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.

Echinococcosis is a neglected zoonotic parasitic disease across the world, which imposes a substantial burden on human health and socioeconomic development in endemic areas. From a One Health perspective, this review systematically summarizes the legal framework, scheme, integrated interventions, control achievements, and challenges in the national echinococcosis control programme of China. An integrated strategy centered on control of the source of Echinococcus infections has been implemented for echinococcosis control in China, and cross-sectoral and cross-regional multidisciplinary coordination mechanisms have been progressively established, resulting in remarkable achievements gained in human health, animal health, and integrated environmental management. The endemicity of echinococcosis remarkably reduced in China in 2023 as compared to results from the national echinococcosis epidemiological survey in China between 2012 and 2016 (baseline), with an 82.14% reduction in human prevalence, an 80.00% reduction in detection of echinococcosis among children, a reduction of prevalent echinococcosis patients to 25 400 cases, a 36.96% reduction in the number of dogs, an 88.24% reduction in the prevalence of Echinococcus infections in dogs, a 67.00% reduction in the number of stray dogs, an 80.77% reduction in the prevalence of echinococcosis in live-stock, and a 69.23% reduction in the prevalence of Echinococcus infections in rodents. Nevertheless, an estimated 14 600 canines were found to have Echinococcus infections in endemic areas across China in 2023, and the prevalence of Echinococcus infections increased by 241.03% in wild canines in 2023 relative to in 2021, which underscores the persistent threat to echinococcosis transmission. Future efforts are required to strengthen the One Health governance system, increase the financial investment, foster innovations in integrated control technologies, enhance cross-sectoral collaboration, and improve the capacity building at the grassroots level to advance the achievement of the national target of basically controlling echinococcosis in all endemic counties in China by 2030, thereby facilitating the process towards echinococcosis control and elimination.

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.

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.

OBJECTIVE To provide a reference for pharmaceutical care in patients with ulcerative colitis （UC） and ankylosing spondylitis （AS） who developed pustular psoriasis induced by infliximab. METHODS Clinical pharmacists participated in the pharmaceutical care process of a patient with UC and AS who developed pustular psoriasis after using infliximab. The clinical pharmacists determined， using Naranjo’s Scale， that the correlation between the patient’s pustular psoriasis and infliximab was “likely”. Regarding the patient’s development of pustular psoriasis after using infliximab， the clinical pharmacists recommended discontinuing infliximab and switching to Upadacitinib extended-release tablets. For the patient’s skin allergic reaction after using upadacitinib， the clinical pharmacists advised continuing the use of upadacitinib and closely monitoring any potential adverse reactions during the treatment period. RESULTS The clinicians adopted the clinical pharmacists’ recommendation. Following the treatment， the patient’s symptoms were significantly alleviated， and the patient was discharged with medication. The follow-up after discharge showed that the treatment was effective and well-tolerated. CONCLUSIONS The clinical pharmacists analyzed the causal relationship between infliximab and pustular psoriasis. Through pharmaceutical care measures such as dynamic monitoring of skin lesions， evaluation of treatment responses， and optimization of drug regimens， they assisted the physicians in formulating an individualized medication plan， ensuring the safety and efficacy of the patient’s medication use.

[Objective] To retrospectively analyze the detection results of alanine aminotransferase (ALT) unqualified repeat blood donors in Guangzhou, so as to provide evidence for further expanding the repeat blood donor pool, reducing the rate of blood discarding and improving the qualified rate of blood test. [Methods] Blood donors with unqualified ALT in Guangzhou Blood Center from January 2018 to April 2024 were selected as the research objects. The past blood donation and population characteristics were analyzed according to the number of blood donations and ALT unqualified times. [Results] Among repeat blood donors with previous ALT disqualification, 99.5% to 99.7% did not have reactive markers for transfusion-transmitted diseases (TTD), which was higher than the rate among first-time blood donors with unqualified ALT (95.8%) (P<0.05). The rate of single-item ALT disqualification in repeat blood donors was higher in males than in females (P<0.05); it also varied by age (18-25 years > 26-35 years > 36-45 years > over 45 years) (P<0.05); and by quarter (third and fourth quarters > first and second quarters) (P<0.05). The ALT unqualified rate was significantly higher whole blood donors than that of platelet donors and returning blood donors (P<0.05). The overall ALT level (51.0 U/L), individual ALT level (56.0 U/L) and individual ALT unqualified rate (66.7%) of repeat blood donors with multiple ALT disqualifications were higher than those of repeat blood donors with single-item ALT disqualifications (26.0 U/L, 38.5 U/L, and 33.3%, respectively) (P<0.05). Moreover, as the number of ALT disqualifications increased, the overall level of ALT in repeat blood donors also increased (P<0.05), and the average level of individual ALT and individual ALT unqualified ratio tended to increase. Repeat blood donors with frequent ALT disqualifications had higher ALT levels (69.0 U/L). [Conclusion] The ALT unqualified rates of repeat blood donors were mostly non-specific elevation without TTD. Repeat blood donors with multiple ALT disqualifications tend to have continuous high ALT. Moreover, and with the increase of ALT disqualifications times, the overall ALT levels the average individual ALT levels and individual ALT unqualified rates showed an increasing trend.