Background: Cardiovascular disease (CVD) has become a key global health issue. Serum carotenoids are associated with CVD, while their effects on different diseases remain unclear. Herein, the relationship between the concentration of serum carotenoid and the CVD risk was investigated using nationwide adult samples obtained from the USA.Materials and methods: Data of National Health and Nutrition Examination Survey (NHANES) in 2001–2006 were employed. The association of serum carotenoids (total, lycopene, β-carotene, α-carotene, lutein/zeaxanthin, and β-cryptoxanthin) with CVD was explored by using multivariate logistic, linear and weighted quantile sum (WQS) regression analyses. Eventually, data from 12,424 volunteers were analyzed for this study.Results: Multivariate model data showed that lutein/zeaxanthin, α-carotene, lycopene, and β-cryptoxanthin were negatively associated with the prevalence of CVD (p < 0.05). In comparison with the first quartile, the fourth quartile was associated with α-carotene ([OR] = 0.61 [0.47–0.79]), β-cryptoxanthin (OR = 0.67 [0.50–0.89]), lutein (OR = 0.69 [0.54–0.86]), and lycopene (OR = 0.53 [0.41–0.67]). WQS analysis revealed that the combination of serum carotenoids had negative correlation with the prevalence of total CVD (OR = 0.88, 95% CI: 0.85–0.92, p < 0.001). Additionally, dose–response analysis demonstrated a negative linear association of hypertension with all the carotenoids involved (p > 0.05 for non-linearity).Conclusion: The concentration of serum carotenoids had negative correlation with the prevalence of CVD, with a more significant negative effect against heart attack and stroke.

Role of TLR4 as a prognostic factor for survival in various cancers: a meta-analysis Role of TLR4 as a prognostic factor for survival in various cancers: a meta-analysis

Numerous studies have demonstrated that serum high-density lipoprotein cholesterol (HDL-C) levels correlate strongly with cancer patient survival. However, other studies have had the opposite results. We therefore conducted a systematic review and meta-analysis to assess the prognostic value of HDL-C levels in people with cancer. We searched PubMed, Embase, and the Cochrane Library (last update by December 28, 2017) for studies evaluating the effect of serum HDL-C levels on cancer patient prognosis. Data from 25 studies covering13,140 patients were included. Combined hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS) were assessed using fixed-effects and random-effects models. High serum HDL-C levels were associated with better OS (pooled HR = 0.70; 95% confidence interval (CI) (0.60–0.82). In the subgroup, the relative high level of HDL-C yielded a favorable outcome in most of tumor types. However, in the nasopharyngeal carcinoma subgroup, the correlation was not significant (combined HR = 1.31; 95% CI (0.91–1.90)). High serum HDL-C levels were associated with better DFS (pooled HR = 0.64; 95% confidence interval (CI) (0.50–0.81)). This meta-analysis demonstrates that high serum HDL-C levels are associated with better OS in patients with solid tumors, but not nasopharyngeal carcinoma; and high serum HDL-C levels are associated with better DFS.

Oxidative stress is crucial to the biology of tumors. Oxidative stress’ potential predictive significance in colorectal cancer (CRC) has not been studied; nevertheless here, we developed a forecasting model based on oxidative stress to forecast the result of CRC survival and enhance clinical judgment. The training set was chosen from the transcriptomes of 177 CRC patients in GSE17536. For validation, 65 samples of colon cancer from GSE29621 were utilized. For the purpose of choosing prognostic genes, the expression of oxidative stress‐related genes (OXEGs) was found. Prognostic risk models were built using multivariate Cox regression analysis, univariate Cox regression analysis, and LASSO regression analysis. The outcomes of the western blot and transcriptome sequencing tests were finally confirmed. ATF4, CARS2, CRP, GPX1, IL1B, MAPK8, MRPL44, MTFMT, NOS1, OSGIN2, SOD2, AARS2, and FOXO3 were among the 14 OXEGs used to build prognostic characteristics. Patients with CRC were categorized into low‐risk and high‐risk groups according on their median risk scores. Cox regression analysis using single and multiple variables revealed that OXEG‐related signals were independent risk factors for CRC. Additionally, the validation outcomes from western blotting and transcriptome sequencing demonstrated that OXEGs were differently expressed. Using 14 OXEGs, our work creates a predictive signature that may be applied to the creation of new prognostic models and the identification of possible medication candidates for the treatment of CRC.

The lymph node ratio (LNR) is useful for predicting survival in patients with small cell lung cancer (SCLC). The present study compared the effectiveness of the N stage, number of positive LNs (NPLNs), LNR, and log odds of positive LNs (LODDS) to predict cancer-specific survival (CSS) in patients with SCLC. 674 patients were screened using the Surveillance Epidemiology and End Results database. The Kaplan-Meier survival and receiver operating characteristic (ROC) curves were performed to address optimal estimation of the N stage, NPLNs, LNR, and LODDS to predict CSS. The optimal LN status group was incorporated into a nomogram to estimate CSS in SCLC patients. The ROC curve, decision curve analysis, and calibration plots were utilized to test the discriminatory ability and accuracy of this nomogram. The LODDS model showed the highest accuracy compared to the N stage, NPLNs, and LNR in predicting CSS for SCLC patients. LODDS, age, sex, tumor size, and radiotherapy status were included in the nomogram. The results of calibration plots provided evidences of nice consistency. The ROC and DCA plots suggested a better discriminatory ability and clinical applicability of this nomogram than the 8th TNM and SEER staging systems. LODDS demonstrated a better predictive power than other LN schemes in SCLC patients after surgery. A novel LODDS-incorporating nomogram was built to predict CSS in SCLC patients after surgery, proving to be more precise than the 8th TNM and SEER staging.

Background: Pulmonary arterial hypertension (PAH) is a severe vascular disorder with a multifactorial etiology, including potential genetic predispositions. Understanding the causal relationship between autoimmune diseases and the risk of developing PAH can inform clinical strategies for prevention and treatment. Methods: We conducted a two-sample Mendelian Randomization (MR) analysis to evaluate the causal effect of genetic predisposition to five autoimmune diseases (systemic lupus erythematosus [SLE], rheumatoid arthritis [RA], inflammatory bowel disease [IBD], multiple sclerosis [MS], and type 1 diabetes [T1D]) on the risk of PAH. This involved employing various MR methods (IVW, MR-Egger, Weighted median, Simple mode, and Weighted mode), as well as conducting tests for heterogeneity and horizontal pleiotropy. Results: The analysis revealed a significant association between genetic predisposition to RA and IBD with an increased risk of PAH (RA: OR = 1.28, 95% CI [1.01–1.61], p = 0.042; IBD: OR = 1.29, 95% CI [1.01–1.64], p = 0.043). However, no association was observed between genetically determined MS, SLE, and T1D with the risk of PAH (MS: p = 0.876; SLE: p = 0.564; T1D: p = 0.061). Additionally, tests for heterogeneity and pleiotropy provided no evidence of their influence, suggesting the robustness of these associations. Reverse MR analysis also indicated no significant effect of PAH on the genetic susceptibility to these autoimmune diseases. Conclusion: The findings suggest a possible genetic causative link between RA and IBD and the risk of developing PAH. Conversely, genetic predisposition to MS, SLE, and T1D does not appear to influence PAH risk. Understanding these relationships may offer insights into the pathophysiology of PAH and inform screening strategies within at-risk populations.