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:This study based on comprehensive bioinformatics technology aimed to investigate the pathogenesis of ferroptosis in IgA nephropathy(IgAN)from an immunological perspective,and to identify the key genes and functional pathways.Methods:Differentially expressed ferroptosis-related genes(DE-FRGs)were identified from GSE93798 and analyzed by Kyoto Ency-clopedia of Genes and Genomes(KEGG)and Gene Ontology(GO).STRING and Cytoscape were used to construct a protein-protein interaction(PPI)network.Degree and MCODE algorithm were run.Combining LASSO regression,SVM-RFE and PLS-DA machine learning to construct the optimal feature selection hub gene.Cibersort and ssGESA algorithms were used to assess the immune infiltra-tion,as well as to explore the relationship between hub genes and immune infiltration.Single cell RNA sequence(scRNA-seq)data was used to analyze the location of hub genes in IgAN cell populations.Gene Set Enrichment Analysis(GSEA)was performed on hub genes.The HPA database was used to obtain the position of the specific protein of the hub genes,and the DsigDB database was used to predict the target drug.The GSE37460,GSE116626 and GSE73953 were treated as validation sets and diagnostic effectiveness evalua-tion.Collecting IgAN and healthy kidney tissue for immunohistochemical testing of hub genes expression.Results:This study identi-fied 94 DE-FRGs and 3 hub genes(JJUN,EGR1 and DDR2).KEGG and GO analysis indicated that the DE-FRGs were mainly con-centrated in pathways of ferroptosis,reactive oxygen species,responsing to oxidative stress and metal particles,mitochondrion,and transcriptional regulatory complex.GESA analysis involved in amino acid and fatty acid metabolism.The analysis of immune cell infil-tration in IgAN revealed an increased ratio of naive B cells,mast cells,and CD4+T cells.Differential analysis of immune function re-vealed that mechanisms such as chemokine receptor signaling pathways,human leukocyte antigen signaling pathways,and inflamma-tion promotion were more active in IgAN.Furthermore,the correlation was observed between immune infiltration and hub genes.ScRNA-seq analysis demonstrated that hub genes were localized in monocytes,macrophages,poximal convoluted tubule cells,princi-pal cells,and smooth muscle cells.Validations set analysis suggested that JUN and SIRT1 had a diagnostic value.The HPA database analysis showed that JUN was mainly located in the nucleus,while EGR1 was located in the membrane and cytoplasm.The 2 278 po-tential drugs for the treatment of IgAN were predicted.Finally,the results of immunohistochemistry and bioinformatics analysis were consistent.Conclusion:Ferroptosis may be associated with immune cell infiltration and immune related function during the occur-rence and development of IgAN.

Objective:To observe the clinical effect of computed tomography(CT)-guided hematoma puncture drainage surgery combined with high-dose(≥50 000 U)urokinase in treating hypertensive intracerebral hemorrhage.Methods:The case data of a total of 90 patients with hypertensive intracerebral hemorrhage who underwent treatment in Zhangjiakou First Hospital from January 2022 to January 2023 were retrospectively selected as the study subjects.They were divided into a control group and an observation group using the average method,with 45 cases in each group.The conventional group received CT-guided hematoma puncture drainage surgery combined with conventional dose urokinase(20 000 U),while the observation group received CT-guided hematoma puncture drainage surgery combined with high-dose urokinase(50 000 U),with a 6-month follow-up for all patients.The changes of hematoma volume,length of hospital stay,levels of inflammatory indicators,the levels of hemodynamics,clinical efficacy,and incidence of postoperative complications after treatment between two groups were analyzed and compared.Results:After treatment,the hematoma volume at the 1st day[(34.64±5.53)mm3]and the 7th day[(34.64±5.53)mm3]post surgery of observation group were significantly lower than those[(44.57±6.85)mm3 and(16.64±3.24)mm3]of conventional group,and the differences of them between the two groups were statistically significant(t=7.567,10.570,P<0.05),respectively.The length of hospital stay of observation group[(16.86±6.63)d]was significantly lower than that of the control group[(23.47±10.34)d](t=3.610,P<0.05).The levels of matrix metalloproteinase-9(MMP-9),interleukin-6(IL-6),C-reactive protein(CRP),tumor necrosis factor-α(TNF-α)at 7th days post surgery of observation group were significantly lower than those of conventional group,and the differences of them between the two groups were statistically significant(t=5.826,10.202,7.661,2.724,P<0.05),respectively.The blood flow levels of middle cerebral artery(MCA),anterior cerebral artery(ACA),and posterior cerebral artery(PCA)after surgery in observation group were significantly higher than those in conventional group(t=2.833,3.329,3.973,P<0.05),respectively.The effective rate of treatment in observation group(95.56%)was significantly higher than that in conventional group(80.00%),and the difference was significant(x2=5.075,P<0.05).There was no significant difference in the incidence of postoperative complications between the two groups(P>0.05).Conclusion:CT-guided hematoma puncture drainage surgery combined with high-dose urokinase can significantly increase the dissolution rate of hematoma,and reduce the body's inflammatory response,and improve cerebral hemodynamic indicators,and effectively enhance clinical efficacy in treating hypertensive intracerebral hemorrhage,which have better treatment safety.

Objective:To analyze the echocardiographic and genetic characteristics of fetuses with common arterial trunk（CAT）.Methods:A retrospective analysis was conducted on 77 480 fetal echocardiograms examined at the Maternal-Fetal Medicine center in Fetal Heart Disease of Beijing Anzhen Hospital from November 2010 to November 2024.Among them，106 fetuses were initially diagnosed with CAT，and 95 cases were ultimately confirmed（0.1%，95/77 480）. The echocardiographic and genetic features of CAT fetuses were analyzed. According to the modified Van Praagh classification，CAT was divided into types A1-A4［with ventricular septal defect（VSD）］and B1-B4（without VSD）based on the origin of the pulmonary artery branches and the presence or absence of a VSD. Additionally，CAT was categorized into isolated and complex types based on the presence of associated intracardiac or extracardiac anomalies.Results:① Among the 95 confirmed CAT fetuses，type A accounted for 90.5%（86/95），and type B accounted for 9.5%（9/95）. All 9 type B CAT fetuses exhibited no overriding of the arterial trunk ， with 8 cases showing left ventricular hypoplasia accompanied by mitral atresia or absence.② Of the 95 CAT fetuses，14 were isolated（14.7%，14/95） ， and 81 were complex（85.3%，81/95）.The main associated intracardiac anomalies included：single ventricle（22 cases），complete atrioventricular septal defect（12 cases），anomalous pulmonary venous drainage（10 cases），right aortic arch with mirror-image branching（16 cases），and persistent left superior vena cava（14 cases）. ③ Genetic testing was performed in 31 fetuses，with 18 showing positive results，primarily 22q11.21 deletion syndrome（29.0%，9/31）. Conclusions:Apart from VSD，the most common intracardiac anomaly associated with CAT fetuses is single ventricle. Type B CAT without trunk overriding is often associated with left ventricular hypoplasia and mitral atresia or absence. The most frequent genetic abnormality in CAT fetuses is 22q11.21 deletion syndrome. Prenatal echocardiography should clarify the CAT subtype and associated anomalies，and genetic testing is strongly recommended for perinatal counseling and prognostic evaluation.

Objective The aim of this study was to explore the predictive value of the systemic inflammatory immune nutri-tion score(SIINS)for the prognosis of immunotherapy for advanced gastric cancer.Methods A retrospective analysis was conducted on the clinical data of 202 patients with advanced gastric cancer who received treatment with programmed death-1(PD-1)inhibitors at the Harbin Medical University Cancer Hospital from October 2018 to July 2022.The LASSO regression analysis was used to screen prognostic indicators,construct SIINS indicator,determine the optimal cutoff value for predicting prognosis using subject operating characteristic curves,and divide patients into the high SIINS and low SIINS groups.Independent prognostic factors for overall survival(OS)were determined using univariate and multivariate Cox regression analyses.Results Four indicators,including lymphocyte count,lactate dehydrogenase,and neutrophil lymphocytes,were selected to construct the SIINS index.The prognosis of patients in the high SIINS group was significantly lower than that in the low SIINS group(P<0.05).The results of the multifactorial Cox regression a-nalysis showed that the Eastern Cooperative Oncology Group(ECOG)score,Geriatric Nutritional Risk Index(GNRI),SIINS,treatment regimen,and number of treatment lines(P<0.05)could serve as the independent predictive prognosis of immunotherapy for advanced gastric cancer.Conclusion SIINS can predict the prognosis of patients with advanced gastric cancer treated with PD-1 inhibitors.

Objective The aim of this study was to explore the predictive value of the systemic inflammatory immune nutri-tion score(SIINS)for the prognosis of immunotherapy for advanced gastric cancer.Methods A retrospective analysis was conducted on the clinical data of 202 patients with advanced gastric cancer who received treatment with programmed death-1(PD-1)inhibitors at the Harbin Medical University Cancer Hospital from October 2018 to July 2022.The LASSO regression analysis was used to screen prognostic indicators,construct SIINS indicator,determine the optimal cutoff value for predicting prognosis using subject operating characteristic curves,and divide patients into the high SIINS and low SIINS groups.Independent prognostic factors for overall survival(OS)were determined using univariate and multivariate Cox regression analyses.Results Four indicators,including lymphocyte count,lactate dehydrogenase,and neutrophil lymphocytes,were selected to construct the SIINS index.The prognosis of patients in the high SIINS group was significantly lower than that in the low SIINS group(P<0.05).The results of the multifactorial Cox regression a-nalysis showed that the Eastern Cooperative Oncology Group(ECOG)score,Geriatric Nutritional Risk Index(GNRI),SIINS,treatment regimen,and number of treatment lines(P<0.05)could serve as the independent predictive prognosis of immunotherapy for advanced gastric cancer.Conclusion SIINS can predict the prognosis of patients with advanced gastric cancer treated with PD-1 inhibitors.

Objective:To observe the clinical effect of computed tomography(CT)-guided hematoma puncture drainage surgery combined with high-dose(≥50 000 U)urokinase in treating hypertensive intracerebral hemorrhage.Methods:The case data of a total of 90 patients with hypertensive intracerebral hemorrhage who underwent treatment in Zhangjiakou First Hospital from January 2022 to January 2023 were retrospectively selected as the study subjects.They were divided into a control group and an observation group using the average method,with 45 cases in each group.The conventional group received CT-guided hematoma puncture drainage surgery combined with conventional dose urokinase(20 000 U),while the observation group received CT-guided hematoma puncture drainage surgery combined with high-dose urokinase(50 000 U),with a 6-month follow-up for all patients.The changes of hematoma volume,length of hospital stay,levels of inflammatory indicators,the levels of hemodynamics,clinical efficacy,and incidence of postoperative complications after treatment between two groups were analyzed and compared.Results:After treatment,the hematoma volume at the 1st day[(34.64±5.53)mm3]and the 7th day[(34.64±5.53)mm3]post surgery of observation group were significantly lower than those[(44.57±6.85)mm3 and(16.64±3.24)mm3]of conventional group,and the differences of them between the two groups were statistically significant(t=7.567,10.570,P<0.05),respectively.The length of hospital stay of observation group[(16.86±6.63)d]was significantly lower than that of the control group[(23.47±10.34)d](t=3.610,P<0.05).The levels of matrix metalloproteinase-9(MMP-9),interleukin-6(IL-6),C-reactive protein(CRP),tumor necrosis factor-α(TNF-α)at 7th days post surgery of observation group were significantly lower than those of conventional group,and the differences of them between the two groups were statistically significant(t=5.826,10.202,7.661,2.724,P<0.05),respectively.The blood flow levels of middle cerebral artery(MCA),anterior cerebral artery(ACA),and posterior cerebral artery(PCA)after surgery in observation group were significantly higher than those in conventional group(t=2.833,3.329,3.973,P<0.05),respectively.The effective rate of treatment in observation group(95.56%)was significantly higher than that in conventional group(80.00%),and the difference was significant(x2=5.075,P<0.05).There was no significant difference in the incidence of postoperative complications between the two groups(P>0.05).Conclusion:CT-guided hematoma puncture drainage surgery combined with high-dose urokinase can significantly increase the dissolution rate of hematoma,and reduce the body's inflammatory response,and improve cerebral hemodynamic indicators,and effectively enhance clinical efficacy in treating hypertensive intracerebral hemorrhage,which have better treatment safety.

Objective:This study based on comprehensive bioinformatics technology aimed to investigate the pathogenesis of ferroptosis in IgA nephropathy(IgAN)from an immunological perspective,and to identify the key genes and functional pathways.Methods:Differentially expressed ferroptosis-related genes(DE-FRGs)were identified from GSE93798 and analyzed by Kyoto Ency-clopedia of Genes and Genomes(KEGG)and Gene Ontology(GO).STRING and Cytoscape were used to construct a protein-protein interaction(PPI)network.Degree and MCODE algorithm were run.Combining LASSO regression,SVM-RFE and PLS-DA machine learning to construct the optimal feature selection hub gene.Cibersort and ssGESA algorithms were used to assess the immune infiltra-tion,as well as to explore the relationship between hub genes and immune infiltration.Single cell RNA sequence(scRNA-seq)data was used to analyze the location of hub genes in IgAN cell populations.Gene Set Enrichment Analysis(GSEA)was performed on hub genes.The HPA database was used to obtain the position of the specific protein of the hub genes,and the DsigDB database was used to predict the target drug.The GSE37460,GSE116626 and GSE73953 were treated as validation sets and diagnostic effectiveness evalua-tion.Collecting IgAN and healthy kidney tissue for immunohistochemical testing of hub genes expression.Results:This study identi-fied 94 DE-FRGs and 3 hub genes(JJUN,EGR1 and DDR2).KEGG and GO analysis indicated that the DE-FRGs were mainly con-centrated in pathways of ferroptosis,reactive oxygen species,responsing to oxidative stress and metal particles,mitochondrion,and transcriptional regulatory complex.GESA analysis involved in amino acid and fatty acid metabolism.The analysis of immune cell infil-tration in IgAN revealed an increased ratio of naive B cells,mast cells,and CD4+T cells.Differential analysis of immune function re-vealed that mechanisms such as chemokine receptor signaling pathways,human leukocyte antigen signaling pathways,and inflamma-tion promotion were more active in IgAN.Furthermore,the correlation was observed between immune infiltration and hub genes.ScRNA-seq analysis demonstrated that hub genes were localized in monocytes,macrophages,poximal convoluted tubule cells,princi-pal cells,and smooth muscle cells.Validations set analysis suggested that JUN and SIRT1 had a diagnostic value.The HPA database analysis showed that JUN was mainly located in the nucleus,while EGR1 was located in the membrane and cytoplasm.The 2 278 po-tential drugs for the treatment of IgAN were predicted.Finally,the results of immunohistochemistry and bioinformatics analysis were consistent.Conclusion:Ferroptosis may be associated with immune cell infiltration and immune related function during the occur-rence and development of IgAN.

Objective:To analyze the echocardiographic and genetic characteristics of fetuses with common arterial trunk（CAT）.Methods:A retrospective analysis was conducted on 77 480 fetal echocardiograms examined at the Maternal-Fetal Medicine center in Fetal Heart Disease of Beijing Anzhen Hospital from November 2010 to November 2024.Among them，106 fetuses were initially diagnosed with CAT，and 95 cases were ultimately confirmed（0.1%，95/77 480）. The echocardiographic and genetic features of CAT fetuses were analyzed. According to the modified Van Praagh classification，CAT was divided into types A1-A4［with ventricular septal defect（VSD）］and B1-B4（without VSD）based on the origin of the pulmonary artery branches and the presence or absence of a VSD. Additionally，CAT was categorized into isolated and complex types based on the presence of associated intracardiac or extracardiac anomalies.Results:① Among the 95 confirmed CAT fetuses，type A accounted for 90.5%（86/95），and type B accounted for 9.5%（9/95）. All 9 type B CAT fetuses exhibited no overriding of the arterial trunk ， with 8 cases showing left ventricular hypoplasia accompanied by mitral atresia or absence.② Of the 95 CAT fetuses，14 were isolated（14.7%，14/95） ， and 81 were complex（85.3%，81/95）.The main associated intracardiac anomalies included：single ventricle（22 cases），complete atrioventricular septal defect（12 cases），anomalous pulmonary venous drainage（10 cases），right aortic arch with mirror-image branching（16 cases），and persistent left superior vena cava（14 cases）. ③ Genetic testing was performed in 31 fetuses，with 18 showing positive results，primarily 22q11.21 deletion syndrome（29.0%，9/31）. Conclusions:Apart from VSD，the most common intracardiac anomaly associated with CAT fetuses is single ventricle. Type B CAT without trunk overriding is often associated with left ventricular hypoplasia and mitral atresia or absence. The most frequent genetic abnormality in CAT fetuses is 22q11.21 deletion syndrome. Prenatal echocardiography should clarify the CAT subtype and associated anomalies，and genetic testing is strongly recommended for perinatal counseling and prognostic evaluation.