Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

Objective:To study and screen the differential expression of inflammatory proteins in diabetes skin ulcers and common skin ulcers, so as to provide experimental basis for further research on anti-inflammatory and healing drug targets of diabetes skin ulcers.Methods:The tissues of 11 patients with diabetes skin ulcer, 12 patients with common skin ulcer and 11 patients with normal skin were collected from the First Hospital of Hunan University of Chinese Medicine. The levels of inflammatory protein Toll like receptor 4 (TLR4), nuclear factor κB (NF-κB), pro-inflammatory factor interferon -γ (IFN -γ), tumor necrosis factor - α (TNF -α), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-1β (IL-1β), macrophage chemotactic protein-1 (MCP-1), anti-inflammatory factors epidermal growth factor (EGF), interleukin-4 (IL-4), and interleukin-10 (IL-10) were detected in three groups of tissues using enzyme-linked immunosorbent assay (ELISA).Results:Compared with normal tissues, the concentrations of TLR4, NF-κB, IFN -γ, TNF -α, IL-1β, IL-6, IL-8, MCP-1 and EGF in common ulcer skin tissues and diabetes ulcer tissues were higher, and the concentrations of IL-10 were lower, with statistically significant differences (all P<0.05); Compared with the normal tissue, the concentration of IL-4 in diabetes ulcer tissue was lower, the difference was statistically significant ( P<0.05); Compared with ordinary ulcer skin tissue, the concentrations of TLR4, NF-κB and MCP-1 in diabetes ulcer tissue were higher, and the concentrations of IL-4 were lower, with statistically significant differences (all P<0.05). Conclusions:The skin ulcer in diabetes patients will have inflammatory reaction, and high glucose promotes the inflammatory reaction of skin ulcer, which may be related to the abnormal expression of TLR4, NF-κB, MCP-1 and IL-4. TLR4/NF-κB signal pathway and inflammatory factors MCP-1 and IL-4 may be the target of the inflammation regulation of diabetes skin ulcer.

Objective:To analyze the association between visceral fat area (VFA) and fatty liver based on quantitative CT (QCT) in people receiving health examination with normal body mass index (BMI).Methods:A cross-sectional study. A total of 1 305 physical examiners who underwent chest CT and QCT examination in the Department of Health Management of Henan Provincial People′s Hospital from January to December 2021 were retrospectively selected as subjects. The physical components at the central level of the lumbar two cone were measured with QCT, including subcutaneous fat area (SFA), VFA and liver fat content (LFC). And the metabolic indexes, such as blood lipids and blood glucose, were collected. The t-test and χ2 test were used to analyze the correlation between the detection rate of fatty live and LFCr and age and gender. According to level of VFA (<100 cm 2, 100-150 cm 2 and≥150 cm 2), the subjects were divided into three groups, and one-way ANOVA and χ2 test were used in comparison between groups. Multiple linear regression was used to analyze the correlation between VFA and metabolic indexes and LFC. Results:Of the 1 305 subjects, there were 634 males and 671 females. The detection rate of fatty liver in normal BMI population was 65.67%, and it was 72.71% and 59.02% respectively in men and women ( χ2=27.12, P<0.001), and the detection rate of fatty liver and LFC increased with age (both P<0.05). With the increase of VFA, the age, BMI, SFA, LFC, total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), alanine aminotransferase (ALT), blood uric acid and prevalence of fatty liver increased (all P<0.05), and the low-density lipoprotein cholesterol (HDL-C) decreased ( P<0.001). Multiple linear regression analysis showed that after adjustment for age factors, regardless of male or female, LFC was independently positively related with VFA, BMI, and ALT (male β=0.206, 0.145, 0.174, female β=0.194, 0.150, 0.184; all P<0.05). FBG was positively correlated with male independently ( β=0.134; P<0.001). The indicators related to female independently were TC, TG, and blood uric acid ( β=-0.121, 0.145, 0.141, all P<0.05) Conclusion:In the population receiving health examination with normal BMI, the VFA measured by QCT technique is closely related to fatty liver.

Objective:To investigate the mechanism of Morin hydrate(MH)on pyroptosis of alveolar epithelial cells in rats with chronic obstructive pulmonary disease(COPD)by inhibiting nucleotide-binding oligomerization domain-like receptor protein 3(NLRP3)/cysteinyl aspartate specific proteinase-1(Caspase-1)/IL-1β signaling pathway.Methods:COPD model rats were estab-lished by smoking method,which were randomly divided into model group(COPD group),low,medium and high doses MH groups(MH-L,MH-M,MH-H groups)(50,100,200 mg/kg)and positive control group(dexamethasone group,DXMS,0.09 mg/kg),another 10 healthy rats were taken as normal control group(NC group).Pulmonary function indexes[tidal volume(TV),forced vital capacity(FVC)and peak expiratory flow rate(PEF)]were measured;HE staining was used to observe pathological changes of lung tissue;pyroptosis of alveolar epithelial cells was observed by immunofluorescence double staining;levels of inflammatory factors in bronchoalveolar lavage fluid(BALF)were detected by ELISA;levels of NLRP3,Caspase-1,gasdermin D(GSDMD)and IL-1β mRNA were detected by RT-qPCR;protein expressions of SP-C,NLRP3,C-Caspase-1,GSDMD,GSDMD-N and IL-1β in lung tissue were detected by Western blot.Results:Compared with COPD group,pathological changes of lung tissue including lumen stenosis,mucus secretion and bronchial epithelial cell necrosis in DXMS group and MH groups were significantly improved,the pulmonary function indexes(TV,FVC,PEF)were increased obviously(P<0.05),and increased in turn in MH-L,MH-M,MH-H groups(P<0.05);levels of TNF-α,IL-6,IL-8,immunofluorescence expressions of NLRP3 and C-Caspase-1,and mRNA levels of NLRP3,Cas-pase-1,GSDMD,IL-1β,protein levels of NLRP3,C-Caspase-1,GSDMD,GSDMD-N and IL-1β were decreased obviously,while SP-C protein expression was gradually increased(P<0.05).Conclusion:MH can inhibit the NLRP3/Caspase-1/IL-1β signaling path-way,the release of inflammatory factors and pyroptosis by it,and alleviate lung pathological changes in COPD rats.

Objective:To analyze the correlation between body fat distribution measured by quantitative CT (QCT) and body mass index in adults receiving physical examination.Methods:It was a cross-sectional study. From January to December 2021, 3 205 adults undergoing physical examination who met the inclusion criteria and underwent chest CT and QCT examination in the health management discipline of Henan Provincial People′s Hospital were selected as the research objects. The general data were collected; and the subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate were measured by QCT. According to body mass index, the subjects were divided into normal group (18.5-<24.0 kg/m 2, 1 343 cases), overweight group (24.0-<28.0 kg/m 2, 1 427 cases) and obesity group (≥28.0 kg/m 2, 435 cases). One-way analysis of variance and χ2 test were used to compare the differences of QCT indexes among the three groups. Pearson and Spearman correlation analysis were used to evaluate the correlation between QCT indexes and body mass index. Receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic effect of QCT on obesity and fatty liver. Results:Subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate in obese group were all significantly higher than those in overweight group and normal group [males, (147.60±46.44) vs (104.33±27.68), (73.46±22.65) cm 2; (297.46±54.70) vs (229.40±53.12), (159.57±49.68) cm 2; (445.06±70.24) vs (333.73±62.91), (233.02±61.87) cm 2; 11.30% (7.90%, 15.55%) vs 8.75% (6.50%, 11.70%), 6.60% (4.80%, 8.70%); 100.0% vs 96.0%, 64.0%; 92.9% vs 86.7%, 73.3%; females, (213.96±48.61) vs (155.85±35.31), (107.24±31.01) cm 2; (185.41±43.88) vs (142.48±41.75), (96.56±36.50) cm 2; (399.37±68.07) vs (298.33±56.86), (203.80±57.53) cm 2; 9.80% (6.90%, 13.30%) vs 7.30% (5.05%, 9.80%), 5.40%(3.50%, 7.20%); 96.4% vs 74.8%, 28.9%; 87.3% vs 75.6%, 56.5%], and were all positively correlated with body mass index (males, r/ rs=0.709, 0.738, 0.831, 0.402, 0.464, 0.225; females, r/ rs=0.798, 0.695, 0.841, 0.416, 0.605, 0.276) (all P<0.001). In both male and female subjects, the detection rates of obesity based on QCT were significantly higher than those based on body mass index (male, 86.9% vs 16.6%; female, 49.3% vs 8.9%), and the detection rates of fatty liver based on QCT were significantly higher than those based on ultrasound (male, 83.6% vs 57.1%; female, 65.2% vs 27.6%) (all P<0.001). ROC curve showed that when the visceral fat area of 142 cm 2 was used as the cut-off value for the diagnosis of obesity in male subjects, the sensitivity and specificity was 100% and 15.8%, respectively; and when the cut-off value of liver fat content 5.0% was used to diagnose fatty liver, the sensitivity and specificity was 88.9% and 25.1%, respectively. When the visceral fat area of 115 cm 2 was set as the cut-off value for the diagnosis of obesity in female subjects, the sensitivity and specificity was 96.4% and 55.3%, respectively; when the liver fat content of 5.0% was set as the cut-off value for the diagnosis of fatty liver, the sensitivity and specificity was 83.7% and 43.2%, respectively. Conclusions:The indexes of abdominal fat and liver fat measured by QCT in adults receiving physical examination are all positively correlated with body mass index. The effect of QCT in the diagnosis of obesity and fatty liver are both better than body mass index and ultrasound.

Objective:To analyze the distribution of body fat with quantitative computed tomography (QCT) in people with normal body mass index (BMI).Methods:A cross-sectional study was conducted in the physical examination population who underwent chest CT and QCT examination in the Department of Health Management, Henan Provincial People′s Hospital from January to December in 2021, and 1 395 physical examination subjects who met the inclusion criteria were selected as the research subjects. The subjects were divided into five groups according to their age. The general data of the subjects were collected. The total abdominal fat area (TFA), visceral fat area (VFA), subcutaneous fat area (SFA), total abdominal muscle area (TMA) and muscle fat content (MFC) in the subjects were measured by QCT. One-way analysis of variance, Welch test and Kruskal-Wallis test were used to compare the above QCT measurement indexes between the two genders among different age groups with normal BMI. Pearson correlation analysis was used to analyze the correlation between VFA and sarcopenia indexes. Multivariate linear regression was used to analyze the relationship between VFA and linear correlation variables in the related indicators of sarcopenia.Results:There were significant differences in TFA, VFA, TMA and SMI among different age groups in subjects with normal BMI (all P<0.05). Pearson correlation analysis showed that VFA was negatively correlated with TMA in some age groups (male: 18-39 years group: r=-0.351; 40-49 years group: r=-0.278; 60-69 years group: r=-0.245; female:40-49 years group: r=-0.251; 50-59 years group: r=-0.270;≥70 years group: r=-0.391; all P<0.01); it was negatively correlated with SMI (male: 18-39 years group: r=-0.352; 40-49 years group: r=-0.340; 50-59 years group: r=-0.266; 60-69 years group: r=-0.316; female: 40-49 years group: r=-0.240; 50-59 years group: r=-0.284; all P<0.001); it was positively correlated with MFC (male: 18-39 years group: r=0.342; 40-49 years group: r=0.291; female: 50-59 years group: r=0.133; 60-69 years group: r=0.284; all P<0.05). Multivariate linear regression analysis showed that VFA was independently and negatively correlated with SMI in both men and women after adjusting for age interference factors (male B=-1.881, t=-6.025, P<0.001; female B=-0.603, t=-2.887, P=0.004), and it was independently positively correlated with MFC (male B=1.230, t=4.271, P<0.001;female B=0.893, t=3.836, P<0.001). There was an independent negative correlation between VFA and TMA in male subjects ( B=0.263, t=2.478, P=0.013). Conclusions:VFA is correlated with TMA, SMI and MFC in people with normal BMI. Regardless of gender, SMI has a negative effect on VFA, and MFC has a positive effect on VFA.

Objective:To evaluate the role of histogram analysis based on amide proton transfer weighted (APTw) and apparent diffusion coefficient (ADC) imaging in predicting alpha-thalassemia/mental retardation syndrome X-linked ( ATRX) mutation in isocitrate dehydrogenase ( IDH)-mutant WHO grading 2/3 gliomas. Methods:Seventy-eight patients with IDH-mutant WHO grading 2/3 gliomas, admitted to and confirmed by surgical pathology in Department of Functional Neurosurgery, Neurosurgery Center, Zhujiang Hospital, Southern Medical University from June 2017 to October 2023, including 52 with ATRX wild and 26 with ATRX mutant-type, were selected. Preoperative 3D-APTw and ADC imaging data were collected; after post-processing, the lesions were segmented using lesion outlining method based on inclusion of peri-tumor edema and lesion outlining method based on tumor entity, respectively; after that, the histogram features (the 10 th percentile, 90 th percentile, maximum, mean, median, minimum, skewness, kurtosis, entropy, range, uniformity, and variance) were extracted from 3D-APTw and ADC imaging, respectively. Univariate Logistic regression was used to compare the differences in histogram features between patients in the ATRX mutant group and ATRX wild-type group, and multivariate Logistic regression was used to screen the independent predictors for ATRX mutation (a Logistic regression prediction model was constructed). Predictive values of independent predictors and Logistic regression prediction models in ATRX mutation were evaluated by receiver operating characteristic (ROC) curve. Results:(1) With lesion outlining method based on inclusion of peri-tumor edema, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw minimum, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity, and ADC entropy ( P<0.05). With lesion outlining method based on tumor entity, univariate analysis indicated significant difference between ATRX mutant group and ATRX wild-type group in 9 histogram features: relative 3D-APTw 90 th percentile, 3D-APTw skewness, relative ADC 90 th percentile, relative ADC mean, relative ADC median, ADC kurtosis, ADC skewness, ADC uniformity and ADC entropy ( P<0.05). (2) With lesion outlining method based on inclusion of peri-tumor edema, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were the independent predictor for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.168, 95% CI: 0.034-0.800, P=0.025; OR=0.508, 95% CI: 0.319-0.807, P=0.004). The constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.827-1.785×3D-APTw skewness-0.678×ADC kurtosis). With lesion outlining method based on tumor entity, multivariate Logistic regression showed that 3D-APTw skewness and ADC kurtosis were independent predictors for ATRX mutation in IDH mutant WHO grading 2/3 glioma patients ( OR=0.164, 95% CI: 0.034-0.791, P=0.024; OR=0.496, 95% CI: 0.312-0.788, P=0.003); the constructed Logistic regression prediction model was P(Y=1|X)=1/1+e -(1.585-1.810×3D-APTw skewness-0.702×ADC kurtosis). (3) ROC curve analysis showed that, with lesion outlining method based on inclusion of peri-tumor edema, area under ROC curve (AUC) of 3D-APTw skewness and ADC kurtosis was 0.725 (95% CI: 0.608-0.842, P=0.001) and 0.794 (95% CI: 0.685-0.904), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.836 (95% CI: 0.729-0.942, P<0.001), and its sensitivity and specificity were 73.10% and 90.40% when the best threshold was 0.505. ROC curve showed that, with lesion outlining method based on tumor entity, AUC of 3D-APTw skewness and ADC kurtosis was 0.705 (95% CI: 0.587-0.823, P=0.003) and 0.808 (95% CI: 0.704-0.913), respectively ( P<0.001); AUC of Logistic regression prediction model was 0.844 (95% CI: 0.739-0.949, P<0.001), and its sensitivity and specificity were 84.60% and 80.80% when the best threshold was 0.399. Conclusion:Histogram analysis based on 3D-APTw and ADC imaging can predict ATRX mutation in IDH mutant WHO grading 2/3 gliomas to a certain extent.