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Near-infrared diffuse optical tomography (DOT) is a promising functional modality for breast cancer imaging; however, the clinical translation of DOT is hampered by technical limitations. Specifically, conventional finite element method (FEM)-based optical image reconstruction approaches are time-consuming and ineffective in recovering full lesion contrast. To address this, we developed a deep learning-based reconstruction model (FDU-Net) comprised of a Fully connected subnet, followed by a convolutional encoder-Decoder subnet, and a U-Net for fast, end-to-end 3D DOT image reconstruction. The FDU-Net was trained on digital phantoms that include randomly located singular spherical inclusions of various sizes and contrasts. Reconstruction performance was evaluated in 400 simulated cases with realistic noise profiles for the FDU-Net and conventional FEM approaches. Our results show that the overall quality of images reconstructed by FDU-Net is significantly improved compared to FEM-based methods and a previously proposed deep-learning network. Importantly, once trained, FDU-Net demonstrates substantially better capability to recover true inclusion contrast and location without using any inclusion information during reconstruction. The model was also generalizable to multi-focal and irregularly shaped inclusions unseen during training. Finally, FDU-Net, trained on simulated data, could successfully reconstruct a breast tumor from a real patient measurement. Overall, our deep learning-based approach demonstrates marked superiority over the conventional DOT image reconstruction methods while also offering over four orders of magnitude acceleration in computational time. Once adapted to the clinical breast imaging workflow, FDU-Net has the potential to provide real-time accurate lesion characterization by DOT to assist the clinical diagnosis and management of breast cancer.

Organic photovoltaics are a sustainable and cost-effective power-generation technology that may aid the move to zero-emission buildings, carbon neutral cities, and electric vehicles. While state-of-the-art organic photovoltaic devices can be encapsulated to withstand air and moisture, they are currently still susceptible to light-induced degradation, leading to a decline in the long-term efficiency of the devices. In this study, the role of ultraviolet (UV) radiation on a multilayer organic photovoltaic device is systematically uncovered using spectral filtering. By applying long-pass filters to remove different parts of the UV portion of the AM1.5G spectrum, two main photodegradation processes are shown to occur in the organic photovoltaic devices. A UV-activated process is found to cause a significant decrease in the photocurrent across the whole spectrum and is most likely linked to the deterioration of the charge extraction layers. In addition, a photodegradation process caused by UV-filtered sunlight is found to change the micromorphology of the bulk heterojunction material, leading to a reduction in photocurrent at high photon energies. These findings strongly suggest that the fabrication of inherently photostable organic photovoltaic devices will require the replacement of fullerene-based electron transporter materials with alternative organic semiconductors.

Impressive power conversion efficiencies coupled with the relative ease of fabrication have made perovskite solar cells a front runner for next-generation photovoltaics. Although perovskite films and optoelectronic devices have been widely studied, relatively little is known about the chemistry of the precursor solutions. Here, we present a study on the hydrolysis of N,N-dimethylformamide, correlating how pH changes related to its degradation affect the crystallization of MAPbI3−xClxperovskite films. By careful manipulation of the pH, and the resulting colloid distribution in precursor solutions, we fabricate perovskite films with greatly improved crystallinity, which when incorporated into photovoltaic devices reproducibly yield efficiencies of over 18%. Extending this method to the mixed cation, mixed halide perovskite FA0.83MA0.17Pb(I0.83Br0.17)3, we obtain power conversion efficiencies of up to 19.9% and open-circuit voltages of 1.21 V for a material with a bandgap of 1.57 eV, achieving the lowest yet reported loss in potential from bandgap to a VOCof only 360 mV.

Introduction:Antithrombotic medications are the subject of multiple transcatheter aortic valve replacement (TAVR) randomized control trials. Pragmatically, decisions are complicated by conditions such as atrial fibrillation (AF) that also require lifetime anticoagulation. Our study examines antithrombotic medications in a real-world cohort to identify risk factors for bleeding by 1-year post-TAVR.Methods:This retrospective study includes 844 patients undergoing transfemoral TAVR between 2015 and 2020. Pre- and post-operative medications, comorbidities, and 1-year outcomes were recorded based on review of the medical record. Antithrombotic regiment decisions were made on a case-by-case basis. Bleeding classification followed VARC2 definitions. Patients were stratified into two groups based on history of AF. Multivariable logistic regression was used to determine independent predictors of bleeding.Results:Among the 844 patients, 290 had comorbid AF (34%). Patients with AF were older (80.3 vs 77.8 years; p<0.001), more frequently had cardiovascular comorbidities, and had lower LVEF (52.4% vs 56.8%; p<0.001). Patients with AF were more likely to experience major or life-threatening bleeding (10% vs 5%; p<0.001), but there were no differences in rates of myocardial infarction, cerebrovascular accident, nor death by 1-year follow-up. After controlling for risk factors including anticoagulation and increases to antithrombotic regiment post-operatively, the independent risk predictors of major or life-threatening bleed included female sex [OR 1.522 (1.118-1.741); p=0.018], severe baseline anemia [2.938 (1.146-7.533); p=0.025], and atrial fibrillation [2.195 (1.206-3.997); p=0.010].Conclusions:Female sex, severe baseline anemia, and comorbid atrial fibrillation are predictors of major or life-threatening bleed by 1 year in patients undergoing transfemoral TAVR, independent of antithrombotic regiment.

In this work, we investigate the vibrational properties of the hybrid organic/inorganic halide perovskite MAPbI3(MA = CH3NH3) in the range 6–3500 cm–1by combining first-principles density-functional perturbation theory calculations and low-temperature infrared (IR) absorption measurements on evaporated perovskite films. By using a group factor analysis, we establish the symmetry of the normal modes of vibration and predict their IR and Raman activity. We validate our analysis via explicit calculation of the IR intensities. Our calculated spectrum is in good agreement with our measurements. By comparing theory and experiment, we are able to assign most of the features in the IR spectrum. Our analysis shows that the IR spectrum of MAPbI3can be partitioned into three distinct regions: the internal vibrations of the MA cations (800–3100 cm–1), the cation librations (140–180 cm–1), and the internal vibrations of the PbI3network (<100 cm–1). The low-frequency region of the IR spectrum is dominated by Pb–I stretching modes of the PbI3network with Busymmetry and librational modes of the MA cations. In addition, we find that the largest contributions to the static dielectric constant arise from Pb–I stretching and Pb–I–Pb rocking modes, and that one low-frequency B2uPb–I stretching mode exhibits a large LO–TO splitting of 50 cm–1.

Neuregulin-1 (NRG) is a member of the epidermal growth factor family possessing a critical role in cardiomyocyte development and proliferation. Systemic administration of NRG demonstrated efficacy in cardiomyopathy animal models, leading to clinical trials using daily NRG infusions. This approach is hindered by requiring daily infusions and off-target exposure. Therefore, this study aimed to encapsulate NRG in a hydrogel to be directly delivered to the myocardium, accomplishing sustained localized NRG delivery.