This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Objective To explore the construction of heart preservation model of empty beating donor based on extracorporeal membrane oxygenation (ECMO). Methods From January 2022 to August 2023, 20 Guangxi Bama miniature pigs weighing 25-30 kg were selected, half male and half female. Under general anesthesia and heparinization, a midline thoracotomy was performed. The pericardium was cut after freeing the anterior and posterior vena cavae, and a perfusion needle was inserted near the brachiocephalic artery in the ascending aorta, connected to a blood collection bag to collect 500-600 mL of blood. The anterior and posterior vena cavae were ligated, the aorta was blocked and perfused with HTK solution to stop the heart beating. The superior and inferior vena cavae were cut off, the right pulmonary vein was decompressed, the aorta and left and right pulmonary arteries and veins were cut off, and the whole heart was removed. An ECMO device was used to continuously perfuse a cardioprotective solution mainly composed of oxygenated warm blood, maintaining the isolated pig heart beating for 8 hours, monitoring (once/hour) ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, inflammatory factors, myocardial enzymes, myoglobin, and troponin levels. Myocardial tissue was taken for hematoxylin-eosin (HE) staining to observe myocardial cell damage and evaluate the quality of heart preservation. Results Among the 20 isolated beating pig hearts, 17 successfully resumed beating, 3 experienced ventricular fibrillation, resuscitated after intracardiac electrical defibrillation, and all 20 pig hearts successfully beat for 8 hours. There was no statistical difference in ECMO perfusion parameters, blood gas indicators, perfusate electrolytes, and inflammatory factors at each time point (P>0.05). There were statistical increases in myocardial enzymes, myoglobin, and troponin levels (P<0.05). HE staining results suggested that there was no severe myocardial damage. Conclusion ECMO technology can be used for pig heart preservation with good results, and this study provides experimental evidence for improving heart preservation research in clinical heart transplantation.

Purpose: Our previous study showed that circulating tumor cell (CTC) count combined with gene mutation detection might help differentiate benign and malignant pulmonary nodules (PNs). Herein, we aimed to expand the study cohort and conduct further sequencing analysis. Materials and Methods: Patients with PNs were included, and CTCs were identified before operation. Low-coverage whole-genome sequencing (LC-WGS) and lung cancer-related targeted gene sequencing were performed on CTCs. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve. The differences in CTC counts among subgroups classified by demographic–clinical characteristics were analyzed. LC-WGS–based copy number variation (CNV) analysis and targeted gene mutation analysis were conducted. Results: A total of 172 patients were included. CTC count of 2.5 was identified by the ROC curves as the optimal diagnostic cutoff. The sensitivity and specificity of CTC count for differentiating benign and malignant PNs were 54.2% and 78.6%, respectively. The diagnostic sensitivity and specificity of combined CTC count, radiological nodule type, and any malignant imaging features were 84.7% and 71.4%, respectively. The CTC counts were significantly greater in patients with aggressive tumors, later stage, and spread through air spaces. CTCs from malignant cases had more CNVs than those from benign cases. Conclusion CTC count can be used in identifying malignant PNs. The diagnostic efficacy can be improved if combined with computed tomography imaging characteristics. Further CNV analysis might help differential diagnosis. Greater CTC count might suggest more aggressive tumors. CTC detection can provide important information and guidance for subsequent management of PNs.

BACKGROUND:Bone relies on the close connection between blood vessels and bone cells to maintain its integrity.Bones are in a physiologically hypoxic environment.Therefore,the study of angiogenesis and osteogenesis in hypoxic environment is closer to the microenvironment in vivo. OBJECTIVE:To explore the influence of Wenshen Tongluo Zhitong(WSTLZT)formula on H-type bone microvascular endothelial cell/bone marrow mesenchymal stem cell co-culture system in hypoxia environment and its related mechanism. METHODS:Enzyme digestion method and flow sorting technique were used to isolate and identify H-type bone microvascular endothelial cells.Mouse bone marrow mesenchymal stem cells were isolated and obtained by bone marrow adhesion method.H-type bone microvascular endothelial cell/bone marrow mesenchymal stem cell hypoxic co-culture system was established using Transwell chamber and anoxic culture workstation.WSTLZT formula powder was used to intervene in each group at a mass concentration of 50 and 100 μg/mL.The angiogenic function of H-type bone microvascular endothelial cells in the co-culture system was evaluated by scratch migration test and tube formation test.The osteogenic differentiation ability of bone marrow mesenchymal stem cells in the co-cultured system was evaluated by alkaline phosphatase staining and alizarin red staining.The protein and mRNA expression changes of PDGF/PI3K/AKT signal axis related molecules in H-type bone microvascular endothelial cells in the co-cultured system were detected by Western Blotting and q-PCR,respectively. RESULTS AND CONCLUSION:(1)Compared with the normal oxygen group,the scratch mobility and new blood vessel length of H-type bone microvascular endothelial cells were significantly higher(P<0.05);the osteogenic differentiation capacity of bone marrow mesenchymal stem cells was higher(P<0.05);the expression of PDGF/PI3K/AKT axis-related molecular protein and mRNA increased(P<0.05)in the hypoxia group.(2)Compared with the hypoxia group,scratch mobility and new blood vessel length were significantly increased in the H-type bone microvascular endothelial cells(P<0.05);bone marrow mesenchymal stem cells had stronger osteogenic function(P<0.05);the expression of PDGF/PI3K/AKT axis-related molecular proteins and mRNA further increased(P<0.05)after treatment with different dose concentrations of WSTLZT formula.These findings conclude that H-type angiogenesis and osteogenesis under hypoxia may be related to the PDGF/PI3K/AKT signaling axis,and WSTLZT formula may promote H-type vasculo-dependent bone formation by activating the PDGF/PI3K/AKT signaling axis,thereby preventing and treating osteoporosis.

Objective: To investigate the current status of iron metabolism among apheresis donors in Guangzhou and analyze the improvement effects of health education on iron deficiency in frequent apheresis donors. Methods: Using a generalized linear mixed model (GLMM), a 180-day follow-up was conducted on 261 eligible apheresis donors at the Guangzhou Blood Center from January to July 2024. Hemoglobin (Hb), serum ferritin (SF), unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), and transferrin saturation (TS) were selected as outcome variables. The effects of gender, age group, and number of donations within 180 days on these outcomes were analyzed and modeled. A general linear model (GLM) with repeated measures was applied to 55 donors who received health education interventions, comparing changes in Hb and iron metabolism-related indicators before and after follow-up and health education. Results: No significant difference in Hb levels was observed between first-time and regular apheresis donors, but SF levels were significantly higher in first-time donors (F=6.195, P<0.05). The GLMM revealed that female donors exhibited more significant reductions in Hb (T=-12.546) and SF (T=-5.829)(P<0.05 for both). Age group showed no interactive effects on Hb or SF changes. While number of donations within 180 days had no interactive effect on Hb, SF levels significantly decreased with increased number of donations (using ≥9 donations as the reference group; P<0.05 for all groups). After health education, Hb levels remained unchanged, but SF increased compared to pre-intervention levels (mean difference: -18.571, P<0.05), though a declining trend persisted compared to baseline (mean difference from baseline to post-intervention: 23.068,P<0.05). Conclusion: Female and number of donations are primary factors contributing to SF reduction in apheresis donors. Health education interventions promote SF recovery. Extending donation intervals and reinforcing iron deficiency-related health education may improve iron status in donors.

Although symptomatic treatment is widely applied in clinical practice， it is often regarded as a relatively low-level therapeutic method. Based on Traditional Chinese Medicine （TCM） state theory， the macroscopic， mesoscopic， and microscopic characterization parameters of TCM symptomatology are horizontally integrated， the full life cycle of states （pre-disease， incipient disease， manifest disease， post-disease） is vertically covered， and the cognitive system of "symptoms" is reconstructed from multiple dimensions. Accordingly， the application approach of symptomatic treatment at different state stages is proposed： implementing preventive intervention in the pre-disease state， strengthening the interception of disease progression in the incipient disease state， regulating dynamic development and treatment in the manifest disease state， and formulating a staged diagnosis and treatment strategy which focuses on functional rehabilitation in the post-disease state.

Objective To evaluate the therapeutic efficacy for surgical treatments among patients with hepatic cystic echinococcosis in Gansu Province from 2006 to 2023, so as to provide insights into optimization of the diagnosis and treatment strategies against hepatic cystic echinococcosis. Methods The demographic and clinical data of all echinococcosis cases included in central government fiscal transfer payment program for echinococcosis control and undergoing surgical treatments in Gansu Province from 2006 to 2023 were captured. Hepatic cystic echinococcosis patients with complete medical records and follow-up data were included in the study, and patients’ characteristics, including hospital where patients received diagnosis and treatment, methods of case identification, year of surgery, classification of lesions, number of lesions, size of lesions, course of disease, surgical methods, and post-surgical follow-up data. The cure and recurrence of hepatic cystic echinococcosis were evaluated according to the Guidelines for Management of Echinococcosis Patients in the Central Government Fiscal Transfer Payment Program, and the cure and recurrent rates were calculated. Results Data were collected from 1 686 surgical patients with hepatic cystic echinococcosis. According to the inclusion and exclusion criteria, 1 222 hepatic cystic echinococcosis patients undergoing surgical treatments were included during the period from 2006 to 2022, including 1 166 cured patients (95.42%) and 88 patients with postsurgical recurrence (7.20%), and the cure rate of surgical treatments appeared a tendency towards a rise among patients with hepatic cystic echinococcosis from 2008 to 2022 (χ²_trend = 19.39, P < 0.05). The cure rates of hepatic cystic echinococcosis were 100% (177/177), 94.81% (128/135) and 94.62% (861/910) among patients detected through regular physical examinations, screened by the central government fiscal transfer payment program for echinococcosis control, and those who passively sought healthcare services, respectively (χ² = 9.95, P < 0.05). The cure rates of hepatic cystic echinococcosis were 95.96% (1 046/1 090) among patients with a disease course of 2 years and less and 90.90% (120/132) among patients with a disease course of over 2 years (χ² = 6.87, P < 0.05), and there were significant differences in the cure rates among patients with hepatic cystic echinococcosis in terms of number of lesions (χ² = 24.44, P < 0.05) and surgical methods (P < 0.05). The cure rate of hepatic cystic echinococcosis patients was significantly higher following initiation of the central government fiscal transfer payment program for echinococcosis control (96.06%, 1 096/1 141) than before the program (86.42%, 70/81) (χ² = 16.06, P < 0.05), and the cure rate of hepatic cystic echinococcosis patients was significantly higher in designated hospitals (96.48%, 741/768) than in non-designated hospitals (93.37%, 366/392) (χ² = 5.78, P < 0.05). The median follow-up period was 4 (interquartile range, 7) years among 1 222 hepatic cystic echinococcosis patients undergoing surgical treatments. The recurrent rate of hepatic cystic echinococcosis appeared a tendency towards a decline from 2008 to 2022 (χ²_trend = 36.86, P < 0.05), with a reduction from 23.08% (9/39) in 2008 to 1.85% (1/54) in 2021, and the post-surgical recurrence rate of hepatic cystic echinococcosis was lower following initiation of the central government fiscal transfer payment program for echinococcosis control (5.87%, 67 / 1 141) than before the program (25.93%, 21/81) (χ² = 45.51, P < 0.05). In addition, the post-surgical recurrence rate of hepatic cystic echinococcosis was higher in non-designated hospitals (10.46%, 41/392) than in designated hospitals (5.60%, 43/768) (χ² = 9.12, P < 0.05), and there was a significant difference in the post-surgical recurrence rate among patients with hepatic cystic echinococcosis in terms of surgical methods (P < 0.05), with the highest recurrence rate (11.54%) seen among patients undergoing percutaneous fine-needle aspiration of cyst fluids-based surgical procedures (P < 0.05). Conclusion Since the initiation of the central government fiscal transfer payment program for echinococcosis control in Gansu Province in 2006, an increase in the surgical cure rate and a reduction in the recurrence of hepatic cystic echinococcosis had been found among patients with hepatic cystic echinococcosis, indicating a high overall therapeutic efficacy.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.