Searching for Preclinical Models of Acute Decompensated Heart Failure: a Concise Narrative Overview and a Novel Swine Model

Cardiovascular Drugs and Therapy - Available animal models of acute heart failure (AHF) and their limitations are discussed herein. A novel and preclinically relevant porcine model of decompensated...     

Catabolic/Anabolic Imbalance Is Accompanied by Changes of Left Ventricular Steroid Nuclear Receptor Expression in Tachycardia-Induced Systolic Heart Failure in Male Pigs

BackgroundSteroid hormones play an important role in heart failure (HF) pathogenesis, and clinical data have revealed disordered steroidogenesis in male patients with HF. However, there is still a lack of studies on steroid hormones and their receptors during HF progression. Therefore, a porcine model of tachycardia-induced cardiomyopathy corresponding to HF was used to assess steroid hormone concentrations in serum and their nuclear receptor levels in heart tissue during the consecutive stages of HF.Methods and ResultsMale pigs underwent right ventricular pacing and developed a clinical picture of mild, moderate, or severe HF. Serum concentrations of dehydroepiandrosterone, testosterone, dihydrotestosterone, estradiol, aldosterone, and cortisol were assessed by enzyme-linked immunosorbent assay. Androgen receptor, estrogen receptor alpha, mineralocorticoid receptor, and glucocorticoid receptor messenger RNA levels in the left ventricle were determined by qPCR.The androgen level decreased in moderate and severe HF animals, while the corticosteroid level increased. The estradiol concentration remained stable. The quantitative real-time polymerase chain reaction revealed the downregulation of androgen receptor in consecutive stages of HF and increased expression of mineralocorticoid receptor messenger RNA under these conditions.ConclusionsIn the HF pig model, deteriorated catabolic/anabolic balance, manifested by upregulation of aldosterone and cortisol and downregulation of androgen signaling on the ligand level, was augmented by changes in steroid hormone receptor expression in the heart tissue.     

Deep Ethical Learning: Taking the Interplay of Human and Artificial Intelligence Seriously

From predicting medical conditions to administering health behavior interventions, artificial intelligence technologies are being developed to enhance patient care and outcomes. However, as Mélanie Terrasse and coauthors caution in an article in this issue of the Hastings Center Report, an overreliance on virtual technologies may depersonalize medical interactions and erode therapeutic relationships. The increasing expectation that patients will be actively engaged in their own care, regardless of the patients’ desire, technological literacy, and economic means, may also violate patients’ autonomy and exacerbate access. Moreover, since AI design is both a technical and social process, algorithms may mirror human biases, calling into question the vision of AI technologies surpassing human judgment and avoiding prejudices in decision‐making. The best answer to these problems is to develop AI health technologies as part of a culture of health care quality improvement, responding to existing needs while being proactive about potential technical and ethical problems that can arise from the technologies’ design and implementation.