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.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic metabolic liver disorder with complex etiologies. Different clinical phenotypes of MAFLD （such as obesity， hyperlipidemia， type 2 diabetes mellitus， the postmenopausal state， and chronic hepatitis B） have different mechanisms of action in the development and progression of MAFLD， leading to high heterogeneity in its clinical progression and prognosis. This article systematically reviews the pathogeneses and clinical features of the above five clinical phenotypes of MAFLD and elaborates on the corresponding individualized diagnosis and treatment regimens integrating traditional Chinese medicine and Western medicine， in order to provide a reference for clinical practice and improve clinical diagnosis and treatment.

Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

Objective To explore the impact of lung cancer screening on the changes of health risk behaviors in 420 high-risk populations. Methods Among the 420 high-risk subjects who underwent lung cancer screening in the hospital from January 2022 to February 2024 were included and underwent low-dose computed tomography (LDCT) screening and were followed up for 1 year. Multivariate logistic regression analysis was used to analyze the association between lung cancer screening and changes in health risk behaviors. Results Compared with the baseline situation, the smoking rate, alcohol drinking rate and long-term exposure to asbestos and other carcinogens were lower during 1-year follow-up, and the regular physical examination rate was increased (P<0.05). In this study, health-risk behaviors of 176 subjects changed during 1-year follow-up, and women, subjects who consulted physicians about physical condition, subjects having positive nodules and subjects having previous history of lung disease accounted for higher proportions (P<0.05). Logistic regression analysis suggested that women, consulting physicians about their physical condition, having positive nodules and having previous history of lung disease were more likely to change health risk behaviors (P<0.05). Conclusion Lung cancer screening prompts high-risk individuals (smokers, drinkers, those with long-term exposure to asbestos and other carcinogens, and those without regular physical examination) to change their health risk behaviors. Women, those who actively consult physicians about their physical condition, those with positive nodules and those with previous history of lung disease are more likely to change their unhealthy habits through screening than other individuals.

ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.

The construction of a medical safety system based on the medical core quality and safty systems is the foundation of the hospital. Multi-campus operation coordinated development is key to the high-quality development of public hospitals and the balanced distribution of high-quality medical resources. Building a medical safety system that comfoms to the specialized layout and operation of branch districts is very important the construction of multi-campus hospitals. In January 2023, Xidan Campus of Peking Union Medical College Hospital established a medical safety system that was compatible with its development, based on the construction of the medical core quality and safty system. The system covered four dimensions: early identification, early assessment, early intervention, and fast response. It included high-risk surgical evaluation and filing, early warning of nursing rooms, periodic medical safety rounds, and rapid response teams and cross hospital transportation of critical care rapid response teams. As of June 2024, the hospital had recorded 570 high-risk surgeries with no unplanned secondary surgeries or unplanned readmissions; Reported nursing warnings 68 times, initiated 93 emergency treatments and cross hospital transfers. All emergency patients received early warning assessments and completed graded and classified transfers and management, effectively ensuring patient safety. This practice could provide references for other multi-campus hospitals to promote the construction and development of medical safety systems.

OBJECTIVE To establish the an optimal prediction model for carbapenem-resistant Acinetobacter bau-mannii(CRAB)infection in ICU patients based on machine learning(ML)so as to help clinicians to diagnose and make decisions.METHODS The clinical data were collected from the patients who were hospitalized in ICUs of a three-A hospital from Jan.1,2017 to Dec.31,2024 and were randomly divided into the training set and the test set in a 7∶3 ratio.The characteristic variables were selected by means of LASSO regression analysis in combina-tion with multivariate logistic regression analysis.Five types of M L classification models were integrated,the opti-mal model was analyzed and identified.The performance of the prediction model for CRAB infection in the ICU patients was evaluated with the use of sensitivity,specificity,accuracy,areas under receiver operating characteris-tic curves(AUCs),calibration curves,Hosmer-Lemeshow test and decision curve analysis(DCA).The outputs of the ML models were interpreted by Shapley additive explanations(SHAP)and permutation importance.RESULTS A total of 2 904 patients were enrolled in the study,695(23.93％)of whom had CRAB infection.The AUC of XGBoost model was highest in the training set and the test set,respectively(0.994 and 0.907).The result of Hosmer-Lemeshow test showed that the calibration curves of the XGBoost model indicated that the predicated risk was highly con-sistent with the observed risk(x2=7.323 and 4.609,P=0.513 and 0.764,respectively).The DCA curves showed that the XGBoost model performed best within the whole range of threshold,with the highest net profit.The length of ICU stay,use of tigecycline,central venous catheterization,use of carbapenems and use of ventilator were determined as the major predictive factors by means of SHAP.CONCLUSIONS The XGBoost model is established and interpreted by SHAP.It provides bases for screening of the ICU patients at high risk of CRAB infection.

Objective To analyze relevant literature on the essence of traditional Chinese medicine syndromes using bibliometric methods;To understand the current research status and hotspots in this field;To provide references for relevant research.Methods Research literature about the essence of TCM syndromes was retrieved from CNKI,VIP,Wanfang Data and CBM from 1st Jan.1979 to 30th June 2024.CiteSpace 6.2 software was used to conduct visualization analysis on authors,institutions,keywords,etc.Results A total of 695 articles were included,with an overall upward trend in publication volume followed by stabilization.The authors who published more articles included Luo Ren(13 articles),Zhao Xiaoshan(13 articles),Li Zegeng(12 articles),etc.The institutions with more publications included Shandong University of Traditional Chinese Medicine(35 articles),Beijing University of Chinese Medicine(33 articles),Chengdu University of Traditional Chinese Medicine(26 articles),etc.Institutions were clustered regionally,and cooperation was mostly between TCM universities and their affiliated hospitals,with less cross regional communication.High frequency keywords included kidney yang deficiency syndrome,metabolomics,animal models,TCM syndrome types,coronary heart disease,lung qi deficiency syndrome,spleen qi deficiency syndrome,liver depression and spleen deficiency syndrome,etc;Keyword clustering covered aspects such as biomolecules and metabolism,TCM syndromes,pathology,disease models,and animal research.Conclusion Research in the field of the essence of TCM syndromes is gradually receiving more attention.Exploring the essence of TCM syndromes at the molecular level through techniques such as genomics,transcriptomics,metabolomics and proteomics is a research hotspot and trend in this field.

OBJECTIVE To analyze the reasons for the outbreak of suspected carbapenem-resistant Acinetobacter baumannii(CRAB)infections in the neurosurgical intensive care unit to take comprehensive prevention and con-trol measures to control the spread of infections,and to provide a reference for the control of multidrug-resistant organisms(MDRO)infections in intensive care units.METHODS Epidemiological data were collected from five patients with CRAB infections in the neurosurgical intensive care unit of Gansu Provincial People's Hospital in Mar.2024,and environmental hygiene monitoring and comprehensive infection prevention and control measures were conducted.RESULTS A total of five cases of lower respiratory tract infections occurred,all of which were hospital-acquired infections,and all patients had consistent spatial-temporal distribution.A.baumannii was detec-ted in the sputum cultures of all patients,and all were resistant to carbapenems,aminoglycosides and some β-lac-tam drugs.Before the implementation of comprehensive prevention and control measures,a total of 25 samples from the surfaces and the hands of health workers were collected,with a pass rate of 52.00％;CRAB was detected on the surface of treatment carts and the wall of sputum suction bottles in the treatment room,with a detection rate of 8.00％.After the implementation,a total of 24 samples were collected,with a pass rate of 100.00％,and the difference was statistically significant when compared with the pre-implementation period(χ2=16.987,P<0.001).Through the implementation of comprehensive measures such as isolation,standardization of the ward cleaning and disinfection process,strengthening hand hygiene,standardization of sterile operations and personnel management,the indicators such as hand hygiene compliance rate,the execution rate of multi-drug-resistant bac-terial preventive and control measures and the fluorescent marker removal rate were all improved,and the suspec-ted CRAB infection outbreak was timely controlled.CONCLUSION This suspected CRAB hospital-acquired infec-tion outbreak may be related to a variety of factors,and timely environmental hygiene monitoring and comprehen-sive infection prevention and control measures can effectively control the spread of CRAB infection.