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Objective Smoking is a common public problem leading to increases in oxidative stress and decreases in the levels of some micronutrients, finally affecting adipokine levels. The aim of this study was to compare the serum levels of omentin (intelectin-1), chemerin, TNF-α, and some micronutrient intakes in male smokers and non-smokers. Methods 40 male smokers and 40 male non-smokers with a mean age of 38.6 ± 14.1 years were included in this study. Serum levels of omentin, chemerin, and TNF-α were measured. To calculate the daily intake of energy, carbohydrate, protein, fat, and some of the micronutrients, the 24-h recall and semi-quantitative food frequency questionnaire (FFQ) was used. Results Omentin, chemerin, and TNF-α levels in male smokers were lower than non-smokers, but these differences were not statistically significant. However, after adjustment for total and saturated fat intakes and age, omentin (β = 138.4, p = 0.027) and TNF-α (β = 144.5, p = 0.015) revealed significant differences. Conclusion The serum levels of omentin, chemerin, TNF-α, and some micronutrient intakes were not significantly different between smokers and non-smokers. Further population studies are needed to clarify this subject.

Advanced glycation end products (AGEs) are involved in the development of several age-related complications. The protective role of soluble receptors for AGEs (sRAGE) against deleterious effects of AGEs has been indicated in several studies. However, findings on the association of AGEs or sRAGE with mortality are equivocal. In this meta-analysis we aimed to present a quantitative estimation of the association between circulating AGEs or sRAGE and all-cause or cardiovascular disease (CVD) mortality. A comprehensive literature search was performed to determine relevant publications through the online databases including PubMed, Scopus, and Web of Science up to 29 November 2020. Prospective observational studies assessing the association between circulating AGEs or sRAGE and all-cause or CVD mortality were included. Seven studies with a total of 3718 participants and 733 mortality cases (345 CVD deaths) were included in the meta-analysis for assessing the association between circulating AGEs and mortality. Our results showed that higher circulating AGEs were associated with increased risk of all-cause (pooled effect measure: 1.05; 95% CI: 1.01, 1.09; P = 0.018, I(2) = 77.7%) and CVD mortality (pooled effect measure: 1.08; 95% CI: 1.01, 1.14; P = 0.015, I(2) = 80.2%), respectively. The association between sRAGE and mortality was assessed in 14 studies with a total of 16,335 participants and 2844 mortality cases (419 CVD deaths). Serum concentrations of sRAGE were not associated with the risk of all-cause mortality (pooled effect measure: 1.01; 95% CI: 1.00, 1.01; P = 0.205, I(2) = 75.5%), whereas there was a significant link between sRAGE and the risk of CVD mortality (pooled effect measure: 1.02; 95% CI: 1.00, 1.04; P = 0.02, I(2) = 78.9%). Our findings showed that a higher serum AGE concentration was associated with increased risk of all-cause and CVD mortality. In addition, higher circulating sRAGE was related to increased risk of CVD mortality. This review was registered at PROSPERO as CRD42021236559.

It remains unknown whether statin therapy in combination with ezetimibe is a beneficial and equivalent alternative to statin monotherapy in reducing proinflammatory cytokines. In the present systematic review and meta-analysis, we aimed to assess the effect of combination therapy with statins and ezetimibe on some proinflammatory cytokines. Databases, including MEDLINE, SciVerse, Scopus, and Clarivate Analytics Web of Science databases, were searched up to February 2022, for terms related to combination therapy with statins and ezetimibe and proinflammatory cytokines. The quality of the included studies was evaluated with Cochrane risk of bias tool 1, and weighted mean difference [WMD] and SD of changes were used for meta-analysis. The results were expressed as differences in means and 95 % CIs with an inverse variance and a random-effects model. Finally, 12 studies [13 arms] were included in the qualitative and quantitative synthesis. The average patient's age ranged from 49.3 to 71 years, and the duration of intervention lasted seven days to 12 months. Overall, our result did not show any significant reduction in interleukin-1beta (IL-1β) (3 randomized controlled trial studies (RCTs), 292 participants, WMD: -0.4 pg/ml; 95 % CI: -1.3, 0.4, P = 0.3, I

Aim Clinical trials on the effect of pycnogenol supplementation on cardiometabolic health have been controversial. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the potential effect of pycnogenol supplementation on cardiometabolic profile. Methods PubMed, Scopus, and ISI Web of Science databases were searched until October 2018. RCTs that evaluated the effects of pycnogenol on cardiometabolic parameters were included. DerSimonian and Laird random-effect models were used to compute the weighted mean differences (WMDs) and 95% confidence intervals (CIs). Results Twenty-four RCTs including 1594 participants were included in the meta-analysis. Pycnogenol significantly reduced fasting blood glucose (WMD: −5.86 mg/dl; 95% CI: −9.56, −2.15), glycated hemoglobin (WMD = −0.29%, 95%CI: −0.56, −0.01), systolic blood pressure (WMD: −2.54 mmhg; 95% CI: −4.08, -0.99), diastolic blood pressure (WMD: −1.76 mmhg; 95% CI: −3.12, −0.41), body mass index (WMD: −0.47 kg/m2; 95% CI: −0.90, −0.03), LDL cholesterol (WMD: −7.12 mg/dl; 95% CI: −13.66, −0.58) and increased HDL cholesterol (WMD: 3.27 mg/dl; 95% CI: 0.87, 5.66). Conclusion This meta-analysis suggests that pycnogenol may have a role in preventing cardiometabolic disease. However, further well-designed RCTs are recommended to evaluate its long-term effects and explore the optimal duration of use and dosage.