Dynamic Cone-beam CT Reconstruction using Spatial and Temporal Implicit Neural Representation Learning (STINR)

Objective: Dynamic cone-beam CT (CBCT) imaging is highly desired in image-guided radiation therapy to provide volumetric images with high spatial and temporal resolutions to enable applications including tumor motion tracking/prediction and intra-delivery dose calculation/accumulation. However, the dynamic CBCT reconstruction is a substantially challenging spatiotemporal inverse problem, due to the extremely limited projection sample available for each CBCT reconstruction (one projection for one CBCT volume). Approach: We developed a simultaneous spatial and temporal implicit neural representation (STINR) method for dynamic CBCT reconstruction. STINR mapped the unknown image and the evolution of its motion into spatial and temporal multi-layer perceptrons (MLPs), and iteratively optimized the neuron weighting of the MLPs via acquired projections to represent the dynamic CBCT series. In addition to the MLPs, we also introduced prior knowledge, in form of principal component analysis (PCA)-based patient-specific motion models, to reduce the complexity of the temporal INRs to address the ill-conditioned dynamic CBCT reconstruction problem. We used the extended cardiac torso (XCAT) phantom to simulate different lung motion/anatomy scenarios to evaluate STINR. The scenarios contain motion variations including motion baseline shifts, motion amplitude/frequency variations, and motion non-periodicity. The scenarios also contain inter-scan anatomical variations including tumor shrinkage and tumor position change. Main results: STINR shows consistently higher image reconstruction and motion tracking accuracy than a traditional PCA-based method and a polynomial-fitting based neural representation method. STINR tracks the lung tumor to an averaged center-of-mass error of <2 mm, with corresponding relative errors of reconstructed dynamic CBCTs <10%

Novel phenanthrene-degrading bacteria identified by DNA-stable isotope probing

Microorganisms responsible for the degradation of phenanthrene in a clean forest soil sample were identified by DNA-based stable isotope probing (SIP). The soil was artificially amended with either 12C- or 13C-labeled phenanthrene, and soil DNA was extracted on days 3, 6 and 9. Terminal restriction fragment length polymorphism (TRFLP) results revealed that the fragments of 219- And 241-bp in HaeIII digests were distributed throughout the gradient profile at three different sampling time points, and both fragments were more dominant in the heavy fractions of the samples exposed to the 13C-labeled contaminant. 16S rRNA sequencing of the 13C-enriched fraction suggested that Acidobacterium spp. within the class Acidobacteria, and Collimonas spp. within the class Betaproteobacteria, were directly involved in the uptake and degradation of phenanthrene at different times. To our knowledge, this is the first report that the genus Collimonas has the ability to degrade PAHs. Two PAH-RHDα genes were identified in 13C-labeled DNA. However, isolation of pure cultures indicated that strains of Staphylococcus sp. PHE-3, Pseudomonas sp. PHE- 1, and Pseudomonas sp. PHE-2 in the soil had high phenanthrene-degrading ability. This emphasizes the role of a culture-independent method in the functional understanding of microbial communities in situ

The Role of Mineral Composition on the Frictional and Stability Properties of Powdered Reservoir Rocks

The growing hazard of induced seismicity driven by the boom in unconventional resources exploitation is strongly linked to fault activation. We perform laboratory measurements on simulated fault gouges comprising powdered reservoir rocks from major oil and gas production sites in China, to probe the control of mineral composition on fault friction and stability responses during reservoir stimulation. Double direct shear experiments were conducted on gouges with phyllosilicate content ranging from 0 to 30wt.% and grain sizes <150m, at constant normal stresses of 10-40MPa and conditions of room temperature and water saturation. The velocity step and slide-hold-slide sequences were employed to evaluate frictional stability and static healing, respectively. Results indicate that the mineralogy of the gouges exhibit a strong control on the frictional strength, stability, and healing. Phyllosilicate-rich samples show lower frictional strength and higher values of (a-b), promoting stable sliding. For the gouges studied, the frictional strength decreases monotonically with increasing phyllosilicate content, and a transition from velocity weakening to velocity strengthening behavior is evident at 15wt.% phyllosilicates. Intermediate healing rates are common in gouges with higher content of phyllosilicates, with high healing rates predominantly in phyllosilicate-poor gouges. As an indispensable component in reservoir rocks, the carbonates are shown to affect both the frictional stability and healing response. These findings can have important implications for understanding the effects of mineralogy on fault behavior and induced seismic potential in geoengineering activities, particularly in reservoirs in China.National Natural Science Foundation of China [41672268, 41772286]; U.S. Department of Energy (DOE) [DE-FE0023354]6 month embargo; published online: 5 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attention

Since radiologists have different training and clinical experiences, they may provide various segmentation annotations for a lung nodule. Conventional studies choose a single annotation as the learning target by default, but they waste valuable information of consensus or disagreements ingrained in the multiple annotations. This paper proposes an Uncertainty-Guided Segmentation Network (UGS-Net), which learns the rich visual features from the regions that may cause segmentation uncertainty and contributes to a better segmentation result. With an Uncertainty-Aware Module, this network can provide a Multi-Confidence Mask (MCM), pointing out regions with different segmentation uncertainty levels. Moreover, this paper introduces a Feature-Aware Attention Module to enhance the learning of the nodule boundary and density differences. Experimental results show that our method can predict the nodule regions with different uncertainty levels and achieve superior performance in LIDC-IDRI dataset.Comment: 10 pages, 4 figures, 30 reference

Identification of Benzo[a]pyrene-metabolizing bacteria in forest soils by using DNA-based stable-isotope probing

DNA-based stable-isotope probing (DNA-SIP) was used in this study to investigate the uncultivated bacteria with benzo[a]pyrene (BaP) metabolism capacities in two Chinese forest soils (Mt. Maoer in Heilongjiang Province and Mt. Baicaowa in Hubei Province). We characterized three different phylotypes with responsibility for BaP degradation, none of which were previously reported as BaP-degrading microorganisms by SIP. In Mt. Maoer soil microcosms, the putative BaP degraders were classified as belonging to the genus Terrimonas (family Chitinophagaceae, order Sphingobacteriales), whereas Burkholderia spp. were the key BaP degraders in Mt. Baicaowa soils. The addition of metabolic salicylate significantly increased BaP degradation efficiency in Mt. Maoer soils, and the BaP-metabolizing bacteria shifted to the microorganisms in the family Oxalobacteraceae (genus unclassified). Meanwhile, salicylate addition did not change either BaP degradation or putative BaP degraders in Mt. Baicaowa. Polycyclic aromatic hydrocarbon ring-hydroxylating dioxygenase (PAH-RHD) genes were amplified, sequenced, and quantified in the DNA-SIP (13)C heavy fraction to further confirm the BaP metabolism. By illuminating the microbial diversity and salicylate additive effects on BaP degradation across different soils, the results increased our understanding of BaP natural attenuation and provided a possible approach to enhance the bioremediation of BaP-contaminated soils

A hybrid single-mode laser based on slotted silicon waveguides

An InGaAsP-Si hybrid single-mode laser based on etched slots in silicon waveguides was demonstrated operating at 1543 nm. The InGaAsP gain structure was bonded onto a patterned silicon-on-insulator wafer by selective area metal bonding method. The mode-selection mechanism based on a slotted silicon waveguide was applied, in which the parameters were designed using the simulation tool cavity modeling framework. The III-V lasers employed buried ridge stripe structure. The whole fabrication process only needs standard photolithography and inductively coupled plasma etching technology, which reduces cost for ease in technology transfer. At room temperature, a single mode of 1543-nm wavelength at a threshold current of 21 mA with a maximum output power of 1.9 mW in continuous-wave regime was obtained. The side mode suppression ratio was larger than 35 dB. The simplicity and flexibility of the fabrication process and a low cost make the slotted hybrid laser a promising light source

Bacteria capable of degrading anthracene, phenanthrene, and fluoranthene as revealed by DNA based stable-isotope probing in a forest soil

Information on microorganisms possessing the ability to metabolize different polycyclic aromatic hydrocarbons (PAHs) in complex environments helps in understanding PAHs behavior in natural environment and developing bioremediation strategies. In the present study, stable-isotope probing (SIP) was applied to investigate degraders of PAHs in a forest soil with the addition of individually 13C-labeled phenanthrene, anthracene, and fluoranthene. Three distinct phylotypes were identified as the active phenanthrene-, anthracene- and fluoranthene-degrading bacteria. The putative phenanthrene degraders were classified as belonging to the genus Sphingomona. For anthracene, bacteria of the genus Rhodanobacter were the putative degraders, and in the microcosm amended with fluoranthene, the putative degraders were identified as belonging to the phylum Acidobacteria. Our results from DNA-SIP are the first to directly link Rhodanobacter- and Acidobacteria-related bacteria with anthracene and fluoranthene degradation, respectively. The results also illustrate the specificity and diversity of three- and four-ring PAHs degraders in forest soil, contributes to our understanding on natural PAHs biodegradation processes, and also proves the feasibility and practicality of DNA-based SIP for linking functions with identity especially uncultured microorganisms in complex microbial biota