Publications by authors named "V Ia Sarukhanov"

Background: Optimal pharmacological therapy for pulmonary arterial hypertension (PAH) remains unclear, as pathophysiological heterogeneity may affect therapeutic outcomes. A ranking methodology based on pulmonary vascular genetic expression analysis could assist in medication selection and potentially lead to improved prognosis.

Objective: To describe a bioinformatics approach for ranking currently approved pulmonary arterial antihypertensive agents based on gene expression data derived from percutaneous endoarterial biopsies in an animal model of pulmonary hypertension.

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Background: Despite the approval of several medications for pulmonary hypertension, morbidity and mortality are unacceptably high. Systemic hypotension may limit the use of pulmonary hypertension medications.

Objectives: This study aimed to assess whether the homing peptide CAR (CARSKNKDC) improves the vasodilatory selectivity of fasudil in the pulmonary circulation or systemic circulation in a porcine pulmonary hypertension model.

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Pulmonary hypertension (PH) results in significant morbidity and mortality. Chronic PH animal models may advance the study of PH's mechanisms, evolution, and therapy. In this report, we describe the challenges and successes in developing three models of chronic PH in large animals: two models (one canine and one swine) utilized repeated infusions of ceramic microspheres into the pulmonary vascular bed, and the third model employed a surgical aorto-pulmonary shunt.

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MicroRNAs (miRNAs) may regulate a number of genes, each of which may have a variety of functions. We utilized an endoarterial biopsy catheter to assess the dysregulation of miRNAs in a porcine shunt model of pulmonary hypertension (PH). Two Yucatan micropigs underwent surgical anastomosis of the left pulmonary artery to the descending aorta.

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Technogenic environmental pollution is the factor of destabilization of natural and agricultural ecological systems. Among various kinds of beings agricultural animals are considered as one of the most vulnerable components of ecosystems to the influence of technogenic factors including ionizing radiation. Therefore, the generalization of experimental data and mathematical modeling are necessary to forecast the mortality of irradiated animals.

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