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Journal: European heart journal


Ambient air pollution is a major health risk, leading to respiratory and cardiovascular mortality. A recent Global Exposure Mortality Model, based on an unmatched number of cohort studies in many countries, provides new hazard ratio functions, calling for re-evaluation of the disease burden. Accordingly, we estimated excess cardiovascular mortality attributed to air pollution in Europe.


The data regarding the associations of body mass index (BMI) with cardiovascular (CVD) risk, especially for those at the low categories of BMI, are conflicting. The aim of our study was to examine the associations of body composition (assessed by five different measures) with incident CVD outcomes in healthy individuals.


To determine whether dietary pattern assessed by a simple self-administered food frequency questionnaire is associated with major adverse cardiovascular events (MACE) in high-risk patients with stable coronary artery disease.

Concepts: Atherosclerosis, Coronary artery disease, Heart, Blood vessel, Heart disease, Artery, Coronary circulation, Cardiovascular system


To investigate the associations between major foods and dietary fibre with subtypes of stroke in a large prospective cohort.


To critically evaluate the clinical implications of the use of non-fasting rather than fasting lipid profiles and to provide guidance for the laboratory reporting of abnormal non-fasting or fasting lipid profiles.

Concepts: Chemistry, The Europeans, Russia, Profiles


Ambient air pollution is a leading cause of non-communicable disease globally. The largest proportion of deaths and morbidity due to air pollution is now known to be due to cardiovascular disorders. Several particulate and gaseous air pollutants can trigger acute events (e.g. myocardial infarction, stroke, heart failure). While the mechanisms by which air pollutants cause cardiovascular events is undergoing continual refinement, the preponderant evidence support rapid effects of a diversity of pollutants including all particulate pollutants (e.g. course, fine, ultrafine particles) and gaseous pollutants such as ozone, on vascular function. Indeed alterations in endothelial function seem to be critically important in transducing signals and eventually promoting cardiovascular disorders such as hypertension, diabetes, and atherosclerosis. Here, we provide an updated overview of the impact of particulate and gaseous pollutants on endothelial function from human and animal studies. The evidence for causal mechanistic pathways from both animal and human studies that support various hypothesized general pathways and their individual and collective impact on vascular function is highlighted. We also discuss current gaps in knowledge and evidence from trials evaluating the impact of personal-level strategies to reduce exposure to fine particulate matter (PM2.5) and impact on vascular function, given the current lack of definitive randomized evidence using hard endpoints. We conclude by an exhortation for formal inclusion of air pollution as a major risk factor in societal guidelines and provision of formal recommendations to prevent adverse cardiovascular effects attributable to air pollution.


The gut microbiome influences metabolic syndrome (MetS) and inflammation and is therapeutically modifiable. Arterial stiffness is poorly correlated with most traditional risk factors. Our aim was to examine whether gut microbial composition is associated with arterial stiffness.


Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction.


To objectively appraise evidence for possible adverse effects of long-term statin therapy on glucose homeostasis, cognitive, renal and hepatic function, and risk for haemorrhagic stroke or cataract.


Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.