Adipose Tissue in Cardiovascular Disease: From Basic Science to Clinical Translation.

The perception of adipose tissue as a metabolically quiescent tissue, primarily responsible for lipid storage and energy balance (with some endocrine, thermogenic, and insulation functions), has changed. It is now accepted that adipose tissue is a crucial regulator of metabolic health, maintaining bidirectional communication with other organs including the cardiovascular system. Additionally, adipose tissue depots are functionally and morphologically heterogeneous, acting not only as sources of bioactive molecules that regulate the physiological functioning of the vasculature and myocardium but also as biosensors of the paracrine and endocrine signals arising from these tissues. In this way, adipose tissue undergoes phenotypic switching in response to vascular and/or myocardial signals (proinflammatory, profibrotic, prolipolytic), a process that novel imaging technologies are able to visualize and quantify with implications for clinical prognosis. Furthermore, a range of therapeutic modalities have emerged targeting adipose tissue metabolism and altering its secretome, potentially benefiting those at risk of cardiovascular disease.

Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Persistently elevated complement alternative pathway biomarkers in COVID-19 correlate with hypoxemia and predict in-hospital mortality.

Mechanisms underlying the SARS-CoV-2-triggered hyperacute thrombo-inflammatory response that causes multi-organ damage in coronavirus disease 2019 (COVID-19) are poorly understood. Several lines of evidence implicate overactivation of complement. To delineate the involvement of complement in COVID-19, we prospectively studied 25 ICU-hospitalized patients for up to 21 days. Complement biomarkers in patient sera and healthy controls were quantified by enzyme-linked immunosorbent assays. Correlations with respiratory function and mortality were analyzed. Activation of complement via the classical/lectin pathways was variably increased. Strikingly, all patients had increased activation of the alternative pathway (AP) with elevated levels of activation fragments, Ba and Bb. This was associated with a reduction of the AP negative regulator, factor (F) H. Correspondingly, terminal pathway biomarkers of complement activation, C5a and sC5b-9, were significantly elevated in all COVID-19 patient sera. C5a and AP constituents Ba and Bb, were significantly associated with hypoxemia. Ba and FD at the time of ICU admission were strong independent predictors of mortality in the following 30 days. Levels of all complement activation markers were sustained throughout the patients' ICU stays, contrasting with the varying serum levels of IL-6, C-reactive protein, and ferritin. Severely ill COVID-19 patients have increased and persistent activation of complement, mediated strongly via the AP. Complement activation biomarkers may be valuable measures of severity of lung disease and the risk of mortality. Large-scale studies will reveal the relevance of these findings to thrombo-inflammation in acute and post-acute COVID-19.

Cardiac Computed Tomography: Assessment of Coronary Inflammation and Other Plaque Features.

Unstable coronary plaques that are prone to erosion and rupture are the major cause of acute coronary syndromes. Our expanding understanding of the biological mechanisms of coronary atherosclerosis and rapid technological advances in the field of medical imaging has established cardiac computed tomography as a first-line diagnostic test in the assessment of suspected coronary artery disease, and as a powerful method of detecting the vulnerable plaque and patient. Cardiac computed tomography can provide a noninvasive, yet comprehensive, qualitative and quantitative assessment of coronary plaque burden, detect distinct high-risk morphological plaque features, assess the hemodynamic significance of coronary lesions and quantify the coronary inflammatory burden by tracking the effects of arterial inflammation on the composition of the adjacent perivascular fat. Furthermore, advances in machine learning, computational fluid dynamic modeling, and the development of targeted contrast agents continue to expand the capabilities of cardiac computed tomography imaging. In our Review, we discuss the current role of cardiac computed tomography in the assessment of coronary atherosclerosis, highlighting its dual function as a clinical and research tool that provides a wealth of structural and functional information, with far-reaching diagnostic and prognostic implications.

Exposure to parental smoking in childhood is associated with increased risk of carotid atherosclerotic plaque in adulthood: the Cardiovascular Risk in Young Finns Study.

BACKGROUND: The association between passive smoking exposure in childhood and adverse cardiovascular health in adulthood is not well understood. Using a 26-year follow-up study, we examined whether childhood exposure to passive smoking was associated with carotid atherosclerotic plaque in young adults. METHODS AND RESULTS: Participants were from the Cardiovascular Risk in Young Finns Study (n=2448). Information on childhood exposure to parental smoking was collected in 1980 and 1983. Carotid ultrasound data were collected in adulthood in 2001 or 2007. Childhood serum cotinine levels from 1980 were measured from frozen samples in 2014 (n=1578). The proportion of children with nondetectable cotinine levels was highest among households in which neither parent smoked (84%), was decreased in households in which 1 parent smoked (62%), and was lowest among households in which both parents smoked (43%). Regardless of adjustment for potential confounding and mediating variables, the relative risk of developing carotid plaque in adulthood increased among those children with 1 or both parents who smoked (relative risk, 1.7; 95% confidence interval, 1.0-2.8; P=0.04). Although children whose parents exercised good "smoking hygiene" (smoking parents whose children had nondetectable cotinine levels) had increased risk of carotid plaque compared with children with nonsmoking parents (relative risk, 1.6; 95% confidence interval, 0.6-4.0; P=0.34), children of smoking parents with poor smoking hygiene (smoking parents whose children had detectable serum cotinine levels) had substantially increased risk of plaque as adults (relative risk, 4.0; 95% confidence interval, 1.7-9.8; P=0.002). CONCLUSIONS: Children of parents who smoke have increased risk of developing carotid atherosclerotic plaque in adulthood. However, parents who exercise good smoking hygiene can lessen their child's risk of developing plaque.

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction.

BACKGROUND: Epicardial adipose tissue (EAT) volume is a marker of visceral obesity that can be measured in coronary computed tomography angiograms (CCTA). The clinical value of integrating this measurement in routine CCTA interpretation has not been documented. OBJECTIVES: This study sought to develop a deep-learning network for automated quantification of EAT volume from CCTA, test it in patients who are technically challenging, and validate its prognostic value in routine clinical care. METHODS: The deep-learning network was trained and validated to autosegment EAT volume in 3,720 CCTA scans from the ORFAN (Oxford Risk Factors and Noninvasive Imaging Study) cohort. The model was tested in patients with challenging anatomy and scan artifacts and applied to a longitudinal cohort of 253 patients post-cardiac surgery and 1,558 patients from the SCOT-HEART (Scottish Computed Tomography of the Heart) Trial, to investigate its prognostic value. RESULTS: External validation of the deep-learning network yielded a concordance correlation coefficient of 0.970 for machine vs human. EAT volume was associated with coronary artery disease (odds ratio [OR] per SD increase in EAT volume: 1.13 [95% CI: 1.04-1.30]; P = 0.01), and atrial fibrillation (OR: 1.25 [95% CI: 1.08-1.40]; P = 0.03), after correction for risk factors (including body mass index). EAT volume predicted all-cause mortality (HR per SD: 1.28 [95% CI: 1.10-1.37]; P = 0.02), myocardial infarction (HR: 1.26 [95% CI:1.09-1.38]; P = 0.001), and stroke (HR: 1.20 [95% CI: 1.09-1.38]; P = 0.02) independently of risk factors in SCOT-HEART (5-year follow-up). It also predicted in-hospital (HR: 2.67 [95% CI: 1.26-3.73]; P ≤ 0.01) and long-term post-cardiac surgery atrial fibrillation (7-year follow-up; HR: 2.14 [95% CI: 1.19-2.97]; P ≤ 0.01). CONCLUSIONS: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification.

Trace residue identification, characterization, and longitudinal monitoring of the novel synthetic opioid ß-U10, from discarded drug paraphernalia.

Empirical data regarding dynamic alterations in illicit drug supply markets in response to the COVID-19 pandemic, including the potential for introduction of novel drug substances and/or increased poly-drug combination use at the "street" level, that is, directly proximal to the point of consumption, are currently lacking. Here, a high-throughput strategy employing ambient ionization-mass spectrometry is described for the trace residue identification, characterization, and longitudinal monitoring of illicit drug substances found within >6,600 discarded drug paraphernalia (DDP) samples collected during a pilot study of an early warning system for illicit drug use in Melbourne, Australia from August 2020 to February 2021, while significant COVID-19 lockdown conditions were imposed. The utility of this approach is demonstrated for the de novo identification and structural characterization of ß-U10, a previously unreported naphthamide analog within the "U-series" of synthetic opioid drugs, including differentiation from its α-U10 isomer without need for sample preparation or chromatographic separation prior to analysis. Notably, ß-U10 was observed with 23 other drug substances, most commonly in temporally distinct clusters with heroin, etizolam, and diphenhydramine, and in a total of 182 different poly-drug combinations. Longitudinal monitoring of the number and weekly "average signal intensity" (ASI) values of identified substances, developed here as a semi-quantitative proxy indicator of changes in availability, relative purity and compositions of street level drug samples, revealed that increases in the number of identifications and ASI for ß-U10 and etizolam coincided with a 50% decrease in the number of positive detections and an order of magnitude decrease in the ASI for heroin.

Imaging and Targeting Coronary Artery Inflammation.

Significance: Coronary artery disease (CAD) continues to be a leading cause of morbidity and mortality across the world despite significant progress in the prevention, diagnosis, and treatment of atherosclerotic disease. Recent Advances: The focus of the cardiovascular community has shifted toward seeking a better understanding of the inflammatory mechanisms driving residual CAD risk that is not modulated by current therapies. Significant progress has been achieved in revealing both proinflammatory and anti-inflammatory mechanisms, and how shift of the balance in favor of the former can drive the development of disease. Critical Issues: Advances in the noninvasive detection of coronary artery inflammation have been forthcoming. These advances include multiple imaging modalities, with novel applications of computed tomography both with and without positron emission tomography, and experimental ultrasound techniques. These advances will enable better selection of patients for anti-inflammatory treatments and assessment of treatment response. The rapid advancement in pharmaceutical design has enabled the production of specific antibodies against inflammatory pathways of atherosclerosis, with modest success to date. The pursuit of demonstrating the efficacy and safety of novel anti-inflammatory and/or proinflammatory resolution therapies for atherosclerotic CAD has become a major focus. Future Directions: This review seeks to provide an update of the latest evidence of all three of these highly related but disparate areas of inquiry: Our current understanding of the key mechanisms by which inflammation contributes to coronary artery atherosclerosis, the evidence for noninvasive assessment of coronary artery inflammation, and finally, the evidence for targeted therapies to treat coronary inflammation for the reduction of CAD risk. Antioxid. Redox Signal. 34, 1217-1243.

Hybrid 213 nm photodissociation of cationized Sterol lipid ions yield [M]+. Radical products for improved structural characterization using multistage tandem mass spectrometry.

Sterols are a class of lipid molecules that include cholesterol, oxysterols, and sterol esters. Sterol lipids play critical functional roles in mammalian biology, including the dynamic regulation of cell membrane fluidity, as precursors for the synthesis of bile acids, steroid hormones and vitamin D, as regulators of gene expression in lipid metabolism, and for cholesterol transport and storage. The most common method employed for sterol analysis is high performance liquid chromatography coupled with tandem mass spectrometry (MS/MS). However, conventional collision induced dissociation (CID) methods used for ion activation during MS/MS typically fail to provide sufficient structural information for unambiguous assignment of sterol species based on their fragmentation behaviour alone. This places a significant burden on the efficiency of the chromatographic separation methods for the effective separation of isomeric sterols. Here, toward developing an improved analysis strategy for sterol lipids, we have explored the novel use of 213 nm photodissociation MS/MS and hybrid multistage-MS/MS (i.e., MSn) data acquisition approaches for the improved structural characterization of cholesterol, representative isomeric oxysterols, and cholesteryl esters. Most notably, UVPD-MS/MS of ammoniated, lithiated and sodiated adducts of cholesterol, several representative oxysterol species, and an oxosterol lipid, are shown to give rise to abundant [M]+. radical cation products, that subsequently fragment during collision induced MS3 to yield extensive structurally informative product ions, similar to those observed by Electron Ionization, and that enable their unambiguously assignment, including isomeric differentiation of oxysterols. For cholesterol esters, a reversed hybrid collision induced-MS/MS and UVPD-MS3 approach is shown to enable assignment of the sterol backbone, and localization of the site(s) of unsaturation within esterified fatty acyl chains.

Early Warning System for Illicit Drug Use at Large Public Events: Trace Residue Analysis of Discarded Drug Packaging Samples.

Inspired by Locard's exchange principle, which states "every contact leaves a trace", a trace residue sampling strategy has been developed for the analysis of discarded drug packaging samples (DPS), as part of an early warning system for illicit drug use at large public events including music/dance festivals. Using direct analysis in real time/mass spectrometry and tandem mass spectrometry, rapid and high-throughput identification and characterization of a wide range of illicit drugs and adulterant substances was achieved, including in complex polydrug mixtures and at low relative ion abundances. A total of 1362 DPS were analyzed either off-site using laboratory-based instrumentation or on-site and in close to real time using a transportable mass spectrometer housed within a mobile analytical laboratory, with each analysis requiring less than 1 min per sample. Of the DPS analyzed, 92.2% yielded positive results for at least one of 15 different drugs and/or adulterants, including cocaine, MDMA, and ketamine, as well as numerous novel psychoactive substances (NPS). Also, 52.6% of positive DPS were found to contain polydrug mixtures, and a total of 42 different drug and polydrug combinations were observed throughout the study. For analyses performed on-site, reports to key stakeholders including event organizers, first aid and medical personnel, and peer-based harm reduction workers could be provided in as little as 5 min after sample collection. Following risk assessment of the potential harms associated with their use, drug advisories or alerts were then disseminated to event staff and patrons and subsequently to the general public when substances with particularly toxic properties were identified.

The effectiveness of student-run organizations within global health promotion initiatives.

INTRODUCTION: This commentary describes a student-led project that distributed long-lasting insecticide-treated nets in Masaka, Uganda. The role of student-led initiatives in global health promotion projects is also discussed. METHODS: A survey of 213 net recipients was conducted after a 12-month period to evaluate malaria prevention knowledge, and net use and maintenance. RESULTS: Only 4.7% of recipients could not recall any malaria prevention methods. Seventy percent of pregnant women and 86.5% of children under five slept under a net the previous night. Only two households (0.9%) no longer possessed a net, and nets were not used in 2.3% of houses. Household observation revealed 17.4% of nets had at least one problem that would compromise effectiveness. CONCLUSIONS: Student-led projects can play an important role in effectively preventing malaria. However coordination with existing programs, targeting hard-to-access groups, and training of students overcomes some common limitations of such student-led initiatives.

APOE Polymorphism Affects Brain Default Mode Network in Healthy Young Adults: A STROBE Article.

To investigate the effect of apolipoprotein E (APOE) gene polymorphism on the resting-state brain function, structure, and blood flow in healthy adults younger than 35 years, using multimodality magnetic resonance (MR) imaging.Seventy-six healthy adults (34 men, 23.7 ±â€Š2.8 y; 31 APOE ε4/ε3 carriers, 31 ε3/ε3 carriers, and 14 ε2/ε3 carriers) were included. For resting-state functional MRI data, default mode network (DMN) and amplitude of low-frequency fluctuation maps were extracted and analyzed. Voxel-based morphometry, diffusion tensor imaging from structural imaging, and cerebral blood flow based on arterial spin labeling MR imaging were also analyzed. Correlation analysis was performed between the above mentioned brain parameters and neuropsychological tests.There were no differences in neuropsychological performances, amplitude of low-frequency fluctuation, gray/white matter volumes, fractional anisotropy, mean diffusivity, or whole brain cerebral blood flow among the 3 groups. As for DMN, the ε4/ε3 group showed increased functional connectivities (FCs) in the left medial prefrontal cortex and bilateral posterior cingulate cortices/precuneus compared with the ε3/ε3 group, and increased FCs in the left medial prefrontal cortex and right temporal lobe compared with the ε2/ε3 group (P < 0.05, Alphasim corrected). No differences of DMN FCs were found between the ε2/ε3 and ε3/ε3 groups. FCs in the right temporal lobe positively correlated with the performances of vocabulary learning, delayed recall, and graph recall in all participants (P < 0.05).APOE ε4 carriers exhibited significantly increased DMN FCs when compared with ε3 and ε2 carriers. The ε4 affects DMN FCs before brain structure and blood flow in cognitively intact young patients, suggesting DMN FC may serve as a potential biomarker for the detection of early manifestations of genetic effect.