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 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 analyze the iodine nutrition status and its related factors among adults aged 18 years and above in Zhejiang Province in 2022.Methods:A multistage stratified sampling method was used to select 4 320 adults aged 18 years and above from 16 on-site survey sites in Zhejiang Province for the study. A questionnaire was used to investigate the general demographic information and personal dietary characteristics of the study participants. Household edible salt and urine samples were collected to detect salt iodine content and urinary iodine level by using direct titration and cerium arsenate-catalyzed spectrophotometry, respectively, to evaluate the iodine nutritional status according to the standard. The multiple-ordered logistic regression model was used to analyze the factors influencing the urinary iodine concentration.Results:The age of the 4 320 study participants was (51.19±15.33) years, with males accounting for 44.44% (1 920). About 40.16% of adults (1 735) were from coastal areas and 56.37% (2 435) from urban areas. The salt iodine content, M ( Q1, Q3), of the 4 320 household edible salt samples was 21.10 (0.00, 24.16) mg/kg, including 1 662 non-iodized salt samples, 182 unqualified iodized salt samples and 2 476 qualified iodized salt samples. The rate of iodized salt coverage was 61.53%, and the rate of qualified iodized salt consumption was 57.31%. There was a statistically significant difference in the proportion of qualified iodized salt in adult households among different regions ( P<0.001), with the proportion of non-iodized salt gradually decreasing from coastal to inland areas ( χ 2trend=618.458, P<0.001). The urinary iodine concentration M ( Q1, Q3) was 137.60 (86.85, 210.60) μg/L in 4 320 adult urine samples, with the urinary iodine levels of<100, 100-199, 200-299, and≥300 μg/L accounting for 31.64% (1 367), 40.56% (1 752), 17.66% (763), and 10.14% (438), respectively. There was a nonlinear positive correlation between household salt iodine content and urinary iodine level in adults aged 18 years and above by using the χ 2 test for trend ( χ 2regression=231.10, P<0.001 and χ 2skew=28.81, P<0.001). Urinary iodine concentrations were higher in men than in women ( P=0.029) and higher in adults in rural areas than in urban areas ( P<0.001). There were statistically significant differences in the distribution of iodine nutritional status among adults of different ages, regions, and urban and rural areas (all P<0.001). The proportion of those with urinary iodine levels<100 μg/L gradually increased with age ( χ 2trend=37.493, P<0.001), and gradually decreased from coastal areas to inland areas ( χ 2trend=71.381, P<0.001). The results of the multiple-ordered logistic regression model analysis showed that compared with adults aged 18 to 44 years and male adults, those aged 45 to 59 years and female adults had lower urinary iodine levels, with OR (95% CI) of 0.75 (0.68-0.83) and 0.85 (0.76-0.95), respectively. Compared with adults in coastal and urban adults, those in sub-coastal, inland and rural adults had higher levels of urinary iodine, with OR (95% CI) of 1.89 (1.63-2.19), 2.02 (1.72-2.37) and 1.46 (1.28-1.66), respectively. Conclusion:The overall iodine nutrition level of adults aged 18 years and above in Zhejiang Province in 2022 is generally appropriate. However, there is a potential risk of iodine deficiency among adults in coastal areas.

Objective:To evaluate the mediating effect of electrocardiographic (ECG) indicators in the association between short-term exposure to fine particulate matter (PM 2.5) and blood pressure and to explore the key PM 2.5 element constituents that produce the mediating effect. Methods:Based on a cross-sectional survey across 10 cities in the Beijing-Tianjin-Hebei region and surrounding areas, PM 2.5 and its element constituents were collected from the nearest air monitoring superstation. Blood pressure and ECG indicators of participants were obtained through physical examinations. A multivariate linear regression was used to evaluate the effect of short-term exposures to PM 2.5 on blood pressure. A mediation analysis was used to identify the mediating effect of ECG indicators in the association between exposure to PM 2.5 and its element constituents and blood pressure. Results:The age of the 1 793 participants was (65.1±13.3) years, and 885 (49.4%) were males. During the study period, the daily mean concentration of PM 2.5 was (70±45) μg/m 3, and the systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP) were (139±20), (82±11), (101±13), and (57±17) mmHg (1 mmHg=0.133 kPa), respectively. The results of the multivariate linear regression showed that for every 10 μg/m 3 increase in PM 2.5 on the same day (lag 0), DBP increased by 0.15 (95% CI: 0.02-0.28) mmHg, and PP decreased 0.18 (95% CI: 0.36-0.01) mmHg. The exposure to 14 elemental constituents, such as Ga, Co and Se, was associated with an increase in DBP, while the exposure to 17 elemental constituents, such as Cs, Se and Ag, was associated with a decrease in PP. At lag 0, the PM 2.5-induced increase in DBP was mediated by the QRS interval (mediation percentage of 18.98%), and the PM 2.5-induced decrease in PP was mediated by the QT interval (mediation percentage of -6.31%). The exposure to K, Br, Pb, Zn, Ca, Co, Pd, Cu, and As constituents was associated with increases in DBP mediated by prolonged QRS interval. The exposure to Pb, Zn, K, and As constituents was associated with decreases in PP mediated by prolonged QRS interval. Conclusion:ECG indicators such as QRS interval may mediate the association between short-term exposure to PM 2.5 and its element constituents and blood pressure.

Objective:To assess the effect of short-term exposures to atmospheric fine particulate matter (PM 2.5) and its components on cognitive function in middle-aged and older people aged 40-89 and identify key components that affect cognitive function. Methods:From October 2018 to March 2019, a cross-sectional survey of middle-aged and older people aged 40-89 was conducted across 10 cities in Beijing-Tianjin-Hebei and neighboring regions of China. Data on PM 2.5 and its components were collected from the nearest air supermonitoring stations to the residential addresses. The cognitive function was assessed using the Min-Mental State Examination (MMSE) scale. Multiple linear regression models were used to assess the effect of short-term exposures to PM 2.5 and its components on cognitive function in middle-aged and older people. The restricted cubic spline function was used to fit the exposure-response relationship between different components and changes in MMSE scores. Results:The age of the 1 978 respondents was (65.1±13.4) years, and 976 (49.34%) were males. During the study period, the daily mean concentration of PM 2.5 was (71.2±43.2) μg/m 3, and the MMSE score was (28.2±3.7). The results of the multiple linear regression model showed that short-term exposures to PM 2.5 and its components were associated with cognitive decline in middle-aged and older people after adjusting for confounding factors, and the effect was higher at lag 0-28 days. For an interquartile range (64.3 μg/m 3) increase in PM 2.5 at lag 0-28 d, the MMSE score decreased by 5.91 (95% CI: 0.04, 11.77). For an interquartile range increase in organic carbon (OC), antimony (Sb), chromium (Cr), zinc (Zn), tin (Sn), and cadmium (Cd), the MMSE scores of middle-aged and older people decreased by 5.71 (95% CI: 1.69, 9.73), 4.67 (95% CI: 2.50, 6.84), 4.49 (95% CI: 1.05, 7.92), 3.65 (95% CI: 0.89, 6.42), 2.76 (95% CI: 1.22, 4.30), and 1.72 (95% CI: 0.53, 2.92). Conclusions:Short-term exposures to atmospheric PM 2.5 and its components (OC, Sb, Cr, Zn, Sn, and Cd) are associated with cognitive decline in middle-aged and older people.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.

Objective:To describe the body mass index (BMI) level and long-term trends of Chinese older adults aged 65 and above.Methods:Older adults aged 65 and above from six waves (2002-2018) of the China Longitudinal Healthy Longevity Survey were selected as the study population. Multiple cross-sectional design with six survey waves conducted in 2002, 2005, 2008, 2011, 2014, and 2018 was adopted, enrolling 15 647, 15 358, 15 622, 9 166, 6 302, and 12 417 participants, respectively. Additionally, a total of 13, 755 participants were included in the cohort study design. Relevant information was collected through questionnaires and physical examinations. The χ2 trend test was used to compare the changes in the rates of underweight and overweight/obesity over the years, and the linear mixed-e?ects model (LMM) was used to fit trajectory curves of BMI changes with advancing age in older adults. Results:The baseline ages of the participants included in 2002, 2005, 2008, 2011, 2014, and 2018 were (85.16±11.26), (84.23±11.83), (84.99±12.16), (81.10±11.86), (78.89±11.30), and (83.08±12.42) years, respectively, with a relatively high proportion of females and rural residents. In the cohort study, the 13 755 participants had a median ( Q1, Q3) follow-up time of 6.5 (5.2, 10.0) years, with a cumulative follow-up duration of 109 041 person-years. In each wave, males had higher BMI than females, urban residents had higher BMI than rural residents, and BMI gradually decreased with increasing age (all P<0.001). The mean BMI of older adults in China increased from (19.37±3.80) kg/m2 in 2002 to (22.04±4.01) kg/m2 in 2018 ( P<0.001). Across all survey years, the prevalence of underweight was consistently higher in women than in men and in rural areas than in urban areas, with an upward trend as age increased (all P<0.001). In 2018, the underweight rates in the 65-79, 80-89, 90-99, and ≥100-year-old age groups were 8.0%, 16.7%, 26.2%, and 35.5%, respectively. Meanwhile, the prevalence of overweight/obesity was higher in men than in women and in urban areas than in rural areas, showing a declining trend with advancing age (all P<0.001). The prevalence of underweight among the older adults decreased significantly from 45.2% in 2002 to 18.9% in 2018 ( P<0.001), while the prevalence of overweight/obesity increased from 11.0% in 1998 to 29.6% in 2018 ( P<0.001). The trajectory curves fitted by the LMM model showed that individuals born in later decades had higher BMI levels at the same age compared to earlier cohorts. Conclusion:From 2002 to 2018, the BMI level among Chinese older adults showed an increasing trend. The prevalence of underweight showed a declining trend, while the rates of obesity and overweight increased. However, the underweight rate remained notably high among the oldest old.

Objective:To investigate the iodine nutrition status of pregnant women in Zhejiang Province, explore the impact of salt industry system reform on iodine nutrition level of pregnant women, and provide scientific basis for prevention and treatment of iodine deficiency disorders.Methods:From 2016 to 2021, a multi-stage stratified sampling method was used to select 100 pregnant women from 90 counties (cities, districts) in Zhejiang Province each year as survey subjects. Salt samples were collected from pregnant women's families, and one random urine sample was taken for salt iodine and urinary iodine level testing, respectively.Results:A total of 56 581 samples of household edible salt were collected from pregnant women, with a median salt iodine level of 23.20 mg/kg. Among them, 7 961 were non iodized salt, 45 803 were qualified iodized salt, and 2 817 were unqualified iodized salt. The iodized salt coverage rate was 85.93% (48 620/56 581), and the qualified iodized salt consumption rate was 80.95% (45 803/56 581). The proportion of non iodized salt increased from 10.05% (897/8 928) in 2016 to 15.09% (1 461/9 679) in 2021 (χ 2trend = 95.16, P < 0.001). A total of 56 581 urine samples were collected from pregnant women, with a median urinary iodine level of 130.50 μg/L. Among them, the proportions of urinary iodine levels < 150, 150 - 249, 250 - 499, and ≥500 μg/L were 58.32% (32 996/56 581), 27.24% (15 410/56 581), 12.24% (6 926/56 581), and 2.21% (1 249/56 581), respectively. The median urinary iodine level of pregnant women in inland areas was significantly higher than that in coastal areas ( Z = 19.15, P < 0.001). Furthermore, urinary iodine levels exhibited a non-linear decline as age increased (χ 2regression = 12.65, P < 0.001; χ 2partial = 22.65, P < 0.001) and as pregnancy progressed (χ 2regression = 37.28, P < 0.001; χ 2partial = 18.89, P < 0.001). Conclusions:The overall iodine nutrition status of pregnant women in Zhejiang Province is in a state of iodine deficiency (< 150 μg/L), and there is a greater risk in coastal areas compared to inland areas. However, in the context of the reform of the salt industry system, it is still necessary to strengthen the quality supervision of iodized salt, provide scientific iodine supplementation education, promote specialized iodized salt for pregnant women, and strengthen interventions for prevention and control of iodine deficiency disorders.

Objective:To investigate the iodine nutrition status of pregnant women in Zhejiang Province, explore the impact of salt industry system reform on iodine nutrition level of pregnant women, and provide scientific basis for prevention and treatment of iodine deficiency disorders.Methods:From 2016 to 2021, a multi-stage stratified sampling method was used to select 100 pregnant women from 90 counties (cities, districts) in Zhejiang Province each year as survey subjects. Salt samples were collected from pregnant women's families, and one random urine sample was taken for salt iodine and urinary iodine level testing, respectively.Results:A total of 56 581 samples of household edible salt were collected from pregnant women, with a median salt iodine level of 23.20 mg/kg. Among them, 7 961 were non iodized salt, 45 803 were qualified iodized salt, and 2 817 were unqualified iodized salt. The iodized salt coverage rate was 85.93% (48 620/56 581), and the qualified iodized salt consumption rate was 80.95% (45 803/56 581). The proportion of non iodized salt increased from 10.05% (897/8 928) in 2016 to 15.09% (1 461/9 679) in 2021 (χ 2trend = 95.16, P < 0.001). A total of 56 581 urine samples were collected from pregnant women, with a median urinary iodine level of 130.50 μg/L. Among them, the proportions of urinary iodine levels < 150, 150 - 249, 250 - 499, and ≥500 μg/L were 58.32% (32 996/56 581), 27.24% (15 410/56 581), 12.24% (6 926/56 581), and 2.21% (1 249/56 581), respectively. The median urinary iodine level of pregnant women in inland areas was significantly higher than that in coastal areas ( Z = 19.15, P < 0.001). Furthermore, urinary iodine levels exhibited a non-linear decline as age increased (χ 2regression = 12.65, P < 0.001; χ 2partial = 22.65, P < 0.001) and as pregnancy progressed (χ 2regression = 37.28, P < 0.001; χ 2partial = 18.89, P < 0.001). Conclusions:The overall iodine nutrition status of pregnant women in Zhejiang Province is in a state of iodine deficiency (< 150 μg/L), and there is a greater risk in coastal areas compared to inland areas. However, in the context of the reform of the salt industry system, it is still necessary to strengthen the quality supervision of iodized salt, provide scientific iodine supplementation education, promote specialized iodized salt for pregnant women, and strengthen interventions for prevention and control of iodine deficiency disorders.

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.