Background/ObjectivesLimited numbers of studies demonstrated obesity-induced macrophage infiltration in skeletal muscle (SM), but dynamics of immune cell accumulation and contribution of T cells to SM insulin resistance are understudied.Subjects/MethodsT cells and macrophage markers were examined in SM of obese humans by RT-PCR. Mice were fed high-fat diet (HFD) for 2–24 weeks, and time course of macrophage and T cell accumulation was assessed by flow cytometry and quantitative RT-PCR. Extramyocellular adipose tissue (EMAT) was quantified by high-resolution micro-CT, and correlation to T cell number in SM was examined. CD11a−/− mice and C57BL/6 mice were treated with CD11a-neutralizing antibody to determine the role of CD11a in T cell accumulation in SM. To investigate the involvement JAK/STAT, the major pathway for T helper I (TH1) cytokine IFNγ? in SM and adipose tissue inflammation and insulin resistance, mice were treated with a JAK1/JAK2 inhibitor, baricitinib.ResultsMacrophage and T cells markers were upregulated in SM of obese compared with lean humans. SM of obese mice had higher expression of inflammatory cytokines, with macrophages increasing by 2 weeks on HFD and T cells increasing by 8 weeks. The immune cells were localized in EMAT. Micro-CT revealed that EMAT expansion in obese mice correlated with T cell infiltration and insulin resistance. Deficiency or neutralization of CD11a reduced T cell accumulation in SM of obese mice. T cells polarized into a proinflammatory TH1 phenotype, with increased STAT1 phosphorylation in SM of obese mice. In vivo inhibition of JAK/STAT pathway with baricitinib reduced T cell numbers and activation markers in SM and adipose tissue and improved insulin resistance in obese mice.ConclusionsObesity-induced expansion of EMAT in SM was associated with accumulation and proinflammatory polarization of T cells, which may regulate SM metabolic functions through paracrine mechanisms. Obesity-associated SM “adiposopathy” may thus play an important role in development of insulin resistance and inflammation.

Objective The Effect of Lipid Modification on Peripheral Artery Disease after Endovascular Intervention Trial (ELIMIT), a prospective double-blind randomized study, was designed to determine the effects of triple-drug lipid modification therapy versus mono-therapy over 24 months on the progression of atherosclerosis in the distal superficial femoral artery (SFA), as assessed by 3.0T magnetic resonance imaging (MRI). Methods A total of 102 patients were randomized to either mono-therapy with simvastatin (40 mg daily) or triple-therapy with simvastatin (40 mg daily), extended-release niacin (1500 mg daily), and ezetimibe (10 mg daily). MRI was performed at baseline and 6, 12, and 24 months. SFA wall, lumen, and total vessel volumes were quantified. MRI-derived SFA parameters and lipids were analyzed with multilevel models and nonparametric tests, respectively. Results Baseline characteristics did not differ between mono and triple-therapy groups, except for ethnicity (p= 0.02). SFA wall, lumen, and total vessel volumes increased non-significantly for both groups between baseline and 24-months. Non–high-density lipoprotein cholesterol was significantly reduced at 12 months with triple-therapy compared with mono-therapy (p= 0.01). Conclusion No significant differences were observed between mono-therapy using simvastatin and triple-therapy with simvastatin, extended-release niacin, and ezetimibe for 24-month changes in SFA wall, lumen, and total vessel volumes.

Accurate quantification of coronary artery calcium provides an opportunity to assess the extent of atherosclerosis disease. Coronary calcification burden has been reported to be associated with cardiovascular risk. Currently, an observer has to identify the coronary calcifications among a set of candidate regions, obtained by thresholding and connected component labeling, by clicking on them. To relieve the observer of such a labor-intensive task, an automated tool is needed that can detect and quantify the coronary calcifications. However, the diverse and heterogeneous nature of the candidate regions poses a significant challenge. In this paper, we investigate a supervised classification-based approach to distinguish the coronary calcifications from all the candidate regions and propose a two-stage, hierarchical classifier for automated coronary calcium detection. At each stage, we learn an ensemble of classifiers where each classifier is a cost-sensitive learner trained on a distinct asymmetrically sampled data subset. We compute the relative location of the calcifications with respect to a heart-centered coordinate system, and also use the neighboring regions of the calcifications to better characterize their properties for discrimination. Our method detected coronary calcifications with an accuracy, sensitivity and specificity of 98.27, 92.07 and 98.62%, respectively, for a testing dataset of non-contrast computed tomography scans from 105 subjects.

Background Increased arterial stiffness has been shown to be associated with aging and cardiovascular risk factors. Speckle-tracking algorithms are being used to measure myocardial strain. We evaluated if speckle-tracking could be used to measure carotid arterial wall strain (CAS) reproducibly in healthy volunteers and then examined if CAS was lesser in individuals with diabetes. Methods Bilateral electrocardiography-gated ultrasound scans of the distal common carotid arteries [D-CCA] (3 cardiac cycles, 14 MHz linear probe, mean 78.7 [Standard deviation (SD) 8.9]) frames per second were performed twice (2–4 days apart) on 10 healthy volunteers to test repeatability. Differences in CAS between healthy (n=20) and diabetic subjects (n=21) were examined. Peak CAS was measured in each of 6 equal segments and averages of all segments (i.e., global average), of the 3 nearest the probe, and of the 3 farthest from the probe (i.e., far wall average) were obtained. Results Global CAS (intraclass correlation coefficient [ICC]=0.40) and far wall average (ICC=0.63) had the greatest test-retest reliability. The global and far wall averaged CAS were lower in diabetics (4.29% [Standard Error (SE) 0.27%]; 4.30% [SE 0.44%], respectively) than in controls (5.48% [SE 0.29%], p=0.001; 5.58% [SE 0.44%], p=0.003, respectively). This difference persisted after adjustment for age, gender, race, and hemodynamic parameters. Conclusions Speckle-tracking for measuring carotid arterial wall strain is feasible and modestly reliable. Diabetic subjects had a lower carotid arterial wall strain obtained with speckle-tracking when compared with healthy controls.

Measurements related to coronary artery calcification (CAC) offer significant predictive value for coronary artery disease (CAD). In current medical practice CAC scoring is a labor-intensive task. The objective of this paper is the development and evaluation of a family of coronary artery region (CAR) models applied to the detection of CACs in coronary artery zones and sections. Thirty patients underwent non-contrast electron-beam computed tomography scanning. Coronary artery trajectory points as presented in the University of Houston heart-centered coordinate system were utilized to construct the CAR models which automatically detect coronary artery zones and sections. On a per-patient and per-zone basis the proposed CAR models detected CACs with a sensitivity, specificity and accuracy of 85.56 (± 15.80)%, 93.54 (± 1.98)%, and 85.27 (± 14.67)%, respectively while the corresponding values in the zones and segments based case were 77.94 (± 7.78)%, 96.57 (± 4.90)%, and 73.58 (± 8.96)%, respectively. The results of this study suggest that the family of CAR models provide an effective method to detect different regions of the coronaries. Further, the CAR classifiers are able to detect CACs with a mean sensitivity and specificity of 86.33 and 93.78%, respectively.