Automated quantification and evaluation of motion artifact on coronary CT angiography images

Abstract Purpose This study developed and validated a Motion Artifact Quantification algorithm to automatically quantify the severity of motion artifacts on coronary computed tomography angiography (CCTA) images. The algorithm was then used to develop a Motion IQ Decision method to automatically identify whether a CCTA dataset is of sufficient diagnostic image quality or requires further correction. Method The developed Motion Artifact Quantification algorithm includes steps to identify the right coronary artery (RCA) regions of interest (ROIs), segment vessel and shading artifacts, and to calculate the motion artifact score (MAS) metric. The segmentation algorithms were verified against ground‐truth manual segmentations. The segmentation algorithms were also verified by comparing and analyzing the MAS calculated from ground‐truth segmentations and the algorithm‐generated segmentations. The Motion IQ Decision algorithm first identifies slices with unsatisfactory image quality using a MAS threshold. The algorithm then uses an artifact‐length threshold to determine whether the degraded vessel segment is large enough to cause the dataset to be nondiagnostic. An observer study on 30 clinical CCTA datasets was performed to obtain the ground‐truth decisions of whether the datasets were of sufficient image quality. A five‐fold cross‐validation was used to identify the thresholds and to evaluate the Motion IQ Decision algorithm. Results The automated segmentation algorithms in the Motion Artifact Quantification algorithm resulted in Dice coefficients of 0.84 for the segmented vessel regions and 0.75 for the segmented shading artifact regions. The MAS calculated using the automated algorithm was within 10% of the values obtained using ground‐truth segmentations. The MAS threshold and artifact‐length thresholds were determined by the ROC analysis to be 0.6 and 6.25 mm by all folds. The Motion IQ Decision algorithm demonstrated 100% sensitivity, 66.7% ± 27.9% specificity, and a total accuracy of 86.7% ± 12.5% for identifying datasets in which the RCA required correction. The Motion IQ Decision algorithm demonstrated 91.3% sensitivity, 71.4% specificity, and a total accuracy of 86.7% for identifying CCTA datasets that need correction for any of the three main vessels. Conclusion The Motion Artifact Quantification algorithm calculated accurate

Recomendação de estirpes para leguminosas florestais-ano 2009.

O objetivo deste trabalho foi selecionar e recomendar estirpes de bactérias mais eficientes na FBN para espécies leguminosas florestais.bitstream/item/104079/1/Recomendacao-de-estirpe-para-leguminsa-florestal-2009-SERIE-DOC-264.pd

Development of a 2,4-diaminothiazole series for the treatment of human African trypanosomiasis highlights the importance of static-cidal screening of analogues

While treatment options for human African trypanosomiasis (HAT) have improved significantly, there is still a need for new drugs with eradication now a realistic possibility. Here, we report the development of 2,4-diaminothiazoles that demonstrate significant potency against Trypanosoma brucei, the causative agent of HAT. Using phenotypic screening to guide structure-activity relationships, potent drug-like inhibitors were developed. Proof of concept was established in an animal model of the hemolymphatic stage of HAT. To treat the meningoencephalitic stage of infection, compounds were optimized for pharmacokinetic properties, including blood-brain barrier penetration. However, in vivo efficacy was not achieved, in part due to compounds evolving from a cytocidal to a cytostatic mechanism of action. Subsequent studies identified a nonessential kinase involved in the inositol biosynthesis pathway as the molecular target of these cytostatic compounds. These studies highlight the need for cytocidal drugs for the treatment of HAT and the importance of static-cidal screening of analogues

Repositioning of a diaminothiazole series confirmed to target the cyclin-dependent kinase CRK12 for use in the treatment of African animal trypanosomiasis

African animal trypanosomiasis or nagana, caused principally by infection of the protozoan parasites Trypanosoma congolense and Trypanosoma vivax, is a major problem in cattle and other livestocks in sub-Saharan Africa. Current treatments are threatened by the emergence of drug resistance and there is an urgent need for new, effective drugs. Here, we report the repositioning of a compound series initially developed for the treatment of human African trypanosomiasis. A medicinal chemistry program, focused on deriving more soluble analogues, led to development of a lead compound capable of curing cattle infected with both T. congolense and T. vivax via intravenous dosing. Further optimization has the potential to yield a single-dose intramuscular treatment for this disease. Comprehensive mode of action studies revealed that the molecular target of this promising compound and related analogues is the cyclin-dependent kinase CRK12