Project description:To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments.The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing.The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm.The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques that require a data fidelity term based on the matching of DRRs and projections.

Project description:Genomic analysis of the model lignocellulosic biomass degrading bacteria C. phytofermentans indicates that it can degrade, transport, and utilize a wide-range of carbohydrates as possible growth substrates. Previous experiments characterized the expression of the degradation and transport machinery using custom whole genome oligonucleotide microarrays. The results indicate that C. phytofermentans utilizes ATP-binding cassette (ABC) transporters for carbohydrate uptake and does not use the sole phosphoenolpyruvate-phosphotransferase system (PTS) for any of the tested substrates. While some ABC transporters are specific for a single carbohydrate, the expression profiles indicate that others may be capable of transporting multiple substrates. Distinct sets of Carbohydrate Active Enzymes (CAZy) genes were also up-regulated on specific substrates indicative of C. phytofermentans ability to selectively degrade plant biomass. We also identified a highly expressed cluster of genes which includes seven extracellular glycoside hydrolases and two ABC transporters with unknown specificity. These results lead to the hypothesis that when grown on plant biomass, C. phytofermentans is capable of degrading and transporting all major carbohydrate components of the plant cell. To test this, C. phytofermentans was grown on cornstover and switchgrass. Results from this expression data and HPLC analysis indicates that C. phytofermentans is utilizing multiple substrates. with multiple sugar ABC transporter clusters and glycoside hydrolases being expressed. Interestingly all of the transporters were initially identified on disaccharides or oligio-saccharides, and none of the transporters identified as monosaccharide specific transporters were expressed. This could be an indication that C. phytofermentans prefers to transport oligiosacchrides over monosaccharides. The results presented here corroborate the genomic data which indicates the breath of the carbohydrate degradation, transport, and utilization machinery of C. phytofermentans.

Project description:Genomic analysis of the model lignocellulosic biomass degrading bacteria C. phytofermentans indicates that it can degrade, transport, and utilize a wide-range of carbohydrates as possible growth substrates. Previous experiments characterized the expression of the degradation and transport machinery using custom whole genome oligonucleotide microarrays. The results indicate that C. phytofermentans utilizes ATP-binding cassette (ABC) transporters for carbohydrate uptake and does not use the sole phosphoenolpyruvate-phosphotransferase system (PTS) for any of the tested substrates. While some ABC transporters are specific for a single carbohydrate, the expression profiles indicate that others may be capable of transporting multiple substrates. Distinct sets of Carbohydrate Active Enzymes (CAZy) genes were also up-regulated on specific substrates indicative of C. phytofermentans ability to selectively degrade plant biomass. We also identified a highly expressed cluster of genes which includes seven extracellular glycoside hydrolases and two ABC transporters with unknown specificity. These results lead to the hypothesis that when grown on plant biomass, C. phytofermentans is capable of degrading and transporting all major carbohydrate components of the plant cell. To test this, C. phytofermentans was grown on cornstover and switchgrass. Results from this expression data and HPLC analysis indicates that C. phytofermentans is utilizing multiple substrates. with multiple sugar ABC transporter clusters and glycoside hydrolases being expressed. Interestingly all of the transporters were initially identified on disaccharides or oligio-saccharides, and none of the transporters identified as monosaccharide specific transporters were expressed. This could be an indication that C. phytofermentans prefers to transport oligiosacchrides over monosaccharides. The results presented here corroborate the genomic data which indicates the breath of the carbohydrate degradation, transport, and utilization machinery of C. phytofermentans. C. phytofermentans was cultured anaerobically on switchgrass and corn stover to determine specific expression patterns. The data in this series consists three independent RNA preparations from replicate cultures.

Dataset Information

First-principles calculated decomposition pathways for LiBH4 nanoclusters.

Publications

First-principles calculated decomposition pathways for LiBH4 nanoclusters.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets