Search

Background: Gastric cancer (GC) remains a malignant tumor with high morbidity and mortality, accounting for approximately 1,080,000 diagnosed cases and 770,000 deaths worldwide annually. Disulfidptosis, characterized by the stress-induced abnormal accumulation of disulfide, is a recently identified form of programmed cell death. Substantial studies have demonstrated the significant influence of immune clearance on tumor progression. Therefore, we aimed to explore the intrinsic correlations between disulfidptosis and immune-related genes (IRGs) in GC, as well as the potential value of disulfidptosis-related immune genes (DRIGs) as biomarkers. Methods: This study incorporated the single-cell RNA sequencing (scRNA-seq) dataset GSE183904 and transcriptome RNA sequencing of GC from the TCGA database. Disulfidptosis-related genes (DRGs) and IRGs were derived from the representative literature on both cell disulfidptosis and immunity. The expression and distribution of DRGs were investigated at the single-cell level in different GC cell types. Pearson correlation analysis was used to identify the IRGs closely related to disulfidptosis. The prognostic signature of DRIGs was established using Cox and LASSO analyses. We then analyzed and evaluated the differences in long-term prognosis, Gene Set Enrichment Analysis (GSEA), immune infiltration, mutation profile, CD274 expression, and response to chemotherapeutic drugs between the two groups. A tissue array containing 63 paired GC specimens was used to verify the expression of 4 DRIGs and disulfidptosis regulator SLC7A11 through immunohistochemistry staining. Results: The scRNA-seq analysis found that SLC7A11, SLC3A2, RPN1 and NCKAP1 were enriched in specific cell types and closely related to immune infiltration. Four DIRGs (GLA, HIF-1α, VPS35 and CDC37) were successfully identified to establish a signature to potently predict the survival time of GC patients. Patients with high risk scores generally experienced worse prognoses and exhibited greater resistant to classical chemotherapy drugs. Furthermore, the expression of GLA, HIF-1α, VPS35, CDC37 and SLC7A11 were elevated in GC tissues. A high expression of GLA, HIF-1α, VPS35 or CDC37 was associated with more advanced clinical stage of GC and increased SLC7A11 expression. Conclusion: Current study first highlights the potential value of DRIGs as biomarkers in GC. We successfully constructed a robust model incorporating four DRIGs to accurately predict the survival time and clinicopathological characteristics of GC patients. [ABSTRACT FROM AUTHOR]

Corrosion fatigue test is the most direct and effective method to study the corrosion fatigue characteristics of sucker rod. At present, the commonly used test method is the high frequency fatigue test, but the working state of sucker rod is typical low-frequency and high-cycle corrosion fatigue, and the test with high frequency will reduce the impact of corrosion. Alloy steel 4330 is widely used in coalbed gas well high strength sucker rod, but the research on its low frequency corrosion fatigue life is relatively few. Therefore, in this paper, the corrosion fatigue test method of axial low-frequency and high-cycle was adopted to study the corrosion fatigue characteristics of 4330 steel sucker rod through the corrosion fatigue test under different typical corrosion media, temperature, and stress levels. The results show that the fatigue life of 4330 sucker rod drops sharply when the Cl− concentration in high salinity well fluid exceeds the threshold value of 155 mg/L. When this threshold is exceeded, the downward trend slows down. It can be seen that the significant factor affecting the corrosion fatigue life of 4330 material is not the concentration of Cl−, but the existence of Cl−. The presence of HCO3− promotes a further decrease in the corrosion fatigue life of the 4330 sucker rod by Cl−. The corrosion fatigue life of 4330 sucker rod decreases with the increase of temperature. When the well fluid temperature is less than 50 °C, the impact is relatively significant. When the well fluid temperature is more than 70 °C, the decline trend of corrosion fatigue life slows down. Based on the fitted S-N curve (stress-fatigue life curve), it is calculated that the fatigue limit of 4330 sucker rod at the stress ratio of 0.6 is 196 MPa in the solution of 10,000 mg/L Cl− at room temperature. These could provide valuable theoretical and technical guidance for design and selection of high-strength sucker rod in high-salinity corrosion well fluid environment. [ABSTRACT FROM AUTHOR]

In this study, the co-combustion of coal and biomass, and the tri-combustion of coal, biomass, and oil sludge in a 130 t h−1 circulating fluidized bed (CFB) boiler are investigated via the computational particle fluid dynamics (CPFD) approach. Furthermore, the effect of biomass feeding position is also comprehensively evaluated. The results show that for the co-combustion of coal and biomass, the O2 mole fraction at the furnace outlet rises from 0.0541 to 0.0640 as the biomass blending ratio enhances from 40% to 100%, while the CO2 mole fraction reduces from 0.1357 to 0.1267. The mole fraction of NOx and SO2 at the furnace outlet decreases from 4.5867 × 10−5 to 3.9096 × 10−5 and 2.8253 × 10−4 to 4.6635 × 10−5, respectively. For the tri-combustion of three fuels, the average NOx mole fraction initially grows quickly and then declines gradually, ranging from 4.1173 × 10−5 to 4.2556 × 10−5. The mole fraction of SO2 at the furnace outlet increases from 3.5176 × 10−4 to 4.7043 × 10−4 when the ratio of oil sludge rises from 10% to 20%. The uniformity of temperature and gas components distribution is "new inlet > secondary air inlet > feed inlet". As for the three inlet positions, the mole fractions of NOx at the furnace outlet are between 3.9096 × 10−5 and 5.1537 × 10−5, while those for SO2 are between 2.5978 × 10−4 and 2.5278 × 10−4. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis. Methods: We conducted differential gene expression analysis on patient samples from The Cancer Genome Atlas (TCGA) and enriched our understanding of gene functions. Using the least absolute selection and shrinkage operator (LASSO) regression, we established a risk model and validated it using an independent dataset from the International Cancer Genome Consortium (ICGC). Clinical variables were incorporated into a nomogram to predict overall survival (OS), and machine learning was used to explore the risk factor characteristics' impact on PCa prognosis. Our prognostic model was confirmed using various databases, including single-cell RNA-sequencing datasets (scRNA-seq), the Cancer Cell Line Encyclopedia (CCLE), PCa cell lines, and tumor tissues. Results: We identified 83 differentially expressed genes (DEGs). Furthermore, WASIR1, KRTAP5-1, TLX1, KIF4A, and IQGAP3 were determined to be significant risk factors for OS and progression-free survival (PFS). Based on these five risk factors, we developed a risk model and nomogram for predicting OS and PFS, with a C-index of 0.823 (95% CI, 0.766–0.881) and a 10-year area under the curve (AUC) value of 0.788 (95% CI, 0.633–0.943). Additionally, the 3-year AUC was 0.759 when validating using ICGC. KRTAP5-1 and WASIR1 were found to be the most influential prognosis factors when using the optimized machine learning model. Finally, the established model was interrelated with immune cell infiltration, and the signals were found to be differentially expressed in PCa cells when using scRNA-seq datasets and tissues. Conclusions: We engineered an original and novel prognostic model based on five gene signatures through TCGA and machine learning, providing new insights into the risk of scarification and survival prediction for PCa patients in clinical practice. [ABSTRACT FROM AUTHOR]