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.

Drug toxicity is closely related to both clinical drug safety and new drug development. Therefore, it is vital to understand the mechanisms of drug toxicity fully and to use appropriate research models with advanced technologies. Zebrafish has become an important vertebrate animal model for high-throughput drug screening and toxicity assessment. At the same time, zebrafish has an intact biological complexity, reflecting the whole organism's toxicity, which gives it an advantage over other high-throughput models in toxicity studies. Despite the gradual increase in toxicity studies utilizing zebrafish, a comprehensive and systematic review of the underlying mechanisms and new techniques is still lacking. This review aims to analyze common toxicity mechanisms in zebrafish models, such as oxidative stress, endoplasmic reticulum stress, inflammation, and apoptosis, and macroscopic changes in biological processes like lipid metabolism disorders and neurotransmitter expression abnormalities. It also introduces new technologies applied in toxicity assessment, such as gene editing, novel fluorescence imaging technology, 3D imaging technology, and novel automated technology for high-throughput screening, such as fish capsules. In addition, it also summarizes the advantages and disadvantages of the model. By doing so, it will provide new suggestions for the development and improvement of the model, make it better serve the toxicity study of clinical drugs and provide a more comprehensive perspective for drug toxicity study, thus promoting the development of the field of drug toxicity study.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

Objective:To construct a Harvard cancer index-based risk predictive model for perioperative venous thromboembolism (VTE) in elderly patients with femoral neck fracture and assess its predictive effectiveness.Methods:A retrospective cohort study was conducted to analyze the clinical data of 610 elderly patients with femoral neck fracture admitted to Peking Union Medical College Hospital between January 2013 and December 2022, including 193 males and 417 females, aged 60-99 years [(77.3±9.0)years]. The patients were divided into VTE group ( n=125) and non-VTE group ( n=485) according to occurrence of VTE during the perioperative period. The two groups were compared in terms of gender, age, body mass index, smoking status, alcohol consumption, time from fracture to admission, surgical waiting time, comorbidities, perioperative electrolyte disorders, past or present history of malignancy, past history of deep vein thrombosis (DVT) or pulmonary embolism (PE), and preoperative use of oral anticoagulants. Univariate analysis and multivariable stepwise Logistic regression analysis were conducted to evaluate and identify independent risk factors for perioperative VTE in elderly patients with femoral neck fracture. A perioperative VTE risk predictive model for elderly patients with femoral neck fracture was constructed using the Harvard cancer index: (1) assigning a risk score to each variable according to the corresponding conversion criteria of the Harvard cancer index and risk score, based on the magnitude of their ORs; (2) determining the exposure rate of each risk factor based on the population distribution observed in this study; (3) calculating the average population risk score; (4) computing the individual VTE risk score; (5) deriving the ratio (X) of each individual ′s VTE risk score to the population average. Based on the Harvard cancer index classification criteria for disease risk levels, individual VTE risk categories were determined. The predictive performance of the risk stratification was evaluated by comparing the incidence of VTE across different risk levels. The predictive performance of the model was evaluated based on sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) test and internal validation was performed using the bootstrap resampling method with 1000 iterations. Results:Univariate analysis showed that gender, age, time from fracture to admission, surgical waiting time, previous cerebral infarction, stroke within the past month, Alzheimer′s disease, primary Parkinson′s syndrome, hysterectomy with bilateral adnexectomy, perioperative electrolyte disorders, history of DVT or PE, and preoperative use of oral anticoagulant drug were moderately associated with the occurrence of VTE in elderly patients with femoral neck fracture ( P<0.10). Multivariable stepwise logistic regression analysis demonstrated that female gender ( OR=2.26, 95% CI 1.34, 3.80, P<0.01), time from fracture to admission>1 day ( OR=3.70, 95% CI 2.24, 6.12, P<0.01), surgical waiting time>70 hours ( OR=2.06, 95% CI 1.29, 3.30, P<0.01), previous cerebral infarction ( OR=3.78, 95% CI 1.04, 13.76, P<0.05), stroke within the past month ( OR=11.57, 95% CI 1.21, 110.44, P<0.05), Alzheimer′s disease ( OR=3.26, 95% CI 1.12, 9.49, P<0.05), primary Parkinson ′s syndrome ( OR=3.47, 95% CI 1.22, 9.85, P<0.05), previous hysterectomy with bilateral adnexectomy ( OR=4.75, 95% CI 2.09, 10.80, P<0.01), perioperative electrolyte disorders ( OR=2.73, 95% CI 1.39, 5.35, P<0.01), and preoperative oral anticoagulant use ( OR=3.86, 95% CI 1.18, 12.67, P<0.05) were significantly associated with the occurrence of perioperative VTE in elderly patients with femoral neck fracture. Based on the above 10 risk factors, a perioperative VTE risk predictive model for elderly patients with femoral neck fracture was constructed with the Harvard cancer index. The formula was as follows: X=[10×(female gender)+25×(time from fracture to admission>1 day)+10×(surgical waiting time>70 hours)+25×(previous cerebral infarction)+50×(stroke within the past month)+25×(Alzheimer′s disease)+25×(primary Parkinson′s disease)+25×(previous hysterectomy with bilateral adnexectomy)+10×(perioperative electrolyte disorders)+25×(preoperative use of oral anticoagulant drug)]/33. Individualized VTE risk was classified into five levels: very low, low, moderate, high, and very high, with corresponding VTE rates of 4.8%, 11.8%, 14.9%, 32.3%, and 73.5%, respectively ( χ2=87.71, P<0.01). The VTE risk predictive model demonstrated an AUC of 0.74 (95% CI 0.69, 0.79, P<0.01), with a sensitivity of 63.2% and specificity of 74.8%. The H-L goodness-of-fit test indicated satisfactory model calibration ( P>0.05). The internal validation with the bootstrap method confirmed that the AUC remained 0.74. Conclusions:Female gender, time from fracture to admission>1 day, surgical waiting time>70 hours, previous cerebral infarction, stroke within the past month, Alzheimer′s disease, primary Parkinson′s syndrome, hysterectomy with bilateral adnexectomy, perioperative electrolyte disorders, and preoperative use of oral anticoagulant drug are independent risk factors for perioperative VTE in elderly patients with femoral neck fracture. Based on these factors, the perioperative VTE risk predictive model constructed using the Harvard cancer index demonstrates good clinical predictive value. Individualized VTE risk stratification can effectively identify high-, intermediate-, and low-risk populations, providing a valuable reference for tailoring anticoagulant prophylaxis strategies and enhancing postoperative surveillance.

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.

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.

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

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.