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.

ObjectiveTranscranial magneto-acoustic stimulation (TMAS) is an emerging non-invasive neuromodulation technique that may provide a novel non-pharmacological intervention strategy for Parkinson's disease (PD). PD is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to motor impairments such as bradykinesia, tremor, and rigidity. Increasing evidence indicates that mitochondrial dysfunction and impaired mitochondrial quality control are central mechanisms underlying dopaminergic neuronal loss. In particular, abnormalities in mitophagy and mitochondrial fission-fusion balance contribute substantially to oxidative stress, energy metabolic failure, and neuronal injury. At present, most clinical treatments for PD mainly alleviate symptoms but do not effectively halt disease progression. Therefore, exploring new interventions targeting the core pathological mechanisms is of considerable significance. This study aims to investigate whether TMAS can improve neural damage and motor dysfunction in PD mice by regulating mitophagy and the fission/fusion dynamic balance, thereby providing theoretical and experimental support for its application in PD treatment. MethodsMale C57BL/6 mice were used in this study. A PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days. After model induction, mice in the intervention group received TMAS once daily for 14 consecutive days, whereas the corresponding control group received sham stimulation. The stimulation target was positioned over the primary motor cortex (M1). Motor performance was evaluated using the pole test and the open-field test. To verify the activation effect of TMAS on the target cortical region, c-Fos immunohistochemistry was performed in the M1. To assess nigral dopaminergic neuronal injury, tyrosine hydroxylase (TH) immunohistochemistry was used to quantify TH-positive neurons in the SNc. Mitochondrial function was evaluated by measuring reactive oxygen species (ROS) levels and adenosine triphosphate (ATP) content in the SNc. Western blot was further performed to determine the expression of mitophagy-related proteins, including PINK1, Parkin, LC3-II, and p62, as well as mitochondrial dynamics-related proteins, including Drp1 and Opa1. ResultsTMAS significantly increased the number of c-Fos-positive cells in M1 (P<0.000 1), indicating effective activation of neurons in the targeted cortical region. Compared with the control group, MPTP-treated mice exhibited marked motor dysfunction, including a significant reduction in total distance traveled in the open-field test (P<0.000 1) and mean speed (P=0.000 1), as well as significant prolongation of turn time and total climbing time in the pole test (P<0.000 1). These behavioral impairments were accompanied by a substantial loss of TH-positive dopaminergic neurons in the SNc, whereas TMAS significantly increased TH-positive neuron survival (P<0.000 1). In parallel, MPTP induced a pronounced increase in ROS levels and a significant reduction in ATP content, indicating severe mitochondrial dysfunction and energy metabolism impairment (P<0.01). TMAS treatment significantly improved motor performance, as reflected by the reversal of MPTP-induced impairment in the open-field and pole tests, and significantly reduced ROS accumulation (P<0.01) while restoring ATP production (P<0.001). At the molecular level, MPTP markedly downregulated PINK1 and Parkin, decreased p62 expression, increased LC3-II accumulation, elevated Drp1 expression, and reduced Opa1 expression, whereas TMAS significantly reversed these abnormalities, suggesting restoration of mitophagy-related mitochondrial quality control and re-establishment of mitochondrial fission-fusion balance. Collectively, these findings indicate that TMAS ameliorates MPTP-induced neurotoxicity and restores mitochondrial homeostasis and energy metabolism. ConclusionTMAS effectively attenuates neural damage and improves motor dysfunction in MPTP-induced PD mice. Its neuroprotective effects are closely associated with multidimensional regulation of the mitochondrial quality control system, including restoration of PINK1/Parkin-mediated mitophagy and rebalancing of Drp1/Opa1-related mitochondrial dynamics. Rather than acting only as a symptomatic neuromodulatory intervention, TMAS may influence a key pathological axis of PD by improving mitochondrial homeostasis in SNc and protecting nigral dopaminergic neurons. These findings provide experimental evidence supporting TMAS as a promising non-invasive physical intervention for PD.

ObjectiveTranscranial magneto-acoustic stimulation (TMAS) is an emerging non-invasive neuromodulation technique that may provide a novel non-pharmacological intervention strategy for Parkinson's disease (PD). PD is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to motor impairments such as bradykinesia, tremor, and rigidity. Increasing evidence indicates that mitochondrial dysfunction and impaired mitochondrial quality control are central mechanisms underlying dopaminergic neuronal loss. In particular, abnormalities in mitophagy and mitochondrial fission-fusion balance contribute substantially to oxidative stress, energy metabolic failure, and neuronal injury. At present, most clinical treatments for PD mainly alleviate symptoms but do not effectively halt disease progression. Therefore, exploring new interventions targeting the core pathological mechanisms is of considerable significance. This study aims to investigate whether TMAS can improve neural damage and motor dysfunction in PD mice by regulating mitophagy and the fission/fusion dynamic balance, thereby providing theoretical and experimental support for its application in PD treatment. MethodsMale C57BL/6 mice were used in this study. A PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days. After model induction, mice in the intervention group received TMAS once daily for 14 consecutive days, whereas the corresponding control group received sham stimulation. The stimulation target was positioned over the primary motor cortex (M1). Motor performance was evaluated using the pole test and the open-field test. To verify the activation effect of TMAS on the target cortical region, c-Fos immunohistochemistry was performed in the M1. To assess nigral dopaminergic neuronal injury, tyrosine hydroxylase (TH) immunohistochemistry was used to quantify TH-positive neurons in the SNc. Mitochondrial function was evaluated by measuring reactive oxygen species (ROS) levels and adenosine triphosphate (ATP) content in the SNc. Western blot was further performed to determine the expression of mitophagy-related proteins, including PINK1, Parkin, LC3-II, and p62, as well as mitochondrial dynamics-related proteins, including Drp1 and Opa1. ResultsTMAS significantly increased the number of c-Fos-positive cells in M1 (P<0.000 1), indicating effective activation of neurons in the targeted cortical region. Compared with the control group, MPTP-treated mice exhibited marked motor dysfunction, including a significant reduction in total distance traveled in the open-field test (P<0.000 1) and mean speed (P=0.000 1), as well as significant prolongation of turn time and total climbing time in the pole test (P<0.000 1). These behavioral impairments were accompanied by a substantial loss of TH-positive dopaminergic neurons in the SNc, whereas TMAS significantly increased TH-positive neuron survival (P<0.000 1). In parallel, MPTP induced a pronounced increase in ROS levels and a significant reduction in ATP content, indicating severe mitochondrial dysfunction and energy metabolism impairment (P<0.01). TMAS treatment significantly improved motor performance, as reflected by the reversal of MPTP-induced impairment in the open-field and pole tests, and significantly reduced ROS accumulation (P<0.01) while restoring ATP production (P<0.001). At the molecular level, MPTP markedly downregulated PINK1 and Parkin, decreased p62 expression, increased LC3-II accumulation, elevated Drp1 expression, and reduced Opa1 expression, whereas TMAS significantly reversed these abnormalities, suggesting restoration of mitophagy-related mitochondrial quality control and re-establishment of mitochondrial fission-fusion balance. Collectively, these findings indicate that TMAS ameliorates MPTP-induced neurotoxicity and restores mitochondrial homeostasis and energy metabolism. ConclusionTMAS effectively attenuates neural damage and improves motor dysfunction in MPTP-induced PD mice. Its neuroprotective effects are closely associated with multidimensional regulation of the mitochondrial quality control system, including restoration of PINK1/Parkin-mediated mitophagy and rebalancing of Drp1/Opa1-related mitochondrial dynamics. Rather than acting only as a symptomatic neuromodulatory intervention, TMAS may influence a key pathological axis of PD by improving mitochondrial homeostasis in SNc and protecting nigral dopaminergic neurons. These findings provide experimental evidence supporting TMAS as a promising non-invasive physical intervention for PD.

Digestive system tumors account for more than half of all malignant tumors in terms of incidence and mortality,and thus pose a serious threat to human health.Haptoglobin(Hp)is an acute-phase glycoprotein that is elevated in both plasma and tumor tissues in various clinical conditions,including different types of cancer,such as liver,gastric,colorectal,pancreatic,and gallbladder cancer.Numerous studies have indicated that Hp plays a significant role in the prognosis of cancer patients,highlighting its potential as a prognostic marker for gastrointestinal tumors,with important clinical applications.Despite its demonstrated crucial role in the development of various tumors,however,the specific mechanisms of Hp in gastrointestinal tumors remain controversial.This review considers the differential expression and clinical significance of Hp in the five major types of gastrointestinal tumors,to explore its role in different stages of cancer progression and prognosis.This review thus aims to provide reliable and accurate serum biomarkers for the screening,early diagnosis,treatment,and prognosis monitoring of gastrointestinal tumors,with important implications for predicting the survival and prognosis of cancer patients.

Objective To investigate the effects of miR-362-3p on the proliferation,migration and invasion of esophageal cancer EC9706 cells and its molecular mechanism.Methods The cancerous tissues and adjacent tissues of 30 patients with esophageal cancer from January 2018 to January 2020 were selected,and human normal esophageal epithelial cells HET-1 A and esophageal cancer cells EC9706,TE10,KYSE-140,KYSE-150 were cultured in vitro.Real-time fluorescence quantitative PCR(RT-qPCR)was used to detect the expression levels of miR-362-3p and dual specificity phosphatase 10(DUSP10)mRNA in tissues and cells.EC9706 cells were divided into NC group(normally cultured),miR-NC group(transfected miR-362-3p mimic NC)and miR-362-3p group(transfected miR-362-3p mimic),si-NC group(transfected with DUSP10 siRNA NC),si-DUSP10 group(transfected with DUSP10 siRNA),miR-362-3p+pcDNA group(co-transfected with miR-362-3p mimic and pcDNA3.1-DUSP10 NC)and miR-362-3p+pcDNA-DUSP10 group(co-transfected with miR-362-3p mimic and pcDNA3.1-DUSP10).The expression levels of miR-362-3p and DUSP10 mRNA in each group were detected by RT-qPCR.Cell proliferation activity was detected by MTT assay.Cell migration and invasion were detected by Transwell assay.The expressions of DUSP10,CyclinD1,p21,matrix metalloproteinase(MMP)-2 and MMP-9 were detected by Western blot.Dual luciferase reporter gene assay was used to detect the targeting relationship between miR-362-3p and DUSP10.Results The expression of miR-362-3p was high and DUSP10 was low in esophageal cancer tissues and cells.Overexpression of miR-362-3p or knockdown of DUSP10 expression significantly reduced the activity,migration and invasion number and the expression of CyclinD1,MMP-2 and MMP-9,and significantly increased the expression of p21 in EC9706 cells(P＜0.05).miR-362-3p targeted the expression of DUSP10(P＜0.05).And up-regulation of DUSP10 expression partially reversed the effects of overexpression of miR-362-3p on the proliferation,migration and invasion of EC9706 cells(P＜0.05).Conclusion miR-362-3p can inhibit the proliferation,migration and invasion of EC9706 cells by down-regulating the expression of DUSP10.

Objective:This study addresses the challenges of data governance for non-computerized instruments in the context of pharmaceutical industry 4.0,proposing an intelligent transformation solution to overcome traditional data management bottlenecks.Methods and Results:By constructing a three-tier technical framework"net-worked architecture,highly compatible connectivity,and tamper-proof conversion":USB middleware is deployed to enable real-time data transmission from multiple instruments.Algorithms convert editable formats into non-editable files compliant with FDA 21 CFR Part 11 in real time;an automated backup system ensures data redundancy.Conclusion:Key innovations include a non-invasive transformation mode and an networked layout,offering a cost-effective pathway for upgrading traditional instruments to meet GxP standards.This research bridges the technical gap in data integrity management for non-computerized systems,ensuring regulatory compliance and operational efficiency.

Objective:To address the critical issue of missing dynamic border molding information in edentulous direct digital impression technology, this study explores innovative digital solutions and conducts preliminary application validation.Methods:Based on the myostatic line theory, a methodology was established: intraoral scanner (IOS) high-frequency video was utilized to dynamically capture functional molding data of soft tissues, integrated with a self-developed mobility gradient recognition algorithm to achieve dynamic threshold segmentation between the muscle dynamic zone and myostatic zone, termed "optical digital molding technology". Ten edentulous patients with well-fitting complete dentures, treated at the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2024 to December 2024, were enrolled. The standard deviation between the muscle static line (generated by mobility gradient algorithm with thresholds of 0.3-0.7 mm) and the denture border curve was analyzed to optimize the dynamic threshold, followed by single-case clinical validation.Results:Among the mobility thresholds of 0.3-0.7 mm, the 0.5 mm threshold yielded the smallest standard deviation between the myostatic line and denture border. Clinical validation demonstrated that dentures designed with this threshold exhibited no displacement during dynamic functional tests, with marginal sealing meeting clinical standards.Conclusions:The optical digital border molding technique for edentulous soft tissue boundaries translates the myostatic line theory into quantifiable parameters for the first time. Based on data from 10 cases, a mobility threshold of 0.5 mm is recommended for clinical application.

Objective To design a night vision simulation training system to provide pilots with practical training on ground night vision goggles.Methods The system had its hardware composed of a control stick,a throttle lever,rudder pedals,a head-up display(HUD),a control box,a computer,a projector and a screen.The HUD and control box were designed using night vision-compatible lighting technology to simulate the ambient light conditions pilots experienced when flying with night vision goggles.The software of the system consisted of five ones developed with C++programming languge for visual scene simulation,instrument simulation,flight performance simulation,integrated management control and cockpit manage-ment.Night vision images and computer-rendered images of typical scenes with varying brightness levels were collected.Objective image evaluation metrics such as contrast and brightness were used as inputs,while subjective evaluation data served as outputs to construct and train a support vector machine(SVM)model.Totally 30 typical night vision training scenarios were selected based on model validation and optimization to evaluate the system's optical fidelity.Results The average fidelity score for the 30 typical night vision training scenarios was 8.05,indicating that the system could realistically simulate terrain and landscapes under various lighting and weather conditions during night flights and static and dynamic targets in the air,on the ground and at sea.Conclusion The system meets the desired requirements and effectively facilitates night vision training for pilots.[Chinese Medical Equipment Journal,2025,46(3):21-26]

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.