ABSTRACT
Prospective studies have failed to establish a causal relationship between animal fat intake and cardiovascular diseases in humans. Furthermore, the metabolic effects of different dietary sources remain unknown. In this four-arm crossover study, we investigated the impact of consuming cheese, beef, and pork meat on classic and new cardiovascular risk markers (obtained from lipidomics) in the context of a healthy diet. A total of 33 young healthy volunteers (23 women/10 men) were assigned to one out of four test diets in a Latin square design. Each test diet was consumed for 14 days, with a 2-week washout. Participants received a healthy diet plus Gouda- or Goutaler-type cheeses, pork, or beef meats. Before and after each diet, fasting blood samples were withdrawn. A reduction in total cholesterol and an increase in high density lipoprotein particle size were detected after all diets. Only the pork diet upregulated plasma unsaturated fatty acids and downregulated triglycerides species. Improvements in the lipoprotein profile and upregulation of circulating plasmalogen species were also observed after the pork diet. Our study suggests that, within the context of a healthy diet rich in micronutrients and fiber, the consumption of animal products, in particular pork meat, may not induce deleterious effects, and reducing the intake of animal products should not be regarded as a way of reducing cardiovascular risk in young individuals.
Subject(s)
Diet , Lipidomics , Male , Animals , Cattle , Humans , Female , Cross-Over Studies , Prospective Studies , Triglycerides , MeatABSTRACT
In the current market, there is a growing interest in traditional herbal nutraceuticals. Therefore, herbal formulations have re-emerged as products with sought-after nutraceutical and disease-preventing properties. The health-promoting effects of herbal bioactives are attributed to the active phytoconstituents of these plants. Thus, the aim of the present study was to evaluate the putative nutraceutical effectiveness of the preparations of ten herbs (chamomile, purple coneflower, lemon verbena, pennyroyal, spearmint, oregano, marjoram, headed savory, sea buckthorn, and St. John’s wort) by combining in silico techniques and LC-MS/MS analysis. The binding potential of the selected phenolic compounds, according to literature and web databases, was investigated by using molecular target prediction tools. Aldose reductase (AR), an enzyme of polyol pathway which is related to hyperglycemic-induced pathologies, emerged as the most promising molecular target. The molecular docking results showed that rosmarinic acid, caftaric acid, naringenin, and quercetin presented the highest binding affinity. In a further step, the phytochemical profile of the examined infusions, obtained by LC-MS/MS analysis, revealed that the abovementioned compounds were present, mainly in the herbs of the Lamiaceae family, designating headed savory as the herbal infusion with possible significant inhibitory activity against AR.
ABSTRACT
Neutrophils play a pathogenic role in COVID-19 by releasing Neutrophils Extracellular Traps (NETs) or human neutrophil elastase (HNE). Given that HNE is inhibited by α1-antitrypsin (AAT), we aimed to assess the content of HNE, α1-antitrypsin (AAT) and HNE-AAT complexes (the AAT/HNE balance) in 33 bronchoalveolar lavage fluid (BALf) samples from COVID-19 patients. These samples were submitted for Gel-Electrophoresis, Western Blot and ELISA, and proteins (bound to AAT or HNE) were identified by Liquid Chromatography-Mass Spectrometry. NETs' release was analyzed by confocal microscopy. Both HNE and AAT were clearly detectable in BALf at high levels. Contrary to what was previously observed in other settings, the formation of HNE-AAT complex was not detected in COVID-19. Rather, HNE was found to be bound to acute phase proteins, histones and C3. Due to the relevant role of NETs, we assessed the ability of free AAT to bind to histones. While confirming this binding, AAT was not able to inhibit NET formation. In conclusion, despite the finding of a high burden of free and bound HNE, the lack of the HNE-AAT inhibitory complex in COVID-19 BALf demonstrates that AAT is not able to block HNE activity. Furthermore, while binding to histones, AAT does not prevent NET formation nor their noxious activity.
ABSTRACT
Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography-mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal-Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.