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At least 883 records · Page 49

Predictive value of {sup 18}F-FDG PET/CT in patients with acute type B aortic intramural hematoma

Background: The clinical course and predictors of adverse aortic events (AAE) in patients with acute Stanford type B intramural hematoma (IMH) remain controversial. This study aimed to investigate whether {sup 18}F-FDG PET/CT can predict risk in patients with acute type B IMH. Methods and Results: This study included 34 patients with acute type B IMH who underwent PET/CT within 14 days from the onset of symptoms. The maximal standardized uptake values (SUVmax) of {sup 18}F-FDG uptake was significantly different between patients with or without AAE (4.3 ± 0.6 vs 3.7 ± 1.0, P = 0.020), but not the target to blood ratio (TBR, SUVmax divided by SUV in the superior vena cava) (1.6 ± 0.2 vs 1.5 ± 0.5, P = 0.064). In patients with initial ulcer-like projection (ULP), a blood-filled pouch protruding into the IMH, which was seen in 25 patients(74%), both the SUVmax and TBR were significantly higher in patients who developed AAE, (4.3 ± 0.6 vs 3.3 ± 0.5, P = 0.001; 1.6 ± 0.2 vs 1.4 ± 0.2, P = 0.01); the TBR >1.5, which is determined from receiver-operating-characteristic curve, had a sensitivity of 73% and a specificity of 80% in predicting AAE. Conclusion: Patients with ULP and high {sup 18}F-FDG uptake were more likely to develop AAE and may require closer surveillance with serial imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

My warranty has expired: I need to be retested

The concept of warranty period, the duration of time during which the patient’s risk remains low, is appealing. However, some points remain to be resolved before its translation in the clinical arena. Methodological issues should be standardized in order to compare the results of studies in different patient populations. Also, the definition of a “normal” study should always take into consideration the history of prior revascularization, the achieved level of exercise, and the stressor used. The promise of warranty can be questioned by the patient’s baseline demographic and clinical characteristics and may also be influenced by life-style modification in the course of the follow-up. The “warranty period” concept should shift from data reflecting the time to a cardiac event to the development of ischemia, given an opportunity for intervention before a cardiac event occurs. In this context, clarify the role of serial imaging can be extremely useful, in particular to evaluate if and when retesting a patient after a normal scan.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Nutrition, risk factors, prevention, and imaging: The 2018 Mario Verani Lecture

Heart disease has been the leading cause of death in the United States since 1918. Cardiac mortality rates have dramatically decreased in this era of advanced medical and interventional therapies. However, this has been aptly described as “mopping up the floor instead of turning off the faucet.” With this recognition, prevention in cardiology is poised to become a central focus. Within prevention, dietary intervention is recognized as the single largest opportunity for improved cardiovascular outcomes, including improvement or elimination of cardiac risk factors, prevention of myocardial infarction, stroke and cardiovascular death, and reduction of plaque burden and myocardial ischemia. Cardiac imaging, particularly nuclear perfusion and coronary computed tomographic angiography, plays a critical role in early diagnosis and serial evaluation of myocardial ischemia and coronary artery disease. These techniques have the potential to help refine research protocols and evaluate their success by providing intermediate markers of improved myocardial blood flow and coronary plaque morphology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

High-Throughput Screening for Acid-Stable Oxygen Evolution Electrocatalysts in the (Mn–Co–Ta–Sb)O x Composition Space

Solar generation of fuel is a promising future energy technology, and strong acidic conditions are highly desirable for integrated solar hydrogen generators. In particular, water splitting near pH 0 is attractive due to the availability of high theoretical efficiency, high performance hydrogen evolution catalysts, and robust ion exchange membranes. The lack of a stable, earth-abundant oxygen evolution catalyst inhibits deployment of this technology, and development of such a material is hampered by the strong anti-correlation between electrochemical stability and catalytic activity of non-precious metal oxides. High-throughput screening of mixed metal oxides offers a promising route to the identification of new stable catalysts and requires careful design of experiments to combine the concepts of rapid experimentation and long-term stability. By combining serial and parallel measurement techniques, we have created a high-throughput platform to assess the catalytic activity of material libraries in the as-prepared state and after 2 h of operation. By screening the entire (Mn–Co–Ta–Sb)O x composition space, we observe that the compositions with highest initial activity comprised cobalt and manganese oxides, but combinations with antimony and tantalum offer improved stability. Finally, by combining the desired properties of catalytic activity and stability, the optimal composition regions are readily identified, demonstrating the success and fidelity of this novel high-throughput screening platform.

10 SYNTHETIC FUELS↗

Laser Desorption/Ionization Mass Spectrometric Imaging of Endogenous Lipids from Rat Brain Tissue Implanted with Silver Nanoparticles

Mass spectrometry imaging (MSI) of tissue implanted with silver nanoparticulate (AgNP) matrix generates reproducible imaging of lipids in rodent models of disease and injury. Gas-phase production and acceleration of size-selected 8 nm AgNP is followed by controlled ion beam rastering and soft landing implantation of 500 eV AgNP into tissue. Focused 337 nm laser desorption produces high quality images for most lipid classes in rat brain tissue (in positive mode: galactoceramides, diacylglycerols, ceramides, phosphatidylcholines, cholesteryl ester, and cholesterol, and in negative ion mode: phosphatidylethanolamides, sulfatides, phosphatidylinositol, and sphingomyelins). Image reproducibility in serial sections of brain tissue is achieved within <10% tolerance by selecting argentated instead of alkali cationized ions. The imaging of brain tissues spotted with pure standards was used to demonstrate that Ag cationized ceramide and diacylglycerol ions are from intact, endogenous species. In contrast, almost all Ag cationized fatty acid ions are a result of fragmentations of numerous lipid types having the fatty acid as a subunit. Almost no argentated intact fatty acid ions come from the pure fatty acid standard on tissue. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Overlapping MALDI-Mass Spectrometry Imaging for In-Parallel MS and MS/MS Data Acquisition without Sacrificing Spatial Resolution

Metabolomics experiments require chemical identifications, often through MS/MS analysis. In mass spectrometry imaging (MSI), this necessitates running several serial tissue sections or using a multiplex data acquisition method. We have previously developed a multiplex MSI method to obtain MS and MS/MS data in a single experiment to acquire more chemical information in less data acquisition time. In this method, each raster step is composed of several spiral steps and each spiral step is used for a separate scan event (e.g., MS or MS/MS). One main limitation of this method is the loss of spatial resolution as the number of spiral steps increases, limiting its applicability for high-spatial resolution MSI. In this work, we demonstrate multiplex MS imaging is possible without sacrificing spatial resolution by the use of overlapping spiral steps, instead of spatially separated spiral steps as used in the previous work. Significant amounts of matrix and analytes are still left after multiple spectral acquisitions, especially with nanoparticle matrices, so that high quality MS and MS/MS data can be obtained on virtually the same tissue spot. This method was then applied to visualize metabolites and acquire their MS/MS spectra in maize leaf cross-sections at 10 μm spatial resolution. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization

In this work, we describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and far-field modalities are employed in situ to track evolution of the material orientation and stress–strain fields at six points during the mechanical test, and these data streams are registered with micro-computed tomography reconstructions which probe the material density. This data volume was matched to a multi-modal serial sectioning characterization of the specimen taken after loading, described in this article’s companion. Twenty-eight grains which were monitored throughout the experiment were selected to form the basis for AFRL AM Modeling Series Challenge 4, Microscale Structure-to-Properties.

36 MATERIALS SCIENCE↗

Numerical and experimental investigation of the geometry dependent layer-wise evolution of temperature during laser powder bed fusion of Ti–6Al–4V

Abstract Laser powder bed fusion (L-PBF) is currently the additive manufacturing process with the widest industrial use for metal parts. Yet some hurdles persist on the way to a widespread industrial serial production, with reproducibility of the process and the resulting part properties being a major concern. As the geometry changes, so do the local boundary conditions for heat dissipation. Consequently, the use of global, geometry-independent processing parameters, which are today’s state of the art, may result in varying part properties or even defects. This paper presents a numerical simulation as a method to predict the geometry-dependent temperature evolution during the build. For demonstration, an overhang structure with varying angles towards the build platform was manufactured using Ti–6Al–4V. A calibrated infrared camera was integrated into a commercial L-PBF system to measure the temperature evolution over time for a total build height of 10 mm, and the results are used for validation of the simulation. It is shown that the simulation is capable of predicting the temperature between layers. The deviations between simulation and measurement remain in single digit range for smaller overhang structures (90°, 60° and 45°). For large overhang structures (30°), the simulation tends to over-predict the temperatures up to 15 °C. Experiments with varying process parameters showed the feasibility of energy reduction as compensation of the heat accumulation produced by overhang structures.

Li, Gefei (ORCID:0000000174837952)↗

Effect of stress on Laves phase precipitation in creep ruptured Grade 92 ferritic martensitic steel characterized by a novel accessible method

At high temperature conditions relevant to fossil and nuclear energy plants, Laves phase (Fe 2 X, X=Mo, W) precipitation is observed in common ferritic martensitic (FM) structural steels, with various reported effects on creep behavior. Despite being valuable metrics to correlate with mechanical properties and other precipitate phases, the volume fraction and number density of Laves phase precipitates has been difficult to quantify accurately using common techniques such as transmission electron microscopy (TEM) due to the relatively large size (∼0.25 μm) and low number density (∼10 11 cm −3 ) of Laves precipitates. Here, to address this characterization challenge, we developed and demonstrated a high-throughput and widely accessible method to quantify the volume fraction and number density of the Laves phase based on scanning electron microscope (SEM) images with a backscattered electron signal and the information depth (ID) of backscattered electrons. We applied this new technique in creep ruptured Grade 92 FM steel to study the effect of Laves phase on creep properties and determine the influence of stress on Laves phase precipitation. The quantitative accuracy of the SEM-based volume fraction and number density values was verified using synchrotron high energy X-ray diffraction and serial sectioning tomography. Stress did not significantly affect the Laves phase size or volume fraction during creep testing at 550 – 650°C and stress levels of 90 – 260 MPa (vs. unstressed conditions). Conversely, a moderate but statistically significant stress-enhanced increase in Laves phase number density, corresponding to an increase in nucleation rate, occurred during creep exposure above 110 MPa.

Creep↗

Controls and process planning strategies for 5-axis laser directed energy deposition of Ti-6Al-4V using an 8-axis industrial robot and rotary motion

Interest in multi-axis additive manufacturing has grown significantly in recent years due to associated benefits that range from improved quality to support for greater geometric complexity. A method of 5-axis Laser Hot-Wire Directed Energy Deposition is developed and demonstrated in this study using an 8-axis industrial robot, comprised of a 6-axis serial link robot and a 2 degree-of-freedom positioner. Coordinated 5-axis motion is used to print Ti-6Al-4V objects predominantly through build plate rotation. Methods of slicing and toolpath generation are presented, including the use of an alternating toolpath direction philosophy and the manipulation of the CAD model surface normal vectors for determining the required build plate tilt angles for maintaining consistent deposition orientations relative to gravity. Another objective of the study was to determine the limits of conventional slicing and layer height control techniques for printing geometries with significant unsupported overhangs. A comparison is made between the behavior of normal and conformal bead alignment in this regard, and the performance of the layer height controller is reported as it relates to process stability and the limits of printing overhang geometries. Unsupported overhangs were successfully printed at 35° without build plate tilt and 45° with build plate tilt. Toolpath velocity and net-shape printing performance are reported as well, with 3D scans of the printed surfaces used for net-shape characterization. In all, the printing of three geometries is presented, including the overhang geometry, a 5-axis toolpath geometry, and a large-scale, multi-bead demonstrator part, which exceeded 500 mm in height and weighed 44 kg (97 lbs).

36 MATERIALS SCIENCE↗

Graphics processing unit accelerated phase field dislocation dynamics: Application to bi-metallic interfaces

We present the first high-performance computing implementation of the meso-scale phase field dislocation dynamics (PFDD) model on a graphics processing unit (GPU)-based platform. The implementation takes advantage of the portable OpenACC standard directive pragmas along with Nvidia's compute unified device architecture (CUDA) fast Fourier transform (FFT) library called CUFFT to execute the FFT computations within the PFDD formulation on the same GPU platform. The overall implementation is termed ACCPFDD-CUFFT. The package is entirely performance portable due to the use of OPENACC-CUDA inter-operability, in which calls to CUDA functions are replaced with the OPENACC data regions for a host central processing unit (CPU) and device (GPU). A comprehensive benchmark study has been conducted, which compares a number of FFT routines, the Numerical Recipes FFT (FOURN), Fastest Fourier Transform in the West (FFTW), and the CUFFT. The last one exploits the advantages of the GPU hardware for FFT calculations. The novel ACCPFDD-CUFFT implementation is verified using the analytical solutions for the stress field around an infinite edge dislocation and subsequently applied to simulate the interaction and motion of dislocations through a bi-phase copper-nickel (Cu–Ni) interface. It is demonstrated that the ACCPFDD-CUFFT implementation on a single TESLA K80 GPU offers a 27.6X speedup relative to the serial version and a 5X speedup relative to the 22-multicore Intel Xeon CPU E5-2699 v4 @ 2.20 GHz version of the code.

97 MATHEMATICS AND COMPUTING↗

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗

Mouse models of Ebola virus tolerance and lethality: characterization of CD-1 mice infected with wild-type, guinea pig-adapted, or mouse-adapted virus

Development of lethal models of Ebola virus disease has been achieved by the serial passage of virus isolates from human cases in mice and guinea pigs. Use of mice infected with non-adapted virus has been limited due to the absence of overt clinical disease. In recent years, newly recognized sequelae identified in human cases has highlighted the importance of continued investigations of non-lethal infection both in humans and animal models. Here, we revisit the use of rodent-adapted and non-adapted Ebola virus (EBOV) in mice to investigate infection tolerance and future utility of these models in pathogenesis and therapeutic intervention studies. We found that like non-adapted wild-type EBOV, guinea pig-adapted EBOV resulted in widespread tissue infection, variably associated with tissue pathology, and alterations in clinical and immunological analytes in the absence of overt disease. Notably, infection with either non-lethal variant did not greatly differ from lethal mouse-adapted EBOV until near the time end-point criteria are reached in these mice. Furthermore, these data support future investigations of pathogenesis, convalescence, and sequelae in mouse models of virus tolerance.

60 APPLIED LIFE SCIENCES↗

Impact of Grain Size on Performance Degradation of TREAT LEU

We argue that radiation damage induced degradation of thermal conductivity does not set a lower limit on fuel grain sizes for the low enriched uranium fuel design of the Transient Reactor Test Facility (TREAT). Earlier work reports that smaller grains cause a larger degradation of thermal conductivity than larger grains constraining the smallest feasible size of fuel grains. This work assesses TREAT’s transient performance in the presence of radiation damage. The difference between the two studies is in treating damaged and fresh graphite as serial (this work) or parallel (previous) heat resistors. We use a multiphysics model of TREAT fuel grains to compute the reduction in transient capability measured by the total deposited energy as a function of irradiation dose. We find that radiation damage has a negligible effect on energy deposition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗

Identification of target genes of synovial sarcoma-associated fusion oncoprotein using human pluripotent stem cells

Highlights: ► We tried to identify targets of synovial sarcoma (SS)-associated SYT–SSX fusion gene. ► We established pluripotent stem cell (PSC) lines with inducible SYT–SSX gene. ► SYT–SSX responsive genes were identified by the induction of SYT–SSX in PSC. ► SS-related genes were selected from database by in silico analyses. ► 51 genes were finally identified among SS-related genes as targets of SYT–SSX in PSC. -- Abstract: Synovial sarcoma (SS) is a malignant soft tissue tumor harboring chromosomal translocation t(X; 18)(p11.2; q11.2), which produces SS-specific fusion gene, SYT–SSX. Although precise function of SYT–SSX remains to be investigated, accumulating evidences suggest its role in gene regulation via epigenetic mechanisms, and the product of SYT–SSX target genes may serve as biomarkers of SS. Lack of knowledge about the cell-of-origin of SS, however, has placed obstacle in the way of target identification. Here we report a novel approach to identify SYT–SSX2 target genes using human pluripotent stem cells (hPSCs) containing a doxycycline-inducible SYT–SSX2 gene. SYT–SSX2 was efficiently induced both at mRNA and protein levels within three hours after doxycycline administration, while no morphological change of hPSCs was observed until 24 h. Serial microarray analyses identified genes of which the expression level changed more than twofold within 24 h. Surprisingly, the majority (297/312, 95.2%) were up-regulated genes and a result inconsistent with the current concept of SYT–SSX as a transcriptional repressor. Comparing these genes with SS-related genes which were selected by a series of in silico analyses, 49 and 2 genes were finally identified as candidates of up- and down-regulated target of SYT–SSX, respectively. Association of these genes with SYT–SSX in SS cells was confirmed by knockdown experiments. Expression profiles of SS-related genes in hPSCs and human mesenchymal stem cells (hMSCs) were strikingly different in response to the induction of SYT–SSX, and more than half of SYT–SSX target genes in hPSCs were not induced in hMSCs. These results suggest the importance of cellular context for correct understanding of SYT–SSX function, and demonstrated how our new system will help to overcome this issue.

60 APPLIED LIFE SCIENCES↗

Thyroid hormone receptor inhibits hepatoma cell migration through transcriptional activation of Dickkopf 4

Highlights: •T{sub 3} affects DKK4 mRNA and protein expression in HepG2-TR cells. •Regulation of DKK4 by T{sub 3} is at transcriptional level. •DKK4 overexpression suppresses hepatoma cell metastasis. -- Abstract: Triiodothyronine (T{sub 3}) is a potent form of thyroid hormone mediates several physiological processes including cellular growth, development, and differentiation via binding to the nuclear thyroid hormone receptor (TR). Recent studies have demonstrated critical roles of T{sub 3}/TR in tumor progression. Moreover, long-term hypothyroidism appears to be associated with the incidence of human hepatocellular carcinoma (HCC), independent of other major HCC risk factors. Dickkopf (DKK) 4, a secreted protein that antagonizes the canonical Wnt signaling pathway, is induced by T{sub 3} at both mRNA and protein levels in HCC cell lines. However, the mechanism underlying T{sub 3}-mediated regulation of DKK4 remains unknown. In the present study, the 5′ promoter region of DKK4 was serially deleted, and the reporter assay performed to localize the T{sub 3} response element (TRE). Consequently, we identified an atypical direct repeat TRE between nucleotides −1645 and −1629 conferring T{sub 3} responsiveness to the DKK4 gene. This region was further validated using chromatin immunoprecipitation (ChIP) and electrophoretic mobility shift assay (EMSA). Stable DKK4 overexpression in SK-Hep-1 cells suppressed cell invasion and metastatic potential, both in vivo andin vitro, via reduction of matrix metalloproteinase-2 (MMP-2) expression. Our findings collectively suggest that DKK4 upregulated by T{sub 3}/TR antagonizes the Wnt signal pathway to suppress tumor cell progression, thus providing new insights into the molecular mechanism underlying thyroid hormone activity in HCC.

60 APPLIED LIFE SCIENCES↗