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.

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: 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*

Objective To analyze the correlation between right atrial strain at various stages and various influencing factors in patients with pulmonary hypertension,and to explore the role of right atrial strain in the assessment of pulmonary hypertension.Methods A total of 239 cases diagnosed with pulmonary hypertension who underwent echocardiography and complete right heart catheterization at hospital from October 2021 to December 2023 were included.Conventional ultrasound parameters such as right heart strain,right atrial area(RA area),inferior vena cava diameter(IVC diameter),and collapse rate of the inferior vena cava(IVC diameter changes)were measured.The heart rate(HR)corresponding to the ultrasound images were recorded.General information such as age and gender,as well as catheter data including mean right atrial pressure(mRAP),mean pulmonary artery pressure(mPAP),and pulmonary vascular resistance(PVR),were collected.The relationship between right atrial strain and its influencing factors was analyzed,and further analysis was conducted by dividing into shunt group and non-shunt group based on the presence or absence of left-to-right shunt disease.Results The correlation with RA reservoir strain(RASr)from high to low is RV global strain(RV4CSL),RV free wall strain(RVFWSL),RA area,IVC diameter,mRAP,age,HR,and PVR;the correlation with RAconduit strain(RAScd)from high to low is RV4CSL,RVFWSL,RA area,IVC diameter,mRAP,age,PVR,and HR;the correlation with RA contraction strain(RASct)from high to low is RA area,RV4CSL,RVFWSL,mRAP,IVC diameter,and HR.The collapse rate of the inferior vena cava is correlated with strain at various stages of the right atrium;gender is correlated with RASr and RASct.Conclusions Right atrial strain can reflect changes in right atrial function,with the highest correlation to right ventricular strain and right atrial area.Right atrial strain can indicate the severity of right ventricular function and right atrial remodeling,serving as an evaluative index for the condition and treatment outcomes of pulmonary arterial hypertension.

Objective Five chloroplast(cp)genomes from members of genus Polygonatum were assembled by hybrid assembly technique,and their intraspecic and interspecific differences were analyzed by comparative genomic method.Codon usage patterns and influencing factors were determined,and the cp genome data were applied to understand the phylogenomic relationships in the entire genus Polygonatum along with the available data.Methods In this study,the chloroplast genomes of 5 species of genus Polygonatum were assembled using Unicycler software.Sequence alignment,collinearity analysis,boundary analysis and other methods were used to evaluate the interspecific differences of these five species.Nucleotide polymorphism analysis was used to discover the high-variation sites of the five species and their related species,predict the distribution of different long repeat sequences and SSRs,and then analyze the use bias of Polygonatum code.Finally,phylogenetic tree was constructed with the coding sequences of other 47 genus Polygonatum and their closely related species to explore their phylogenetic relationships in this study.Results ①Chloroplast genomes of 155 408-155 623 bp were assembled from five species of Polygonatum.A total of 132-133 genes were annotated,and 369 long repeats and 1553 simple repeats were detected.②The contraction and expansion of chloroplast genomes in 8 species were not obvious at the IRs boundary,and the size and distribution of individual genes at the LSC-IRs-SSC boundary,such as ndhF gene and ycf1 gene,were slightly different.No interspecific or intraspecific rearrangement was observed in 8 species.③ The high-variation regions of the 8 chloroplast genomes are mainly located in two single-copy regions,the duplicate copy region is relatively conserved,and the coding region is more conserved than the non-coding region.High nucleotide polymorphic loci rps16-trnQ,trnS-trnG,trnTUGU-trnL,ndhF-rpl32 and rpl32-trnL are located in the single copy region and most of them are gene spacer regions.④ The codon preference results showed that the codon preference of the five species was similar and mainly affected by selection pressure,and the third base of the codon played A dominant role and mainly ended in A/U.RSCU clustering heat map shows that PK and PZ,PCB and PS have close relationship.⑤ Phylogenetic trees divided 52 species into five branches:Ⅰ,Ⅱ,Ⅲ,ⅣandⅤ.PS,PK,PCB,PCZ and PZ were divided into ⅣandⅤbranches,among which PK and PZ were most closely related,while PCZ was more distant than the other four,was divided into the Ⅴbranch alone.Conclusion This study provided a reference for the phylogenetic research and molecular marker development of the medicinal plants of the Polygonum genus.

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 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.