. The application of optical technologies, including quantitative light-induced fluorescence, optical coherence tomography, near-infrared light transillumination, fiber-optic transillumination, and laser-induced fluorescence, enables digital characterization of caries lesions, providing a data foundation for demineralization assessment, lesion activity evaluation, and AI model development. The management of early caries primarily relies on noninvasive and minimally invasive approaches. Remineralization therapy is suitable for superficial lesions, resin infiltration offers the dual advantages of inhibiting lesion progression and improving aesthetics, and microabrasion and bleaching may serve as adjunctive aesthetic treatments. Emerging modalities such as laser, ozone, and photodynamic therapy have also demonstrated potential. Treatment decision-making should comprehensively consider lesion activity, patient caries risk status, demineralization depth, patient compliance, and treatment preferences. However, precise quantification of demineralization depth remains challenging, and standardized decision-making criteria are still lacking. Follow-up management should be individualized based on risk stratification, with attention to lesion changes, patient compliance, and the risk of recurrence. In summary, intelligent and precision-based approaches are expected to define the future of early caries management, and the application of AI in risk prediction, image analysis, and clinical decision support is anticipated to further enhance the efficiency and effectiveness of early caries diagnosis and treatment.

Intelligent prescription recommendation has become an important research direction in traditional Chinese medicine (TCM), offering new opportunities to support clinical decision-making and promote the modernization of TCM practice. With the rapid development of artificial intelligence (AI), a variety of computational approaches have been proposed to learn prescription patterns from clinical data and generate personalized treatment recommendations. However, despite increasing research activity, systematic and comprehensive reviews of AI-driven methods for TCM prescription recommendation remain limited. In this study, we present a comprehensive review of computational approaches for herbal prescription recommendation (HPR) in TCM. Existing methods are systematically categorized into several major paradigms, including traditional machine learning methods, topic model methods, sequential generative methods, deep learning and graph-based methods, and large language model–based frameworks. In addition to summarizing methodological developments, we also review commonly used public datasets and evaluation metrics in this field. Furthermore, representative models with publicly available implementations are experimentally evaluated on multiple benchmark datasets to provide a comparative analysis of their performance on the HPR task. Finally, we discuss the key challenges that hinder the practical deployment of intelligent prescription recommendation systems, including data heterogeneity, limited interpretability, and insufficient integration of TCM domain knowledge. Future research directions are outlined to facilitate the development of more reliable, interpretable, and clinically applicable AI-assisted HPR systems for TCM.

Objective:To establish the method of bacterial endotoxin detection for raw materials and injections of paliperidone palmitate.Methods:Paliperidone palmitate was dissolved with tetrahydrofuran and polysorbate 20 as solvent,and then diluted with BET H2O.According to bacterial endotoxin test in Chinese Pharmacopoeia 2020 Vol general charpters 1143,methodology validation of chromogenic substrate method in bacterial endotoxin test was con-ducted and then the interference experiment of solubilizer was added.Results:Paliperidone palmitate did not pre-cipitate during the experimental process,and then diluted to 0.007 mg·mL-1 with BET H2O.There was no inter-ference for chromogenic substrate method,while the bacterial endotoxin recovery of the solubilizer does not interfere with endotoxin testing.Conclusion:The method established in this paper is suitable for bacteria endotoxin test of raw materials and injections of paliperidone palmitate.

Objective:To establish the method of bacterial endotoxin detection for raw materials and injections of paliperidone palmitate.Methods:Paliperidone palmitate was dissolved with tetrahydrofuran and polysorbate 20 as solvent,and then diluted with BET H2O.According to bacterial endotoxin test in Chinese Pharmacopoeia 2020 Vol general charpters 1143,methodology validation of chromogenic substrate method in bacterial endotoxin test was con-ducted and then the interference experiment of solubilizer was added.Results:Paliperidone palmitate did not pre-cipitate during the experimental process,and then diluted to 0.007 mg·mL-1 with BET H2O.There was no inter-ference for chromogenic substrate method,while the bacterial endotoxin recovery of the solubilizer does not interfere with endotoxin testing.Conclusion:The method established in this paper is suitable for bacteria endotoxin test of raw materials and injections of paliperidone palmitate.

BACKGROUND:As a temporary matrix for new bone growth,the porous scaffold plays a key role in the process of bone repair.The structural design of porous scaffolds is a research priority in the process of bone repair.OBJECTIVE:To summarize traditional bone scaffolds(regular,uniform scaffolds)and bionic scaffolds(irregular,inhomogeneous scaffolds)in the field of bone tissue engineering research.METHODS:A computerized search was performed in the databases of CNKI,VIP,WanFang,Web of Science,Science Direct,PubMed,and EI.Literature published from January 2008 to March 2024 was selected.The search terms in Chinese included"bone tissue engineering,bionic scaffolds,bone trabeculae,traditional scaffolds,bone repair,triple-period minimal surfaces."The search terms in English were"bone tissue engineering,bionic scaffolds,bone trabeculae,traditional scaffolds,bone repair,TPMS."Finally,81 articles were included for review.RESULTS AND CONCLUSION:The structural design of bone scaffolds is the key to achieve bone repair and bone regeneration,and scaffold technology in bone tissue engineering has made remarkable progress.Traditional regular porous scaffolds are widely used due to their simple manufacturing process and good mechanical properties.However,these scaffolds often lack biological activity and are difficult to mimic the complex microenvironment of natural bone tissue,limiting their ability to promote cell proliferation and bone regeneration.On the contrary,bionic scaffolds provide a more suitable physiological microenvironment by mimicking the structural features of natural bone tissues,which promotes the proliferation and differentiation of osteoblasts,as well as the formation of new bone,and provides a new way of thinking for the effective treatment of bone defects.Despite the great potential of bionic scaffolds in theory,they still face many challenges in practical applications.Factors such as the scaffold's biocompatibility,bioactivity,and its long-term stability still need to be further verified through clinical trials.

Objective:To explore the advantages of internet-based smart healthcare for full-cycle transcatheter edge-to-edge repair (TEER) management in reducing postoperative adverse events rate, improving cardiac function, and enhancing quality of life.Methods:This retrospective study enrolled patients with mitral regurgitation who underwent transcatheter TEER at Beijing Anzhen Hospital Valve Intervention Center between June 2021 and September 2023. Patients were classified into degeneration mitral regurgitation (DMR) and functional mitral regurgitation (FMR) according to etiology, with further stratification by enrollment period into usual care group (June 2021 to October 2022) and full-cycle management group (November 2022 to September 2023). The 1-year postoperative follow-up data were collected and compared between subgroups with the same etiology. Kaplan-Meier survival curves were plotted, and log-rank tests were used to compare the differences in major endpoint event-free survival rates between the two groups. Univariate and multivariate Cox regression and logistic regression analyses were performed to evaluate the impact of the full-cycle management system on patients′ outcomes.Results:A total of 130 patients were included, aged (72.0±8.6) years, including 82 (63%) males. DMR was identified in 84 cases (40 in the usual care group and 44 in the full-cycle management group), while FMR was observed in 46 cases (27 in the usual care group and 19 in the full-cycle management group). Kaplan-Meier analysis demonstrated higher 1-year major endpoint event-free survival rates in the full-cycle management group compared to the usual care group, though the difference was not statistically significant (log-rank P>0.05). Compared to the usual care group, the full-cycle management group showed significantly higher proportions of New York Heart Association classification Ⅰ-Ⅱ patients (DMR: 67% vs. 52%, P=0.031; FMR: 68% vs. 52%, P=0.021), greater 6-minute walking distances (DMR: (346.39±70.41) m vs. (294.11±60.47) m, P=0.012; FMR: (356.60±54.68) m vs. (318.55±39.02) m, P=0.004), and superior Kansas City Cardiomyopathy Questionnaire scores (DMR: 81.50 (74.50, 85.00) points vs. 71.00 (66.00, 82.25) points, P=0.014; FMR: 83.00 (76.00, 85.00) points vs. 74.00 (70.75, 80.00) points, P=0.030). Multivariate logistic regression confirmed the full-cycle management system as an independent predictor for the above improved outcomes (all P<0.05). Conclusion:Smart healthcare-based full-cycle management improves cardiac function and quality of life in mitral regurgitation patients after TEER, demonstrating lower rates of major endpoint events compared to usual care.

Objective:To explore the molecular epidemiological characteristics of human metapneumovirus (HMPV) in children with acute respiratory infection (ARI) in Beijing from 2023 to 2024.Methods:In the longitudinal study, 9 834 children with ARI were enrolled from August 2023 to December 2024, including the influenza-like illness (ILI) group from emergency and outpatient department receiving influenza virus (Flu) and HMPV test and the ARI inpatient group for 13 common respiratory pathogen screening test including HMPV, Flu, respiratory syncytial virus, and so on. All respiratory samples positive with HMPV were genotyped by amplifying and sequencing of G gene and further phylogenetic analysis. The χ2 test and Wilcoxon rank-sum test were used to compare the positive rate and basic clinical data of the 2 groups. Results:Among 9 834 enrolled patient, there were 5 276 male and 4 558 female children, with age 5.4 (1.9, 8.2) years. In ILI group of 1 460 patients, there were 83 cases (5.7%) positive for HMPV, with the age 4.9 (3.6, 6.6) years and children under 6.0 years old 59 cases (71.1%). Among 8 374 ARI inpatients, there were 256 cases (3.1%) positive for HMPV, with age 3.5 (1.3, 6.4) years and children under 6.0 years old 188 cases (73.4%). The HMPV positive rate and the age of children positive for HMPV in ARI inpatient group were significantly lower than that in ILI group (both P<0.001). In December, 2024, the HMPV positive rates of ILI and ARI inpatient group (21.3% (17/80), 15.0% (47/314)) were significantly higher than the total positive rates of each group (both P<0.001). Among 279 subtyped specimens, there were 155 cases (55.6%) belonging to genotype A and 124 cases (44.4%) belonging to genotype B. Sub-lineage A2.2.2 containing 111nt-insertions was predominate one in 2023 with positive ratio 89.2% (91/102), and B2 was predominate in 2024 with positive ratio 64.4% (114/177). Conclusions:From 2023 to 2024, the positive rate of HMPV in the ILI group was higher than that in the ARI inpatient group, suggesting a common epidemic of HMPV infection. Children positive for HMPV in the ARI inpatient group were younger than that in the ILI group. A severe epidemic of HMPV was observed in the winter of 2024, which requires attention. Sub-lineage A2.2.2 with 111nt-duplicate insertions and B2 were the predominant epidemic strains in 2023 and 2024, respectively.

Objective:Middle ear cholesteatoma is a common otolaryngological disease, and traditional diagnostic methods have certain limitations. This study aims to construct a computer-aided diagnosis model for middle ear cholesteatoma based on integrated convolutional neural networks (CNNs) to improve diagnostic accuracy and efficiency.Methods:Firstly, Data were collected from patients who visited the Department of Otorhinolaryngology Head and Neck Surgery at the First People′s Hospital of Yinchuan between January 2020 and December 2021. 8 000 temporal bone CT images were collected, including 5 000 images diagnosed pathologically as middle ear cholesteatoma and 3 000 normal images. A five-fold cross-validation method was used to divide the dataset into training and testing sets. Next, a transfer learning approach was used to initialize model parameters, and the AlexNet, GoogleNet, and ResNet networks were pre-trained to extract deep features from the images. Then, the Softmax classification algorithm was applied to classify the features, resulting in three independent classifiers. These classifiers were combined using an ensemble learning method with a weighted voting approach to obtain the final diagnostic results. Finally, the model was evaluated by comparing the ensemble classifier with individual classifiers to assess its accuracy, precision, sensitivity, specificity, and diagnostic time, and a comparison with low-mid-and high-experience physician groups was conducted to comprehensively evaluate the model′s diagnostic performance.Results:The experimental results showed that the model achieved an accuracy of 88.8%(178/200), precision of 92.9%,(112/120) sensitivity of 89.8%(108/120), and specificity of 88.1%(70/80). The average diagnostic time for individual patient temporal bone CT images was reduced to 2-3 seconds. Compared to the diagnostic results from low-mid-and high-experience physician groups, the model demonstrated significant advantages and effectively assisted clinicians in making rapid and accurate middle ear cholesteatoma diagnoses.Conclusion:The proposed middle ear cholesteatoma diagnostic model based on integrated convolutional neural networks exhibits high recognition accuracy and rapid diagnostic speed, significantly improving clinical diagnostic efficiency, especially in early screening and auxiliary diagnosis, making it of considerable value in clinical practice.

BACKGROUND:As a temporary matrix for new bone growth,the porous scaffold plays a key role in the process of bone repair.The structural design of porous scaffolds is a research priority in the process of bone repair.OBJECTIVE:To summarize traditional bone scaffolds(regular,uniform scaffolds)and bionic scaffolds(irregular,inhomogeneous scaffolds)in the field of bone tissue engineering research.METHODS:A computerized search was performed in the databases of CNKI,VIP,WanFang,Web of Science,Science Direct,PubMed,and EI.Literature published from January 2008 to March 2024 was selected.The search terms in Chinese included"bone tissue engineering,bionic scaffolds,bone trabeculae,traditional scaffolds,bone repair,triple-period minimal surfaces."The search terms in English were"bone tissue engineering,bionic scaffolds,bone trabeculae,traditional scaffolds,bone repair,TPMS."Finally,81 articles were included for review.RESULTS AND CONCLUSION:The structural design of bone scaffolds is the key to achieve bone repair and bone regeneration,and scaffold technology in bone tissue engineering has made remarkable progress.Traditional regular porous scaffolds are widely used due to their simple manufacturing process and good mechanical properties.However,these scaffolds often lack biological activity and are difficult to mimic the complex microenvironment of natural bone tissue,limiting their ability to promote cell proliferation and bone regeneration.On the contrary,bionic scaffolds provide a more suitable physiological microenvironment by mimicking the structural features of natural bone tissues,which promotes the proliferation and differentiation of osteoblasts,as well as the formation of new bone,and provides a new way of thinking for the effective treatment of bone defects.Despite the great potential of bionic scaffolds in theory,they still face many challenges in practical applications.Factors such as the scaffold's biocompatibility,bioactivity,and its long-term stability still need to be further verified through clinical trials.

ObjectiveTo develop a scientifically rigorous and contextually appropriate instrument for evaluating the health service experience of pulmonary tuberculosis patients in China, to enable systematic assessment of core medical care dimensions, and to provide quantitative evidence for service improvement. MethodsGrounded in the theoretical framework of healthcare accessibility and the clinical care pathway for tuberculosis patients, the tool was developed through a systematic literature review and the Delphi expert consultation method. A multi-stage cluster sampling strategy was employed to survey pulmonary tuberculosis patients who had been receiving treatment for more than two months, aimed to explore the scale’s applicability in real-world settings. Reliability was assessed using Cronbach’s α and split-half reliability coefficients. Validity was evaluated through content validity, structural validity, convergent validity, and discriminant validity. ResultsThe tool was composed of 21 items across four dimensions: awareness, accessibility, affordability, and acceptability of tuberculosis medical care. It demonstrated a Cronbach’s α coefficient of 0.838 and a split-half reliability coefficient of 0.859. Exploratory factor analyses extracted six factors: satisfaction with healthcare services, supportive role of nurses, affordability of treatment costs, doctor-patient communication, waiting time for medical appointments, and transportation cost. The goodness-of-fit index (GFI) and other indices met the recommended standards, with the loading matrix indicating robust structural validity of the tool. The constructed factor model exhibited satisfactory content validity and discriminant validity. ConclusionThe scale for assessing patients’ experiences with tuberculosis-related medical care developed in this study demonstrates good reliability and validity and serves as a practical tool for evaluating patient experiences of tuberculosis medical care in China.