Tetracycline antibiotics act by inhibiting bacterial protein translation. Given the bacterial ancestry of mitochondria, we tested the hypothesis that doxycycline—which belongs to the tetracycline class—reduces mitochondrial function, and results in cardiac contractile dysfunction in cultured H9C2 cardiomyoblasts, adult rat cardiomyocytes, in Drosophila and in mice. Ampicillin and carbenicillin were used as control antibiotics since these do not interfere with mitochondrial translation. In line with its specific inhibitory effect on mitochondrial translation, doxycycline caused a mitonuclear protein imbalance in doxycycline-treated H9C2 cells, reduced maximal mitochondrial respiration, particularly with complex I substrates, and mitochondria appeared fragmented. Flux measurements using stable isotope tracers showed a shift away from OXPHOS towards glycolysis after doxycycline exposure. Cardiac contractility measurements in adult cardiomyocytes and Drosophila melanogaster hearts showed an increased diastolic calcium concentration, and a higher arrhythmicity index. Systolic and diastolic dysfunction were observed after exposure to doxycycline. Mice treated with doxycycline showed mitochondrial complex I dysfunction, reduced OXPHOS capacity and impaired diastolic function. Doxycycline exacerbated diastolic dysfunction and reduced ejection fraction in a diabetes mouse model vulnerable for metabolic derangements. We therefore conclude that doxycycline impairs mitochondrial function and causes cardiac dysfunction.

Purpose 19F‐MRI is gaining widespread interest for cell tracking and quantification of immune and inflammatory cells in vivo. Different fluorinated compounds can be discriminated based on their characteristic MR spectra, allowing in vivo imaging of multiple 19F compounds simultaneously, so‐called multicolor 19F‐MRI. We introduce a method for multicolor 19F‐MRI using an iterative sparse deconvolution method to separate different 19F compounds and remove chemical shift artifacts arising from multiple resonances. Methods The method employs cycling of the readout gradient direction to alternate the spatial orientation of the off‐resonance chemical shift artifacts, which are subsequently removed by iterative sparse deconvolution. Noise robustness and separation was investigated by numerical simulations. Mixtures of fluorinated oils (PFCE and PFOB) were measured on a 7T MR scanner to identify the relation between 19F signal intensity and compound concentration. The method was validated in a mouse model after intramuscular injection of fluorine probes, as well as after intravascular injection. Results Numerical simulations show efficient separation of 19F compounds, even at low signal‐to‐noise ratio. Reliable chemical shift artifact removal and separation of PFCE and PFOB signals was achieved in phantoms and in vivo. Signal intensities correlated excellently to the relative 19F compound concentrations (r−2 = 0.966/0.990 for PFOB/PFCE). Conclusions The method requires minimal sequence adaptation and is therefore easily implemented on different MRI systems. Simulations, phantom experiments, and in‐vivo measurements in mice showed effective separation and removal of chemical shift artifacts below noise level. We foresee applicability for simultaneous in‐vivo imaging of 19F‐containing fluorine probes or for detection of 19F‐labeled cell populations.

Atherosclerosis is a prevalent disease affecting a large portion of the population at one point in their lives. There is an unmet need for noninvasive diagnostics to identify and characterize at-risk plaque phenotypes noninvasively and in vivo, to improve the stratification of patients with cardiovascular disease, and for treatment evaluation. Magnetic resonance imaging is uniquely positioned to address these diagnostic needs. However, currently available magnetic resonance imaging methods for vessel wall imaging lack sufficient discriminative and predictive power to guide the individual patient needs. To address this challenge, physicists are pushing the boundaries of magnetic resonance atherosclerosis imaging to increase image resolution, provide improved quantitative evaluation of plaque constituents, and obtain readouts of disease activity such as inflammation. Here, we review some of these important developments, with specific focus on emerging applications using high-field magnetic resonance imaging, the use of quantitative relaxation parameter mapping for improved plaque characterization, and novel 19 F magnetic resonance imaging technology to image plaque inflammation.