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.

The technologies for ovarian tissue cryopreservation and entire process for ovarian tissue cryopreservation and transplantation were introduced,and the medical equipment configuration was summarized for each stage of ovarian tissue cryopreservation and transplantation.Detailed plans and management methods were proposed for the medical equipment configuration of ovarian tissue cryopreservation and transplantation,and relevant precautions,possible problems and solutions during the process were put forward.References were provided for medical institutions planning to carry out ovarian tissue cryopreservation and transplantation.[Chinese Medical Equipment Journal,2025,46(4):63-69]

Objective To explore the mechanism of Jiawei Jisheng Shenqi Decoction in improving the hypoxic microenvironment and antagonizing liver cirrhosis.Methods In vivo experiments were conducted using a rat model of carbon tetrachloride(CCL4)-induced liver cirrhosis.Rats were divided into normal,model,colchicine,JWJSSQ low-dose,JWJSSQ medium-dose,and JWJSSQ high-dose group.Pathological changes in liver tissues in each group were examined by hematoxylin and eosin(HE)and Masson staining,changes in serum liver function were detected using test kits,levels of hyaluronic acid(HA),laminin(LN),procollagen Ⅲ(PC Ⅲ),and collagen typeⅣ(COL4)were detected by enzyme-linked immunosorbent assay(ELISA),and protein expression levels of hypoxia-inducible factor-1α(HIF-1α),Notch1,Jagged1,and α-smooth muscle actin(α-SMA)were detected by Western blot.In vitro experiments were conducted in HSC-T6 cells,and the optimal concentration of CoCl2(100 μ mol/L,200μmol/L,400 μmol/L,600 μmol/L and 800 μmol/L)in the cultured cells and the optimal concentration of drug-containing serum(5％,10％,15％,20％)were determined by Cell Counting Kit-8(CCK-8)assay.The migration ability of cells in each group was detected by scratch testing,and changes in the apoptosis rates were determined by flow cytometry.Protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,matrix metallopeptidase 9(MMP9),and tissue inhibitor of metalloproteinases 1(TIMP-1)were detected by Western blot.Results In the in vivo experiments,liver swelling,inflammatory cell infiltration,collagen deposition,and the appearance of pseudolobules were significantly increased in the model group compared with those in the normal group.Serum levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),HA,LN,PCⅢ,and COL4 were significantly increased and albumin(ALB)was significantly decreased in the model group,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were significantly increased(P＜0.01).Liver swelling,inflammatory cell infiltration,and collagen deposition were significantly reduced in each treatment group compared with those in the model group,and the degree of fibrosis was reduced.Serum ALT,AST,HA,LN,PCⅢ,and COL4 were significantly decreased and ALB was significantly increased,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were also significantly decreased to varying degrees(P＜0.05).In the in vitro experiments,hypoxia promoted HSC-T6 migration and reduced apoptosis,increased the protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1,and reduced the expression levels of MMP9(P＜0.01).Serum containing Jiawei Jisheng Shenqi Decoction inhibited HSC-T6 migration,promoted HSC-T6 apoptosis,lowered the expression of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1 proteins,and enhanced the expression of MMP9 protein(P＜0.01).The inhibitory effect of Jiawei Jisheng Shenqi on HSC-T6 cell activation was reversed by the HIF-1α agonist dimethyloxalylglycine.Conclusions Jiawei Jisheng Shenqi Decoction can improve the hypoxic microenvironment via the HIF-1α/Notch pathway,thereby exerting an anti-liver cirrhosis effect.

Aim To investigate the possible mechanism of the myocardial protective effect of Danzhi Jiangtang capsules(DJC)on db/db mice based on NLRP3 in-flammasome-mediated pyroptosis.Methods The db/db mice were randomly divided into the model group,DJC low,medium,and high dose groups,and the met-formin group,and the db/m mice were taken as the blank group.The administration lasted for eightweeks.At the end of drug administration,blood glucose,blood lipids,cardiac enzymes and inflammatory factors were detected in each group of mice.HE and Masson stai-ning was performed to observe the morphology and fi-brosis of myocardial tissue.TUNEL staining was per-formed to detect apoptosis.RT-qPCR was performed to detect the mRNA expression of ANP,BNP and β-MHC,and Western blot was performed to detect the protein expression of NLRP3,ASC,caspase-1,cleaved-caspase-1,GSDMD and GSDMD-NT in myocardial tis-sue.Results DJC could alleviate myocardial patho-logical damage,reduce collagen deposition and apopto-sis,reduce the levels of blood glucose,blood lipid,myo-cardial enzyme and inflammatory factors in db/db mice.DJC could reduce the mRNA expressions of ANP,BNP and β-MHC,and the protein expressions of NLRP3,ASC,caspase-1,cleavedcaspase-1,GSDMD and GSDMD-NT in myocardial tissues.Conclusion DJC attenuates myocardial injury in db/db mice,prob-ably by inhibiting the activation of NLRP3 inflamma-somes,attenuating cardiomyocyte pyroptosis,and amel-iorating the inflammatory state.

Objective:To assess the efficacy of "three-step" strategy for preparing autologous pedicled nasal mucosal flaps in repairing cerebrospinal fluid（CSF） leaks following transsphenoidal pituitary adenoma surgery. Methods:A retrospective study was conducted on the clinical data of 25 patients who developed CSF leaks after transsphenoidal pituitary adenoma surgery at the First Affiliated Hospital of Kunming Medical University between July 2012 and June 2022. Surgical repair was selected step by step using nasal septal mucosal flap with either the posterior septal artery or septal branch of the sphenopalatine artery as the pedicle, or a pedicled middle turbinate mucosal flap. All patients underwent ≥2-year endoscopic follow-up to assess flap viability and CSF leak recurrence. Results:The median postoperative hospital stay was 4 days. Five patients developed intracranial infections postoperatively. The follow-up period ranged from 2 to 12 years. Nasal endoscopic examinations showed good mucosal flap growth, with no recurrence of CSF leakage in any of the patients. Conclusion:High-flow cerebrospinal fluid（CSF） leaks following pituitary tumor surgery pose significant challenges for clinical repair. Based on intraoperative nasal septal mucosal preservation and the condition of sellar base CSF leakage, the "three-step" strategy for preparing autologous pedicled nasal mucosal flaps-utilizing posterior septal artery, ethmoidal artery-based, or pedicled middle turbinate mucosal flaps sequentially-is a safe and effective repair method.
Humans ; Retrospective Studies ; Pituitary Neoplasms/surgery* ; Surgical Flaps ; Nasal Mucosa/surgery* ; Cerebrospinal Fluid Leak/surgery* ; Adenoma/surgery* ; Postoperative Complications/surgery* ; Male ; Female ; Middle Aged ; Adult ; Aged

Objective:To investigate the effect of circular RNAs (circRNAs) expressions in peripheral blood of residents around radon hot springs.Methods:Totally 51 residents around radon hot springs were selected as the radon hot sping group, and another 51 residents around non-radon hot springs were selected as the control group. Questionnaires were used to collect demographic information and the radon exposure levels in the two groups. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative expressions of selected circRNA candidates in peripheral blood of the two groups. Mann-Whitney U test was used to compare the differences in the relative expressions of the circRNAs between the two groups. Results:The cumulative doses of radon exposure per capita for residents around radon hot springs was (111.47±99.03) mSv, with dose range 3.32-458.68 mSv. The difference in the relative expressions of hsa_circ_0040573 between the two groups was statistically significant ( Z=-2.88, P<0.05). The expression of hsa_circ_0040573 was suppressed by radon exposure ( t=-2.52, P<0.05) with a dose-dependent manner ( H=12.21, P<0.05). Conclusion:Hsa_circ_0040573 has a potential to serve as a radiological response biomarker for radon exposure, contributing to early diagnosis and monitoring of health risks associated with radon exposure.

AIM:To investigate the therapeutic effects and potential mechanism of pachymic acid(PA)on li-popolysaccharide(LPS)-induced acute kidney injury(AKI)in mice.METHODS:(1)Genes related to AKI were screened using the DAVID database.Core genes were identified by intersecting related genes and analyzed using Cyto-scape software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed through the DAVID database for the cross-targets.Molecular docking and activity assays were conducted on the primary core targets.(2)A total of 100 C57BL/6J mice were randomly divided into five groups:normal control(NC),model(LPS),solvent control(LPS+DMSO),and treatment groups(LPS+PA-10 and LPS+PA-20),with 20 mice in each group.The LPS-AKI model was established by intraperitoneal injection of 18 mg/kg LPS.The treatment groups received 10 mg/kg and 20 mg/kg PA,respectively,and the solvent control group was administered an equivalent dose of DMSO.Mice were euthanized 24 h after injection.Serum was collected for biochemical analysis,and Western blot was used to detect neutro-phil gelatinase-associated lipocalin(NGAL),kidney injury molecule-1(KIM-1),caspase-3,cleaved caspase-3,interleu-kin-1β(IL-1β),and monocyte chemoattractant protein-1(MCP-1)protein expression.RT-qPCR was employed to detect inflammatory factor mRNA levels.Molecular docking was used to simulate the optimal binding site of PA to caspase-3.En-zyme activity assays were performed to assess caspase protein activity,and renal lesions were observed via hematoxylin and eosin(HE)staining.Apoptosis was detected by TUNEL staining.RESULTS:(1)Thirty-one potential targets of PA against AKI were identified through network pharmacology.GO and KEGG enrichment analyses indicated that these tar-gets were primarily involved in immune response,inflammatory processes,apoptosis and survival,angiogenesis and hemo-dynamics,oxidative stress,and endoplasmic reticulum stress.Key targets included CASP3(caspase-3),PTGS2,BCL2,CCL2,and CYP219.(2)PA treatment improved renal function and reduced tubular epithelial injury.It significantly de-creased NGAL,KIM-1,and cleaved caspase-3 protein levels,as well as inflammatory factors TNF-α,IL-1β,and MCP-1 mRNA and protein expression.PA also reduced apoptosis of renal tubular epithelial cells.Enzyme activity assays and mo-lecular docking revealed that PA exerted its anti-apoptotic effect by directly binding to caspase-3,thereby inhibiting its ac-tivation by caspase-8.CONCLUSION:PA demonstrated a therapeutic effect in LPS-AKI,potentially through the inhibi-tion of inflammatory factor synthesis and release,as well as the inhibition of caspase-3 activation by caspase-8,reducing apoptosis in renal tubular epithelial cells.

Radon, the only naturally occurring radioactive noble gas, is among the most common radioactive nuclides to which humans are exposed. Radon can induce various biological effects in the human body and is a risk factor for lung cancer. Circular RNAs (circRNAs) are stable, tissue-specific, and abundantly expressed in body fluids. circRNAs can regulate gene expression and play an important role in the development of cancer. In this paper, we summarized the changes in the expression and function of circRNAs, highlighting the potential mechanisms of circRNAs in radon exposure-induced cancers. Our results provided theoretical support for the use of circRNAs as a biomarker of radon exposure-induced radiation damage, and offer a theoretical basis for the early diagnosis, treatment, and prevention of radon exposure-induced diseases.