Anti-inflammatory activity of Chios mastic gum is associated with inhibition of TNF-alpha induced oxidative stress

<p>Abstract</p> <p>Background</p> <p>Gum of Chios mastic (<it>Pistacia lentiscus var. chia) </it>is a natural antimicrobial agent that has found extensive use in pharmaceutical products and as a nutritional supplement. The molecular mechanisms of its anti-inflammatory activity, however, are not clear. In this work, the potential role of antioxidant activity of Chios mastic gum has been evaluated.</p> <p>Methods</p> <p>Scavenging of superoxide radical was investigated by electron spin resonance and spin trapping technique using EMPO spin trap in xanthine oxidase system. Superoxide production in endothelial and smooth muscle cells stimulated with TNF-α or angiotensin II and treated with vehicle (DMSO) or mastic gum (0.1-10 μg/ml) was measured by DHE and HPLC. Cellular H₂O₂was measured by Amplex Red. Inhibition of protein kinase C (PKC) with mastic gum was determined by the decrease of purified PKC activity, by inhibition of PKC activity in cellular homogenate and by attenuation of superoxide production in cells treated with PKC activator phorbol 12-myristate 13-acetate (PMA).</p> <p>Results</p> <p>Spin trapping study did not show significant scavenging of superoxide by mastic gum itself. However, mastic gum inhibited cellular production of superoxide and H₂O₂in dose dependent manner in TNF-α treated rat aortic smooth muscle cells but did not affect unstimulated cells. TNF-α significantly increased the cellular superoxide production by NADPH oxidase, while mastic gum completely abolished this stimulation. Mastic gum inhibited the activity of purified PKC, decreased PKC activity in cell homogenate, and attenuated superoxide production in cells stimulated with PKC activator PMA and PKC-dependent angiotensin II in endothelial cells.</p> <p>Conclusion</p> <p>We suggest that mastic gum inhibits PKC which attenuates production of superoxide and H₂O₂by NADPH oxidases. This antioxidant property may have direct implication to the anti-inflammatory activity of the Chios mastic gum.</p

0245: Echocardiographic and clinical outcome in patients undergoing trans-catheter aortic valve replacement with concomitant mitral regurgitation

BackgroundSevere aortic stenosis (AS) is commonly associated with mitral regurgitation (MR) in patients undergoing transcatheter aortic valve replacement (TAVR). The natural history of MR is not well defined in this population.MethodsConsecutive high risk, inoperable patients undergoing TAVR between 2007 and 2011 for AS has echos at baseline and 1 year and were followed for clinical outcomes. MR severity was graded and patients were grouped as having minimal (none-mild) or significant (moderate- severe) MR.Results164 patients underwent TAVR, reducing gradients from 47 to 10mHg. LVEF increased from 48% to 52% while pulmonary aretry systolic pressure (PAPS), LVESD and LVEDD were unchanged. Signficant MR patents had a median 1 grade reduction (p<0,0001) in MR at 1 year. Median LVEF increased by 2% (p=0.0412). Median LVESD decreased by 2.3mm±7.5 (p=0.039). Univariate analysis showed no significant predictors of MR reduction in significant MR patients. Functional and organic significant MR decreased after TAVR but only functional MR patients had improved LVEF (6%, p=0.034), PAPS (5.9mmHg, p=0.022) and LVESD (3.8mm, p=0.013). Multivariate analysis showed functional MR to be a predictor of improved LVEF and PAPS. Clinical outcomes at a mean follow-up of 925 days were not different in patients with significant vs minimal MR; however organic MR patients tended to have more events than functional MR patients (p=0.06).Conclusion:Significant MR patients undergoing TAVR for severe AS improved in LVEF and LVESD, particularly patients with functional MR. Organic MR is marginally predictive of cardiac complications in AS patients

Epicardial adipose tissue measured by magnetic resonance imaging predicts abnormal adenosine stress cardiovascular magnetic resonance imaging and future adverse cardiovascular events

Background A growing body of evidence demonstrates a quantitative association between Epicardial Adipose Tissue (EAT), cardiometabolic risk factors and measures of coronary artery disease (CAD). It is still unclear, however, if EAT is predictive of abnormal functional stress tests and clinical outcomes. The aim of this study is to elucidate the relationship between the total volume of EAT, the detection of ischemia and/or infarct with Adenosine Stress Cardiovascular Magnetic Resonance imaging (AS-CMR), and combined future adverse cardiovascular events. Method

HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes

The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer learning approaches result in suboptimal performance when pre-training is done on natural images. We leveraged masked image modeling to create the first vision-based transformer model, HeartBEiT, for electrocardiogram waveform analysis. We pre-trained this model on 8.5 million ECGs and then compared performance vs. standard CNN architectures for diagnosis of hypertrophic cardiomyopathy, low left ventricular ejection fraction and ST elevation myocardial infarction using differing training sample sizes and independent validation datasets. We show that HeartBEiT has significantly higher performance at lower sample sizes compared to other models. Finally, we also show that HeartBEiT improves explainability of diagnosis by highlighting biologically relevant regions of the EKG vs. standard CNNs. Thus, we present the first vision-based waveform transformer that can be used to develop specialized models for ECG analysis especially at low sample sizes