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'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.

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.

The characteristics of plateau field conditions and the application of the medical equipment and devices were summarized.The influences of plateau field conditions on the use and maintenance of the medical equipment and devices were pointed out,and some countermeasures were put forward accordingly.The causes for the problems were analyzed,and some suggestions were proposed from the aspects of top-level design,standard and personnel training.References were provided for the use and maintenance of medical equipment and devices during stationed field training and support for military operations other than war in plateau field areas.[Chinese Medical Equipment Journal,2025,46(3):86-89]

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.

Aim To investigate the effect of total gly-cosides of peony on Th17/Treg balance in autoimmune thyroiditis(AIT)by regulating miR-155 expression.Methods Sixty female SD rats were randomly divided into a blank control group,a model group,high-dose,medium,and low-dose groups of total glycosides of peony,and a Western medicine control group(seleni-um yeast group).After eight weeks of modeling,the pathological changes in thyroid tissue were observed by HE staining,the expression of miR-155 in the thyroid of rats was detected by RT-PCR,the targeting effect of miR-155 on SOCS1 was verified by dual luciferase method,and the levels of TGAb,TPOAb,IL-10,and IL-17 in peripheral serum were detected by ELISA,the expression of thyroid SOCS1 was detected by WB,and the proportion of Th17 and Treg in CD4+cells of the spleen was detected by flow cytometry.Results Com-pared with the blank group,the expression of miR-155 in the thyroid gland of the model group rats significant-ly increased,and the serum levels of TGAb,TPOAb,and IL-17 significantly increased,with an increase in the proportion of Th17;the IL-10 level significantly decreased,the proportion of Treg decreased,and the expression of SOCS1 protein decreased,with statistical significance(P＜0.01);compared with the model group,the high,medium,and low dose groups of total glycosides of peony and selenium yeast groups showed a decrease in miR-155 expression,a decrease in TGAb,TPOAb,IL-17 levels,a decrease in Th17 pro-portion,an increase in IL-10 level,an increase in Treg proportion,and an increase in SOCS1 expression,all with statistical significance(P＜0.01).Moreover,the improvement in the medium dose group of total glyco-sides of peony was more significant.Conclusion To-tal glycosides of peony downregulate miR-155 expres-sion,regulate Th17/Treg balance,alleviate inflamma-tory response,and exert immune regulatory effects.

Objective To investigate the mechanism of Achyranthoside Ⅰ inhibits pyroptosis in chondrocytes through the nuclear factor-κB(NF-κB)/NOD receptor protein structure domain related proteins 3(NLRP3)/cystine containing aspartate specific proteins-1(caspase-1)signaling pathway.Methods Primary mouse chondrocytes were divided into blank group(phosphate buffered solution with the same volume),model group[10 ng·mL-1 interleukin-1β(IL-1 β)],control group(10 ng·mL-1 IL-1β+20 μmol·L-1 celecoxib)and experimental group(10 ng·mL-1 IL-1β+3 μg·mL-1 Achyranthoside Ⅰ).After 24 hours of intervention,the cell proliferation was measured by cell counting kit 8,the levels of superoxide dismutase(SOD),malondialdehyde(MDA),IL-1 and IL-6 were detected by enzyme-linked immunosorbent assay,the protein expression levels of NF-κB p65,NLRP3 and caspase-1 were detected by Western Blot.Results The apoptosis rates in experimental,control,model and blank groups were(13.34±0.61)％,(15.64±1.01)％,(21.81±1.10)％and 0;the SOD levels were(147.03±16.49),(130.09±7.33),(122.03±10.71)and(164.40±22.74)nU·mL-1;the MDA levels were(6.43±0.71),(7.63±1.01),(8.89±1.84)and(5.69±0.81)nmol·L-1;the IL-1 levels were(338.69±40.95),(361.78±32.15),(391.44±30.59)and(289.23±25.19)pg·mL-1;the IL-6 levels were(89.96±8.81),(101.10±11.59),(120.39±14.71)and(60.29±6.03)pg·mL-1;the relative expression levels of NF-κB p65 were 0.68±0.05,0.97±0.05,1.26±0.05 and 0.57±0.05;the relative expression levels of NLRP3 were 0.71±0.08,1.02±0.10,1.50±0.06 and 0.31±0.05;the relative expression levels of caspase-1 were 0.70±0.07,1.29±0.08,1.66±0.07 and 0.51±0.07,respectively.Compared with the model group,the differences of above indexes were statistically significant in the experimental group(all P＜0.05).Conclusion Achyranthoside Ⅰ can improve the oxidative stress status induced by IL-1 β in chondrocytes,reduce the expression of proteins related to the NF-κB signaling pathway,and thereby decrease the occurrence of caspase-1 dependent pyroptosis,providing a protective effect on chondrocytes.

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.

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.