Abnormal mitochondrial respiration in skeletal muscle in patients with peripheral arterial disease

AbstractObjectiveDiscrete morphologic, enzymatic and functional changes in skeletal muscle mitochondria have been demonstrated in patients with peripheral arterial disease (PAD). We examined mitochondrial respiration in the gastrocnemius muscle of nine patients (10 legs) with advanced PAD and in nine control patients (nine legs) without evidence of PAD.MethodsMitochondrial respiratory rates were determined with a Clark electrode in an oxygraph cell containing saponin-skinned muscle bundles. Muscle samples were obtained from the anteromedial aspect of the gastrocnemius muscle, at a level 10 cm distal to the tibial tuberosity. Mitochondria respiratory rate, calculated as nanoatoms of oxygen consumed per minute per milligram of noncollagen protein, were measured at baseline (V0), after addition of substrates (malate and glutamate; (VSUB), after addition of adenosine diphosphate (ADP) (VADP), and finally, after adenine nucleotide translocase inhibition with atractyloside (VAT). The acceptor control ratio, a sensitive indicator of overall mitochondrial function, was calculated as the ratio of the respiratory rate after the addition of ADP to the respiratory rate after adenine nucleotide translocase inhibition with atractyloside (VADP/ VAT).ResultsRespiratory rate in muscle mitochondria from patients with PAD were not significantly different from control values at baseline (0.31 ± 0.06 vs 0.55 ± 0.12; P = .09), but Vsub was significantly lower in patients with PAD compared with control subjects (0.43 ± 0.07 vs 0.89 ± 0.20; P < .05), as was VADP (0.69 ± 0.13 vs 1.24 ± 0.20; P < .05). Respiratory rates after atractyloside inhibition in patients with PAD were no different from those in control patients (0.47 ± 0.07 vs 0.45 ± P = .08). Compared with control values, mitochondria from patients with PAD had a significantly lower acceptor control ratio (1.41 ± 0.10 vs 2.90 ± 0.20; P < .001).ConclusionMitochondrial respiratory activity is abnormal in lower extremity skeletal muscle in patients with PAD. When considered in concert with the ultrastructural and enzymatic abnormalities previously documented in mitochondria of chronically ischemic muscle, these data support the concept of defective mitochondrial function as a pathophysiologic component of PAD

Right subclavian double steal syndrome: a case report

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Cystathionine γ Lyase Sulfhydrates the RNA Binding Protein Human Antigen R to Preserve Endothelial Cell Function and Delay Atherogenesis

Hydrogen sulfide (H2S), generated by cystathionine γ lyase (CSE), is an important endogenous regulator of vascular function. The aim of the present study was to investigate the control and consequences of CSE activity in endothelial cells under physiological and proatherogenic conditions

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions