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 clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

Objective To evaluate the influence of the wearing position of dosimeters outside lead aprons on effective dose estimation for interventional radiology workers, analyze the differences between single and double dosimeter methods in effective dose estimation, and provide a reference for the personal dose monitoring of interventional radiology workers. Methods This study employed a combined approach of on-site monitoring and Monte Carlo simulation to evaluate the impact of the wearing position of dosimeters outside lead aprons on effective dose estimation, as well as the differences between effective doses measured using single and double dosimeters. Interventional radiology workers wore dosimeters at three positions: the neck outside the lead collar, the left chest outside the lead apron, and inside the lead apron. Effective doses were estimated using the single and double dosimeter methods specified in GBZ 128-2019 Specifications for individual monitoring of occupational external exposure, and the impact of different wearing positions on the estimation results was compared. Geant4 Monte Carlo simulations were used to model dose distributions at the neck outside the lead collar and at the left chest outside the lead apron for operators performing cardiovascular interventions under tube voltages of 70, 80, 90, and 100 kVp and exposure angles of posteroanterior (PA), anteroposterior (AP), and left anterior oblique 45° (LAO45°) positions. The study assessed the impact of dosimeter wearing position on effective dose estimation. Results Monte Carlo simulations demonstrated that neck doses consistently exceeded left chest doses across different tube voltages and exposure angles, with neck-to-chest dose ratios of 0.80-0.90. Under identical tube voltage conditions, AP showed the highest doses, followed by LAO45°, and PA demonstrated the lowest doses. The single and double dosimeter methods exhibited consistent patterns in effective dose estimation. Single dosimeter method generally yielded higher effective doses with relative deviations of 9.9% to 83%, though these deviations decreased under high tube voltages. Field monitoring data indicated that most interventional radiology workers maintained relative deviations between single and double dosimeter calculations below 6%, with neck-to-chest dose ratios of 0.95-1.1. The estimation patterns remained consistent across both methods, though single dosimeter method showed slightly higher results. Conclusion Under PA, AP, or LAO45°, the doses at the neck consistently exceeded those at the left chest. Therefore, when wearing lead protective equipment, the dosimeter should be properly positioned at the neck outside the lead collar to accurately reflect the radiation doses of surgeons. Some interventional radiology workers improperly positioned the dosimeter (intended at the neck outside the lead collar) at the left chest outside the lead apron, and this may result in an underestimation of the effective dose.

AIM To study the chemical constituents from Fomes officinalis(Vill.ex Fr.)Ames and their anti-inflammatory activities.METHODS The 95％ethanol extract from F.officinalis was isolated and purified by silica gel,Sephadex LH-20,HW-40C,MCI and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities in vitro were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as asperginine A(1),laricinolic acid(2),methoxylaricinolic acid(3),fomeffic acid(4),19-acetoxy-13S-hydroxylabda-8(17),14-diene(5),bisbenzopyran(6),lariciresinol acetate(7),fomitopsin G(8),fomitopsin H(9),demalonyl fomitopsin H(10),fomlactone A(11),fomlactone B(12),fomefficinol A(13),fomefficinol B(14),laetiporins A(15),laetiporins B(16),dehydrosulphurenic acid(17),dehydroeburicoic acid(18),3-keto-dehydrosulfurenic acid(19),eburicoic acid(20).The IC50 values of compounds 7,13,20 were(4.00±1.02),(3.29±0.62),(3.22±0.94)μmol/L,respectively.CONCLUSION Compound 1 is a new compound,3,6,15,16 are isolated from this plant for the first time.Compounds 7,13,20 have strong anti-inflammatory activities.

Objective To evaluate the value of left ventricular(LV)systolic function impairment in patients with different activity levels of systemic lupus erythematosus(SLE)by applying automatic myocardial motion quantification(aCMQ)technique,and to explore the correlation between left ventricular strain parameters and clinical laboratory indexes,systemic lupus erythematosus disease activity index(SLEDAI).Methods A total of 80 patients diagnosed with SLE from November 2023 to August 2024 in the First Afticiated Hospital of Jinzhou Medical University were selected and divided into two groups:40 cases with SLEDAI＜10points were in mild lupus group,34 cases with SLEDAI ≥ 10points were in moderately severe lupus group.Forty healthy volunteers for physical examination at the same time were randomly selected as control group,relevant parameters were obtained by conventional echocardiography and aCMQ technique respectively.Results aCMQ technique related parameters were compared,and the differences in left ventricular global longitudinal strain(LVGLS),apical two-chamber longitudinal strain(AP2LS),apical three-chamber longitudinal strain(AP3LS),and apical four-chamber longitudinal strain(AP4LS)were statistically significant in all three groups(P＜0.05).The differences in left ventricular global circumferential strain(LVGCS)in lupus moderate-severe group were statistically significant when compared with other two groups(P＜0.05),Pearson correlation analysis showed LVGLS,AP2LS,AP3LS,AP4LS and LVGCS were positively correlated with complement 3 and complement 4,and negatively correlated with anticardiolipin antibody(ACA)IgA,IgG,IgM,and sedimentation,and ultrasensitive C-reactive protein,and the SLEDAI was correlated with LVGLS,AP2LS,AP3LS,AP4LS were negatively correlated,and there was no significant correlation with LVGCS.Conclusion aCMQ technique can detect changes in LV systolic function in SLE patients at an early stage,and the impairment of LV systolic function is more severe with higher disease activity.Better correlation between LV strain parameters and clinical laboratory indexes and SLED AI may help to better assess cardiac involvement in SLE patients.

Objective:To compare the efficacy and safety of Rotarex mechanical thrombectomy (Rotarex) combined with drug-coated balloon (DCB) versus percutaneous transluminal angioplasty (PTA) combined with DCB in the treatment of femoropopliteal artery in-stent restenosis (ISR).Methods:A multicenter, prospective, randomized controlled trial was conducted. 46 patients with femoropopliteal artery ISR admitted to five hospitals (Beijing Friendship Hospital, Capital Medical University; Beijing Chaoyang Hospital, Capital Medical University; Beijing Jishuitan Hospital, Capital Medical University; Xuanwu Hospital, Capital Medical University; Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University) from July 2020 to June 2024 were enrolled. Patients were randomly divided into the Rotarex+ DCB group ( n=24) and the PTA+ DCB group ( n=22) using a random number table. The clinical data of the two groups were collected, including clinical characteristics, Fontaine classification, stent placement location, stent duration, and lesion length. The primary endpoint was the target blood vessel patency rate at 6 and 12 months postoperatively; the secondary endpoints included improvement in clinical symptoms (Fontaine classification), rate of reintervention, and safety indicators. Measurement data were expressed as mean±standard deviation ( ± s), and the t-test was used for comparison between groups; count data were expressed as the number of cases and percentages, and intergroup comparisons were performed using the Chi-test or Fisher exact probability method. Results:At 12 months postoperatively, the target blood vessel patency rate in the Rotarex+ DCB group was significantly higher than that in the PTA+ DCB group (81.8% vs 45.5%, P=0.012), and the proportion of patients in Fontaine classification stage I was also higher (86.4% vs 45.5%, P=0.004). The results at the 6-month follow-up were consistent (target blood vessel patency rate: 87.0% vs 59.1%, P=0.035). In terms of safety, no severe complications such as arterial rupture, amputation, or procedure-related death occurred during the perioperative period in either group. During the postoperative follow-up, no amputation or procedure-related deaths occurred in either group. Conclusion:For the treatment of femoropopliteal artery ISR, Rotarex mechanical thrombectomy combined with DCB is significantly superior to PTA+ DCB in terms of 12-month target blood vessel patency rate and improvement of clinical symptoms, with comparable safety.

Traditional mass measurement methods are not applicable in microgravity environments,and the main challenge for in-orbit body mass measurement technology based on inertial principles is to address the random errors brought about by the weightless environment.These include additional torques due to shifts in the center of mass,nonlinear accelerations due to non-rigid human bodies,mechanical energy consumption due to organ vibrations,and random vibrations of the measurement device itself.To address the above difficulties,the project proposes a technical scheme based on the principle of linear acceleration,designs and constructs a ground-specific air-floating experimental and simulation platform,studies key data such as motion trajectory,acceleration change,and vibration frequency amplitude during the mass measurement process,and simulates the changes in the center of mass and random vibrations of the human body in a weightless environment.The project has designed an adjustable posture bracket to adapt to changes in the center of mass,enhance body restraint,and greatly reduce shaking;it has also developed an integrated four-bar linkage motion guidance mechanism,high-precision integrated photoelectric distance measurement,and modular motion constant force measurement device to ensure the accurate measurement of acceleration and constant force data.The product has undergone simulation calculations,ground human applicability tests,and in-orbit applicability verification in the space station.Ground test results show that the device achieves a body mass measurement accuracy better than 0.5%,and the dispersion is better than 0.38%;after flight mission verification and evaluation,the in-orbit body mass measurement dispersion is less than 0.4%,which is superior to the SLAMMD,a mass measurement device of the same principle on the International Space Station,and is at the forefront internationally,achieving accurate body mass measurement.

As a comprehensive high technology,robotics has gained extensive attention from numerous researchers.Intelligent soft robots,representing a new direction in robotics research,are shining brightly in fields such as fragile objects manipulating,medical assistance,and environment exploration due to their unique advantages.In the field of specialized medicine,intelligent soft robots can adapt to the complex and extreme space working environment due to their small stiffness,strong variability and high flexibility,and have broad application prospects in specialized medicine like aerospace,navigation and diving.In this paper,the research status of intelligent soft robots is reviewed from four aspects:materials,structure,actuation modalities,modeling and simulation.Furthermore,the application of intelligent soft robots in the field of specialized medicine is summarized and prospected in this paper.

Paclitaxel， a highly effective natural antitumor drug， has been demonstrated to be efficacious in the treatment of a variety of cancers， including breast cancer， ovarian cancer， and lung cancer. The traditional paclitaxel injections have been observed to present certain issues， including overt adverse reactions and a decline in the quality of life of patients following treatment. This ultimately leads to an inability to meet the comprehensive needs of patients， thereby limiting the clinical applications of the drugs. Compared with injectable administration， the oral administration can avoid the risk of infection present in the invasive route， is conducive to improving patient compliance and quality of life， and reduces healthcare costs， and has a good application prospect. However， paclitaxel has low solubility， poor permeability， and is susceptible to the exocytosis of P-glycoprotein， which presents a significant challenge in the development of its oral preparations. Novel drug delivery technologies can enhance the solubility of paclitaxel and facilitate its controlled release， which is beneficial for the oral absorption and efficacy. The paper reviews the development history of oral preparations of paclitaxel， and summarizes the delivery technologies such as polymer micelles， nanoparticles， nanoemulsions and nanocrystals， and discusses the application mechanisms， advantages and limitations of these technologies and their adaptability in different cancer treatments. Finally， the challenges faced in the development of oral preparations of paclitaxel are summarized， and future research directions are proposed in order to provide new ideas for the development of oral delivery of paclitaxel.