Methods for measuring fluoroscopic skin dose

This paper briefly reviews available technologies for measuring or estimating patient skin dose in the interventional fluoroscopic environment

Nanoparticles as multimodal photon transducers of ionizing radiation

In biomedical imaging, nanoparticles combined with radionuclides that generate Cerenkov luminescence are used in diagnostic imaging, photon-induced therapies, and as activatable probes. In these applications, the nanoparticle is often viewed as a carrier inert to ionizing radiation from the radionuclide. However, certain phenomena such as enhanced nanoparticle luminescence and generation of reactive oxygen species cannot be explained by only Cerenkov luminescence interactions with nanoparticles. Herein, we report methods to examine the mechanisms of nanoparticle excitation by radionuclides, including interactions with Cerenkov luminescence, β particles, and γ radiation. We demonstrate that β scintillation contributes appreciably to excitation and reactivity in certain nanoparticle systems and that excitation of nanoparticles composed of large atomic number atoms by radionuclides generates X-rays, enabling multiplexed imaging through single photon emission computed tomography. These findings demonstrate practical optical imaging and therapy using radionuclides with emission energies below the Cerenkov threshold, thereby expanding the list of applicable radionuclides

Discovery of blood transcriptomic markers for depression in animal models and pilot validation in subjects with early-onset major depression

Early-onset major depressive disorder (MDD) is a serious and prevalent psychiatric illness in adolescents and young adults. Current treatments are not optimally effective. Biological markers of early-onset MDD could increase diagnostic specificity, but no such biomarker exists. Our innovative approach to biomarker discovery for early-onset MDD combined results from genome-wide transcriptomic profiles in the blood of two animal models of depression, representing the genetic and the environmental, stress-related, etiology of MDD. We carried out unbiased analyses of this combined set of 26 candidate blood transcriptomic markers in a sample of 15–19-year-old subjects with MDD (N=14) and subjects with no disorder (ND, N=14). A panel of 11 blood markers differentiated participants with early-onset MDD from the ND group. Additionally, a separate but partially overlapping panel of 18 transcripts distinguished subjects with MDD with or without comorbid anxiety. Four transcripts, discovered from the chronic stress animal model, correlated with maltreatment scores in youths. These pilot data suggest that our approach can lead to clinically valid diagnostic panels of blood transcripts for early-onset MDD, which could reduce diagnostic heterogeneity in this population and has the potential to advance individualized treatment strategies

Genomic prediction for tuberculosis resistance in dairy cattle

The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates.We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data.These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies