ObjectiveThyroid nodules are an exceptionally common thyroid disorder. Past studies suggested a possible link between thyroid diseases and breast neoplasms. However, few studies have delved into the causal relationship between thyroid nodules and breast neoplasms. This study conducted a Mendelian randomization (MR) analysis to further investigate the causal relationship between them. MethodsThis study was conducted using data sourced from genome-wide association study (GWAS) summary datasets. The study focused on thyroid nodules, benign breast tumors, and malignant breast cancers as the research objects, and relevant single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs). The inverse-variance weighted (IVW) was primarily used to assess the causal relationship between thyroid nodules and breast neoplasms. Cochran’s Q test was employed to detect heterogeneity, while MR-Egger intercept and MR-PRESSO were used to test for pleiotropy. Sensitivity analysis was conducted using the leave-one-out method. ResultsThere was a significant causal relationship between thyroid nodules and malignant neoplasm of breast (OR=0.88, 95%CI 0.83 to 0.95, P<0.01), with no evidence of reverse causality between them (OR=1.01, 95%CI 0.99 to 1.03, P=0.16). No causal relationship was found between thyroid nodules and benign neoplasm of breast, as indicated by both forward MR analysis (OR=0.97, 95%CI 0.89 to 1.06, P=0.51) and reverse MR analysis (OR=0.97, 95%CI 0.92 to 1.04, P=0.40). Sensitivity analyses suggested that the study findings were accurate and reliable. ConclusionThe present study identifies thyroid nodules as a potential protective factor for malignant neoplasm of breast.
To analyze the current doctor-patient relationship and explore its underlying reasons. Evidence-based medicine may provide scientific evidence for the deepening of healthcare reforms as well as the improvement of social security system; provide abundant information for both sides of the doctor-patient relationship; improve medical quality and reduce medical costs, so as to establish a harmonious patient-oriented doctor-patient relationship .
Objective To explore the factors which influence the doctor-patient relationship and to provide evidence to help decision makers improve hospital management and construct a harmonious doctor-patient relationship. Methods Discharged patients of West China Hospital from 2003-2006 were randomly selected and asked to complete a specially designed questionnaire. Results In total, 8 000 questionnaires were distributed and 2 526 were returned. The retrieval rate was 31.57%. The responses showed that non-medical factors have became the main factors affecting the doctor-patient relationship (91.8%). Other important factors included medical cost (21.5%) and doctor-patient communication (11.51%). Conclusion We should boost hospital management level, train non-medical staff, save costs and improve doctor-patient communication.
Objective To investigate the effects of QUE on proliferation and DNA synthesis of cultured retinal pigment epithelium(RPE) cells with or without EGF. Methods With or without EGF, cultured RPE cells were treated with QUE by various concentrations(200,100,50,1mu;mol/L) and with QUE 200mu;mol/L at different times(24-168 hr), cells proliferation and DNA synthesis were evaluated by cell count method and the uptake of thymidine. The viability of cells was determined by trypanblue exclusion. Results The best concentration of QUE which inhibits proliferation and DNA synthesis of PRE cells was 200mu;mol/L. The significant inhibition effect of QUE occurred at 48hr, and the best inhibition of QUE occurred at 96hr. QUE had more powerful effect of antiproliferation on RPE cells, and the viability of RPE cells was over85%. Conclusion The results suggested that QUE could inhibit the proliferation of RPE cells in a dose-dependent and time-dependent manner, especially inhibit the proliferation induced by EGF stimulating. QUE had no cyto-toxic effect on RPE cells cultured in vitro. (Chin J Ocul Fundus Dis,1999,15:27-29)
Objective To analyze the potential causal relationship between sunscreen/ultraviolet protection and the risk of non-Hodgkin lymphoma using a two sample Mendelian randomization (MR) study method. Methods The summary data of genome-wide association study was used to select three types of non-Hodgkin lymphoma, namely diffuse large B-cell lymphoma (DLBCL), follicular lymphoma, T/NK cell lymphoma, and sunscreen/ultraviolet protection highly correlated genetic loci, namely single nucleotide polymorphism (SNP), as instrumental variables. The reverse variance weighting method was used as the main method for MR analysis, MR Egger and MR-PRESO were used to detect level pleiotropy, and leave-one-out method was used for sensitivity analysis to ensure the robustness of the results. Results A total of 132 SNPs were included in the analysis. The results of the inverse variance weighted analysis showed that sunscreen/ultraviolet protection increased the incidence of DLBCL [odds ratio=2.439, 95% confidence interval (1.109, 5.362), P=0.027]. The heterogeneity test results showed that there was no heterogeneity in the causal relationship between sunscreen/ultraviolet protection and DLBCL (P>0.05). The results of the horizontal pleiotropy test showed that SNP did not exhibit horizontal pleiotropy (P>0.05). The leave-one-out method showed that no SNP with a significant impact on the results was found. There was no causal relationship between sunscreen/ultraviolet protection and follicular lymphoma and T/NK cell lymphoma. Conclusion There is a positive causal relationship between sunscreen/ultraviolet protection and the incidence of DLBCL.
Objective To systematically review the dose-response relationship between cadmium exposure and the risk of stroke onset. Methods The PubMed, Web of Science, Cochrane Library, Embase, CNKI, VIP, WanFang Data, and CBM databases were electronically searched to collect studies related to objectives from inception to June 2024. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 15.1 software. Results There were 10 studies that involved 28 250 participants, and 7 of them were prospective cohort studies and 3 were case-control studies. Meta-analysis results showed that cadmium exposure significantly increased the risk of stroke (RR=1.39, 95%CI 1.20 to 1.59, P<0.01), blood cadmium exposure significantly increased the risk of stroke (RR=1.79, 95%CI 1.34 to 2.25, P<0.01), urinary cadmium exposure significantly increased the risk of stroke (RR=1.30, 95%CI 1.09 to 1.52, P<0.01). Blood cadmium exposure had a significantly nonlinear dose-response relationship associated with an increased risk of stroke (χ2=8.56, P<0.05). The risk of stroke increased by 15% with the blood cadmium exposure concentration of 0.8 μg/L (RR=1.15, 95%CI 0.98 to 1.36), and 51% with the blood cadmium exposure concentration of 1.2 μg/L (RR=1.51, 95%CI 1.14 to 2.01) than those without blood cadmium exposure. Urinary cadmium exposure had significantly linear dose-response relationship associated with an increased risk of stroke (χ2=2.47, P=0.12). The risk of stroke increased by 26% with the urinary cadmium exposure concentration of 0.8 μg/g (RR=1.26, 95%CI 1.20 to 1.31), and 31% with the urinary cadmium exposure concentration of 1.2 μg/g (RR=1.31, 95%CI 1.27 to 1.36) than those without urinary cadmium exposure. Conclusion Cadmium exposure increases the risk of stroke. There was a significant dose-response relationship between cadmium exposure and the risk of stroke.
This paper explores the relationship between the cardiac volume and time, which is applied to control dynamic heart phantom. We selected 50 patients to collect their cardiac computed tomography angiography (CTA) images, which have 20 points in time series CTA images using retrospective electrocardiograph gating, and measure the volume of four chamber in 20-time points with cardiac function analysis software. Then we grouped patients by gender, age, weight, height, heartbeat, and utilize repeated measurement design to conduct statistical analyses. We proposed structured sparse learning to estimate the mathematic expression of cardiac volume variation. The research indicates that all patients’ groups are statistically significant in time factor (P = 0.000); there are interactive effects between time and gender groups in left ventricle (F = 8.597, P = 0.006) while no interactive effects in other chambers with the remaining groups; and the different weight groups’ volume is statistically significant in right ventricle (F = 9.004, P = 0.005) while no statistical significance in other chambers with remaining groups. The accuracy of cardiac volume and time relationship utilizing structured sparse learning is close to the least square method, but the former’s expression is more concise and more robust. The number of nonzero basic function of the structured sparse model is just 2.2 percent of that of least square model. Hence, the work provides more the accurate and concise expression of the cardiac for cardiac motion simulation.
Objective To analyze the causal relationship between cerebrospinal fluid (CSF) metabolites and tic disorder (TD) based on two-sample Mendelian randomization (MR). Methods CSF metabolites data from humans were downloaded from genome-wide association study databases, and CSF metabolites were selected as exposure factors. single nucleotide polymorphisms (SNPs) strongly associated with the exposure factors and independent of each other were selected as instrumental variables. The TD dataset from the Finngen database was downloaded, including 365 cases of TD and 411 816 controls. Analysis was conducted using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode. Sensitivity analysis was conducted using leave-one-out, and multiple-effects testing was conducted using MR-Egger and MR-PRESSO. Heterogeneity was detected using Cochran’s Q. Results A total of 9 CSF metabolites were found to have a causal relationship with the occurrence and development of TD (P<0.05), with a total of 394 SNPs included in the analysis. Inverse variance weighting results showed that N-acetylneuraminic acid [odds ratio (OR)=2.715, 95% confidence interval (CI) (1.102, 6.961), P=0.030], γ-glutamylglutamine [OR=1.402, 95%CI (1.053, 1.868), P=0.021], lysine [OR=2.816, 95%CI (1.084, 7.319), P=0.034] could increase the risk of TD. Cysteinylglycine disulfide [OR=0.437, 95%CI (0.216, 0.885), P=0.021], propionylcarnitine [OR=0.762, 95%CI (0.616, 0.941), P=0.012], pantothenate [OR=0.706, 95%CI (0.523, 0.952), P=0.023], gulareic acid [OR=0.758, 95%CI (0.579, 0.992), P=0.044], and cysteine-glycine [OR=0.799, 95%CI (0.684, 0.934), P=0.005] could reduce the risk of TD. The results of leave-one-out sensitivity analysis were stable, and no horizontal pleiotropy or heterogeneity was observed. Conclusions N-acetylneuraminic acid, γ-glutamylglutamine, and lysine can increase the risk of TD, but cysteinylglycine disulfide, propionylcarnitine, pantothenate, gulagic acid and cysteine-glycine can reduce the risk of TD. However, the mechanism of their effects on TD still needs to be further explored.
Dose-response meta-analysis, an important tool in investigating the relationship between a certain exposure and risk of disease, has been increasingly applied. Traditionally, the dose-response meta-analysis was only modelled as linearity. However, since the proposal of more powerful function models, which contains both linear, quadratic, cubic or more higher order term within the regression model, the non-linearity model of dose-response relationship is also available. The packages suit for R are available now. In this article, we introduced how to conduct a dose-response meta-analysis using dosresmeta and mvmeta packages in R.