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.

ObjectiveTo explore the therapeutic effect of Xuebijing injection （XBJ） on severe acute pancreatitis induced acute lung injury （SAP-ALI） by regulating formyl peptide receptors （FPRs）/nucleotide-binding oligomerization domain-like receptor 3 （NLRP3） inflammatory pathway. MethodsSixty rats were randomly divided into a sham group， a SAP-ALI model group， low-， medium-， and high-dose XBJ groups （4， 8， and 12 mL·kg^-1）， and a positive drug （BOC2， 0.2 mg·kg^-1） group. For the sham group， the pancreas of rats was only gently flipped after laparotomy， and then the abdomen was closed， while for the remaining five groups， SAP-ALI rat models were established by retrograde injection of 5% sodium taurocholate （Na-Tc） via the biliopancreatic duct. XBJ and BOC2 were administered via intraperitoneal injection once daily for 3 d prior to modeling and 0.5 h after modeling. Blood was collected from the abdominal aorta 6 h after the completion of modeling， and the expression of interleukin （IL）-1β， IL-6， and tumor necrosis factor-α （TNF-α） in plasma was measured by enzyme-linked immunosorbent assay （ELISA）. The amount of ascites was measured， and the dry-wet weight ratios of pancreatic and lung tissue were determined. Pancreatic and lung tissue was taken for hematoxylin-eosin （HE） staining to observe pathological changes and then scored. The protein expression levels of FPR1， FPR2， and NLRP3 in lung tissue were detected by the immunohistochemical method. Western blot was used to detect the expression of FPR1， FPR2， and NLRP3 in lung tissue. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of FPR1， FPR2， and NLRP3 in lung tissue. ResultsCompared with the sham group， the SAP-ALI model group showed significantly decreased dry-wet weight ratio of lung tissue （P<0.01）， serious pathological changes of lung tissue， a significantly increased pathological score （P<0.01）， and significantly increased protein and mRNA expression levels of FPR1， FPR2， and NLRP3 in lung tissue （P<0.01）. After BOC2 intervention， the above detection indicators were significantly reversed （P<0.01）. After treatment with XBJ， the groups of different XBJ doses achieved results consistent with BOC2 intervention. ConclusionXBJ can effectively improve the inflammatory response of the lungs in SAP-ALI rats and reduce damage. The mechanism may be related to inhibiting the expression of FPRs and NLRP3 in lung tissue， which thereby reduces IL-1β and simultaneously antagonize the release of inflammatory factors IL-6 and TNF-α.

ObjectiveTo delineate the species composition structure and seasonal density fluctuations of mosquito populations in Yangpu District, Shanghai, and to provide scientific insights for the prevention and control of vector-borne diseases. MethodsA total of 12 monitoring sites from different habitats were selected to conduct adult mosquito monitoring using the CO₂ trap light method during 2019‒2023, elucidating the temporal and spatial distribution and change patterns of mosquito populations and densities in Yangpu District. ResultsFrom 2019 to 2023, a total of 1 321 female mosquitoes was captured, with an overall density of 0.16 case·(lamp·h)^-1. The species identified were predominantly Culex pipiens pallens (87.28%), followed by Aedes albopictus (12.64%), and Culex tritaeniorhynchus (0.08%). Seasonal distribution showed a typical single-peak pattern, with June‒August being the peak period. In terms of habitat distribution, the highest mosquito population density was found in residential areas [0.18 case·(lamp·h)^-1], followed by hospitals [0.13 case·(lamp·h)^-1] and parks [0.11 case·(lamp·h)^-1]. Culex pipiens pallens was the dominant species in all habitats, with a density of [0.14 case·(lamp·h)^-1]. Notably, there was a statistically significant difference in the composition of Culex pipiens pallens and Aedes albopictus among the three habitats mentioned(χ²=38.396, P<0.001; χ²=36.790, P<0.001). The mosquito density of the 12 streets from high to low is Changhai Road, Pingliang, Yinhang, Xinjiangwan City, Yanji, Daqiao, Wujiaochang, Kongjiang, Changbai New Village, Jiangpu, Siping and Dinghai.The distribution of mosquito density was relatively balanced across different communities (H=1.559, P=1.000). ConclusionThe results of CO₂ trap light monitoring reveals a relatively low density of adult mosquitoes in Yangpu District, with Culex pipiens pallens as the predominant species, and summer being the peak season for mosquitoes. In light of the threat of mosquito-borne diseases such as dengue fever, more effective and evidence-based mosquito control strategies, aligning with the distribution and behavioral patterns of mosquitoes, should be developed.

Objective To evaluate the resuscitation efficacy of novel lyophilized platelets(LP,thrombin-stimulated platelets)combined with lactated Ringer's(LR)solution in rabbits with hemorrhagic shock and seawater immersion.Methods Fifty rabbits were randomly assigned to 5 groups(Groups A,B,C,D and E,n=10).After all rabbits were anesthetized with 3%pentobarbital sodium at a dose of 1 mL/kg,soft tissue injury was inflicted in the left lower limb.The blood loss from the soft tissue injury was quantified after gauze hemostasis.The right lower limb was subjected to femoral artery catheterization,followed by blood withdrawal equivalent to 26%of the total blood volume of the rabbit.The rabbits were then vertically immersed in 3%artificial seawater,with the water level reaching above the xiphoid process,and were retrieved in 15 min later.Resuscitation strategies were applied to the rabbits from different group:Group A(no resuscitation),Group B(resuscitation with LR solution),Group C(resuscitation with LR solution and fresh platelets),Group D(resuscitation with LR solution and LP),and Group E(resuscitation with LR solution and novel LP).Coagulation function test,routine blood test,blood gas analysis,and thromboelastography were conducted at baseline and at 1,2 and 4 h after injury.Results The LP and rabbit model of hemorrhagic shock and seawater immersion were successfully prepared.At 1 h after injury,the mean arterial pressure(MAP)of Groups C,D and E(infused with platelet preparations)was significantly higher than that of Group A(without resuscitation,P<0.05);the lactate(Lac)content of Group C was obviously lower than that of Groups A and B(P<0.05);the base excess(BE)and blood urea nitrogen(BUN)levels of Groups C,D and E were notably lower than those of Groups A and B(P<0.05);and the prothrombin time(PT)of Group A was significantly longer than that of before injury(P<0.05).At 2 h after injury,the MAP of Groups C and D was significantly higher than that of Groups A and B,and that of Group E was notably higher than that of Group A(P<0.05);the Lac content of Groups C and E was obviously lower than that of Groups A and B,while that of Group D was also lower than that of Group A(P<0.05);the BE and BUN levels of Groups C,D and E were remarkably lower than those of Groups A and B(P<0.05);the maximum amplitude(MA)value of Group C was higher than that of Group A,while the value of Groups A and D at this time was significantly lower than the corresponding value before injury(P<0.05);and the activated partial clotting time(APTT)of Groups A and D was statistically longer than the corresponding baseline time(P<0.05).At 4 h after injury,the MAP of Groups C,D,and E was higher than that of Groups A and B,and that of Group B was higher than that of Group A(P<0.05);the Lac and BUN levels of Groups C,D,and E were lower than those of Groups A and B(P<0.05);the BE level of Groups C and D were lower than those of Groups A and B(P<0.05);the MA value of Groups B,C,and E were higher than those of Group A(P<0.05),while the MA value and APTT value of Groups A and D were significantly lower than their corresponding baseline values(P<0.05).Conclusion For rabbits with hemorrhagic shock and seawater immersion,the novel LP combined with LR solution can significantly increase the MAP level,reduce Lac content,and sustainably maintain blood clot firmness and coagulation function.

Objective To evaluate the efficacy of transcatheter arterial chemoembolization(TACE)combined with argon-helium cryoablation(AHC)in the treatment of hypervascular small hepatocellular carcinoma(sHCC).Methods The clinical data of 35 patients with hypervascular sHCC,who received TACE combined with AHC at the Affiliated Cancer Hospital of Zhengzhou University of China from March 2018 to February 2019,were retrospectively analyzed.All patients were treated with TACE treatment first,after 3-7 days the patients received AHC therapy.The postoperative 1-,3-,and 6-month curative effect were evaluated,and the postoperative 1-,3-,and 5-year survival rates were calculated.The liver function and immune function indicators,as well as the serum tumor markers were detected.The adverse reactions during treatment were recorded.Results The postoperative 1-,3-,and 6-month objective remission rate(ORR)were 100.00％,94.29％and 91.43％respectively,and the disease control rate(DCR)were 100.00％,100.00％and 97.14％ respectively.The overall survival(OS)was(46.54±2.88)months,and the postoperative 1-,3-,and 5-year survival rates were 94.29％(33/35),65.71％(23/35)and 48.57％(17/35)respectively.The postoperative 3-day serum levels of ALT,AST and TBIL were significantly elevated when compared with their preoperative baseline levels(all P＜0.05),which returned to preoperative levels in 2 weeks after treatment(P＞0.05).The postoperative 2-week CD4+％and CD4+％/CD8+％ratio were remarkably increased when compared with their preoperative values(both P＜0.05),while the postoperative 2-week AFP,AFP-L3％,DCP and GPC3 levels were strikingly decreased when compared with their preoperative values(all P＜0.001).None of the patients developed procedure-related severe complications after treatment.Conclusion For the treatment of hypervascular sHCC,TACE combined with AHC has satisfactory clinical efficacy and safety.

A subset of patients with multiple myeloma(MM)present with reduced serum vitamin B12 levels at initial diagnosis;however,its clinical significance and underlying mechanisms remain unclear.Vitamin B12 plays a crucial role in hematopoiesis and immune regulation.This study aims to elucidate its association with extramedullary diseases,immune function,and prognosis in MM patients.A retrospec-tive analysis was conducted of 92 newly diagnosed MM patients,who received treatment at the Second Af-filiated Hospital of Soochow University between January 2020 and December 2023.Patients were classi-fied into a low vitamin B12 group(n=37)and a normal vitamin B12 group(n=55)based on their ser-um vitamin B12 levels.The findings revealed that the incidence of extramedullary infiltration was signifi-cantly higher in the low vitamin B12 group than in the normal group(26.5％vs.17.0％,P=0.031).Survival analysis demonstrated that patients with low vitamin B12 levels had significantly shorter overall survival(OS)and progression-free survival(PFS)(OS:P=0.0123;PFS:P=0.0136).Additionally,these patients showed a decreasing trend in peripheral blood total T cell,CD4+T cell,and CD8+T cell counts,with serum vitamin B12 levels showing a significant positive correlation with the total T cell count(R=0.2717,P=0.0135)and CD4+T cell count(R=0.2175,P=0.0497).In conclusion,reduced serum vitamin B12 levels at initial diagnosis are significantly associated with poor prognosis in MM pa-tients and may serve as a potential prognostic biomarker.Furthermore,vitamin B12 deficiency may con-tribute to immune dysfunction,particularly impaired T cell immunity,and a higher incidence of extr-amedullary diseases.

Insomnia is often comorbid with anxiety and/or depression.Identifying biomarkers for this comorbidity is crucial for precise diagnosis,elucidating the underlying pathological mechanisms,and developing personalized treatment strategies.Current research has preliminarily revealed a series of potential biomarkers for insomnia comorbid with anxiety and/or depression.Elevated peripheral pro-inflammatory factors(e.g.,interleukin-6),and decreased peripheral brain-derived neurotrophic factor,and monoamine neurotransmitters(e.g.,5-hydroxytryptamine)may indicate the presence of a comorbid state.However,studies focusing on this comorbidity remain relatively limited.In the future,it will be necessary to systematically explore and verify the clinical application value of potential biomarkers through measures such as expanding sample size,strengthening longitudinal design,and expanding the categories of biomarkers.This will provide a more solid theoretical foundation for the early diagnosis and personalized treatment of insomnia comorbid with anxiety and/or depression.

Due to advances in treatment methods, the survival rate and quality of life of cancer patients have been improved. Radiation-induced vascular injury (RIVI) is a common adverse reaction following radiotherapy, mainly manifested as capillary injury and atherosclerosis in the irradiated area. Radiotherapy induces RIVI in the cerebral vessels, carotid arteries, coronary arteries, and large arteries through mechanisms such as endothelial cell injury and senescence, oxidative stress and inflammatory responses, angiogenesis, and vascular remodeling. In this review research progress in the pathological features, pathophysiological mechanisms, clinical manifestations, prevention and treatment strategies of RIVI was summarized, aiming to provide insights for future research on RIVI.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.