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 explore the chain mediating effect of coping style and illness perception between intolerance of uncertainty and fear of disease progression in patients with intracranial aneurysm.Methods:A total of 270 patients with intracranial aneurysms admitted to the neurosurgery department of 2 hospitals in Guangzhou from October 2023 to June 2024 were selected by convenience sampling method. The general information questionnaire, intolerance of uncertainty scale-12, the brief disease perception questionnaire, medical coping mode questionnaire(MCMQ) and fear of progression questionnaire-short form were used to investigate the subjects. Statistical description and Spearman correlation analysis were performed using IBM SPSS 25.0 software, and AMOS 23.0 software was used to test and correct the structural equation models.Results:The total score of fear of disease progression in patients with intracranial aneurysms was 27.50(20.00, 34.00). The total score of intolerance of uncertainty was 23.50(19.75, 29.00). The sores of confrontation, avoidance and submission in MCMQ were 18.69±5.44, 12.00(10.00, 15.00) and 7.00(5.00, 9.00), respectively.The total score of illness perception was 37.23±11.60. Fear of disease progression was positively correlated with intolerance of uncertainty, submission and illness perception ( r=0.614, 0.696, 0.680, all P<0.01). The direct effect of intolerance of uncertainty on fear of disease progression was significant in patients with intracranial aneurysms ( β=0.431, P<0.001). Intolerance of uncertainty indirectly affected fear of disease progression through submission ( β=0.181, P<0.001) and illness perception ( β=0.092, P<0.001). Submission and illness perception played chain-mediating effect in the relationship between intolerance of uncertainty and fear of disease progression ( β=0.103, P<0.001). Conclusion:The intolerance of uncertainty in patients with intracranial aneurysms can positively predict the fear of disease progression. Submission and illness perception played a chain mediating role between intolerance of uncertainty and fear of disease progression in patients with intracranial aneurysms.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

OBJECTIVE To explore the optimal parameters of simmered Rhei Radix et Rhizoma and the correlation between the chroma values and the intrinsic composition of simmered Rhei Radix et Rhizoma decoction pieces powder.METHODS The single-factor-response surface method was used to investigate the simmering temperature,simmering time,paper dosage and plant ash dos-age,the response surface experiment was carried out on the basis of the single factor experiment,the appearance traits,total anthraqui-nones,free anthraquinones,leachables,sennoside A and B contents were taken as indicators,the analytic hierarchy process(AHP)was used to give weights to each index,and the process was optimized.The chroma values of raw and simmered products were deter-mined by electronic eye,the correlation and regression analysis were carried out by SPSS22.0 software,and the chroma-component re-gression equation was constructed.RESULTS The optimal process of simmering Rhei Radix et Rhizoma was 140 ℃,5 times of plant ash,2 layers of wet paper wrapped and being simmered for 2.5 h.CONCLUSION The simmering process of Rhei Radix et Rhizoma optimized by AHP combined with response surface method is reasonable and feasible,the color of decoction pieces has a significant correlation with the component content,and the regression equation constructed is reliable,which can predict the intrinsic component content of decoction pieces through chroma values.

The application of sensors to the monitoring of spinal morphology and motion was reviewed in terms of the research object and monitoring index.The present situation of the application of sensors was introduced,such as inertial sensor,stretchable strain sensor and electromagnetic sensor.The deficiencies of sensors applied to the monitoring of spinal morphology and motion were analyzed,and the future directions of the application were pointed out.[Chinese Medical Equipment Journal,2025,46(6):105-110]

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective:To explore the chain mediating effect of coping style and illness perception between intolerance of uncertainty and fear of disease progression in patients with intracranial aneurysm.Methods:A total of 270 patients with intracranial aneurysms admitted to the neurosurgery department of 2 hospitals in Guangzhou from October 2023 to June 2024 were selected by convenience sampling method. The general information questionnaire, intolerance of uncertainty scale-12, the brief disease perception questionnaire, medical coping mode questionnaire(MCMQ) and fear of progression questionnaire-short form were used to investigate the subjects. Statistical description and Spearman correlation analysis were performed using IBM SPSS 25.0 software, and AMOS 23.0 software was used to test and correct the structural equation models.Results:The total score of fear of disease progression in patients with intracranial aneurysms was 27.50(20.00, 34.00). The total score of intolerance of uncertainty was 23.50(19.75, 29.00). The sores of confrontation, avoidance and submission in MCMQ were 18.69±5.44, 12.00(10.00, 15.00) and 7.00(5.00, 9.00), respectively.The total score of illness perception was 37.23±11.60. Fear of disease progression was positively correlated with intolerance of uncertainty, submission and illness perception ( r=0.614, 0.696, 0.680, all P<0.01). The direct effect of intolerance of uncertainty on fear of disease progression was significant in patients with intracranial aneurysms ( β=0.431, P<0.001). Intolerance of uncertainty indirectly affected fear of disease progression through submission ( β=0.181, P<0.001) and illness perception ( β=0.092, P<0.001). Submission and illness perception played chain-mediating effect in the relationship between intolerance of uncertainty and fear of disease progression ( β=0.103, P<0.001). Conclusion:The intolerance of uncertainty in patients with intracranial aneurysms can positively predict the fear of disease progression. Submission and illness perception played a chain mediating role between intolerance of uncertainty and fear of disease progression in patients with intracranial aneurysms.