Daniels Hsu (memorybubble2)

The goal of this work was to determine the quantitative accuracy and optimal reconstruction parameters for I-PET imaging in the presence of therapeutic levels of I. In this effort, images were acquired on a GE D710 PET/CT scanner using a NEMA IEC phantom with spheres containing I and increasing amounts of I activity in the background. At each activity level, two scans were acquired, one with the phantom centered in the field of view (FOV) and one 11.2 cm off-center. Reconstructions used an ordered subset expectation maximization algorithm with up to 100 iterations of 16 subsets, with and without time-of-flight (TOF) information. Results were evaluated visually and by comparing the I activity relative to the scan performed in the absence of I. I within the FOV added to the randoms rate, to dead time, and to pile-up within the detectors. Using our standard clinical reconstruction parameters, the image quality and quantitative accuracy suffered at I activities above 1.4 GBq. Convergence rates slowed progressively in the presence of increasing amounts of I for both TOF and nonTOF reconstructions. TOF reconstructions converged more quickly than nonTOF but often towards erroneous concentrations. Iterating nonTOF reconstructions to convergence produced quantitatively accurate images except for the off-center phantom at the very highest level of background I tested. This study shows that quantitative PET is feasible in the presence of large amounts of I. The high randoms fractions resulted in slow reconstruction convergence and negatively impacted TOF corrections and/or the accuracy of TOF information. Therefore, increased iterations and nonTOF reconstructions are recommended. This study shows that quantitative PET is feasible in the presence of large amounts of 131I. The high randoms fractions resulted in slow reconstruction convergence and negatively impacted TOF corrections and/or the accuracy of TOF information. Therefore, increased iterations and nonTOF reconstructions are recommended.Osteoporosis is a common form of metabolic bone disease that is costly to treat and is primarily diagnosed on the basis of bone mineral density. As the influences of genetic lesions and environmental factors are increasingly studied in the pathological development of osteoporosis, regulated epigenetics are emerging as the important pathogenesis mechanisms in osteoporosis. Recently, osteoporosis genome-wide association studies and multi-omics technologies have revealed that susceptibility loci and the misregulation of epigenetic modifiers are key factors in osteoporosis. Over the past decade, extensive studies have demonstrated epigenetic mechanisms, such as DNA methylation, histone/chromatin modifications, and non-coding RNAs, as potential contributing factors in osteoporosis that affect disease initiation and progression. Herein, we review recent advances in epigenetics in osteoporosis, with a focus on exploring the underlying mechanisms and potential diagnostic/prognostic biomarker applications for osteoporosis. The gut microbiome plays a protective role in the host defense against pneumonia. The composition of the lung microbiota has been shown to be predictive of clinical outcome in critically ill patients. RGT-018 datasheet However, the dynamics of the lung and gut microbiota composition over time during severe pneumonia remains ill defined. We used a mouse model of pneumonia-derived sepsis caused by Klebsiella pneumoniae in order to follow the pathogen burden as well as the composition of the lung, tongue and fecal microbiota from local infection towards systemic spread. Already at 6h post-inoculation with K. pneumoniae, marked changes in the lung microbiota were seen. The alpha diversity of the lung microbiota did not change throughout the infection, whereas the beta diversity did. A shift between the prominent lung microbi