Background The failing human heart is characterized by metabolic abnormalities, but these defects remains incompletely understood. In animal models of HF there is a switch from a predominance of fatty acid utilization to the more oxygen-sparing carbohydrate metabolism. Recent studies have reported decreases in myocardial lipid content, but inclusion of diabetics and nondiabetics obscures the distinction of adapations to metabolic derangements from adaptations to heart failure per se. Methods and Results We performed both unbiased and targeted myocardial lipid surveys using liquid chromatography-mass spectroscopy in non-diabetic, lean, predominantly non-ischemic advanced HF patients at the time of heart transplantation or LVAD implantation. We identified significantly decreased concentrations of the majority of myocardial lipid intermediates, including long-chain acylcarnitines, the primary subset of energetic lipid substrate for mitochondrial fatty acid oxidation. We report for the first time significantly reduced levels of intermediate and anaplerotic acyl-CoA species incorporated into Krebs cycle, while the myocardial concentration of acetyl-CoA was significantly increased in end-stage heart failure. In contrast, we observed an increased abundance of ketogenic β-hydroxybutyryl CoA, in association with increased myocardial utilization of β-hydroxybutyrate. We observed a significant increase in the expression of the gene encoding succinyl-CoA: 3oxoacid-CoA transferase (SCOT), the rate limiting enzyme for myocardial oxidation of βOHB and acetoacetate. Conclusions These findings indicate increased ketone utilization in the severely failing human heart independent of diabetes, support the role of ketone bodies as an alternative fuel and myocardial ketone oxidation as a key metabolic adaptation in the failing human heart.

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This paper presents a fully integrated CMOS multimodality joint sensor/stimulator array with 1024 pixels for real-time holistic cellular characterization and drug screening. The proposed system consists of four pixel groups and four parallel signal-conditioning blocks. Every pixel group contains 16 × 16 pixels, and each pixel includes one gold-plated electrode, four photodiodes, and in-pixel circuits, within a pixel footprint. Each pixel supports real-time extracellular potential recording, optical detection, charge-balanced biphasic current stimulation, and cellular impedance measurement for the same cellular sample. The proposed system is fabricated in a standard 130-nm CMOS process. Rat cardiomyocytes are successfully cultured on-chip. Measured high-resolution optical opacity images, extracellular potential recordings, biphasic current stimulations, and cellular impedance images demonstrate the unique advantages of the system for holistic cell characterization and drug screening. Furthermore, this paper demonstrates the use of optical detection on the on-chip cultured cardiomyocytes to real-time track their cyclic beating pattern and beating rate.

Cells are complex systems with concurrent multi-physical responses, and cell physiological signals are often encoded with spatiotemporal dynamics and further coupled with multiple cellular activities. However, most existing electronic sensors are only single-modality and cannot capture multi-parametric cellular responses. In this paper, a 1024-pixel CMOS quad-modality cellular interfacing array that enables multi-parametric cell profiling for drug development is presented. The quad-modality CMOS array features cellular impedance characterization, optical detection, extracellular potential recording, and biphasic current stimulation. The fibroblast transparency and surface adhesion are jointly monitored by cellular impedance and optical sensing modalities for comprehensive cell growth evaluation. Simultaneous current stimulation and opto-mechanical monitoring based on cardiomyocytes are demonstrated without any stimulation/sensing dead-zone. Furthermore, drug dose-dependent multi-parametric feature extractions in cardiomyocytes from their extracellular potentials and opto-mechanical signals are presented. The CMOS array demonstrates great potential for fully automated drug screening and drug safety assessments, which may substantially reduce the drug screening time and cost in future new drug development.