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This paper investigates the comproportionation reaction of Mn with [Formula: see text] as a route for manganese oxide nanoparticle synthesis in the protein ferritin. We report that [Formula: see text] serves as the electron acceptor and reacts with Mn in the presence of apoferritin to form manganese oxide cores inside the protein shell. Manganese loading into ferritin was studied under acidic, neutral, and basic conditions and the ratios of Mn and permanganate were varied at each pH. The manganese-containing ferritin samples were characterized by transmission electron microscopy, UV/Vis absorption, and by measuring the band gap energies for each sample. Manganese cores were deposited inside ferritin under both the acidic and basic conditions. All resulting manganese ferritin samples were found to be indirect band gap materials with band gap energies ranging from 1.01 to 1.34 eV. An increased UV/Vis absorption around 370 nm was observed for samples formed under acidic conditions, suggestive of MnO formation inside ferritin.

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Left ventricular assist devices (LVADs) are surgically implanted mechanical pumps that improve survival rates for individuals with advanced heart failure. While life-saving, LVAD therapy is also associated with high morbidity, which can be partially attributed to the difficulties in identifying an LVAD complication before an adverse event occurs. Methods that are currently used to monitor for complications in LVAD-supported individuals require frequent clinical assessments at specialized LVAD centers. Remote analysis of digitally recorded precordial sounds has the potential to provide an inexpensive point-of-care diagnostic tool to assess both device function and the degree of cardiac support in LVAD recipients, facilitating real-time, remote monitoring for early detection of complications. To our knowledge, prior studies of precordial sounds in LVAD-supported individuals have analyzed LVAD noise rather than intrinsic heart sounds, due to a focus on detecting pump complications, and perhaps the obscuring of heart sounds by LVAD noise. In this letter, we describe an adaptive filtering method to remove sounds generated by the LVAD, making it possible to automatically isolate and analyze underlying heart sounds. We present preliminary results describing acoustic signatures of heart sounds extracted from in vivo data obtained from LVAD-supported individuals. These findings are significant as they provide proof-of-concept evidence for further exploration of heart sound analysis in LVADsupported individuals to identify cardiac abnormalities and changes in LVAD support.

No abstract