BACKGROUND:Micro-robots have the characteristics of small size,flexibility,and strong targeting,and can complete complex tasks in a single or clustered manner in a narrow environment.With the continuous optimization of materials,preparation processes,and driving approaches,they have shown increasingly important application value in the field of biomedicine. OBJECTIVE:To analyze the application of field-driven micro-robots in medical field and to look forward to their application prospect. METHODS:Using"microrobots,nanorobots,drivers,biomedical,medical"as Chinese keywords and"microrobots,micro-robots,nanorobots,micromachine,microswimmer,medical"as English keywords,WanFang Data and PubMed databases were searched,respectively.The search time range was from January 2010 to January 2024,and a small number of long-term articles were included.Through reading the titles and preliminarily screening the abstracts,the repetitive studies,low-quality journals,and irrelevant literature were excluded.After reading the entire text,66 papers were finally included for review. RESULTS AND CONCLUSION:Field-driven medical micro-robots mainly include magnetic,optical,thermal,ultrasonic,and multi-mixed factor-driven robots.Field-driven robots have been used in intestinal diagnosis,drug targeting therapy,and stem cell therapy.Medical micro-robots are currently only used in a small number of clinical applications,but most of which are still in the theoretical and experimental stages.Medical micro-robots will face many challenges in future,such as large-scale preparation,precise control of micro-robots,recycling or degradation in vivo,whether the materials used will cause adverse reactions to the human body,and the related minimally invasive medical procedures.

Objective To construct a dynamic framework for bidirectional transitions of mild cognitive impairment(MCI),quantifying both rare reversion and high-risk progression trajectories in cognitive dynamics.Methods Patients diagnosed with MCI at baseline from 2005 to 2022 and completed at least two follow-up visits were selected from the Alzheimer's Disease Neuroimaging Initiative(ADNI),and a retrospective cohort was constructed.Demographic information,APOEε4 genotype,and neuropsychological scales data were collected.Longitudinal cognitive assessments were functionally reconstructed using multivariate functional principal component analysis(MFPCA),with functional principal components(FPCs)extracted based on cumulative variance contribution rate(PVE＞90％).Functional multi-state Markov models were developed to estimate inter-state transition intensities,year to year transition probabilities,and covariate effects.Results Among 1,019 MCI patients(4,657 follow-up visits),93(9.1％)reverted to normal cognition,while 359(35.2％)progressed to Alzheimer's disease(AD).Longitudinal trajectory analysis revealed significant heterogeneity:progressive MCI＞stable MCI＞reverted MCI in the first functional principal component(MFPC1)scores.The transition intensity for MCI reversion(0.020)was approximately one-fourth of the AD progression risk(0.086),but the post-reversion cognitive re-impairment intensity was 0.138.Reduced MFPC1(HR=0.993,95％Cl:0.991,0.995)and elevated MFPC2(HR=1.004,95％Cl:1.001,1.007)were closely associated with MCI reversion.Conclusion MCI exhibits marked heterogeneity in longitudinal cognitive trajectories.Although reversion is rare,reversed patients remain at high risk of cognitive re-impairment.

Purpose To investigate the clinicopathological features,diagnosis,and molecular genetic characteris-tics of central nervous system(CNS)high-grade neuroepithelial tumors with BCOR alterations.Methods Five cases of CNS high-grade neuroepithelial tumors harboring BCOR alterations were collected.Using immunohistochemistry and molecular detection to analyze its clinical and histological characteristics,and review relevant literatures.Results A-mong the 5 patients,3 cases with EP300 ∷ BCOR tumor(male-to-female ratio 2∶1).These tumors were located in supratentorial regions(right temporal lobe,right frontotemporal lobe,and right frontal lobe).The 2 patients with BCOR-ITD tumors were younger,both with tumors located in the left cerebellum.Imaging studies revealed well-defined large mass lesions in all cases.Histologically,all 5 cases tumor exhibited ependymoma-like or oligodendroglioma-like morphology,featuring uniformly oval or round cells.Focal areas showed increased cellular density,nuclear enlarge-ment,and readily identifiable mitotic figures indicative of anaplastic features.A rich capillary network was frequently observed in the stroma.Palisading necrosis,microcystic changes,and microcalcifications were present in 3 cases.Im-munohistochemically,all 5 cases consistently expressed vimentin and CD56,focal Olig-2 positivity,variable S-100 ex-pression,and were uniformly negative for GFAP.BCOR immunostaining was weakly positive in 1 case with an EP300∷ BCOR fusion and strongly positive in 2 cases with BCOR-ITD.NGS identified an EP300 ∷ BCOR fusion in 3 cases,and Sanger sequencing confirmed the ITD in exon 15 of BCOR gene in 2 cases.During a follow-up period of 8 to 77 months,one pediatric patient with a BCOR-ITD tumor died,while the remaining four patients were alive with no evi-dence of recurrence or metastasis.Conclusion BCOR-ITD and EP300 ∷ BCOR fusion tumors are similar in morphology and immunophenotype,and the incidence rate of BCOR fusion tumors may be underestimated.NGS sequencing based on DNA and RNA and DNA methylation spectrum analysis are helpful for accurate diagnosis of this type of tumor.

Purpose To investigate the clinicopathological features,diagnosis,and molecular genetic characteris-tics of central nervous system(CNS)high-grade neuroepithelial tumors with BCOR alterations.Methods Five cases of CNS high-grade neuroepithelial tumors harboring BCOR alterations were collected.Using immunohistochemistry and molecular detection to analyze its clinical and histological characteristics,and review relevant literatures.Results A-mong the 5 patients,3 cases with EP300 ∷ BCOR tumor(male-to-female ratio 2∶1).These tumors were located in supratentorial regions(right temporal lobe,right frontotemporal lobe,and right frontal lobe).The 2 patients with BCOR-ITD tumors were younger,both with tumors located in the left cerebellum.Imaging studies revealed well-defined large mass lesions in all cases.Histologically,all 5 cases tumor exhibited ependymoma-like or oligodendroglioma-like morphology,featuring uniformly oval or round cells.Focal areas showed increased cellular density,nuclear enlarge-ment,and readily identifiable mitotic figures indicative of anaplastic features.A rich capillary network was frequently observed in the stroma.Palisading necrosis,microcystic changes,and microcalcifications were present in 3 cases.Im-munohistochemically,all 5 cases consistently expressed vimentin and CD56,focal Olig-2 positivity,variable S-100 ex-pression,and were uniformly negative for GFAP.BCOR immunostaining was weakly positive in 1 case with an EP300∷ BCOR fusion and strongly positive in 2 cases with BCOR-ITD.NGS identified an EP300 ∷ BCOR fusion in 3 cases,and Sanger sequencing confirmed the ITD in exon 15 of BCOR gene in 2 cases.During a follow-up period of 8 to 77 months,one pediatric patient with a BCOR-ITD tumor died,while the remaining four patients were alive with no evi-dence of recurrence or metastasis.Conclusion BCOR-ITD and EP300 ∷ BCOR fusion tumors are similar in morphology and immunophenotype,and the incidence rate of BCOR fusion tumors may be underestimated.NGS sequencing based on DNA and RNA and DNA methylation spectrum analysis are helpful for accurate diagnosis of this type of tumor.

Objective To construct a dynamic framework for bidirectional transitions of mild cognitive impairment(MCI),quantifying both rare reversion and high-risk progression trajectories in cognitive dynamics.Methods Patients diagnosed with MCI at baseline from 2005 to 2022 and completed at least two follow-up visits were selected from the Alzheimer's Disease Neuroimaging Initiative(ADNI),and a retrospective cohort was constructed.Demographic information,APOEε4 genotype,and neuropsychological scales data were collected.Longitudinal cognitive assessments were functionally reconstructed using multivariate functional principal component analysis(MFPCA),with functional principal components(FPCs)extracted based on cumulative variance contribution rate(PVE＞90％).Functional multi-state Markov models were developed to estimate inter-state transition intensities,year to year transition probabilities,and covariate effects.Results Among 1,019 MCI patients(4,657 follow-up visits),93(9.1％)reverted to normal cognition,while 359(35.2％)progressed to Alzheimer's disease(AD).Longitudinal trajectory analysis revealed significant heterogeneity:progressive MCI＞stable MCI＞reverted MCI in the first functional principal component(MFPC1)scores.The transition intensity for MCI reversion(0.020)was approximately one-fourth of the AD progression risk(0.086),but the post-reversion cognitive re-impairment intensity was 0.138.Reduced MFPC1(HR=0.993,95％Cl:0.991,0.995)and elevated MFPC2(HR=1.004,95％Cl:1.001,1.007)were closely associated with MCI reversion.Conclusion MCI exhibits marked heterogeneity in longitudinal cognitive trajectories.Although reversion is rare,reversed patients remain at high risk of cognitive re-impairment.

Objective The Bayesian joint model was applied to predict conversion from mild cognitive impairment(MCI)to Alzheimer's disease(AD),and to compare time effect in longitudinal outcomes,and functional forms for the longitudinal outcomes that are included in the survival model.Methods The longitudinal sub-model used generalized linear mixed models to model the trajectory of longitudinal neuropsychological tests changes pattern,and the survival sub-model adopted a Cox proportional risk model.The longitudinal sub-model utilized two forms of effects,t and t2,and the link structures of longitudinal sub-model and survival sub-model adopted three functional forms(updated value,slope,and area).The data were divided into training and validation sets according to 7∶3,the model parameters were estimated based on Bayesian algorithm,and the dynamic AUC was used to evaluate model prediction performance.Results There were 374(54.20％)of 690 patients with MCI progressed to AD during the follow-up period.In training set,the results of Bayesian joint model with a time effect of t and area effect of three longitudinal neuropsychological tests were optimal,with a mean dynamic AUC of 0.8336.The APOEε4 gene and a low functional activities questionary were risk factors for MCI conversion to AD.The dynamic AUCs of the joint model with the t time effects and area effect for longitudinal data were above 0.75 in the validation sets.Conclusion The application of multivariate Bayesian joint model to MCI risk prediction may provide a theoretical basis for individualized interventions for cognitive impairment and inform statistical methods for survival modeling of chronic diseases.

Objective Using meta-analysis to identify the risk factors for slow-flow or no-reflow during percutaneous coronary intervention(PCI)in patients with ST-segment elevation acute myocardial infarction(AMI).Methods A computerized retrieval of academic papers concerning the risk factors for slow-flow or no-reflow during PCI in patients with ST-segment elevation AMI from the databases of CNKI,Wanfang Database,VIP,SinoMed,PubMed,Web of Science,Embase,and Cochrane Library was conducted.The retrieval time period was from the establishment of the database to January 2024.In order to ensure the accuracy and reliability of the study,two independent reviewers screened the literature according to the preset inclusion and exclusion criteria,extracted key data,and strictly evaluated the quality of the literature.RevMan5.4 software was used to make meta-analysis.Results A total of 23 articles with a total of 9 780 cases were included in this analysis.The results of meta-analysis showed that reperfusion time ≥6 h(OR=1.52),preoperative TIMI blood flow≤level-Ⅰ(OR=1.12),heavy thrombus burden(OR=1.60),advanced age(OR=1.56),diabetes(OR=1.83),preoperative Killip grade≥Ⅲ(OR=2.52),long target vessel disease(OR=1.95),and collateral flow≤level-Ⅰ(OR=1.61)were the risk factors for slow-flow or no-reflow during PCI in patients with ST-segment elevation AMI.Preoperative systolic blood pressure＜90 mmHg(OR=1.17)and high white blood cell(WBC)count(OR=1.27)were not the risk factors for slow-flow or no-reflow during PCI in patients with ST-segment elevation AMI.Conclusion Reperfusion time ≥ 6 h,preoperative TIMI blood flow≤level-Ⅰ,heavy thrombus burden,advanced age,diabetes,preoperative Killip grade≥level-Ⅲ,long target vessel lesion,and collateral blood flow≤level-Ⅰ are the independent risk factors for slow-flow or no-reflow during PCI in patients with ST-segment elevation AMI.

Objective The Bayesian joint model was applied to predict conversion from mild cognitive impairment(MCI)to Alzheimer's disease(AD),and to compare time effect in longitudinal outcomes,and functional forms for the longitudinal outcomes that are included in the survival model.Methods The longitudinal sub-model used generalized linear mixed models to model the trajectory of longitudinal neuropsychological tests changes pattern,and the survival sub-model adopted a Cox proportional risk model.The longitudinal sub-model utilized two forms of effects,t and t2,and the link structures of longitudinal sub-model and survival sub-model adopted three functional forms(updated value,slope,and area).The data were divided into training and validation sets according to 7∶3,the model parameters were estimated based on Bayesian algorithm,and the dynamic AUC was used to evaluate model prediction performance.Results There were 374(54.20％)of 690 patients with MCI progressed to AD during the follow-up period.In training set,the results of Bayesian joint model with a time effect of t and area effect of three longitudinal neuropsychological tests were optimal,with a mean dynamic AUC of 0.8336.The APOEε4 gene and a low functional activities questionary were risk factors for MCI conversion to AD.The dynamic AUCs of the joint model with the t time effects and area effect for longitudinal data were above 0.75 in the validation sets.Conclusion The application of multivariate Bayesian joint model to MCI risk prediction may provide a theoretical basis for individualized interventions for cognitive impairment and inform statistical methods for survival modeling of chronic diseases.

Objective The aim of this study was to explore the natural history of Alzheimer's disease(AD)based on the multi-state Markov model and to provide methodological reference for the chronic diseases.Methods Based on the American public database ADNI,we constructed a three states Markov model to estimate the transition intensity,transition probability,influencing factors and sojourn time of different states.Survival curves and goodness of fit was obtained.Results Gender,age,FAQ,MMSE,CDRSB,ADAS13 and TMT-B-Time were important influencing factors in the natural history of AD.The mean sojourn time of NC and MCI was 7.502 and 11.621 years,respectively.Model fit can be accepted.Conclusion Multi-state Markov model has a good application value for the outcome prediction of multi-state chronic diseases such as AD.

Objective The shared random-effect model(SREM)was applied to study the reversion of mild cognitive impairment(MCI)to normal cognition(NC),to compare the predictive performance of different longitudinal cognitive markers for the reversion,and to evaluate the covariate effects of predictors.Methods The SREM model consisted of two sub-models:the longitudinal sub-model adopted linear mixed model to describe different longitudinal cognitive markers trajectories;and the survival sub-model used proportional risk model to fit the survival process.Goodness of fit was based on the log-likelihood value,and information criterion.AUC(area under the curve)was used to evaluate the predictive performance of different longitudinal cognitive markers,including MMSE,CDRSB,FAQ,ADAS11,ADAS13 and ADASQ4.Results There were 72(8.54%)of 843 patients with MCI reversed to NC at the end of follow-up.The log-likelihood value of the SREM model based on spline-PH-GH parameter distribution was the largest,and AIC and BIC were the smallest;the SREM model based on CDRSB score as longitudinal cognitive marker had the best fitting performance,with high AUC values at different times ranging from 0.797 to 0.852,and the lowest prediction error,ranging from 0.0427 to 0.0429.Age,gender,education level,marital status and APOEε4 gene affected the cognitive function and daily activity function.Six different longitudinal cognitive markers influenced the reversion.Conclusion CDR score was the best predictor of cognitive function and the reversion in MCI patients.Cognitive function and daily activity function can be used as dynamic monitoring indicators of MCI reversion.