A systematic review and meta-analysis of human population studies on the association between exposure to toxic environmental chemicals and left ventricular dysfunction (LVD).

BACKGROUND: Exposure to environmental chemicals has been associated with an elevated risk of heart failure (HF). However, the impact on early markers of HF, such as left ventricular dysfunction (LVD), remains limited. OBJECTIVE: To establish a foundation of evidence regarding early HF markers and their association with environmental pollutants, a systematic review and meta-analysis was conducted. METHODS: The search, conducted on October 13th, 2023, encompassed PubMed, Embase, and Web of Science without filters, focusing on observational studies reporting myocardial geometrical, structural, or functional alterations in individuals without a history of heart disease. This included the general adult population, workers, young people, and the elderly. The risk of bias was assessed using the ROBINS-I tool at both study and item levels. RESULTS: The systematic review included 17 studies involving 43.358 individuals exposed to air pollution and 2038 exposed to heavy metals. Approximately 41% of the effect measures of associations reported significant abnormalities in myocardial structure or function. The metanalyses by pollutants categories indicated positive associations between LV systolic and diastolic abnormalities and exposure to PM2.5 [-0.069 (-0.104, -0.033); -0.044 (-0.062, -0.025)] and PM10 [-0.055 (-0.087, -0.022); -0.030 (-0.050, -0.010)] and NO2 [-0.042 (-0.071, -0.013); -0.021 (-0.037, -0.004)], as well as positive associations between lead exposure and LV systolic abnormalities [-0.033 (-0.051, -0.016)]. CONCLUSIONS: Existing evidence shows that specific early markers of HF may be associated with exposure to chemical pollutants. It is recommended to include such endpoints in new longitudinal and case-control studies to confirm further risk associations. These studies should consider co-exposures, account for vulnerable groups, and identify cardiotoxic compounds that may require regulation. When examining the link between myocardial abnormalities and environmental exposure, it is also advisable to explore the supportive use of Adverse Outcome Pathway (AOP) approaches to confirm a causal relationship.

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar electrocardiographic (ECG) patterns, characterized by ST-segment elevation in the right precordial leads, and risk of Sudden Cardiac Death (SCD). Furthermore, although various ECG patterns are described in the literature, different individual ECG may show high-grade variability, making the diagnosis problematic. The study aims to develop an innovative system for an accurate diagnosis of Type 1 BrS based on ECG pattern recognition by Machine Learning (ML) models and blood markers analysis trough transcriptomic techniques. METHODS: The study is structured in 3 parts: (a) a retrospective study, with the first cohort of 300 anonymized ECG obtained in already diagnosed Type 1 BrS (75 spontaneous, 150 suspected) and 75 from control patients, which will be processed by ML analysis for pattern recognition; (b) a prospective study, with a cohort of 11 patients with spontaneous Type 1 BrS, 11 with drug-induced Type 1 BrS, 11 suspected BrS but negative to Na + channel blockers administration, and 11 controls, enrolled for ECG ML analysis and blood collection for transcriptomics and microvesicles analysis; (c) a validation study, with the third cohort of 100 patients (35 spontaneous and 35 drug-induced BrS, 30 controls) for ML algorithm and biomarkers testing. DISCUSSION: The BrAID system will help clinicians improve the diagnosis of Type 1 BrS by using multiple information, reducing the time between ECG recording and final diagnosis, integrating clinical, biochemical and ECG information thus favoring a more effective use of available resources. Trial registration Clinical Trial.gov, NCT04641585. Registered 17 November 2020, https://clinicaltrials.gov/ct2/show/NCT04641585.

Novel in vitro evidence on the beneficial effect of quercetin treatment in vascular calcification.

Vascular calcification is a pathological chronic condition characterized by calcium crystal deposition in the vessel wall and is a recurring event in atherosclerosis, chronic kidney disease, and diabetes. The lack of effective therapeutic treatments opened the research to natural products, which have shown promising potential in inhibiting the pathological process in different experimental models. This study investigated the anti-calcifying effects of Quercetin and Berberine extracts on vascular smooth muscle cells (VSMCs) treated with an inorganic phosphate solution for 7 days. Quercetin has shown the highest anti-calcifying activity, as revealed by the intracellular quantitative assay and morphological analysis. Confocal microscopy revealed downregulation of RUNX2, a key marker for calcified phenotype, which was otherwise upregulated in calcified VSMCs. To investigate the anti-inflammatory activity of Quercetin, culture media were subjected to immunometric assays to quantify the levels of IL-6 and TNF-α, and the caspase-1 activity. As expected, calcified VSMCs released a large quantity of inflammatory mediators, significantly decreasing in the presence of Quercetin. In summary, our findings suggest that Quercetin counteracted calcification by attenuating the VSMC pathological phenotypic switch and reducing the inflammatory response. In our opinion, these preliminary in vitro findings could be the starting point for further investigations into the beneficial effects of Quercetin dietary supplementation against vascular calcification.

Modulated molecular markers of restenosis and thrombosis byin-vitrovascular cells exposed to bioresorbable scaffolds.

Drug-eluting bioresorbable vascular scaffolds (BVSs) have emerged as a potential breakthrough for the treatment of coronary artery stenosis, providing mechanical support and drug delivery followed by complete resorption. Restenosis and thrombosis remain the primary limitations in clinical use. The study aimed to identify potential markers of restenosis and thrombosis analyzing the vascular wall cell transcriptomic profile modulation triggered by BVS at different values of shear stress (SS). Human coronary artery endothelial cells and smooth muscle cells were cultured under SS (1 and 20 dyne cm-2) for 6 h without and with application of BVS and everolimus 600 nM. Cell RNA-Seq and bioinformatics analysis identified modulated genes by direct comparison of SS conditions and Gene Ontology (GO). The results of different experimental conditions and GO analysis highlighted the modulation of specific genes as semaphorin 3E, mesenchyme homeobox 2, bone morphogenetic protein 4, (heme oxygenase 1) and selectin E, with different roles in pathological evolution of disease. Transcriptomic analysis of dynamic vascular cell cultures identifies candidate genes related to pro-restenotic and pro-thrombotic mechanisms in anin-vitrosetting of BVS, which are not adequately contrasted by everolimus addition.

HEMET: mathematical model of biochemical pathways for simulation and prediction of HEpatocyte METabolism.

Many computer studies and models have been developed in order to simulate cell biochemical pathways. The difficulty of integrating all the biochemical reactions that occur in a cell in a single model is the main reason for the poor results in the prediction and simulation of cell behaviour under different chemical and physical stimuli. In this paper we have translated biochemical reactions into differential equations for the development of modular model of metabolism of a hepatocyte cultured in static and standard conditions (in a plastic multiwell placed in an incubator at 37 degrees C with 5% of CO(2)). Using biochemical equations and energetic considerations a set of non-linear differential equations has been derived and implemented in Simulink. This set of equations mimics some of the principal metabolic pathways of biomolecules present in the culture medium. The software platform developed is subdivided into separate modules, each one describing a different metabolic pathway; they constitute a library which can be used for developing new modules and models to project, predict and validate cell behaviour in vitro.

Patient specific multiscale modelling for plaque formation and progression.

We present a three-dimensional model of plaque formation and progression that was tested in a set of patients who underwent coronary Computed Tomography angiography (CTA) for anginal symptoms. The 3D blood flow is described by the Navier-Stokes equations, together with the continuity equation. Mass transfer within the blood lumen and through the arterial wall is coupled with the blood flow and is modeled by a convection-diffusion equation. The Low Density Lipoprotein (LDL) transports in lumen of the vessel and through the vessel tissue (which has a mass consumption term) are coupled by Kedem-Katchalsky equations. The inflammatory process is modeled using three additional reaction-diffusion partial differential equations. A full three-dimensional model was created. Furthermore, features potentially affecting plaque growth, such as patient risk score, circulating biomarkers, localization and composition of the initial plaque, and coronary vasodilating capability were also investigated. The proof of concept of the model effectiveness was assessed 6 months after the baseline evaluation.

HEMETß: improvement of hepatocyte metabolism mathematical model.

This article describes hepatocyte metabolism mathematical model (HEMETß), which is an improved version of HEMET, an effective and versatile virtual cell model based on hepatic cell metabolism. HEMET is based on a set of non-linear differential equations, implemented in Simulink®, which describes the biochemical reactions and energetic cell state, and completely mimics the principal metabolic pathways in hepatic cells. The cell energy function and modular structure are the core of this model. HEMETß as HEMET model describes hepatic cellular metabolism in standard conditions (cell culture in a plastic multi-well placed in an incubator at 37° C with 5% of CO2) and with excess substrates concentration. The main improvements in HEMETß are the introductions of Michaelis-Menten models for reversible reactions and enzymatic inhibition. In addition, we eliminated hard non-linearities and modelled cell proliferation and every single aminoacid degradation pathway. All these innovations, combined with a user-friendly aspect, allow researchers to create new cell types and validate new experimental protocols just varying 'peripheral' pathways or model inputs.

Expression of C-type natriuretic peptide and its receptor NPR-B in cardiomyocytes.

C-type natriuretic peptide (CNP) was recently found in myocardium at the mRNA and protein levels, but it is not known whether cardiomyocytes are able to produce CNP. The aim of this study was to determine the expression of CNP and its specific receptor NPR-B in cardiac cells, both in vitro and ex vivo. CNP, brain natriuretic peptide (BNP) and natriuretic peptide receptor (NPR)-B mRNA expression were examined by RT-PCR in the H9c2 rat cardiac myoblast cell line, in neonatal rat primary cardiomyocytes and in human umbilical vein endothelial cells (HUVECs) as control. CNP protein expression was probed in cardiac tissue sections obtained from adult male minipigs by immunohistochemistry, and in H9c2 cells both by immunocytochemistry and by specific radioimmunoassay. The results showed that cardiac cells as well as endothelial cells were able to produce CNP. Unlike cardiomyocytes, as expected, in endothelial cells expression of BNP was not detected. NPR-B mRNA expression was found in both cell types. Production of CNP in the heart muscle cells at protein level was confirmed by radioimmunological determination (H9c2: CNP=0.86 ± 0.083 pg/mg) and by immunocytochemistry studies. By immunostaining of tissue sections, CNP was detected in both endothelium and cardiomyocytes. Expression of CNP in cardiac cells at gene and protein levels suggests that the heart is actively involved in the production of CNP.

A new library of HEMET model: Insulin effects on hepatic metabolism.

Prediction and simulation of cell culture behaviour, under different chemical and physical stimuli by a mathematical model, represent an innovative way to create a virtual cell laboratory, where it is possible to perform and optimize experimental protocol, saving time and money. In silico experiments permit to reproduce pathological and physiological situations and make toxicological tests. In this paper we introduce a new library of HEMET (HEpatocyte METabolism) software that allows the insulin effects on hepatic metabolism to be simulated. This new set of nonlinear differential equations, derived from biochemical reactions which involve this pancreatic hormone, allows the catabolites concentration in hepatic cell culture after insulin infusion to be predicted. The validation procedures were carried out using data obtained from specifically designed cell experiments and from literature. A user friendly interface allows to easily change model parameters, rate constants and inputs simulating a wide range of physiological and pathological scenarios.

Consecutive exposure to lamotrigine and citalopram during pregnancy.

We describe the case of a pregnancy healthy outcome after in utero consecutive exposure to lamotrigine and citalopram.