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.

Definitive treatment of lung cancer with radiotherapy is challenging, as respiratory motion and anatomical changes can increase the risk of severe off-target effects during radiotherapy. Online adaptive radiotherapy (ART) is an evolving approach that enables timely modification of a treatment plan during the interfraction of radiotherapy, in response to physiologic or anatomic variations, aiming to improve the dose distribution for precise targeting and delivery in lung cancer patients. The effectiveness of online ART depends on the seamless integration of multiple components: sufficient quality of linear accelerator-integrated imaging guidance, deformable image registration, automatic recontouring, and efficient quality assurance and workflow. This review summarizes the present status of online ART for lung cancer, including key technologies, as well as the challenges and areas of active research in this field.
Humans ; Lung Neoplasms/radiotherapy* ; Radiotherapy Planning, Computer-Assisted/methods*

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 growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

OBJECTIVE To evaluate the efficacy and mechanism of Kai-Xin-San in improving intestinal function damage in-duced by intragastric administration of fluoxetine in chronic unpredictable mild stress(CUMS)depression model mice.METHODS A CUMS depression mouse model was established and treated with fluoxetine(9 mg·kg-1·d-1),low-dose(1.5 g·kg-1·d-1)and high-dose(4.5 g·kg-1·d-1)Kai-Xin-San,fluoxetine combined with low-dose(9 mg·kg-1·d-1+1.5 g·kg-1·d-1)and high-dose(9 mg·kg-1·d-1+4.5 g·kg-1·d-1)Kai-Xin-San,and mosapride combined with fluoxetine(2 mg·kg-1·d-1+9 mg·kg-1·d-1)for 28 consecutive days.The body weight of mice was measured;the food utilization was calculated and the serum D-xylose content was measured to evaluate the intestinal mucosal absorption capacity of mice;HE staining was used to evaluate the intestinal structural dam-age of mice;TUNEL staining was used to evaluate the intestinal tissue apoptosis of mice;ELISA was used to detect the expression lev-els of brain gut peptides such as vasoactive intestinal peptide(VIP),gastrin(MTL),substance P(SP)and Ghrelin in the intestine of mice;Western blot was used to detect the expression of apoptosis signaling pathway proteins.RESULTS Compared with the model group,fluoxetine significantly reduced the body weight of mice after 2 weeks of administration(P<0.05);the food utilization and ser-um D-xylose content of mice were significantly reduced after 4 weeks of administration(P<0.05),and the intestinal villi of depressed mice were damaged(P<0.05)and intestinal epithelial apoptosis of mice was enhanced(P<0.01);the expression of VIP in the small intestine of mice was upregulated(P<0.05),and the expression of MTL,SP and Ghrelin was downregulated(P<0.05,P<0.01);cleaved Caspase-3/Caspase-3 and cleaved Caspase-9/Caspase-9 in the intestinal apoptosis signaling pathway of mice were upregulat-ed(P<0.05,P<0.01).Compared with the fluoxetine group,the body weight of mice was significantly increased after 2 weeks of com-bined use of Kai-Xin-San and fluoxetine(P<0.05,P<0.01).After 4 weeks of combined use of high-dose Kai-Xin-San and fluoxe-tine,the food utilization and serum D-xylose expression of mice were significantly increased(P<0.05);intestinal villus damage was improved(P<0.05);intestinal epithelial tissue apoptosis was significantly reduced(P<0.01);small intestinal VIP expression was significantly downregulated(P<0.01),and the expression of MTL,SP and Ghrelin was significantly upregulated(P<0.05);cleaved Caspase-3/Caspase-3 and cleaved Caspase-9/Caspase-9 in the apoptosis signaling pathway were significantly reduced(P<0.05,P<0.01).CONCLUSION Kai-Xin-San has the effect of improving the gastrointestinal motility and intestinal absorption function dam-age caused by fluoxetine in depressed mice.Its mechanism may be related to improving the expression of brain gut peptide in the small intestine and inhibiting intestinal villi damage and intestinal tissue apoptosis.

Objective To evaluate the effect of Kaixin San(KXS)combined with fluoxetine on hippocampal neural stem cells in mice with chronic stress stress and depression.Methods A mouse model of depression was constructed using the method of chronic unpredictable stress stress,and the highest dose of KXS water extract and fluoxetine for clinical application was given for 28 days,and behavioral tests were carried out.Nissl staining was used to detect the pathological status of hippocampal tissues in mice.The expression of TUNEL and Nestin in mouse hippocampus was determined by immunofluorescence.Western blotting was used to detect the expressions of apoptotic proteins cleaved caspase-3 and caspase-3,pyroptosis proteins GSDMD and cleaved caspase-1,as well as the expression of neural stem cell marker Nestin in the hippocampus,and the expression of Wnt/β-catenin signaling pathway-related proteins in the hippocampus.Results The combination of KXS extract and fluoxetine can significantly improve the depression-like behavior of model mice,and the effect is better than fluoxetine alone.The combination inhibited the activation of apoptosis and pyroptosis signaling pathways in the hippocampus when used alone with high-dose fluoxetine,significantly upregulated the expression of Nestin,and regulated the expression of Wnt/β-catenin signaling pathway protein.Conclusion The combination of KXS and high-dose fluoxetine can improve apoptosis and pyroptosis in the hippocampus of stress stress and depression model mice,and upregulate the expression of neural stem cell marker Nestin by regulating the Wnt/β-catenin signaling pathway,which may be a key link to improve the antidepressant effect of the combination drug.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

Depression is a highly heterogeneous psychiatric disorder with complex pathogenesis influenced by the interplay of biological,psychological,and social-environmental factors.Based on the 2021 edition of the Chinese Guidelines for the Prevention and Treatment of Depressive Disorders,which explicitly identify gender as a significant risk factor for depression onset,this paper systematically reviews the gender-differentiated pathogenesis and therapeutic advances in depression from both traditional Chinese medicine(TCM)and Western medical perspectives.In Western medicine,a large number of studies have demonstrated the sex-specific mechanism of estrogen/testosterone fluctuations and monoamine transmitter system regulation.While in TCM,although the constitution theory proposes that there are significant gender differences in congenital constitution and that qi depression and qi deficiency are associated with susceptibility to depression,current evidence primarily relies on cross-sectional surveys and lacks validation through high-quality RCTs.Compared with Western medicine,the direct research on gender-differentiated antidepressant effects in TCM remains relatively underdeveloped.In future study,it may be possible to deepen and improve the research on anti-depression in TCM from the biological markers of particular constitutions in the gender dimension.This paper advocates establishing a bio-psycho-social integrated intervention model,advancing mechanistic exploration through prospective cohort studies and multi-omics technologies,and promoting precision diagnosis and treatment systems based on gender differences,and to form a three-dimensional diagnosis and treatment and research system that covers biomarkers,social role assessment,and TCM constitution identification,in order to provide a new theoretical framework and a practical pathway for the precise medical treatment of depression.