RESUMO
In the recent years, micronutrients play an important role in improving body health with preventing and treating of chronic diseases. Chromium is one of the vital minerals involved in the regulation of insulin action. According to abundant evidences this mineral seems to be an essential factor involved in the reduction of insulin resistance and decreasing the risk of type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVDs). Moreover, it has been proposed that Chromium supplementation affects mechanisms involved in blood pressure, lipid metabolism, inflammation, and oxidative stress. For instance, it may affect blood pressure through alteration of the renin-angiotensin system, as well as reducing the angiotensin-converting enzyme activity. Furthermore, Chromium supplementation might help reduce the coronary heart disease rates. This study aims to provide a comprehensive review regarding to the effects of Chromium supplementation on CVDs risk factors with an emphasis on possible molecular mechanisms.
RESUMO
Biofilm-related infections substantially contribute to bacterial illnesses, with estimates indicating that at least 80% of such diseases are linked to biofilms. Biofilms exhibit unique metabolic patterns that set them apart from their planktonic counterparts, resulting in significant metabolic reprogramming during biofilm formation. Differential glycolytic enzymes suggest that central metabolic processes are markedly different in biofilms and planktonic cells. The glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is highly expressed in Staphylococcus aureus biofilm progenitors, indicating that changes in glycolysis activity play a role in biofilm development. Notably, an important consideration is a correlation between elevated cyclic di-guanylate monophosphate (c-di-GMP) activity and biofilm formation in various bacteria. C-di-GMP plays a critical role in maintaining the persistence of Pseudomonas aeruginosa biofilms by regulating alginate production, a significant biofilm matrix component. Furthermore, it has been demonstrated that S. aureus biofilm development is initiated by several tricarboxylic acid (TCA) intermediates in a FnbA-dependent manner. Finally, Glucose 6-phosphatase (G6P) boosts the phosphorylation of histidine-containing protein (HPr) by increasing the activity of HPr kinase, enhancing its interaction with CcpA, and resulting in biofilm development through polysaccharide intercellular adhesion (PIA) accumulation and icaADBC transcription. Therefore, studying the metabolic changes associated with biofilm development is crucial for understanding the complex mechanisms involved in biofilm formation and identifying potential targets for intervention. Accordingly, this review aims to provide a comprehensive overview of recent advances in metabolomic profiling of biofilms, including emerging trends, prevailing challenges, and the identification of potential targets for anti-biofilm strategies.
Assuntos
Biofilmes , Staphylococcus aureus , Staphylococcus aureus/metabolismo , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismo , Matriz Extracelular de Substâncias Poliméricas/metabolismo , Metabolômica , Fosforilação , Regulação Bacteriana da Expressão Gênica , Pseudomonas aeruginosa/genética , Pseudomonas aeruginosa/metabolismoRESUMO
BACKGROUND: The role of screen time in promoting obesity among children has been reported in previous studies. However, the effects of different screen types and the dose-response association between screen time and obesity among children is not summarized yet. In the current meta-analysis we systematically summarized the association between obesity and screen time of different screen types in a dose-response analysis. METHODS: A systematic search from Scopus, PubMed and Embase electronic databases was performed. Studies that evaluated the association between screen time and obesity up to September 2021 were retrieved. We included 45 individual studies that were drawn from nine qualified studies into meta-analysis. RESULTS: The results of the two-class meta-analysis showed that those at the highest category of screen time were 1.2 times more likely to develop obesity [odds ratio (OR) = 1.21; confidence interval (CI) = 1.113, 1.317; I2 = 60.4%; P < 0.001). The results of subgrouping identified that setting, obesity status and age group were possible heterogeneity sources. No evidence of non-linear association between increased screen time and obesity risk among children was observed (P-nonlinearity = 0.310). CONCLUSION: In the current systematic review and meta-analysis we revealed a positive association between screen time and obesity among children without any evidence of non-linear association. Due to the cross-sectional design of included studies, we suggest further studies with longitudinal or interventional design to better elucidate the observed associations.