Construction and validation of a nomogram for cancer specific survival of postoperative pancreatic cancer based on the SEER and China database.

BACKGROUND: The recurrence rate and mortality rate among postoperative pancreatic cancer patients remain elevated. This study aims to develop and validate the cancer-specific survival period for individuals who have undergone pancreatic cancer surgery. METHODS: We extracted eligible data from the Surveillance, Epidemiology, and End Results database and randomly divided all patients into a training cohort and an internal validation cohort. External validation was performed using a separate Chinese cohort. The nomogram was developed using significant risk factors identified through univariate and multivariate Cox proportional hazards regression. The effectiveness of the nomogram was assessed using the area under the time-dependent curve, calibration plots, and decision curve analysis. Kaplan-Meier survival curves were utilized to visualize the risk stratification of nomogram and AJCC stage. RESULTS: Seven variables were identified through univariate and multivariate analysis to construct the nomogram. The consistency index of the nomogram for predicting overall survival was 0.683 (95% CI: 0.675-0.690), 0.689 (95% CI: 0.677-0.701), and 0.823 (95% CI: 0.786-0.860). The AUC values for the 1- and 2-year time-ROC curves were 0.751 and 0.721 for the training cohort, 0.731 and 0.7554 for the internal validation cohort, and 0.901 and 0.830 for the external validation cohorts, respectively. Calibration plots demonstrated favorable consistency between the predictions of the nomogram and actual observations. Moreover, the decision curve analysis indicated the clinical utility of the nomogram, and the risk stratification of the nomogram effectively identified high-risk patients. CONCLUSION: The nomogram guides clinicians in assessing the survival period of postoperative pancreatic cancer patients, identifying high-risk groups, and devising tailored follow-up strategies.

[Study on mechanism of icariin-induced ferroptosis in HepG2 hepatoma carcinoma cells through PPARG/FABP4/GPX4 pathway].

The aim of this study was to explore the mechanism of icaritin-induced ferroptosis in hepatoma HepG2 cells. By bioinformatics screening, the target of icariin's intervention in liver cancer ferroptosis was selected, the protein-protein interaction(PPI) network was constructed, the related pathways were focused, the binding ability of icariin and target protein was evaluated by molecular docking, and the impact on patients' survival prognosis was predicted and the clinical prediction model was built. CCK-8, EdU, and clonal formation assays were used to detect cell viability and cell proliferation; colorimetric method and BODIPY 581/591 C1 fluorescent probe were used to detect the levels of Fe~(2+), MDA and GSH in cells, and the ability of icariin to induce HCC cell ferroptosis was evaluated; RT-qPCR and Western blot detection were used to verify the mRNA and protein levels of GPX4, xCT, PPARG, and FABP4 to determine the expression changes of these ferroptosis-related genes in response to icariin. Six intervention targets(AR, AURKA, PPARG, AKR1C3, ALB, NQO1) identified through bioinformatic analysis were used to establish a risk scoring system that aids in estimating the survival prognosis of HCC patients. In conjunction with patient age and TNM staging, a comprehensive Nomogram clinical prediction model was developed to forecast the 1-, 3-, and 5-year survival of HCC patients. Experimental results revealed that icariin effectively inhibited the activity and proliferation of HCC cells HepG2, significantly modulating levels of Fe~(2+), MDA, and lipid peroxidation ROS while reducing GSH levels, hence revealing its potential to induce ferroptosis in HCC cells. Icariin was found to diminish the expression of GPX4 and xCT(P<0.01), inducing ferroptosis in HCC cells, potentially in relation to inhibition of PPARG and FABP4(P<0.01). In summary, icariin induces ferroptosis in HCC cells via the PPARG/FABP4/GPX4 pathway, providing an experimental foundation for utilizing the traditional Chinese medicine icariin in the prevention or treatment of HCC.

Causal relationship between human blood metabolites and risk of ischemic stroke: a Mendelian randomization study.

Background: Ischemic stroke (IS) is a major cause of death and disability worldwide. Previous studies have reported associations between metabolic disorders and IS. However, evidence regarding the causal relationship between blood metabolites and IS lacking. Methods: A two-sample Mendelian randomization analysis (MR) was used to assess the causal relationship between 1,400 serum metabolites and IS. The inverse variance-weighted (IVW) method was employed to estimate the causal effect between exposure and outcome. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode approaches were employed as supplementary comprehensive evaluations of the causal effects between blood metabolites and IS. Tests for pleiotropy and heterogeneity were conducted. Results: After rigorous selection, 23 known and 5 unknown metabolites were identified to be associated with IS. Among the 23 known metabolites, 13 showed significant causal effects with IS based on 2 MR methods, including 5-acetylamino-6-formylamino-3-methyluracil, 1-ribosyl-imidazoleacetate, Behenoylcarnitine (C22), N-acetyltyrosine, and N-acetylputrescine to (N (1) + N (8))-acetate,these five metabolites were positively associated with increased IS risk. Xanthurenate, Glycosyl-N-tricosanoyl-sphingadienine, Orotate, Bilirubin (E,E), Bilirubin degradation product, C17H18N2O, Bilirubin (Z,Z) to androsterone glucuronide, Bilirubin (Z,Z) to etiocholanolone glucuronide, Biliverdin, and Uridine to pseudouridine ratio were associated with decreased IS risk. Conclusion: Among 1,400 blood metabolites, this study identified 23 known metabolites that are significantly associated with IS risk, with 13 being more prominent. The integration of genomics and metabolomics provides important insights for the screening and prevention of IS.

Development of a Nomogram Using the Inflammatory Risk Score for Prognostication in Moderate and Advanced Hepatocellular Carcinoma Associated with Hepatitis B Virus.

Background: The changes in risk scores of inflammatory markers among patients diagnosed with hepatocellular carcinoma (HCC) remain unknown. Aims: To investigate the relationship between the inflammation risk score and other contributing factors and the prognostic outcomes in patients with moderate and advanced hepatitis B virus (HBV)-related HCC. Study Design: A retrospective cohort study. Methods: A total of 174 patients with moderate and advanced HBV related HCC were recruited to investigate the impact of stratified inflammatory risk scores and other associated risk factors on disease prognosis. Based on the optimal cut-off values calculated by the Youden index, the patients were divided into high-risk and low-risk groups based on their inflammation risk scores. Results: The study found a significant difference in median survival time between the low-risk and high-risk groups based on the inflammation risk score. Furthermore, the inflammation risk score, alpha-fetoprotein levels, transarterial chemoembolization treatment, and Barcelona Clinic Liver Cancer stage were identified as independent prognostic factors. The four variables were used to construct a prognostic nomogram for HCC. Subsequent evaluations using time-dependent receiver operating characteristic analysis and calibration curve tests revealed the nomogram's commendable discriminatory ability. As a result, the nomogram proved to be an effective tool for predicting survival at 2- to 4-years. Conclusion: The inflammation risk score has been identified as a significant prognostic factor for HBV-related HCC. The development of nomogram models has provided a practical and effective tool for determining the prognosis of patients affected by HBV-related HCC.

Polyphyllin II (PPII) Enhances the Sensitivity of Multidrug-resistant A549/DDP Cells to Cisplatin by Modulating Mitochondrial Energy Metabolism.

BACKGROUND/AIM: Cisplatin resistance often leads to treatment futility and elevated mortality rates in patients with lung cancer. One promising strategy to address this challenge involves the integration of traditional Chinese medicine (TCM) with chemotherapeutic drugs. Currently, the potential synergistic effect and underlying mechanism of polyphyllin II (PPII) and cisplatin combination in combating cisplatin (DDP) resistance in lung cancer remain unexplored. MATERIALS AND METHODS: In this study, we established a cisplatin resistance model using A549 cells and explored the underlying mechanisms of PPII in combination with cisplatin in A549/DDP resistant cells. Specifically, we assessed the impact of PPII combined with cisplatin on A549/DDP cell proliferation, viability, and the expression of apoptosis-related proteins. To gain deeper insights into the underlying mechanism, we examined the effects of PPII and cisplatin on mitochondrial function in A549/DDP cells. RESULTS: This combination induced cell cycle arrest at both the S phase and G2/M phase in A549/DDP cells, thereby promoting apoptosis. Western blotting confirmed that DDP acted synergistically with PPII to enhance the expression of apoptotic proteins, diminish the expression of anti-apoptotic proteins, and promote the expression of anti-proliferation proteins in the mitochondrial pathway of A549/DDP cells. CONCLUSION: The combination of PPII and cisplatin effectively modulated the mitochondrial function, thereby reversing drug resistance in A549/DDP cells. This innovative combination therapy shows significant promise as a novel strategy for overcoming cisplatin resistance in lung cancer.

Construction and validation of a SEER-based prognostic nomogram for young and middle-aged males patients with hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common digestive tumor, and we aimed to develop and validate nomogram models, predicting the overall survival (OS) of young and middle-aged male patients with HCC. METHODS: We extracted eligible data from relevant patients between 2000 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. In addition, randomly divided all patients into two groups (training and validation = 7:3). The nomogram was established using effective risk factors based on univariate and multivariate analysis. The area under the time-dependent curve, calibration plots, and decision curve analysis (DCA) were used to evaluate the effective performance of the nomogram. The risk stratifications of the nomogram and the AJCC criteria-based tumor stage were compared. RESULTS: 11 variables were selected by univariate and multivariate analysis to establish the nomogram of HCC. The AUC values of 3, 4, and 5 years of the time-ROC curve are 0.858, 0.862 and 0.859 for the training cohort, and 0.858, 0.877 and 0.869 for the validation cohort, respectively, indicating that the nomogram has a good ability of discrimination. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. In addition, the decision curve DCA showed that the nomogram was clinically useful and had better discriminative ability to recognize patients at high risk than the AJCC criteria-based tumor stage. CONCLUSION: Prognostic nomogram of young and middle-aged male patients with HCC was developed and validated to help clinicians evaluate the prognosis of patients.

Construction and validation of a nomogram for hepatocellular carcinoma patients treated by traditional Chinese medicine based on inflammation, nutrition, and blood lipid indicators.

PURPOSE: To establish a nomogram for hepatocellular carcinoma (HCC) patients treated by traditional Chinese medicine (TCM). METHODS: Clinical cases of HCC patients treated by TCM at Hunan Integrated Traditional Chinese and Western Medicine Hospital, and it was randomly divided into the training cohort (n = 222) and the validation cohort (n = 95). In the training cohort, independent risk factors were determined by Cox regression analysis and a nomogram was constructed. The efficiency and clinical applicability of nomograms were evaluated using time-dependent curves, calibration, and the decision curve (DCA), and the patients were divided into high-risk, middle-risk and low-risk groups using X-tile software. RESULTS: Multivariate Cox regression analysis screened 6 independent risk factors to construct a nomogram of HCC patients, including TNM stage, treatment methods, high-density lipoprotein (HDL), neutrophil-to-lymphocyte ratio (NLR), albumin-to-globulin ratio (AGR), and prognostic nutritional index (PNI). The consistency index (C-index) of the nomogram of the training was 0.811 (0.794-0.829) and the validation cohort was 0.825 (0.800-0.849). The time dependency showed the AUC values of the nomogram for 3 and 5 years in training cohort were 0.894 (95% CI 0.840-0.948) and 0.952 (95% CI 0.914-0.990), and the validation cohort were 0.928 (95% CI 0.865-0.990) and 0.96 3(95% CI 0.916-1.010). The calibration plot showed the nomogram fits well onto perfect curves, and the DCA curve showed the net benefit of the nomogram at a certain probability threshold is significantly higher than the net benefit of the TNM stage at the same threshold probability. Finally, all the patients were divided into high-risk, middle-risk and low-risk groups based on the total score of nomogram, and it showed effectively how to identify to high-risk patients. CONCLUSION: The nomogram established by the independent risk factors of TNM stage, treatment methods, HDL, AGR, NLR and PNI can predict the prognosis of HCC patients treated by TCM, providing an effective tool to clinical workers to evaluate the prognosis and survival time of HCC patients.

Construction and validation of a nomogram for hepatocellular carcinoma patients based on HCC-GRIm score.

PURPOSE: To construct a nomogram for hepatocellular carcinoma (HCC) patients base on HCC-GRIm score. METHODS: Clinical cases of HCC patients diagnosed at Hunan Integrated Traditional Chinese and Western Medicine Hospital were included, and these were randomly divided into the training cohort (n = 219) and the validation cohort (n = 94), and those patients were divided into low GRIm-Score group (scores 0, 1, and 2) and high GRIm-Score group (scores 3, 4, and 5). In the training cohort, independent risk factors were determined by Cox regression analysis, and a nomogram was constructed by independent risk factors. The efficiency and the clinical applicability of nomograms were evaluated using ROC curves, calibration plot, and the decision curve (DCA), and the patients were divided into high-risk, middle-risk, and low-risk groups according to total score of nomogram. RESULTS: Compared to low HCC-GRIm score group, high HCC-GRIm score group with BCLC stage is more advanced (P < 0.001), and fewer patients received TACE (P = 0.005) and surgical treatment (P = 0.001). There was higher rate of the presence of vascular invasion (P < 0.001) and distant metastasis (P < 0.001). Multivariate Cox regression analysis screened 4 independent risk factors to construct a nomogram of HCC patients, including HCC-GRIm score, BCLC stage, albumin-to-globulin ratio (AGR), and glutamyl trans-peptidase (GGT). The consistency index (C-index) of the nomogram of the training was 0.843 (0.832-0.854) and the validation was 0.870 (0.856-0.885). The time-dependent parameter showed the AUC values of the training cohort at 1, 3, and 5 years were 0.954 (95% CI 0.929-0.980), 0.952 (95% CI 0.919-0.985), and 925 (95% CI 0.871-0.979), while the AUC values of validation cohort at 1, 3, and 5 years were 0.974 (95% CI 0.950-0.998), 0.965 (95% CI 0.931-0.999), and 0.959 (95% CI 0.898-1.021). The calibration plot showed the nomogram fits well onto perfect curves, and the DCA curve showed the net benefit of the nomogram at a certain probability threshold is significantly higher than the net benefit of the BCLC stage at the same threshold probability. Finally, all patients were divided into high-risk, middle-risk, and low-risk groups based on the total score of nomogram, and it showed effectively to identify high-risk patients. CONCLUSION: The nomogram constructed by the independent risk factors can predict the prognosis of HCC patients, providing an effective tool with clinical workers to evaluate the prognosis and survival time of HCC patients.

Analysis on Spatio-Temporal Evolution and Influencing Factors of Air Quality Index (AQI) in China.

After the reform and opening up, China's economy has developed rapidly. However, environmental problems have gradually emerged, the top of which is air pollution. We have used the following methods: In view of the shortcomings of the current spatio-temporal evolution analysis of the Air Quality Index (AQI) that is not detailed to the county level and the lack of analysis of its underlying causes, this study collects the AQI of all counties in China from 2014 to 2021, and uses spatial autocorrelation and other analysis methods to deeply analyze the spatio-temporal evolution characteristic. Based on the provincial panel data, the spatial econometric model is used to explore its influencing factors and spillover effects. The research results show that: (1) From 2014 to 2021, the AQI of all counties in China showed obvious spatial agglomeration characteristics, and counties in central and western Xinjiang, as well as Beijing, Tianjin, and Hebei, were high-value agglomeration areas; (2) the change trend of the AQI value also has obvious spatial autocorrelation, and generally presents a downward trend. However, the AQI value in a small number of regions, such as Xinjiang, shows a slow decline or even a reverse rise; (3) there are some of the main factors affecting AQI, such as GDP per capita, percentage of forest cover, total emissions of SO2, and these factors have different impacts on different regions. In addition, the increase of GDP per capita, the reduction of industrialization level, and the increase of forest coverage will significantly improve the air quality of other surrounding provinces. An in-depth analysis of the spatio-temporal evolution, influencing factors, and spillover effects of AQI in China is conducive to formulating countermeasures to improve air quality according to local conditions and promoting regional sustainable development.

Atherosclerosis Vascular Endothelial Secretion Dysfunction and Smooth Muscle Cell Proliferation.

Atherosclerosis is a chronic inflammatory disease of the arterial wall and the main cause of cardiovascular disease and cerebrovascular disease. In recent years, the mortality rate of atherosclerotic diseases has become higher and higher. This article aims to study the dysregulation of atherosclerotic vascular endothelial secretion and smooth muscle cell proliferation, and put forward and practice the pathological research of atherosclerotic disease. This article describes in detail atherosclerosis, endothelial dysfunction, and smooth muscle cell proliferation, and studies the causes of atherosclerosis. Research results indicate that atherosclerotic vascular endothelial dysfunction also has a great influence on the proliferation of smooth muscle cells. Many genes and environmental factors can regulate the functions of endothelial cells, vascular smooth muscle cells, and mononuclear macrophages and affect the formation of atherosclerosis. At the same time, diabetes, hypertension, hyperlipidemia, obesity, etc. are the main causes of atherosclerosis. The number of patients with cardiovascular and cerebrovascular diseases dying from atherosclerosis in the country is increasing, and the proportion is close to 30%.