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.

Purpose To explore the predictive value of CT-enhanced for tumor mutation burden(TMB)in hepatocellular carcinoma(HCC).Materials and Methods A total of 22 patients with pathologically confirmed HCC after undergoing radical resection in the First Affiliated Hospital,Army Medical University(Third Military Medical University)from January 2020 to January 2023 were collected,all of whom were quantified for TMB.Clinical,laboratory tests,CT imaging characteristics and follow-up of patients were recorded.Variables with P<0.2 were screened by stepwise regression analysis for independent risk factors for TMB.The area under the curve of receiver operating characteristic was used to assess the diagnostic efficacy.Results High TMB level was a risk factor for disease-free survival after HCC surgery(HR=1.115,P<0.05).According to the optimal cut-off value,TMB was classified into a high-risk group(>9.25 mutation/Mb)and low-risk group(≤9.25 mutation/Mb).Univariate analysis of intratumor ischemia or necrosis was statistically different between the high-risk and low-risk groups(P=0.005),and only intratumor ischemia or necrosis was an independent risk factor for predicting high TMB level by stepwise regression analysis(P<0.05).The area under the curve for predicting disease-free survival was 0.833(95%CI 0.615-0.956,P<0.001),with a sensitivity of 100.0%and a specificity of 66.7%.Conclusion High TMB level is associated with poor prognosis after HCC resection.Intratumor ischemia or necrosis have certain clinical value in predicting high TMB level,and are expected to provide a reference basis for personalized diagnosis and treatment of HCC patients.

Objective To understand the epidemiological characteristics and trends of postoperative pneumonia(POP)in tertiary general hospitals in Jiangsu Province,and provide theoretical basis for carrying out targeted pre-vention and control measures.Methods Surgery patients from 22 tertiary general hospitals in 12 cities in north,central,and south of Jiangsu Province from January 1,2022 to December 31,2023 were chosen as studied subjects,occurrence of POP was analyzed and compared.Results A total of 848 274 surgical procedures were performed in 22 hospitals,and 3 606 cases of POP occurred,with an incidence of 0.43％.The incidence in 2023 was 0.37％,which was lower than that in 2022(0.49％),with statistically significant difference(P＜0.001).The top three de-partments with high incidence of POP were neurosurgery(6.71％),cardiothoracic surgery(2.91％),and general surgery(0.77％).Among hospitals of different grades,the incidence of POP in tertiary first-class hospitals was 0.44％,which was higher than that in other tertiary hospitals(0.37％).There was no statistically significant difference in the incidence of POP between municipal and district/county hospitals(P＞0.05).The incidence of POP in hospitals with a bed:infection control full-time staff ratio＜200∶1 was lower than that in hospitals with the ratio ≥200∶1(0.39％vs 0.47％,P＜0.001),while the incidence of POP in hospitals with a proportion ≥30％of full-time staff being doctors was higher than that in hospitals with a proportion＜30％(0.45％vs 0.36％,P＜0.001).The incidence of POP in male patients was higher than that in female patients(0.62％vs 0.26％,P＜0.001).The incidence of POP in elderly patients aged≥65 was higher than that in patients aged＜65(0.73％vs 0.26％,P＜0.001).A total of 2 667 strains of infectious pathogens were detected,with the top three being Acine-tobacter baumannii,Klebsiella pneumoniae,and Pseudomonas aeruginosa,accounting for 28.95％,22.72％,and 15.45％,respectively.The detection rates of carbapenem-resistant Acinetobacter baumannii(CRAB),carba-penem-resistant Klebsiella pneumoniae(CRKP),and carbapenem-resistant Pseudomonas aeruginosa(CRPA)were 60.75％,21.45％,and 32.28％,respectively.The detection rate of CRKP decreased in 2023 compared with 2022,with statistically significant difference(P＜0.05).Conclusion The overall incidence of POP in tertiary general hos-pitals in Jiangsu Province is relatively low,but there are significant differences among different hospitals.There-fore,perioperative prevention and control measures should be carried out based on the epidemiological characteristics of patients.

Objective:To analyze the iodine nutrition status of children and adolescents and influencing factors in Zhejiang Province, providing scientific basis for optimizing iodine deficiency disorders (IDD) prevention and control strategies.Methods:In June 2022, a multistage stratified sampling method was used to divide 16 counties (cities, districts, abbreviated as counties) in Zhejiang Province into three categories based on their geographical locations (average distance from the coastline): coastal areas (including Dinghai District, Jiaojiang District, Sanmen County, Cixi City and Lucheng District), sub-coastal areas (including Wuxing District, Haining City, Linping District, Fuyang District and Fenghua District), and inland areas(including Suichang County, Changshan County, Shengzhou City, Jindong District, Dongyang City and Yongjia County). One county was selected from each category, and one township (street) was selected from each county. Two administrative villages (neighborhood committees) were selected from each township (street). Ten households including all children and adolescents aged 6-17 in each household were selected from each administrative village (neighborhood committee). Demographic information and personal dietary characteristics were collected via questionnaires, while household salt and a random urine sample were tested for iodine level. Trend analysis was conducted using a χ 2trend test, and a multivariate logistic stepwise regression model was used to analyze the influencing factors of urinary iodine levels. Results:A total of 755 children and adolescents aged 6-17 were selected, including 387 males (51.26%) and 368 females (48.74%), with an age of (11.24 ± 3.32) years. There were 269 children and adolescents in coastal areas (35.63%) and 409 children and adolescents in urban areas (54.17%). A total of 755 household salt samples were collected, with a median salt iodine concentration of 21.80 mg/kg. These included 263 non-iodized salt samples, 38 unqualified iodized salt samples, and 454 qualified iodized salt samples. The coverage rate of iodized salt was 65.17% (492/755), and the consumption rate of qualified iodized salt was 60.13% (454/755). The distribution of salt iodine quality among children and adolescents in different geographical locations showed statistically significant differences (χ 2 = 111.95, P < 0.001), with the proportion of non-iodized salt gradually decreasing from coastal areas to inland areas (χ 2trend = 90.17, P < 0.001). A total of 755 urine samples were collected, with a median urinary iodine concentration of 186.60 μg/L. The proportions of urinary iodine < 100, 100-199, 200-299, and ≥300 μg/L were 16.95% (128/755), 37.62% (284/755), 24.37% (184/755), and 21.06% (159/755), respectively. The χ 2trend test revealed a nonlinear positive correlation between salt iodine level and urinary iodine level (χ 2regression = 21.98, P < 0.001; χ 2partial = 6.96, P < 0.001). The frequency distribution of urinary iodine in children and adolescents from different geographical locations and between urban and rural areas showed statistically significant differences (χ 2 = 29.63, 16.56, P < 0.001). Among them, the proportion of children and adolescents with urinary iodine < 100 μg/L gradually decreasing from coastal areas to inland areas (χ 2trend = 6.15, P = 0.013). The results of multivariate logistic regression analysis revealed that sub-coastal regions, inland regions, and urban-rural regions ( OR = 1.57, 1.53, 1.64, 95% CI: 1.11-2.24, 1.03-2.27, 1.17-2.32, P < 0.05) were significantly associated with urinary iodine levels in children and adolescents aged 6-17. Conclusions:In 2022, the iodine nutrition of children and adolescents in Zhejiang Province is generally suitable, but there is a risk of iodine deficiency among coastal children and adolescents. Geographic location and urban/rural areas are influencing factors on iodine nutrition status of children and adolescents in Zhejiang Province.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

Objective:To evaluate the efficacy of gadolinium ethoxybenzyl- diethy-lenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI features in the preoperative prediction of tertiary lymphoid structures (TLS) within hepatocellular carcinoma (HCC) lesions.Methods:This retrospective cross-sectional study included clinical and pathological data from 297 HCC patients treated at the Southwest Hospital, Army Medical University between June 2021 and November 2022. Based on postoperative pathology, patients were categorized into TLS-negative ( n=93) and TLS-positive ( n=204) groups. MRI features of HCC lesions using Gd-EOB-DTPA enhancement and relevant clinical data were analyzed. Intergroup comparisons of imaging features and laboratory findings were performed using independent sample t-test, Mann-Whitney U test, χ2 test, or Fisher exact test, as appropriate. The logistic regression analysis was conducted to identify independent predictors of TLS positivity. A predictive model was constructed and visualized using a nomogram. The model′s predictive performance and clinical utility were assessed using the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The area under the ROC curve (AUC) was compared using the DeLong test. Results:Significant differences were observed between the TLS-negative and TLS-positive groups in alpha-fetoprotein (AFP) levels, intratumoral hemorrhage, and peritumoral satellite nodules in the hepatobiliary phase ( P<0.05). Multivariate logistic regression identified intratumoral hemorrhage ( OR=0.123, 95% CI 0.070-0.216, P<0.001) and peritumoral satellite nodules in the hepatobiliary phase ( OR=0.236, 95% CI 0.093-0.596, P=0.002) as independent predictive factors for TLS-positivity. The imaging model based on these two features yielded an AUC of 0.764 (95% CI 0.709-0.809) for predicting TLS-positivity. When combined with AFP levels, the resulting clinical-imaging model achieved a superior AUC of 0.784 (95% CI 0.732-0.829), which was significantly higher than that of the imaging model alone ( Z=2.20, P=0.028). A nomogram was constructed based on the clinical-imaging model. The calibration curve demonstrated good predictive performance of the nomogram, and the DCA showed that the curve remained above the default line across a range of reasonable threshold probabilities, indicating that patients could derive clinical benefit. Conclusion:A nomogram model based on Gd-EOB-DTPA enhanced MRI features combined with AFP levels can effectively predict the presence of TLS in HCC.

Purpose To explore factors influencing vaginal delivery during the first stage of labor using intrapartum ultrasound and to construct predictive models for delivery decision-making.Materials and Methods A total of 473 nulliparous women admitted to Heping Hospital,Northern Theater General Hospital from July to December 2021 were prospectively enrolled as the training set.Clinical data on admission and fetal biometric parameters(biparietal diameter,femur length,head circumference and abdominal circumference)measured within one week before delivery were collected.Ultrasound assessments of fetal position,angle of progression(AOP)and head-perineum distance(HPD)were performed during the first stage of labor.The latent phase group(n=255)was subdivided into vaginal delivery group(n=186)and cesarean section group(n=69);the active phase group(n=218)was divided into vaginal delivery group(n=168)and cesarean section group(n=50).The associations between fetal position,AOP,HPD and vaginal delivery were analyzed,and predictive models were constructed for the latent phase(model 1)and active phase(model 2).A validation set of 547 women from January to September 2022 was used to evaluate model performance via area under the curve(AUC),calibration curves and decision curve analysis.Results In the latent phase,multivariate regression identified maternal height(OR=3.970,P=0.002),pre-pregnancy body mass index(OR=0.893,P=0.036),labor onset type(OR=2.415,P=0.045),neonatal birth weight(OR=3.728,P=0.002),AOP(OR=11.649,P<0.001)and HPD(OR=4.240,P=0.004)as significant predictors.The training and validation sets showed AUCs of 0.917 and 0.869,respectively.Goodness-of-fit tests indicated excellent model calibration(χ2=3.437,P=0.904;χ2=10.877,P=0.209).Decision curve analysis demonstrated strong clinical utility.For the active phase,significant predictors included maternal height(OR=6.532,P<0.001),neonatal birth weight(OR=11.890,P<0.001),fetal position(OR=4.600,P=0.003),AOP(OR=7.229,P<0.001)and HPD(OR=4.722,P=0.005).AUCs were 0.943(training)and 0.906(validation),with good calibration(χ2=4.340,P=0.740;χ2=9.836,P=0.277)and clinical applicability.Conclusion First stage ultrasound assessment of fetal position,AOP and HPD correlates with delivery outcomes.The developed nomogram models combining these parameters with clinical factors provide valuable guidance for delivery decision-making.

As a non-invasive physiological indicator,electroencephalography signal provides an objective assessment of psychological stress levels among nursing staff in major public health emergencies,offering a scientific basis for targeted psychological interventions while overcoming the limitations of subjective bias inherent in traditional questionnaire-based methods.A psychological stress classification model based on bidirectional long short-term memory and attention mechanism is proposed to classify the psychological stress of clinical nurses more effectively by analyzing their electroencephalography signals.Experimental results show that the proposed model exhibits better classification performance than the traditional long short-term memory model on the DREAMER dataset,the Feeling Emotions dataset and the self-built dataset.This study provides a novel approach for assessing psychological stress,which is helpful to improve the pertinence and effectiveness of clinical nursing work.

As a non-invasive physiological indicator,electroencephalography signal provides an objective assessment of psychological stress levels among nursing staff in major public health emergencies,offering a scientific basis for targeted psychological interventions while overcoming the limitations of subjective bias inherent in traditional questionnaire-based methods.A psychological stress classification model based on bidirectional long short-term memory and attention mechanism is proposed to classify the psychological stress of clinical nurses more effectively by analyzing their electroencephalography signals.Experimental results show that the proposed model exhibits better classification performance than the traditional long short-term memory model on the DREAMER dataset,the Feeling Emotions dataset and the self-built dataset.This study provides a novel approach for assessing psychological stress,which is helpful to improve the pertinence and effectiveness of clinical nursing work.

Objective To investigate the effects of miR-483-3p on hypoxia/reoxygenation(H/R)-induced apoptosis and pyroptosis of H9c2 cardiomyocytes and its possible mechanism.Methods Rat H9c2 cardiomyocytes were cultured in vitro,adeno-associated virus-infected H9c2 and the H/R model were constructed by triple-air incuba-tor,and the cells were randomly divided into blank control(Sham)group,model(H/R)group,AAV-miR-483-3p mimic+H/R(AAV-miR-483-3p)group,AAV-miR-483-3p negative control+H/R(AAV-NC)group.The growth status of cells in each group was observed using an inverted microscope;cell proliferation activity was detected by cell counting kit-8(CCK-8);LDH release by lactate dehydrogenase(LDH)kit;apoptosis rate by flow cytometry;apoptosis by notched end labeling(TUNEL).Western blot(WB)was used to detect the expression levels of IL-1β and GSDMD proteins in each group.Results Compared with the Sham group,the H/R group showed abnormal cell status and increased cell death,decreased cell activity,increased LDH release,increased apoptosis rate and apopto-sis level,and increased expression levels of IL-1β and GSDMD proteins(P<0.05);compared with the H/R group,the AAV-miR-483-3p group showed improved cell status and less cell death,increased cell proliferation activity,increased LDH release,and increased IL-1β and GSDMD protein expression levels(P<0.05).Compared with the H/R group,the AAV-miR-483-3p group showed improved cell status and less cell death,increased cell proliferation activity,decreased LDH release,decreased apoptosis rate and apoptosis level,and decreased expression of IL-1β and GSDMD proteins(P<0.05).Conclusion Over-expression of miR-483-3p can improve H/R-inducedH9c2 cardiomyocyte injury by enhancing cell activity and cell metabolism,and inhibiting apoptosis and cell charring.