OBJECTIVE To investigate the neuroprotective effect and mechanism of eleutheroside B （ELB） on Parkinson’s disease （PD） model mice by regulating the IκB kinase β （IKKβ）/nuclear factor-κB （NF-κB） signaling pathway. METHODS Fifty mice were randomly divided into normal control group， model group， positive control group （selegiline hydrochloride， 10 mg/kg）， and ELB low-dose and high-dose groups （80， 160 mg/kg）， with 10 mice in each group. Each group was given relevant medicine or normal saline intragastrically for 14 consecutive days. Starting from the 10th day of administration， the model group and all administration groups were intraperitoneally injected with 1-methyl-4-phenyl-1，2，3，6-tetrahydropyridine （MPTP） 30 mg/kg， for five consecutive days to establish the chronic PD model. After the last administration for 24 h， six mice were randomly selected from each group to test their behavioral abilities； detect the levels of interleukin-1β （IL-1β）， IL-10， tumor necrosis factor-α （TNF-α） in brain tissue and their mRNA expressions were measured， and positive expression of tyrosine hydroxylase （TH）， protein expressions of TH， α -synuclein （ α -syn）， ionized calcium-binding adaptor molecule 1 （Iba-1）， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in the brain tissue were detected. The ultrastructure of neurons in substantia nigra was observed. RESULTS Compared with the model group， rotarod endurance time and climbing score of each administration group （except for the ELB low-dose group） were increased significantly （ P ＜0.05）， while the levels and mRNA expressions of IL-1β， TNF-α， α -syn， and Iba-1， as well as phosphorylation levels of IKKβ and NF-κB p65 proteins in brain tissue were decreased significantly （except for TNF-α in the ELB low-dose group）. Conversely， the level and mRNA expression of IL-10 （except for the ELB low-dose group）， TH positive expression and protein expressions were significantly increased （ P ＜0.05）. Typical neurodegenerative pathological changes， such as neuronal karyopyknosis， mitochondrial swelling and vacuolization， and endoplasmic reticulum dilation， all showed varying degrees of improvement. CONCLUSIONS ELB may exert neuroprotective effects by inhibiting the activation of the IKKβ/NF-κB signaling pathway， alleviating inflammatory responses， reducing abnormal α -syn aggregation and neuronal loss， and further improving motor dysfunction in PD mice.

Objective:To investigate the effect of dulagopeptide on physical examination indexes,plasma glucose metabolism and islet function in type 2 diabetes mellitus(T2DM)patients with poorly controlled plasma glucose.Methods:135 T2DM patients with poorly controlled plasma glucose who were admitted in our hospital from January 2023 to July 2024 were selected.A prospective randomized controlled design was adopted,they were divided into control group 1(received treatment with sitagliptin,n=45),control group 2(received treatment with insulin glargine,n=45),and observation group(received treatment with dulaglutide,n=45)according to the random number table method.Physical examination indexes,plasma glucose indicators,islet function,and incidence of adverse reactions were compared among the three groups.Results:12 weeks after treatment,body mass index(BMI),waist circumference,fasting plasma glucose(FPG),glycated hemoglobin(HbA1c),and postprandial 2-hour plasma glucose(2hPG)in the observation group were lower than those in control group 1 and control group 2(P＜0.05).12 weeks after treatment,the observation group had the highest HbA1c compliance rate,reaching 71.1％(P＜0.05).12 weeks after treatment,the fasting C-peptide(FC-P)and HOMA-islet(CP-DM)levels in the observation group were higher than those in control group 1 and control group 2(P＜0.05).Conclusion:Dulagopeptide can effectively improve physical examination indexes,plasma glucose indicators,and islet function in T2DM patients with poorly controlled plasma glucose.

Objective:To investigate the current situation and influencing factors of work ability in gynecological cancer patients, so as to provide a reference for occupational rehabilitation management of cancer patients.Methods:A total of 183 gynecological cancer patients who visited the gynecological oncology outpatient department of Women′s Hospital of Nanjing Medical University from November 2022 to March 2023 were selected by the convenience sampling. The General Information Questionnaire, Return-to-Work Self-efficacy Questionnaire, Social Support Rating Scale, the European Organization for Research and Treatment of Cancer Quality of Life Quesionnaire Core 30, Work Ability Index were selected for cross-sectional investigaton. The multiple linear regression analysis was used to explore the influencing factors of work ability in gynecological cancer patients.Results:A total of 189 questionnaires were sent out in this study, and 183 were effectively collected, with an effective recovery rate of 96.83% (183/189). The patients were (44.64 ± 7.06) years old. The scores of the patients were (27.77 ± 7.58) points on Work Ability Index, (4.72 ± 1.14) points on Return-to-Work Self-efficacy Questionnaire, (86.93 ± 23.44) points on Social Support Rating Scale, (79.46 ± 19.53) points on overall health status area and (41.23 ± 27.80) points on the field of fatigue symptoms area of the European Organization for Research and Treatment of Cancer Quality of Life Quesionnaire Core 30. Multiple linear regression analysis showed that fatigue, comorbidities, clinical stage of disease, primary treatment, per capita monthly income of families, return-to-work self efficacy and job nature were independent influencing factors of work ability in gynecological cancer patients ( t values were -10.47-2.86, all P<0.05), which explained 67.9% of the total variance. Conclusions:Clinical medical staff should pay attention to the influencing factors that affect work ability in gynecological cancer patients, in order to take targeted occupational rehabilitation measures to improve their work ability.

Objective:To investigate the effect of dulagopeptide on physical examination indexes,plasma glucose metabolism and islet function in type 2 diabetes mellitus(T2DM)patients with poorly controlled plasma glucose.Methods:135 T2DM patients with poorly controlled plasma glucose who were admitted in our hospital from January 2023 to July 2024 were selected.A prospective randomized controlled design was adopted,they were divided into control group 1(received treatment with sitagliptin,n=45),control group 2(received treatment with insulin glargine,n=45),and observation group(received treatment with dulaglutide,n=45)according to the random number table method.Physical examination indexes,plasma glucose indicators,islet function,and incidence of adverse reactions were compared among the three groups.Results:12 weeks after treatment,body mass index(BMI),waist circumference,fasting plasma glucose(FPG),glycated hemoglobin(HbA1c),and postprandial 2-hour plasma glucose(2hPG)in the observation group were lower than those in control group 1 and control group 2(P＜0.05).12 weeks after treatment,the observation group had the highest HbA1c compliance rate,reaching 71.1％(P＜0.05).12 weeks after treatment,the fasting C-peptide(FC-P)and HOMA-islet(CP-DM)levels in the observation group were higher than those in control group 1 and control group 2(P＜0.05).Conclusion:Dulagopeptide can effectively improve physical examination indexes,plasma glucose indicators,and islet function in T2DM patients with poorly controlled plasma glucose.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

BACKGROUND:The decreased postural control ability due to mild cognitive impairment in elderly people leads to the increased risk of falls.Dual-task is the primary research paradigm for evaluating the relationship between cognition and postural control in the scenes close to real life.The sample entropy of the plantar center of pressure(COP)displacement during standing can represent the complexity of postural control. OBJECTIVE:Based on the COP displacement sample entropy,to analyze the differences in postural stability characteristics and control strategies between older adults with mild cognitive impairment and cognitively normal older adults during the dual-task with postural control and spatial working memory,aiming to explore the impact of cognitive impairment on the postural control ability during standing. METHODS:Sixteen older adults with mild cognitive impairment and 17 cognitively normal older adults were eligible and selected for the study.They completed five test tasks,including spatial working memory,double-feet balance stance,Romberg stance,double-feet balance stance-spatial working memory dual-task,and Romberg stance-spatial working memory dual-task,with three valid completions of each task.The plantar COP data were collected by the Kistler 3D force platform.The indicators included cognitive behavior(cognitive score and reaction time)and kinematic indexes(COP displacement and sample entropy). RESULTS AND CONCLUSION:The older adults with mild cognitive impairment performed the spatial working memory task with the greatest cognitive score and the shortest reaction time,the double-feet balance stance-spatial working memory dual-task with moderate cognitive score and reaction time,and the Romberg stance-spatial working memory dual-task with the smallest cognitive score and the longest reaction time,where the differences were significant among the tasks(P<0.05).In the older adults with mild cognitive impairment,the anterior-posterior and medial-lateral COP displacements were significantly greater,and their sample entropy values were significantly smaller in the double-feet balance stance-spatial working memory dual-task and Romberg stance-spatial working memory dual-task than in the double-feet balance stance and Romberg stance tasks(P<0.05).In the spatial working memory task,there were no significant differences in cognitive score and reaction time between the both groups(P>0.05);however,in the double-feet balance stance-spatial working memory dual-task and Romberg stance-spatial working memory dual-task,cognitive scores were significantly smaller and reaction times were longer in the older adults with mild cognitive impairment compared with the cognitively normal older adults(P<0.05).In the double-feet balance stance-spatial working memory dual-task and Romberg stance-spatial working memory dual-task,the older adults with mild cognitive impairment exhibited significantly greater anterior-posterior and medial-lateral COP displacements and significantly smaller sample entropy values compared with the cognitively normal older adults(P<0.05).All findings indicate that compared with cognitively normal older adults,older adults with mild cognitive impairment exhibit smaller complexity,poorer systematic adaption and decreased automatic regulation of the postural control during performing the dual-tasks,who are more susceptible to spatial working memory interference,leading to the increased risk of falls.

The aim of this study was to investigate the trend in testicular volume changes after orchiopexy in children with cryptorchidism. The clinical data of 854 children with cryptorchidism who underwent orchiopexy between January 2013 and December 2016 in Shenzhen Children's Hospital (Shenzhen, China) were retrospectively analyzed. The mean (standard deviation) age of the patients was 2.8 (2.5) years, and the duration of follow-up ranged from 1 year to 5 years. Ultrasonography was conducted preoperatively and postoperatively. The variables analyzed included age at the time of surgery, type of surgical procedure, laterality, preoperative testicular position, preoperative and postoperative testicular volumes, and the testicular volume ratio of them. The average testicular volumes preoperatively and at 1 year, 2 years, 3 years, and 5 years postoperatively were 0.27 ml, 0.38 ml, 0.53 ml, 0.87 ml, and 1.00 ml, respectively ( P < 0.001). The corresponding testicular volume ratios were 0.67, 0.76, 0.80, 0.83, and 0.84 ( P < 0.001). The mean volume of the undescended testes was significantly smaller than the mean normative value ( P < 0.001, lower than the 10 th percentile). The postoperative testicular volumes in children with cryptorchidism were generally lower than those in healthy boys but were still greater than the 10 th percentile and exhibited an increasing trend. The older the child is at the time of surgery, the larger the gap in volume between the affected and normal testes. Although testicular volume tends to gradually increase after orchiopexy for cryptorchidism, it could not normalizes. Earlier surgery results in affected testicular volumes closer to those of healthy boys.
Humans ; Male ; Cryptorchidism/diagnostic imaging* ; Orchiopexy ; Child, Preschool ; Testis/surgery* ; Retrospective Studies ; Organ Size ; Ultrasonography ; Infant ; Child ; Postoperative Period ; Follow-Up Studies

OBJECTIVES: To investigate the association between maternal depressive symptoms and adolescent suicidal ideation, and to examine the chain mediating roles of childhood trauma and ineffectiveness. METHODS: A cross-sectional online survey was administered by school psychologists to 4 157 mother-adolescent pairs from middle schools in Shanghai and Henan, China. Measures included the Center for Epidemiological Studies Depression Scale, the Childhood Trauma Questionnaire, and the Children's Depression Inventory. Using Bootstrap method to examine the chain mediating effect of childhood trauma and ineffectiveness on the relationship between maternal depression symptoms and adolescent suicidal ideation. RESULTS: The prevalence of maternal depressive symptoms was 17.68% (735/4 157); among adolescents, the prevalence of depressive symptoms was 15.49% (644/4 157), and suicidal ideation was 28.19% (1 172/4 157). Adolescent depressive symptoms and suicidal ideation were positively correlated with maternal depressive symptoms, childhood trauma, and ineffectiveness (all P<0.01). Childhood trauma significantly mediated the association between maternal and adolescent depressive symptoms (95%CI: 0.046 9-0.077 2). The chain mediation of childhood trauma and ineffectiveness in the association between maternal depressive symptoms and adolescent suicidal ideation was also significant (95%CI: 0.000 7-0.001 3). CONCLUSIONS Higher maternal depressive symptom levels are associated with a greater likelihood of adolescents' exposure to childhood trauma, which increases adolescents' ineffectiveness and, in turn, is associated with suicidal ideation. This chain effect has important implications for social interventions targeting adolescent depression.
Humans ; Suicidal Ideation ; Adolescent ; Female ; Depression/etiology* ; Cross-Sectional Studies ; Mothers/psychology* ; Male ; Child ; Adult

BACKGROUND: Biomarkers-based prediction of long-term risk of acute coronary syndrome (ACS) is scarce. We aim to develop a risk score integrating clinical routine information (C) and plasma biomarkers (B) for predicting long-term risk of ACS patients. METHODS: We included 2729 ACS patients from the OCEA (Observation of cardiovascular events in ACS patients). The earlier admitted 1910 patients were enrolled as development cohort; and the subsequently admitted 819 subjects were treated as validation cohort. We investigated 10-year risk of cardiovascular (CV) death, myocardial infarction (MI) and all cause death in these patients. Potential variables contributing to risk of clinical events were assessed using Cox regression models and a score was derived using main part of these variables. RESULTS: During 16,110 person-years of follow-up, there were 238 CV death/MI in the development cohort. The 7 most important predictors including in the final model were NT-proBNP, D-dimer, GDF-15, peripheral artery disease (PAD), Fibrinogen, ST-segment elevated MI (STEMI), left ventricular ejection fraction (LVEF), termed as CB-ACS score. C-index of the score for predication of cardiovascular events was 0.79 (95% CI: 0.76-0.82) in development cohort and 0.77 (95% CI: 0.76-0.78) in the validation cohort (5832 person-years of follow-up), which outperformed GRACE 2.0 and ABC-ACS risk score. The CB-ACS score was also well calibrated in development and validation cohort (Greenwood-Nam-D'Agostino: P = 0.70 and P = 0.07, respectively). CONCLUSIONS CB-ACS risk score provides a useful tool for long-term prediction of CV events in patients with ACS. This model outperforms GRACE 2.0 and ABC-ACS ischemic risk score.