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:In vitro construction of tissue-engineered intestinal models plays an important role in intestinal regeneration and intestinal disease research.The interaction of intestinal nervous system and intestinal epithelial barrier to maintain body homeostasis is a hot topic in the bionic construction of tissue-engineered intestinal tract.OBJECTIVE:To construct a bionic model that can mimic the enteric nervous system in vivo.METHODS:Using fibroin protein with villus structure as scaffold,human induced neural stem cells solidified with collagen were added to intestinal epithelial cells(Caco-2 and HT29-MTX-E12)for 3-day culture to construct a co-culture system of intestinal epithelial cells and nerve cells(co-culture group).Human induced neural stem cells or intestinal epithelial cells cultured alone that were inoculated with fibroin scaffolds were set as controls.Cell morphology was observed by scanning electron microscopy and hematoxylin-eosin staining.Cell activity was detected by Live/Dead cell staining.Human induced neural stem cell differentiation was detected by β-microtubulin immunofluorescence staining.Intestinal epithelial histological properties and barrier function were detected by microvillin,sucrase-isomaltase,tight junction protein 1,E-calmodulin,and mucin-2 immunofluorescence staining.The function of mucus secretion from intestinal epithelial cells was detected by Alcian blue staining.Alkaline phosphatase staining was performed to detect differentiation of intestinal epithelial cells,at the same time,sucrase-isomaltase,tight junction protein 1,and alkaline phosphatase mRNAs were detected by RT-qRCR.RESULTS AND CONCLUSION:The neuralized intestinal mucosal co-culture model with villi structure was successfully constructed,and neural stem cells and intestinal epithelial cells on the fibroin scaffold showed good cellular activities.After neuralization,the activity of alkaline phosphatase and sucrase-isomaltase in intestinal epithelial cells was enhanced,while the expression level of tight junction protein 1 was up-regulated.To conclude,the neuralized bionic intestinal epithelial model is beneficial to the maturation of intestinal mucosal epithelial cells and the formation of barrier function.

BACKGROUND:Triptolide,a bioactive component of the traditional Chinese medicine Tripterygium wilfordii,has a certain protective effect on neurons.OBJECTIVE:To investigate the effect of triptolide on cerebral ischemia/reperfusion injury.METHODS:(1)Cell experiment:Hippocampal neurons(HT22 cells)were randomly divided into control group,glucose oxygen deprivation/reoxygenation(OGD/R)group,OGD/R+triptolide group,OGD/R+triptolide+si-TIGAR group,OGD/R+si-TIGAR group,and OGD/R+triptolide+rapamycin group.HT22 cell viability was detected by cell counting kit 8.Tp53-induced glycolysis and apoptosis factors,glutathione peroxidase 4,7 members of the solsolic vector family 11,sphingosine kinase 1(SPHK1)and(mTOR)were detected by western blot assay.Glutathione,malondialdehyde and iron level were detected using the biochemical kit.(2)Animal experiment:Rats were randomly divided into sham surgery group,model group,and triptolide group.Cerebral artery occlusion/reperfusion rat models were prepared in the latter two groups.Rats in the triptolide group were orally administered 50 mg/kg triptolide for 7 days.Twenty-four hours after administration,LONGA method was used to evaluate the neurological impairment of rats,TTC method was used to observe the conditions of cerebral infarction,TUNEL staining was used to detect cell apoptosis,and western blot was performed to detect the expression level of related proteins.RESULTS AND CONCLUSION:(1)At the cellular level,triptolide promoted cell viability and inhibited apoptosis in HT22 cells treated with OGD/R.Triptolide also increased the expression levels of Tp53-induced glycolysis and apoptosis factors,glutathione peroxidase 4,and 7 members of the solsolic vector family 11,activated the SPHK1/mTOR pathway,increased glutathione content,inhibited malondialdehyde content and iron levels.Rapamycin treatment counteracted the protective effect of triptolide on HT22 cells.(2)At the animal level,triptolide significantly reduced neurological deficits,infarct volume,and cell apoptosis,and inhibited neuronal ferroptosis in brain tissue of rats.To conclude,triptolide can inhibit ferroptosis by upregulating the expression level of Tp53-induced glycolysis and apoptosis factors and activating the SPHK1/mTOR signaling,and thereby reduced cerebral ischemia/reperfusion injury.These findings suggest that triptolide may be a candidate drug for the treatment of cerebral ischemia/reperfusion injury.

BACKGROUND:As a mainstream surgical technique for the treatment of cervical spondylotic myelopathy through the anterior cervical subtotal decompression and bone graft fusion,it has many advantages.However,due to the high risk of this surgery and the particularity of the cervical anatomy,it is also a challenge for the surgeon.The gradual maturity of 3D printing technology and the continuous development of applications in the medical field are now able to provide more perfect personalized treatment.OBJECTIVE:To investigate the efficacy of 3D printed titanium cage cutting model in anterior cervical vertebrae subtotal decompression and bone graft fusion.METHODS:Medical records of 57 patients undergoing anterior cervical corpectomy decompression and fusion surgery admitted to the Department of Spine Surgery of Affiliated Hospital of Yan'an University from April 2021 to April 2023 were retrospectively analyzed.According to whether the 3D printed titanium cage cutting model was used in the operation,the patients were divided into the traditional titanium cage bone grafting group(control group,n=30)and the 3D printed titanium cage model group(observation group,n=27).The general data,amount of blood loss during operation,number ofC-arm X-ray machine fluoroscopy during operation,operation time,as well as anterior intervertebral edge height(H1),posterior intervertebral edge height(H2)and C2-C7 Cobb angle of the two groups measured on the cervical lateral X-ray films before,3 days and 6 months after operation were recorded and analyzed.The settling degree of the titanium cage was assessed with the distance of the height of the anterior and posterior edges of the vertebral body at 3 days and 6 months after surgery.Visual analog scale was used to evaluate neck pain and Japanese Orthopaedic Association was used to evaluate nerve function.RESULTS AND CONCLUSION:(1)Follow-up was conducted for at least 6 months.(2)The amount of intraoperative blood loss and fluoroscopy times in the observation group were less than those in the control group(P＜0.05).The operative time of the observation group was significantly shorter than that of the control group(P＜0.05).(3)There were no significant differences in C2-C7 Cobb angle,visual analog scale score,Japanese Orthopaedic Association score,anterior vertebral border height(H1)and posterior vertebral border height(H2)before surgery,3 days and 6 months after surgery between the two groups(P＞0.05).(4)There were five patients in the observation group(with severe subsidence rate of 19％)with severe subsidence at the anterior and posterior edges of the surgical segment,and seven patients in the control group(with severe subsidence rate of 23％)with severe subsidence(H1 or H2 subsidence≥3 mm)at the surgical segment 6 months after surgery.There was no significant difference in the rate of severe subsidence of titanium cage between the two groups(P＞0.05).(5)At the last follow-up,bone fusion was achieved at the operative level in both groups,and there was no statistical significance in bone graft fusion rate between the two groups(P＞0.05).(6)The results showed that the application of 3D printed titanium cage cutting model in anterior cervical corpectomy decompression and fusion surgery had the same clinical effect as that of traditional surgery,but the former could effectively reduce the fluoroscopy times of C-arm X-ray machine,the amount of blood loss and the operation time,and had unique advantages in the pruning and implantation of titanium cage during surgery.

BACKGROUND:The local immune microenvironment plays an important regulatory role in the process of bone formation,and the immune system is intricately linked to the skeletal system.OBJECTIVE:To systematically review the promotion of bone regeneration from three aspects:immune cell regulation of microenvironment,regulation of immune response by small extracellular vesicles,and induction of immune response by bone biomaterials,and to elucidate the immune regulatory mechanisms involved in bone regeneration.METHODS:Relevant literature was retrieved from PubMed,CNKI,WanFang Database,and VIP Database,using the search terms of"osteoimmunology,immune microenvironment,small extracellular vesicles,bone regeneration,bone tissue repair,biomaterials,and tissue engineering"in English and Chinese.Repeat and irrelevant literature was screened and removed,and 92 articles that met the criteria were selected for intensive reading and review.RESULTS AND CONCLUSION:Multiple immune cells and bone cells are in the same microenvironment,and immune cells can regulate the differentiation and activity of bone cells,collectively forming an immune microenvironment that affects bone regeneration.Neutrophils can significantly reduce local inflammatory responses in the early stages of bone injury,creating a favorable microenvironment for bone regeneration.M1 macrophages can clear foreign bodies and reduce early inflammatory responses,while M2 macrophages can promote the expression of osteogenic markers and factors,playing an important role in the repair process of bone injury.B cells and T cells can directly or indirectly affect the generation and activity of osteoblasts and osteoclasts,regulate bone metabolism,and promote bone regeneration.Extracellular vesicles of small cells regulate the local immune microenvironment through paracrine secretion,promoting bone formation and angiogenesis at the site of bone injury.The metal ions,surface hydrophilicity,porosity,pore size,surface morphology,and surface roughness on the surface of biomaterials can directly regulate local immune responses,and have anti-inflammatory,angiogenic,and osteogenic effects,thereby accelerating bone regeneration.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

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:In vitro construction of tissue-engineered intestinal models plays an important role in intestinal regeneration and intestinal disease research.The interaction of intestinal nervous system and intestinal epithelial barrier to maintain body homeostasis is a hot topic in the bionic construction of tissue-engineered intestinal tract.OBJECTIVE:To construct a bionic model that can mimic the enteric nervous system in vivo.METHODS:Using fibroin protein with villus structure as scaffold,human induced neural stem cells solidified with collagen were added to intestinal epithelial cells(Caco-2 and HT29-MTX-E12)for 3-day culture to construct a co-culture system of intestinal epithelial cells and nerve cells(co-culture group).Human induced neural stem cells or intestinal epithelial cells cultured alone that were inoculated with fibroin scaffolds were set as controls.Cell morphology was observed by scanning electron microscopy and hematoxylin-eosin staining.Cell activity was detected by Live/Dead cell staining.Human induced neural stem cell differentiation was detected by β-microtubulin immunofluorescence staining.Intestinal epithelial histological properties and barrier function were detected by microvillin,sucrase-isomaltase,tight junction protein 1,E-calmodulin,and mucin-2 immunofluorescence staining.The function of mucus secretion from intestinal epithelial cells was detected by Alcian blue staining.Alkaline phosphatase staining was performed to detect differentiation of intestinal epithelial cells,at the same time,sucrase-isomaltase,tight junction protein 1,and alkaline phosphatase mRNAs were detected by RT-qRCR.RESULTS AND CONCLUSION:The neuralized intestinal mucosal co-culture model with villi structure was successfully constructed,and neural stem cells and intestinal epithelial cells on the fibroin scaffold showed good cellular activities.After neuralization,the activity of alkaline phosphatase and sucrase-isomaltase in intestinal epithelial cells was enhanced,while the expression level of tight junction protein 1 was up-regulated.To conclude,the neuralized bionic intestinal epithelial model is beneficial to the maturation of intestinal mucosal epithelial cells and the formation of barrier function.

BACKGROUND:Triptolide,a bioactive component of the traditional Chinese medicine Tripterygium wilfordii,has a certain protective effect on neurons.OBJECTIVE:To investigate the effect of triptolide on cerebral ischemia/reperfusion injury.METHODS:(1)Cell experiment:Hippocampal neurons(HT22 cells)were randomly divided into control group,glucose oxygen deprivation/reoxygenation(OGD/R)group,OGD/R+triptolide group,OGD/R+triptolide+si-TIGAR group,OGD/R+si-TIGAR group,and OGD/R+triptolide+rapamycin group.HT22 cell viability was detected by cell counting kit 8.Tp53-induced glycolysis and apoptosis factors,glutathione peroxidase 4,7 members of the solsolic vector family 11,sphingosine kinase 1(SPHK1)and(mTOR)were detected by western blot assay.Glutathione,malondialdehyde and iron level were detected using the biochemical kit.(2)Animal experiment:Rats were randomly divided into sham surgery group,model group,and triptolide group.Cerebral artery occlusion/reperfusion rat models were prepared in the latter two groups.Rats in the triptolide group were orally administered 50 mg/kg triptolide for 7 days.Twenty-four hours after administration,LONGA method was used to evaluate the neurological impairment of rats,TTC method was used to observe the conditions of cerebral infarction,TUNEL staining was used to detect cell apoptosis,and western blot was performed to detect the expression level of related proteins.RESULTS AND CONCLUSION:(1)At the cellular level,triptolide promoted cell viability and inhibited apoptosis in HT22 cells treated with OGD/R.Triptolide also increased the expression levels of Tp53-induced glycolysis and apoptosis factors,glutathione peroxidase 4,and 7 members of the solsolic vector family 11,activated the SPHK1/mTOR pathway,increased glutathione content,inhibited malondialdehyde content and iron levels.Rapamycin treatment counteracted the protective effect of triptolide on HT22 cells.(2)At the animal level,triptolide significantly reduced neurological deficits,infarct volume,and cell apoptosis,and inhibited neuronal ferroptosis in brain tissue of rats.To conclude,triptolide can inhibit ferroptosis by upregulating the expression level of Tp53-induced glycolysis and apoptosis factors and activating the SPHK1/mTOR signaling,and thereby reduced cerebral ischemia/reperfusion injury.These findings suggest that triptolide may be a candidate drug for the treatment of cerebral ischemia/reperfusion injury.

BACKGROUND:As a mainstream surgical technique for the treatment of cervical spondylotic myelopathy through the anterior cervical subtotal decompression and bone graft fusion,it has many advantages.However,due to the high risk of this surgery and the particularity of the cervical anatomy,it is also a challenge for the surgeon.The gradual maturity of 3D printing technology and the continuous development of applications in the medical field are now able to provide more perfect personalized treatment.OBJECTIVE:To investigate the efficacy of 3D printed titanium cage cutting model in anterior cervical vertebrae subtotal decompression and bone graft fusion.METHODS:Medical records of 57 patients undergoing anterior cervical corpectomy decompression and fusion surgery admitted to the Department of Spine Surgery of Affiliated Hospital of Yan'an University from April 2021 to April 2023 were retrospectively analyzed.According to whether the 3D printed titanium cage cutting model was used in the operation,the patients were divided into the traditional titanium cage bone grafting group(control group,n=30)and the 3D printed titanium cage model group(observation group,n=27).The general data,amount of blood loss during operation,number ofC-arm X-ray machine fluoroscopy during operation,operation time,as well as anterior intervertebral edge height(H1),posterior intervertebral edge height(H2)and C2-C7 Cobb angle of the two groups measured on the cervical lateral X-ray films before,3 days and 6 months after operation were recorded and analyzed.The settling degree of the titanium cage was assessed with the distance of the height of the anterior and posterior edges of the vertebral body at 3 days and 6 months after surgery.Visual analog scale was used to evaluate neck pain and Japanese Orthopaedic Association was used to evaluate nerve function.RESULTS AND CONCLUSION:(1)Follow-up was conducted for at least 6 months.(2)The amount of intraoperative blood loss and fluoroscopy times in the observation group were less than those in the control group(P＜0.05).The operative time of the observation group was significantly shorter than that of the control group(P＜0.05).(3)There were no significant differences in C2-C7 Cobb angle,visual analog scale score,Japanese Orthopaedic Association score,anterior vertebral border height(H1)and posterior vertebral border height(H2)before surgery,3 days and 6 months after surgery between the two groups(P＞0.05).(4)There were five patients in the observation group(with severe subsidence rate of 19％)with severe subsidence at the anterior and posterior edges of the surgical segment,and seven patients in the control group(with severe subsidence rate of 23％)with severe subsidence(H1 or H2 subsidence≥3 mm)at the surgical segment 6 months after surgery.There was no significant difference in the rate of severe subsidence of titanium cage between the two groups(P＞0.05).(5)At the last follow-up,bone fusion was achieved at the operative level in both groups,and there was no statistical significance in bone graft fusion rate between the two groups(P＞0.05).(6)The results showed that the application of 3D printed titanium cage cutting model in anterior cervical corpectomy decompression and fusion surgery had the same clinical effect as that of traditional surgery,but the former could effectively reduce the fluoroscopy times of C-arm X-ray machine,the amount of blood loss and the operation time,and had unique advantages in the pruning and implantation of titanium cage during surgery.