RESUMO
Objective: This study aimed to assess the correlation and consistency between quantitative CT (QCT) and MRI asymmetric echo least squares estimation iterative water-lipid separation sequence (IDEAL-IQ) in determining pancreatic fat content in patients with type 2 diabetes. Methods: A total of 67 patients with type 2 diabetes mellitus who met the inclusion criteria were included in the study. QCT and MRIIDEAL-IQ technologies were utilized to evaluate the patients quantitatively. The pancreatic head, body, and tail regions were examined to measure the fat content and obtain the CT pancreatic fat fraction (CT-PFF) and MRI pancreatic fat fraction (MR-PFF). Pearson correlation analysis examined the relationship between diabetes-related factors and CT-PFF/MR-PFF. Additionally, Bland-Altman analysis assessed the consistency between CT-PFF and MR-PFF. Results: Among the 67 patients, 33 were males and 34 were females. The average age was (66.55±6.23) years, with an average abdominal circumference of (83.34 ± 10.10) cm. The mean values for glycated hemoglobin, fasting blood glucose, BMI, and liver fat content were (6.97±1.07) mmol ⢠L-1, (6.83±1.82) mmol ⢠L-1, (24.02 ± 2.96) kg/m², and (5.28±2.76)%, respectively. Pearson correlation analysis indicated a significant correlation between abdominal circumference, liver fat content, and MR-PFF (r=0.261, 0.267, P < .05). However, no significant correlation was observed between age, glycated hemoglobin, fasting blood glucose, BMI, and MR-PFF (all, P > .05). The minimum and maximum values for CT-PFF among the 67 patients were 7.3% and 60.3%, respectively, with an average value of (19.90±10.61)%. For MR-PFF, the minimum and maximum values were 2% and 48%, respectively, with an average value of (12.21±10.71)%. Pearson correlation analysis demonstrated a significant correlation between CT-PFF and MR-PFF (r = .842, P < .05). Bland-Altman analysis revealed an average bias value of 7.7% and a standard deviation of 5.6% for CT-PFF and MR-PFF. The mean 95% confidence interval ranged from 4.15% to 19.75% (P < .05), with 64 cases falling within this interval and 3 cases falling outside. Conclusion: A correlation exists between pancreatic fat content, abdominal circumference, and liver fat content. Both QCT and MRI can accurately quantify pancreatic fat content, and their correlation and consistency are relatively ideal. QCT technology is particularly suitable for patients with contraindications for magnetic resonance examination.
RESUMO
Gastric cancer (GC) is an aggressive malignancy with high incidence and mortality. Radiotherapy is a common treatment for patients with advanced GC. Many long noncoding RNAs (lncRNAs) have been verified to affect the radiosensitivity of multiple cancers in previous studies. Nevertheless, whether lncRNA opioid growth factor receptor pseudogene 1 (OGFRP1) affects the radiosensitivity of GC has not been determined. We hypothesized that OGFRP1 might affect cellular processes in GC development. The present study aims to explore the role of OGFRP1 in GC development. First, high expression of OGFRP1 in GC tissues and cells was determined through RT-qPCR. Subsequently, functional assays including colony formation assays, 5-Ethynyl-2'-deoxyuridine assays and flow cytometry analyses were performed to probe the biological functions of OGFRP1 in GC. Specifically, the effect of OGFRP1 on the radiosensitivity of GC cells was detected. Subsequently, with the help of the starBase tool, we found that miR-149-5p might bind to OGFRP1, which was confirmed through a luciferase reporter assay. Furthermore, we identified that MAP3K3 was targeted by miR-149-5p in GC cells. Finally, the results from rescue experiments validated that enhanced MAP3K3 expression counteracted the effect of OGFRP1 silencing on GC cell proliferation, apoptosis and radiosensitivity. Overall, OGFRP1 was determined to promote GC cell proliferation while suppressing cell apoptosis and radiosensitivity by regulating the miR-149-5p/MAP3K3 axis.