AIM: To investigate variation patterns of corneal biomechanical parameters and binocular symmetry among children of different genders aged 8-16 years.METHODS:A retrospective study was conducted, and children who underwent optometric examinations at the ophthalmology department of our hospital were enrolled between January 2022 and December 2024. Measurements included the flat keratometry(K1), steep keratometry(K2), and mean curvature(Km)of the anterior corneal surface, horizontal visible iris diameter(HVID), central corneal thickness(CCT), corneal endothelial cell density(CECD), average cell size(ACS), coefficient of variation(CV), and hexagonality(HEX). Corneal parameters and binocular differences were compared between genders and across age groups.RESULTS:A total of 621 children(1 242 eyes)were enrolled in this study, including 284 males(568 eyes), 337 females(674 eyes), 528 children aged 8-12 years(1 056 eyes), and 93 children aged 13-16 years(186 eyes). In children aged 8-16 years, the K1, K2, Km and CV of both eyes, as well as the interocular CCT differences in boys were significantly lower than those in girls(all P<0.05), while the HVID and HEX of both eyes, as well as the CCT of the left eye in boys were significantly higher than those in girls(all P<0.05). Children aged 8-12 years had significantly higher K1, Km, CECD and HEX in both eyes, and significantly lower ACS in both eyes than those aged 13-16 years(all P<0.05). K1, K2, Km, CECD and HEX in both eyes were negatively correlated with age(P<0.05); ACS in both eyes was positively correlated with age(P<0.001); K1 and Km of the right eye were positively correlated with the CECD of the right eye(P<0.05), and K1 and CCT of the left eye were positively correlated with the CECD of the left eye(P<0.05).CONCLUSION:Significant gender differences exist in corneal parameters among children aged 8 to 16 years, while binocular symmetry remained stable.

Alzheimer disease(AD)is a neurological disease characterized by cognitive decline.AD continuum refers to the dynamic development progression from early pathological changes to obvious clinical symptoms,covering the continuous spectrum of subjective cognition decline(SCD)stage,mild cognitive impairment(MCI)stage and dementia stage.As one of the key brain regions involved in early stage,hippocampus(HP)in AD continuum is closely related to the progression of disease.MRI has been widely used in the study of HP in the AD continuum.The progresses in structural and functional MRI research of HP changes in AD continuum were reviewed in this article.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.

Alzheimer disease(AD)is a neurological disease characterized by cognitive decline.AD continuum refers to the dynamic development progression from early pathological changes to obvious clinical symptoms,covering the continuous spectrum of subjective cognition decline(SCD)stage,mild cognitive impairment(MCI)stage and dementia stage.As one of the key brain regions involved in early stage,hippocampus(HP)in AD continuum is closely related to the progression of disease.MRI has been widely used in the study of HP in the AD continuum.The progresses in structural and functional MRI research of HP changes in AD continuum were reviewed in this article.

Objectives:To analyze the clinical characteristics,strategies,success and complication rates of lead extraction and re-implantation during the upgrade of cardiovascular implantable electronic devices(CIED)in non-infectious patients.Methods:This retrospective study collected and analyzed the baseline clinical data and surgical data of 66 non-infected patients who had their existing CIEDs(including cardiac pacemaker,implantable cardioverter defibrillator[ICD],cardiac resynchronization therapy pacemaker[CRT-P])upgraded to ICD or CRT-P or cardiac resynchronization therapy defibrillator(CRT-D)or subcutaneous implantable cardioverter defibrillator(S-ICD)in Peking University People's Hospital from March 2018 to March 2024.We analyzed the strategies of lead extraction and reimplantation as well as the operation success rate and complication rate.Results:Among the 66 patients,preoperative imaging revealed that 12 patients(18.2%)had severe stenosis/occlusion of the venous access route,with lead wear/perforation in 26 patients(39.4%).32 patients(48.5%)underwent transvenous lead extraction(TLE),of which all leads were removed in 27 patients(84.4%),and only non-functional leads were removed in 5 patients(15.6%).The success rate of the TLE procedure was 100%and no complication occurred.Among the 66 patients,functional leads retained and new leads were implanted on the same side in 28 patients(42.4%),all leads were removed and new leads were reimplanted on the opposite side in 22 patients(33.3%),only non-functional leads were removed and new leads were reimplanted on the same side in 5 patients(7.6%),all leads were removed and new leads were reimplanted on the same side in 5 patients(7.6%),and 6 patients(9.1%)had the leads abandoned and then were re-implanled.The success rate of the upgrade surgery was 100%,no complications were reported.Conclusions:When the existing CIEDs(including cardiac pacemaker,ICD,CRT-P)of non-infected patients are upgraded to ICD,CRT-P,CRT-D or S-ICD,lead extraction and reimplantation are safe and feasible,and reimplantation can be performed on the ipsilateral or contralateral side.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

The exoskeleton robot for lower limb medical rehabilitation in foreign countries and China was introduced in terms of the research status,structure and working principle,and analysis was carried out over its key technologies.It's pointed out the exoskeleton robot for lower limb medical rehabilitation would be enhanced in energy endurance,safety and comfort,individualized and intelligent control,modularity and lightweight design.[Chinese Medical Equipment Journal,2025,46(1):88-100]

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.