Tissue engineering applications demand 3D, non-invasive, and longitudinal assessment of bioprinted constructs. Current emphasis is on developing tissue constructs mimicking conditions; however, these are increasingly challenging to image as they are typically a few millimeters thick and turbid, limiting the usefulness of classical fluorescence microscopic techniques. For such applications, we developed a Mesoscopic Fluorescence Molecular Tomography methodology that collects high information content data to enable high-resolution tomographic reconstruction of fluorescence biomarkers at millimeters depths. This imaging approach is based on an inverse problem; hence, its imaging performances are dependent on critical technical considerations including optode sampling, forward model design and inverse solver parameters. Herein, we investigate the impact of the optical system configuration parameters, including detector layout, number of detectors, combination of detector and source numbers, and scanning mode with uncoupled or coupled source and detector array, on the 3D imaging performances. Our results establish that an MFMT system with a 2D detection chain implemented in a de-scanned mode provides the optimal imaging reconstruction performances.
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http://dx.doi.org/10.1364/BOE.10.005660 | DOI Listing |
J Med Internet Res
January 2025
Research Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Jülich, Germany.
Background: Traditional in-clinic methods of collecting self-reported information are costly, time-consuming, subjective, and often limited in the quality and quantity of observation. However, smartphone-based ecological momentary assessments (EMAs) provide complementary information to in-clinic visits by collecting real-time, frequent, and longitudinal data that are ecologically valid. While these methods are promising, they are often prone to various technical obstacles.
View Article and Find Full Text PDFJ Particip Med
January 2025
Department of Ambulatory Care, Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Background: Health authorities worldwide have invested in digital technologies to establish robust information exchange systems for improving the safety and efficiency of medication management. Nevertheless, inaccurate medication lists and information gaps are common, particularly during care transitions, leading to avoidable harm, inefficiencies, and increased costs. Besides fragmented health care processes, the inconsistent incorporation of patient-driven changes contributes to these problems.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Qingdao Institute for Theoretical and Computational Sciences and Center for Optics Research and Engineering, Shandong University, Qingdao 266237, China.
Given a number of data sets for evaluating the performance of single reference methods for the low-lying excited states of closed-shell molecules, a comprehensive data set for assessing the performance of multireference methods for the low-lying excited states of open-shell systems is still lacking. For this reason, we propose an extension (QUEST#4X) of the radical subset of QUEST#4 ( , , 3720) to cover 110 doublet and 39 quartet excited states. Near-exact results obtained by iterative configuration interaction with selection and second-order perturbation correction (iCIPT2) are taken as benchmark to calibrate static-dynamic-static configuration interaction (SDSCI) and static-dynamic-static second-order perturbation theory (SDSPT2), which are minimal MRCI and CI-like perturbation theory, respectively.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.
In the field of computational chemistry, predicting bond dissociation energies (BDEs) presents well-known challenges, particularly due to the multireference character of reactive systems. Many chemical reactions involve configurations where single-reference methods fall short, as the electronic structure can significantly change during bond breaking. As generating training data for partially broken bonds is a challenging task, even state-of-the-art reactive machine learning interatomic potentials (MLIPs) often fail to predict reliable BDEs and smooth dissociation curves.
View Article and Find Full Text PDFEnviron Technol
February 2025
PGEAGRI/CCET - Center of Exact Sciences and Technology, State University of Western of Paraná - UNIOESTE, Cascavel, Brazil.
The deammonification process is an efficient alternative to remove nitrogen from wastewater with a low carbon/nitrogen ratio. However, the reactor configuration and operational factors pose challenges for applications in treatment systems to remove nitrogen from municipal and industrial wastewater on a large scale. To address this gap, this study evaluated a new deammonification strategy using a single-stage membrane aerated biofilm reactor (MABR), operated with continuous flow, under different hydraulic retention times (HRT) in the post-treatment of poultry slaughterhouse wastewater with a low nitrogen load, similar to domestic wastewater.
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