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 clinical characteristics, diagnosis and treatment strategies, and prognosis of pulmonary embolism (PE) complicating childhood rheumatic diseases.Methods:A retrospective case series study was performed on the demographic data, laboratory indicators, imaging features, treatment regimens, and follow-up data of 8 children with rheumatic diseases complicated by PE who were admitted to the Department of Rheumatology and Immunology, Capital Center for Children′s Health, Capital Medical University from January 2014 to October 2023.Results:Among the 8 children, there were 4 boys and 4 girls, with an age of 12.0 (7.5, 13.0) years. Among the primary diseases, there were 3 cases of systemic lupus erythematosus, 2 cases of Beh?et′s disease, 2 cases of Takayasu arteritis, and 1 case of antiphospholipid syndrome. All children developed PE during the active phase of the primary disease. PE was detected at the onset of the primary disease in 3 cases, and the median time from the diagnosis of the primary disease to the development of PE was 10.0 (6.0, 25.0) months in the remaining 5 cases. Fever was present in all 8 children, 4 cases were accompanied by chest tightness, dyspnea, etc., and 2 cases only presented with fever. Laboratory examinations revealed the following results: erythrocyte sedimentation rate was 42.0 (17.0, 78.0) mm/1 h, high-sensitivity C-reactive protein was 12.7 (2.6, 78.7) mg/L, white blood cell count was 9.6 (7.2, 18.7)×10 9/L; D-dimer was 2.3 (0.9, 6.2) mg/L; and hemoglobin was (109±16) g/L.Imaging examinations revealed that 5 cases had involvement of the bilateral lower pulmonary arteries, 5 cases had peripheral embolism, and 3 cases had central PE. Complications included 3 cases of deep vein thrombosis, 2 cases of intracranial venous sinus thrombosis, and 1 case of mild pulmonary hypertension.In terms of treatment, 7 cases received anticoagulation with heparin followed by warfarin. Immunomodulation was mainly based on glucocorticoids combined with immunosuppressants, and 4 cases were combined with biological agents. The follow-up time of 4.17 (1.75, 7.17) years, the time for complete absorption of PE was 10.5 (6.0, 18.0) months; all 8 children had no target events, with no recurrence or chronic thromboembolic pulmonary hypertension, and the pulmonary artery remodeling was good. Conclusions:PE complicating childhood rheumatic diseases is closely related to the activity of the primary disease. The clinical manifestations are insidious, with fever as the main symptom. Imaging examination is the key to diagnosis.Early adoption of heparin followed by warfarin anticoagulation and glucocorticoids combined with immunosuppressants and (or) biological agents to control the primary disease can achieve a favorable prognosis.

Objective:To explore the clinical characteristics, diagnosis and treatment strategies, and prognosis of pulmonary embolism (PE) complicating childhood rheumatic diseases.Methods:A retrospective case series study was performed on the demographic data, laboratory indicators, imaging features, treatment regimens, and follow-up data of 8 children with rheumatic diseases complicated by PE who were admitted to the Department of Rheumatology and Immunology, Capital Center for Children′s Health, Capital Medical University from January 2014 to October 2023.Results:Among the 8 children, there were 4 boys and 4 girls, with an age of 12.0 (7.5, 13.0) years. Among the primary diseases, there were 3 cases of systemic lupus erythematosus, 2 cases of Beh?et′s disease, 2 cases of Takayasu arteritis, and 1 case of antiphospholipid syndrome. All children developed PE during the active phase of the primary disease. PE was detected at the onset of the primary disease in 3 cases, and the median time from the diagnosis of the primary disease to the development of PE was 10.0 (6.0, 25.0) months in the remaining 5 cases. Fever was present in all 8 children, 4 cases were accompanied by chest tightness, dyspnea, etc., and 2 cases only presented with fever. Laboratory examinations revealed the following results: erythrocyte sedimentation rate was 42.0 (17.0, 78.0) mm/1 h, high-sensitivity C-reactive protein was 12.7 (2.6, 78.7) mg/L, white blood cell count was 9.6 (7.2, 18.7)×10 9/L; D-dimer was 2.3 (0.9, 6.2) mg/L; and hemoglobin was (109±16) g/L.Imaging examinations revealed that 5 cases had involvement of the bilateral lower pulmonary arteries, 5 cases had peripheral embolism, and 3 cases had central PE. Complications included 3 cases of deep vein thrombosis, 2 cases of intracranial venous sinus thrombosis, and 1 case of mild pulmonary hypertension.In terms of treatment, 7 cases received anticoagulation with heparin followed by warfarin. Immunomodulation was mainly based on glucocorticoids combined with immunosuppressants, and 4 cases were combined with biological agents. The follow-up time of 4.17 (1.75, 7.17) years, the time for complete absorption of PE was 10.5 (6.0, 18.0) months; all 8 children had no target events, with no recurrence or chronic thromboembolic pulmonary hypertension, and the pulmonary artery remodeling was good. Conclusions:PE complicating childhood rheumatic diseases is closely related to the activity of the primary disease. The clinical manifestations are insidious, with fever as the main symptom. Imaging examination is the key to diagnosis.Early adoption of heparin followed by warfarin anticoagulation and glucocorticoids combined with immunosuppressants and (or) biological agents to control the primary disease can achieve a favorable prognosis.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

Objective To investigate the association of endometrial thickness(EMT)with obstetric and neonatal outcomes of monoparous pregnancy in fresh cleavage embryos transfer.Methods A total of 1 845 patients of monoparous pregnancy after fresh cleavage embryos transfer cycles from Jan 2016 to Mar 2022 at Shanghai First Maternity and Infant Hospital,Tongji Universtiy were analyzed retrospectively.Patients were categorized into three groups by EMT on transferation day:≤8 mm(group A),8-14 mm(group B)and≥14 mm(group C).The primary outcomes were preterm birth(PTB),birth weight and birth weight z-score,small-for-gestation age,large-for-gestation age,very low birth weight,low birth weight and macrosomia.The second outcomes were pregnancy and perinatal complications.The relationship between EMT and adverse neonatal outcomes was estimated by Logistic regression analysis.Results The rate of ectopic pregnancy was increased significantly in group A.No significant differences were found among the three groups in gestation age,birth weight,birth weight z-score,PTB,small for gestation age,large for gestation age,low birth weight,very low birth weight and macrosomia.Compared with group B,the odds of adverse neonatal outcomes did not show significant differences before and after adjustment in both group A and group C by Logistic regression analysis.Conclusion Thinner EMT in fresh cleavage embryos transfer is associated with higher rate of ectopic pregnancy,while it is not independently associated with adverse perinatal outcomes.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.