Research Article
Regression–Based Diagnostic Models for Early Lung Cancer Integrating Conventional Indicators with Tumor Markers
Shufang Zhou,
Xiaojun Ge*,
Zhifang Yang,
Fei Zeng
Issue:
Volume 12, Issue 3, June 2024
Pages:
20-27
Received:
25 April 2024
Accepted:
4 June 2024
Published:
6 June 2024
Abstract: The aim of this research was to develop a lung cancer diagnostic and predictive model that integrates traditional laboratory indicators with tumor markers. This model is intended to facilitate early screening and assist in the process of identifying or detecting lung cancer through a cost-effective, rapid, and convenient approach, ultimately enhancing the early detection rate of lung cancer. A retrospective study was conducted on 66 patients diagnosed with lung cancer and 159 patients with benign pulmonary conditions. Data including general clinical information, conventional laboratory test results, and tumor marker levels were collected. Data analysis was conducted using SPSS 26.0 (Statistical Product and Service Solutions 26.0). The lung cancer diagnosis and prediction model is created using a composite index established through binary logistic regression. The combined diagnostic prediction models, incorporating both traditional indicators and tumor markers, demonstrated a greater area under the curve (AUC) when compared to the diagnostic prediction model based solely on tumor markers and their combination testing. The values of cut-off point, AUC, accuracy, sensitivity, specificity, positive and negative detection rate and accuracy rate are 0.1805, 0.959, 86.67%, 0.955, 0.830, 95.45%, 83.02% and 89.33 respectively and it is shown that the combined diagnostic model display notable efficacy and clinical relevance in aiding the early diagnosis of lung cancer.
Abstract: The aim of this research was to develop a lung cancer diagnostic and predictive model that integrates traditional laboratory indicators with tumor markers. This model is intended to facilitate early screening and assist in the process of identifying or detecting lung cancer through a cost-effective, rapid, and convenient approach, ultimately enhanc...
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Research Article
Study on the Effect of Rhubarb and Its Active Components on Pyroptosis in DKD by Regulating STAT3/Caspase-11 Axis
Issue:
Volume 12, Issue 3, June 2024
Pages:
28-44
Received:
5 July 2024
Accepted:
22 July 2024
Published:
29 July 2024
Abstract: Rhubarb has been found to have a certain protective effect on improving the kidney function. However, the specific mechanism is still unclear. In this study, network pharmacology, molecular docking spontaneous binding technology and molecular biology experiments were used to verify the mechanism of rhubarb and its active ingredients in the treatment of DKD. A total of 10 active compounds and 121 (larger than average) target proteins were collected. The target proteins with higher degree value were screened by PPI according to degree value as follows: AKT1, STAT3, EGFR, NFKB1, SRC, etc. GO and KEGG enrichment analysis suggest that rhubarb therapy for DKD mainly involves Pathways in cancer, Prostate cancer, Proteoglycans in cancer, Chemokine signaling pathway, PI3K-Akt signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, EGFR tyrosine kinase inhibitor resistance signaling pathway and so on. Furthermore, molecular docking results suggest that hydrogen bonding, salt bridge and hydrophobic interactions contribute to spontaneous binding of the compound to the target protein. Experimental verification shows that rhubarb and aloe emodin affect the mechanism of pyroptosis in diabetic kidney disease by regulating STAT3/Caspase11 axis. In conclusion, this study comprehensively elaborated the active compounds, potential targets and molecular experimental mechanisms of rhubarb to provide the basic experimental theory for clinical treatment of DKD.
Abstract: Rhubarb has been found to have a certain protective effect on improving the kidney function. However, the specific mechanism is still unclear. In this study, network pharmacology, molecular docking spontaneous binding technology and molecular biology experiments were used to verify the mechanism of rhubarb and its active ingredients in the treatmen...
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,
Minghao Zhang
