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 investigate the association between serum 25-hydroxyvitamin D [25(OH)D] levels and 24-h urinary calcium excretion (24-h UCaE) and hypercalciuria in Chinese adults.Methods:This cross-sectional study was conducted from March 2022 to March 2023 in nine cities in China and included 1 239 residents. Demographic characteristics were collected through questionnaires and physical examinations, fasting blood samples were assessed for bone metabolism indicators, and 24-h urine samples were used to determine the 24-h UCaE. Multiple linear regression analysis was used to explore the relationship between serum 25(OH)D and 24-h UCaE and bone metabolism indexes. The relationship between serum 25(OH)D and hypercalciuria was analyzed using a multiple logistic regression model combined with restricted cubic spline modeling.Results:The mean participant age was (47.9±18.1) years, of which 453 (36.6%) were male. The percentages of vitamin D sufficiency, insufficiency, and deficiency were 7.6% (94/1 239), 29.0% (359/1 239), and 63.4% (786/1 239), respectively. The multiple linear regression model showed that after adjusting for the covariates the 24-h UCaE gradually increased with higher levels of 25(OH)D ( P overall <0.001, P nonlinear <0.001). The logistic regression analysis revealed that compared with the vitamin D deficient group, the OR for the prevalence of hypercalciuria in the vitamin D sufficient and vitamin D insufficient groups were 3.290 (95% CI 1.745 to 6.202) and 3.742 (95% CI 2.458 to 5.697), respectively. The results of the restricted cubic spline modeling showed a positive nonlinear relationship between 25(OH)D and the prevalence of hypercalciuria ( P overall <0.001, P nonlinear <0.001). The prevalence of hypercalciuria increased when 25(OH)D was >17.00 μg/L and peaked at 26.71 μg/L, after which there was a decreasing trend in the prevalence of hypercalciuria with increasing 25(OH)D. Conclusion:Associations between serum 25(OH)D levels and urinary calcium excretion and the prevalence of hypercalciuria were observed in the Chinese adult population.

AIM To investigate the tumor-suppressive mechanism of Guiqi Yiyuan Extract combined with cisplatin in Lewis lung cancer mice.METHODS Ten intact C57BL/6J mice were assigned to the blank group.Sixty additional mice were developed into Lewis lung cancer models bearing transplanted tumor and subsequently allocated into the model group,the cisplatin group(5 mg/kg),the high-dose Guiqi Yiyuan Extract group(6.6 g/kg),and the low-dose,medium-dose and high-dose Guiqi Yiyuan Extract combined with cisplatin group(1.6,3.3,6.6 g/kg+5 mg/kg),with 10 mice in each group.Mice in the blank and model groups received saline via daily gavage,while treatment groups were administered Guiqi Yiyuan Extract orally(once daily),and cisplatin injection intraperitoneally(once every other day).After 14 days of drug administration,mice were euthanized for endpoint analysis.The following assessments were conducted:general health status and body weight changes monitored throughout the study period;tumor excision and weighing for inhibition rate calculation;histopathological examination of tumors via hematoxylin-eosin(HE)staining;serum quantification of IL-1 β,IL-18 and HMGB1 by ELISA;ultrastructural analysis of tumor cell death using transmission electron microscopy(TEM);spatial localization of TXNIP and GSDMD-N in tumor sections via immunofluorescence(IF);and Western blot detection of TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD,GSDMD-N protein expressions in tumor tissues.RESULTS Compared to the model group,the cisplatin group and all combination therapy groups exhibited significant reduction in tumor weight(P＜0.05)and increased tumor suppression rate;enhanced tumor tissue necrosis with characteristic pyroptotic morphology;elevated serum levels of IL-1β,IL-18 and HMGB1(P＜0.05);and upregulated expressions of pyroptosis-associated proteins TXNIP,NLRP3,Caspase-1,cleaved Caspase-1,GSDMD and GSDMD-N(P＜0.05).The high dose combination group demonstrated optimal therapeutic efficacy(P＜0.05).CONCLUSION Guiqi Yiyuan Extract enhances cisplatin sensitivity,demonstrating synergistic anti-tumor effects in Lewis lung carcinoma-bearing mice.This combinatorial therapeutic effect likely involves modulation of the TXNIP/NLRP3/Caspase-1/GSDMD pathway.

Malignant tumors(commonly referred to as cancer)represent a major global public health challenge and contribute significantly to the worldwide disease burden.Early screening plays a critical role in improving detection rates,enabling timely intervention,and enhancing pa-tient survival rates.However,current cancer screening guidelines primarily focus on site-specific screening,which may not fully address the need for comprehensive early detection.A scientifical-ly rational,multi-cancer screening approach offers several advantages:it optimizes the use of bio-logical samples,reduces time costs for participants,enhances the efficiency and comprehensive-ness of screening,and minimizes overall expenses.Such an approach also facilitates the rational allocation of healthcare resources,ultimately helping to reduce the societal burden of cancer.To address this need,the Cancer Epidemiology Committee of the Chinese Anti-Cancer Association has developed the Expert Consensus on Combined Screening for Common Cancers in China.This consensus integrates multidisciplinary expertise and synthesizes the latest domestic and interna-tional researches on cancer screening,early detection,and treatment for prevalent malignancies.Drawing upon China's unique demographic and healthcare context,as well as practical screening experiences,the consensus provides evidence-based recommendations on target populations,screening technologies,and procedural workflows for multi-cancer screening.These guidelines align with the principles and methodologies established by the World Health Organization(WHO),aiming to:enhance the effectiveness of combined cancer screening in China,improve early detec-tion rates,and provide a scientific foundation for national cancer prevention and control strategies.

AIM To investigate the promotional effects of esculin combined with bone marrow mesenchymal stem cells(BM-MSCs)transplantation on the repair of spinal cord injury(SCI)in rats.METHODS The rats were randomly divided into the sham operation group,the model group,the esculin group for gavage of 20 mg/kg esculin,the BM-MSCs group for tail vein injection of 1 mL of 1×106/mL BM-MSCs,and the combinaiton treatment group.The SCI rat model was established using Allen's method,followed by the 14 days consecutive corresponding drug administration starting from the 2nd day after modeling.On days 3,7 and 14 of drug administration,the rats had their hind limbs motor function evaluated by the BBB scoring;and their footprint experiment conducted on the 14th day after modeling.After 14 days of administration,the rats had their morphological changes of spinal cord tissue observed with HE staining and Nissl staining;their activities of SOD and GSH,and level of MDA in spinal cord tissue detected by kits;their expressions of MAP2,GAP43 and GFAP in spinal cord tissue detected by immunofluorescence;and their expressions of NQO-1,Nrf-2,Bcl-2 and Bax proteins in spinal cord tissue detected by Western blot.RESULTS Compared with the model group,the groups interved with esculin,or BM-MSCs,or the combination treatment showed improvements in hind limb function and spinal cord tissue morphology(P＜0.05);decreased MDA levels(P＜0.05);increased SOD and GSH activities(P＜0.05);increased MAP2 and GAP43 fluorescence intensity(P＜0.05);decreased GFAP fluorescence intensity(P＜0.05);increased NQO-1,Nrf-2 and Bcl-2 protein expressions(P＜0.05);and decreased Bax protein expression(P＜0.05).And the combination treatment group was observed with an even better effects(P＜0.05).CONCLUSION The combination of esculin and BM-MSCs transplantation can effectively improve the spinal cord tissue damage and hind limb function in SCI rats.This effect may be achieved by activating the Nrf-2/NQO-1 signaling pathway to inhibit oxidative stress response,thereby reducing neuronal apoptosis,blocking glial scar formation,and promoting stem cell differentiation to rebuild neurons.

Malignant tumors(commonly referred to as cancers)represent a major global public health challenge and contribute substan-tially to the global disease burden.Early screening plays a crucial role in improving detection rates,enabling timely intervention,and enhan-cing patient survival.However,current cancer screening guidelines primarily focus on site-specific screening,which may not fully address the need for comprehensive early detection.A scientifically rational,multi-cancer screening approach offers several advantages:it optimizes the use of biological samples,reduces the time burden for participants,enhances the efficiency and comprehensiveness of screening,and min-imizes overall expenses.Moreover,this approach facilitates rational allocation of healthcare resources,ultimately helping to reduce the soci-etal burden of cancer.To address gap,the Cancer Epidemiology Committee of the China Anti-Cancer Association has developed the Expert Consensus on Combined Screening for Common Cancers.This consensus integrates multidisciplinary expertise and synthesizes the latest do-mestic and international researches on cancer screening,early detection,and treatment of prevalent malignancies.Drawing upon China's unique demographic and healthcare context and practical screening experiences,the consensus provides evidence-based recommendations on target populations,screening technologies,and procedural workflows for multi-cancer screening.These guidelines align with the prin-ciples and methodologies established by the World Health Organization(WHO),aiming to enhance the effectiveness of combined cancer screening in China,improve early detection rates,and provide a scientific foundation for national cancer prevention and control strategies.

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.

Objective To explore the clinical value of energy-spectrum CT single-energy imaging in enhancing the image quality and stent display of stent placement CT angiography(CTA)in lower extremity atherosclerotic occlusive disease.Methods Twenty patients[mean(65.61±9.65)years;male/female,16/4]who underwent stenting for chronic occlusive disease of the lower extremity arteries by lower extremity arterial energetic spectral CTA were retrospectively recruited at our hospital.The original images were reconstructed into seven sets of single energy(40-100 keV),120 kVp,virtual unenhanced images(VUE)and metal artifact reduction(MAR)technique images.Images were debossed and then scaffolded for display with volumetric reconstruction(VR),maximum density projection(MIP)and curve planar reconstruction(CPR),and were objectively and subjectively assessed and compared using one-way analysis of variance(ANOVA).Results The 80 keV and MAR images had the highest scores compared to the other reconstruction group images(P＜0.01).Conclusion 80 keV single-energy imaging and de-metallization artifacts MAR improve the image quality of lower extremity arterial stent lumen and structure display;therefore,they have higher diagnostic value for clinicians.

Department of Kidney Transplantation, the First Affiliated Hospital of Xi'an Jiaotong University reported a case of vasoplegic syndrome (VS). During a livingdonor kidney transplantation, the patient developed abrupt hypotension immediately after allograft reperfusion, with blood pressure dropping to 50/30 mmHg (1 mmHg=0.133 kPa). The diagnosis of VS was confirmed through multidisciplinary consultation, integration of clinical indicators, and ultrasonographic assessment. Management included vasopressor therapy (dopamine, norepinephrine, and epinephrine), fluid resuscitation, blood transfusion, and albumin administration. Hemodynamics were subsequently stabilized, and kidney allograft function returned to normal. At more than three months of followup, both kidney function and blood pressure remained stable.