ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective:To systematically evaluate the current status of research on the development of indicators for entrustable professional activities (EPAs) of residents in China.Methods:We searched the China National Knowledge Infrastructure, Wanfang Data, Airiti Library, PubMed, Embase, and Web of Science databases for literature on the development of EPA indicators for residents in China published between January 1, 2005 and February 28, 2025. Two researchers independently screened the literature and extracted data, followed by descriptive analysis. The quality of the studies was assessed using the Joanna Briggs Institute critical appraisal tool for expert opinion. Quantitative data were presented as medians (ranges) and qualitative data were presented as frequencies (percentages).Results:A total of eight articles were included, in which two general EPA indicator systems and six specialty-specific EPA indicator systems were developed for residents. The overall quality of the research was high, with the main shortcomings related to the methods used in the process of constructing the consensus indicators. The number of experts recruited ranged from 22 to 45, with 100.00% response rate, high authority coefficients (0.820-0.914), and high coordination coefficients (0.157-0.741). Most of the studies used literature reviews as one source for the indicator pool (8 studies, 100.00%), employed the Delphi method to reach consensus (6 studies, 75.00%), and provided inclusion criteria for the indicators (7 studies, 87.50%). However, only one study (12.50%) explored the practical application of the developed indicators, and none of the studies set indicator weights or conducted quality assessments. The number of EPA indicators developed ranged from 10 to 38 per study. The reporting of EPA indicators was included in most studies regarding titles (8 studies, 100.00%) and the expected levels of entrustment at various stages of training (6 studies, 75.00%), but the reporting on other aspects was lacking. Among the specialty-specific EPA indicators, 38.39% overlapped with the general EPAs indicators.Conclusions:The research on the development of EPA indicators for residents in China is still in its early stages, and there is room for improvement in methodological quality and reporting coverage. There is partial overlap between specialty-specific and general EPA indicators, failing to fully reflect the unique characteristics of different specialties.

Objective:To compare the accuracy of a Chinese large language model (LLM) and radiologists in Chinese middle level professional qualification examination of radiology, and evaluate the quality of answer reasoning provided by the Chinese LLM.Methods:In this study, 100 high-quality questions were selected using stratified random sampling to form a test set. We asked the ERNIE Bot by dialogues on the website to provide the correct answers and answer reasoning for these questions. These questions were also answered by 15 radiologists with different levels of experience. The accuracy of Chinese LLM and that of radiologists were compared. Two radiologists evaluated the quality of answer reasoning using a 5-point semi-quantitative scale.Results:The accuracy of ERNIE Bot was 60.00%, which was lower than the median (interquartile) accuracy of 67.00% (64.00%, 73.00%) for radiologists, and the difference was statistically significant ( W=2.47, P=0.013). The word count of the reasoning provided by Ernie Bot was (196.44±99.25) words, with no significant difference in word count between correct and incorrect answer reasoning, which were (211.03±107.53) words and (174.55±81.84) words, respectively ( t=1.82, P=0.072). Among the correct answers, the quality of reasoning was scored as follows: 1 point for 3 questions, 2 points for 9 questions, 3 points for 12 questions, and 4 points for 36 questions. No reasoning received a score of 5. Conclusions:Chinese LLM demonstrates a certain level of medical knowledge and clinical reasoning ability, which can assist clinical teachers in educational activities. However, it is not yet able to independently tutor residents and lacks the ability of invitational and heuristic teaching.

Objective:To investigate the current status of Chinese-foreign cooperative education programs for medical majors, and to discuss the potential problems and development trends of this field.Methods:Related data were collected from the information platform of Chinese-Foreign Cooperation in Running Schools by Ministry of Education of the People's Republic of China, and the characteristics of Chinese-foreign cooperative education programs for medical majors were extracted for analysis. Categorical data were expressed as frequency (percentage), and continuous data were expressed as mean±standard deviation.Results:A total of 83 Chinese-foreign cooperative education programs for medical majors were included in the study, accounting for only 3.45% (83/2 406) of all programs. Chinese partners in these cooperative programs were mainly from East China (41 programs, 49.40%), while foreign partners were mainly from Europe (39 programs, 46.99%). The mean duration of these programs was (3.61±0.88) years, with an enrollment of (87.08±35.52) students. Most of the students were included in National General Higher Education Enrollment Plan (79 programs, 95.18%), and the main majors included nursing (39 programs, 46.99%), medical technology (19 programs, 22.89%), and clinical medicine (11 programs, 13.25%), with the main enrollment level of junior college (45 programs, 54.22%). Chinese partners in the cooperative programs mainly issued academic certificate (45 programs, 54.22%) or academic certificate plus degree certificate (36 programs, 43.37%), while most foreign partners did not issue such certificates (44 programs, 53.01%).Conclusions:There are several problems in Chinese-foreign cooperative education programs for medical majors, such as a limited number of programs, a significant regional difference, an imbalanced distribution of specialties, a low level of education, and inconsistency in issuance of certificates, which still requires further improvement and standardization. However, there are also high-level and high-quality programs for reference.

Objective:To explore the application effect of Kaitianmen point massage on pain, faligue, anxiety and depression in patients with rheumatoid arthritis.Methods:This study was a randomized controlled study, a total of 80 patients with rheumatoid arthritis who were admitted to Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine from May to November 2023 were selected as the research objects. The control group was given routine treatment and nursing, and the experimental group was given Kaitianmen acupoint massage on the basis of routine treatment and nursing. The differences in pain score, fatigue score, anxiety and depression score before and after intervention were compared between the two groups.Results:In the final, there were 37 cases in the experimental group and 36 cases in the control group completed the study. Before intervention, there was no statistically significant difference in pain scores, fatigue scores, anxiety and depression scores between the two groups (all P>0.05). After four weeks of intervention, the pain score of the experimental group was (2.06 ± 0.35), and that of the control group was (3.72 ± 0.59), the difference was statistically significant ( t=14.57, P<0.05). After four weeks of intervention, the fatigue score of the experimental group was (20.11 ± 8.03), and that of the control group was (25.02 ± 8.32), the difference was statistically significant ( t=2.55, P<0.05). After four weeks of intervention, the anxiety score of the experimental group was (48.33 ± 6.13), which was significantly different from (53.99 ± 4.91) of the control group ( t=4.35, P<0.05), and the depression score of the experimental group was (49.99 ± 6.33), compared with the (54.86 ± 4.83) of control group, the difference was statistically significant ( t=3.69, P<0.05). Conclusions:Kaitianmen acupoint massage can relieve limb pain, fatigue, anxiety and depression in patients with rheumatoid arthritis, which is worthy of clinical promotion.

AIM To investigate the effects of Congrong San on neuronal apoptosis and the Bax/Bcl-2/Caspase3 signaling pathway in a rat model of Alzheimer's disease(AD).METHODS A total of 60 2-month-old SD male rats were randomly divided into the blank group,the model group,the memantine hydrochloride group(0.025 g/kg)and low-dose,medium-dose and high-dose Congrong San groups(4.62,9.24,18.48 g/kg).All groups except the control group received stereotactic intracerebral injection of Aβ1-42 to establish AD models.Following the successful modeling,each group received its corresponding intragastric administration once daily for 28 consecutive days.After the administration,the rats had their learning and memory ability detected by the morris water maze test;their hippocampal neuronal morphology observed with HE and Nissl staining;their hippocampal neuronal apoptosis observed with TUNEL staining;and their hippocampal expressions of amyloid precursor protein(APP),β-site APP-cleaving enzyme 1(BACE1),and apoptosis-related proteins Bax,Bcl-2 and Caspase3 detected with Western blot assay.RESULTS Compared with the model group,the groups intervened with medium-dose and high-dose Congrong San exhibited improved learning and memory performance,alleviated hippocampal neuronal damage,increased Nissl body count(P＜0.01),reduced hippocampal apoptosis rate(P＜0.05,P＜0.01),decreased protein expressions of APP,BACE1,Bax and cleaved-Caspase3/Caspase3 ratio(P＜0.05,P＜0.01),and elevated Bcl-2 expression(P＜0.01).CONCLUSION Congrong San mitigates cognitive impairment,hippocampal neuronal damage,and apoptosis in AD rats,probably through inhibition of the Bax/Bcl-2/Caspase3 signaling pathway activation.

Objective:To conduct a study on pricing by service unit to address the problems of hospice and palliative care pricing and fee system in China.Methods:Combining theoretical research and empirical evidence,this study organized the pricing mechanism of initiative hospice and palliative care services and established a graded and categorized pricing strategy.Empirical research was conducted based on real-world data from 36 pilot institutions in typical areas.Results:This study developed a comprehensive pricing framework for value-based classification price standard of initiative hospice and palliative care services from the perspective of incentive regulation.We proposed a pricing plan based on service units,with inpatient bed fee ranging from 459 to 606 yuan or 459 to 1 102 yuan,and home visit fee ranging from 89 to 264 yuan.Conclusions and suggestions:This study proposes a pricing scheme based on the technique and service value with a gradient fluctuation by service unit,and forms a set of price standards with high economic and technical feasibility,which can provide scientific evidences for solving the pricing problem of hospice care.In addition,there is still a need to establish a multi-level incentive compensation mechanism to motivate all levels and types of organisations and healthcare provider,and to promote the high-quality and sustainable development of hospice and palliative care.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective:To explore the application effect of Kaitianmen point massage on pain, faligue, anxiety and depression in patients with rheumatoid arthritis.Methods:This study was a randomized controlled study, a total of 80 patients with rheumatoid arthritis who were admitted to Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine from May to November 2023 were selected as the research objects. The control group was given routine treatment and nursing, and the experimental group was given Kaitianmen acupoint massage on the basis of routine treatment and nursing. The differences in pain score, fatigue score, anxiety and depression score before and after intervention were compared between the two groups.Results:In the final, there were 37 cases in the experimental group and 36 cases in the control group completed the study. Before intervention, there was no statistically significant difference in pain scores, fatigue scores, anxiety and depression scores between the two groups (all P>0.05). After four weeks of intervention, the pain score of the experimental group was (2.06 ± 0.35), and that of the control group was (3.72 ± 0.59), the difference was statistically significant ( t=14.57, P<0.05). After four weeks of intervention, the fatigue score of the experimental group was (20.11 ± 8.03), and that of the control group was (25.02 ± 8.32), the difference was statistically significant ( t=2.55, P<0.05). After four weeks of intervention, the anxiety score of the experimental group was (48.33 ± 6.13), which was significantly different from (53.99 ± 4.91) of the control group ( t=4.35, P<0.05), and the depression score of the experimental group was (49.99 ± 6.33), compared with the (54.86 ± 4.83) of control group, the difference was statistically significant ( t=3.69, P<0.05). Conclusions:Kaitianmen acupoint massage can relieve limb pain, fatigue, anxiety and depression in patients with rheumatoid arthritis, which is worthy of clinical promotion.