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Theranostics is a field of nuclear medicine which uses the same targeting vector and chelating system for both a diagnostic and therapeutic radionuclide, allowing for uniformity in imaging and treatment.
Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper, we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture the thermodynamic, dynamic, and steric challenges typically faced by self-assembly processes, including competition between multiple partially completed structures. Self-assembly pathways are extracted from the simulation trajectories by a fully extendable scheme for identifying structural fragments, which are then assembled into history diagrams for successfully completed target structures. For the simple target, a one-component assembly scheme is most efficient and robust overall, but hierarchical and addressable strategies can have an advantage under some conditions if high yield is a priority.
Motivated by the significant biological functions of polysulfides in life processes and important applications of sodium polysulfides in battery sciences, herein we report a joint experimental and computational study on the electronic and geometric structures of a series of NaSn- (n = 5-9) clusters. The cryogenic, size-selective, negative ion photoelectron spectroscopy (NIPES) is employed to obtain their photoelectron spectra, in which distinctive spectral features with electron binding energy (EBE) up to 6.4 eV are unraveled. The EBE of the first peak in each spectrum for NaSn- (n =5-9), assigned to the transition from the ground state of anion to the ground state of each neutral radical, is observed to increase with cluster size. The vertical detachment energies (VDEs), determined from the first peak maximum, are 3.43 ± 0.02, 3.57 ± 0.02, 3.82 ± 0.03, 3.86 ± 0.02, and 4.00 ± 0.02 eV and the adiabatic detachment energies (ADEs), determined by the onset of the first peak, are 3.27 ± 0.05, 3.44 ± 0.05, 3.65 ± 0.05, 3.75 ± 0.05, and 3.93 ± 0.05 eV, for n = 5-9, respectively. A plural of low-lying isomers of anions are screened and identified with density functional theory calculations, showing that all featuring preference for a chain-like polysulfide moiety electrostatically interacted with a sodium cation. The calculated VDEs and ADEs using the high-level CCSD(T)/aug-cc-pVTZ method are in excellent agreement with experimental results, further confirming the identified isomers as most stable ones. Further analyses based on the excited-state transition, molecular orbitals and natural population charge are performed to assign all observed spectral bands along the binding energy axis, suggesting that the electron detachment process and observed excitations mainly derived from the polysulfide chain of NaSn- clusters. This work provides a fundamental understanding of the intrinsic molecular properties of sodium polysulfide systems, which widely exist in life science and sodium-sulfur cells.
CHESS, chopper spectrometer examining small samples, is a planned direct geometry neutron chopper spectrometer designed to detect and analyze weak signals intrinsic to small cross sections (e.g., small mass, small magnetic moments, or neutron absorbing materials) in powders, liquids, and crystals. CHESS is optimized to enable transformative investigations of quantum materials, spin liquids, thermoelectrics, battery materials, and liquids. The broad dynamic range of the instrument is also well suited to study relaxation processes and excitations in soft and biological matter. The 15 Hz repetition rate of the Second Target Station at the Spallation Neutron Source enables the use of multiple incident energies within a single source pulse, greatly expanding the information gained in a single measurement. Furthermore, the high flux grants an enhanced capability for polarization analysis. This enables the separation of nuclear from magnetic scattering or coherent from incoherent scattering in hydrogenous materials over a large range of energy and momentum transfer. This paper presents optimizations and technical solutions to address the key requirements envisioned in the science case and the anticipated uses of this instrument.
The past decade has witnessed the emergence of a new X-ray light source technology that has been under development for some decades: the so-called self-amplified spontaneous emission-based free-electron laser (FEL). Furthermore, such lasers provide pulses with durations from just below 1 fs (10 –15 s) to over 100 fs and with energies from a few microjoules to a few millijoules, permitting the study of, for example, nonlinear optical effects (1), ultrafast processes (2), coherent diffractive imaging of biological systems such as protein crystals (3, 4), and mimivirus (5). After the opening of the first extreme-UV to soft X-ray user facility, namely FLASH in the Deutsches Elektronen-Synchrotron at Hamburg, Germany (6), a number of other machines covering the extreme-UV (FERMI FEL-1, DALIAN), soft X-ray (FERMI FEL-2, FLASH1/FLASH2), and hard X-ray spectral ranges (LCLS, PAL-XFEL, SACLA, and XFEL) have been opened to users from a wide range of scientific and engineering disciplines.
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Phenylpropanoid biosynthesis in plants engenders myriad phenolics with diverse biological functions. Phenylalanine ammonia-lyase (PAL) is the first committed enzyme in the pathway, directing primary metabolic flux into a phenylpropanoid branch. Previously, we demonstrated that the Arabidopsis Kelch-domain containing F-box proteins, AtKFB01, -20, and -50, function as the negative regulators controlling phenylpropanoid biosynthesis via mediating PAL’s ubiquitination and subsequent degradation. Here, we reveal that Arabidopsis KFB39, a close homolog of AtKFB50, also interacts physically with PAL isozymes and modulates PALs' stability and activity. Disturbing the expression of KFB39 reciprocally affects the accumulation/deposition of a set of phenylpropanoid end products, suggesting that KFB39 is an additional post-translational regulator responsible for the turnover of PAL and negatively controlling phenylpropanoid biosynthesis. Furthermore, we discover that exposure of Arabidopsis to UV-B radiation suppresses the expression of all four KFB genes while inducing the transcription of PAL isogenes; these data suggest that Arabidopsis consolidates both transcriptional and post-translational regulation mechanisms to maximize its responses to UV stress. Simultaneous down-regulation of all four identified KFBs significantly enhances the production of (poly)phenols and the plant’s tolerance to UV irradiation. This study offers a biotechnological approach for engineering the production of useful phenolic chemicals and for increasing a plant’s resistance to environmental stress.
Here, an analysis is performed of how uncorrected antisymmetric aberrations, such as coma and trefoil, affect cryo-EM single-particle reconstruction (SPR) results, and an analytical formula quantifying information loss owing to their presence is inferred that explains why Fourier-shell coefficient-based statistics may report significantly overestimated resolution if these aberrations are not fully corrected. The analysis is validated with reference-based aberration refinement for two cryo-EM SPR data sets acquired with a 200 kV microscope in the presence of coma exceeding 40 µm, and 2.3 and 2.7 Å reconstructions for 144 and 173 kDa particles, respectively, were obtained. The results provide a description of an efficient approach for assessing information loss in cryo-EM SPR data acquired in the presence of higher order aberrations, and address inconsistent guidelines regarding the level of aberrations that is acceptable in cryo-EM SPR experiments.
Cryo-electron microscopy (cryo-EM) is a Nobel Prize-winning technique for deter-mining high-resolution 3D structures of biological macromolecules. A 3D structure is reconstructed from hundreds of thousands of noisy 2D projection images. However, existing 3D reconstruction methods are still time-consuming, and one of the major computational bottlenecks is to recover the unknown orientation of the particle in16each 2D image. The dominant methods typically exploit expensive global search on each image to estimate the missing orientations. Here, a novel end-to-end supervised learning method is introduced to directly recover the missing orientations from 2D cryo-EM images. A neural network is used to approximate the mapping from images to orientations. Furthermore, a robust loss function is proposed for optimizing the parameters of the network, which can handle both asymmetric and symmetric 3D structures. Experiments on synthetic datasets with various symmetry types confirm that the neural network is capable of recovering orientations from 2D cryo-EM images, and the results on one real cryo-EM dataset further demonstrate its potential in more challenging imaging conditions.
In plants, the process of state transition regulates the allocation of sunlight energy between Photosystem II (PSII) and PSI. However, the implications of state transitions for harmonizing electron transport rates between photosystems, and a full quantitative picture of this process, remain underexplored. We integrated quantitative biology (biochemical and biophysical approaches) with in vivo spectroscopy on wild-type Arabidopsis and protein phosphorylation mutants. This combination facilitated monitoring of Chl redistribution and its functional implications for light harvesting and electron transport. Our findings demonstrate the reallocation of 12% of highly phosphorylated ‘extra’ light-harvesting complex II under state 2 from stacked to unstacked thylakoids. This reduces the number of Chls per PSII from 216 to 182, while increasing the number in PSI from 187 to 223. Such Chl redistribution compensates for differences in photosystem stoichiometry and photochemical quantum efficiencies, thereby precisely synchronizing electron transport rates in both photosystems. Mutant analyses corroborate that this regulatory mechanism involves reversible phosphorylation. We inferred that state transitions optimize linear electron transport, leaving no additional capacity for cyclic electron transport. Furthermore, the results suggest that the controversies about long-range migration of LHCII from stacked to unstacked thylakoid domains arise from differences in phosphorylation levels.
Purpose: To demonstrate fast and accurate Monte Carlo (MC) calculations of proton dose-averaged linear energy transfer (LETd) and biological dose (BD) on a Graphics Processing Unit (GPU) card. Methods: A previously validated GPU-based MC simulation of proton transport was used to rapidly generate LETd distributions for proton treatment plans. Since this MC handles proton-nuclei interactions on an event-by-event using a Bertini intranuclear cascade-evaporation model, secondary protons were taken into account. The smaller contributions of secondary neutrons and recoil nuclei were ignored. Recent work has shown that LETd values are sensitive to the scoring method. The GPU-based LETd calculations were verified by comparing with a TOPAS custom scorer that uses tabulated stopping powers, following recommendations by other authors. Comparisons were made for prostate and head-and-neck patients. A python script is used to convert the MC-generated LETd distributions to BD using a variety of published linear quadratic models, and to export the BD in DICOM format for subsequent evaluation. Results: Very good agreement is obtained between TOPAS and our GPU MC. Given a complex head-and-neck plan with 1 mm voxel spacing, the physical dose, LETd and BD calculations for 10{sup 8} proton histories can be completed in ∼5 minutes using a NVIDIA Titan X card. The rapid turnover means that MC feedback can be obtained on dosimetric plan accuracy as well as BD hotspot locations, particularly in regards to their proximity to critical structures. In our institution the GPU MC-generated dose, LETd and BD maps are used to assess plan quality for all patients undergoing treatment. Conclusion: Fast and accurate MC-based LETd calculations can be performed on the GPU. The resulting BD maps provide valuable feedback during treatment plan review. Partially funded by Varian Medical Systems.
Purpose: New advances in radiation therapy are most likely to come from the complex interface of physics, chemistry and biology. Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can thus help bridge the gap between physics and biology. The aim of TOPAS-nBio is to provide a comprehensive tool to generate advanced radiobiology simulations. Methods: TOPAS wraps and extends the Geant4 Monte Carlo (MC) simulation toolkit. TOPAS-nBio is an extension to TOPAS which utilizes the physics processes in Geant4-DNA to model biological damage from very low energy secondary electrons. Specialized cell, organelle and molecular geometries were designed for the toolkit. Results: TOPAS-nBio gives the user the capability of simulating biological geometries, ranging from the micron-scale (e.g. cells and organelles) to complex nano-scale geometries (e.g. DNA and proteins). The user interacts with TOPAS-nBio through easy-to-use input parameter files. For example, in a simple cell simulation the user can specify the cell type and size as well as the type, number and size of included organelles. For more detailed nuclear simulations, the user can specify chromosome territories containing chromatin fiber loops, the later comprised of nucleosomes on a double helix. The chromatin fibers can be arranged in simple rigid geometries or within factual globules, mimicking realistic chromosome territories. TOPAS-nBio also provides users with the capability of reading protein data bank 3D structural files to simulate radiation damage to proteins or nucleic acids e.g. histones or RNA. TOPAS-nBio has been validated by comparing results to other track structure simulation software and published experimental measurements. Conclusion: TOPAS-nBio provides users with a comprehensive MC simulation tool for radiobiological simulations, giving users without advanced programming skills the ability to design and run complex simulations.
The Office of Radiological Security (ORS) within the U.S. DOE’s National Nuclear Security Administration (NNSA) is charged to “work with government, law enforcement, and businesses across the globe to protect radioactive sources used for medical, research, and commercial purposes; remove and dispose of disused radioactive sources; and reduce the global reliance on high activity radioactive sources through the promotion of viable non-radioisotopic alternative technologies.” In this effort, the NNSA/ORS, along with the Office of Defense Nuclear Nonproliferation R&D, has been working with government and private entities that utilize gamma-ray irradiators in areas that include blood irradiation, radiotherapy, biology research, well logging, and radiation processing to consider alternative technologies that do not depend upon radioactive materials. In the medical device industry, nearly 50% of products are sterilized with ethylene oxide, 40.5% with cobalt-60 gamma-rays, 4.5% with electron-beam (e-beam), and <1% with X-ray.(1,2) The cobalt-60 irradiation facilities use an estimated 150 MCi of isotope to sterilize approximately 200 million cubic feet of product annually.(3) Due to growing safety regulations governing cobalt-60 use, continued advancements in e-beam and X-ray accelerator technology, and the greater irradiation durations and costs for cobalt-60 irradiation compared to e-beam and X-ray, switching to these non-radionuclide modalities is increasingly economically competitive. However, this breakdown of 40.5% cobalt-60 and 5.5% accelerator for product sterilization illustrates the difficulty that market forces and industry players have had in overcoming barriers in transitioning to non-nuclide alternatives. Besides those associated with construction of new e-beam and X-ray facilities, significant financial and regulatory obstacles are also associated with the irradiation and comprehensive testing of product constituent polymers and elastomers. The standards associated with product material performance testing are the Association for the Advancement of Medical Instrumentation (AAMI) Technical Information Report 17 (TIR 17), and its referenced American Society for Testing and Materials (ASTM) polymer testing standards. In the study now underway, and the subject of this article, the NNSA/ORS provided R&D funding to the Pacific Northwest National Laboratory (PNNL) in partnership with university researchers, leading medical product manufacturers, accelerator manufacturers, and contract sterilizers. The resulting Team Nablo (in memory of Sam Nablo) includes individuals representing PNNL, Becton Dickinson (BD), Johnson & Johnson, Stryker, Texas A&M University (TAMU), Steri-Tek, Mevex, Ion Beam Applications (IBA), and Sterigenics. The goals of this study are to 1) Identify specific polymer and/or elastomer-based medical products that are currently sterilized with gamma-rays, and for which there are data gaps and would be of greatest industry impact, 2) Work with relevant ASTM subcommittees for guidance and for potential standard revision, 3) Work with an appropriate Food & Drug Administration (FDA) office for potential collaboration on a guidance document for device manufacturers, 4) Measure the physical effects that product materials exhibit when they are given sterilization-level radiation doses from cobalt-60, e-beam or X-ray, and determine whether these effects would preclude the use of e-beam or X-ray for sterilization, 5) Communicate the resulting scientific datasets and findings via industry conferences, peer-reviewed journals, and relevant trade magazines, and 6) Post the resulting datasets on a publicly accessible website, which can be built on in future years. The end objective is to identify technical barriers preventing the adoption of X-ray and e-beam technologies, and share the results to encourage X-ray and e-beam adoption where feasible.
This grant supported work in the Tokmakoff lab at the University of Chicago aimed at understanding the fundamental properties of water at a molecular level, and how water participates in proton transport in aqueous media. The physical properties of water and aqueous solutions are inextricably linked with efforts to develop new sustainable energy sources. Energy conversion, storage, and transduction processes, particularly those that occur in biology and soft matter, make use of water for the purpose of storing and moving charge. Water’s unique physical and chemical properties depend on the ability of water molecules to participate in up to four hydrogen bonds, and the rapid fluctuations and ultrafast energy dissipation of its hydrogenbonded networks. Our work during the grant period led to advances in four areas: (1) the generation of short pulses of broadband infrared light (BBIR) for use in time-resolved twodimensional spectroscopy (2D IR), (2) the investigation of the spectroscopy and transport of excess protons in water, (3) the study of aqueous hydroxide to describe the interaction of the ion and water and the dynamics of proton transfer, and (4) the coupled motion of water and its hydrogen-bonding solutes.
A proof-of-concept tool, the Produced Water-Economic, Socio, Environmental Simulation model (PW-ESESim), was developed to support ease of analysis. The tool was designed to facilitate head-to-head comparison of alternative produced water source, treatment, and reuse water management strategies. A graphical user interface (GUI) guides the user through the selection and design of alternative produced water treatment and reuse strategies and the associated health and safety risk and economic benefits. At the highest conceptual level, alternative water strategies include the selection of a source water (locally or regionally available produced water), treatment strategy (pre-treatment, physical, chemical, biological, desalination, and post-treatment processes) and product water purpose (e.g., irrigation, industrial processing, environmental). After selection of these details, the PW-ESESim output a number of key economic, societal, environmental, public/ecological health and safety metrics to support user decision-making; specific examples include, cost of treatment, improvements in freshwater availability, human and ecologic health impacts and growth in local jobs and the economy. Through the simulation of different produced water treatment and management strategies, tradeoffs are identified and used to inform fit-for-purpose produced water treatment and reuse management decisions. While the tool was initially designed using Southeastern New Mexico (Permian Basin) as a case study, the general design of the PW-ESESim model can be extended to support other oil and gas regions of the U.S.
Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.
CHESS is a direct geometry neutron spectrometer designed to detect and analyze weak signals intrinsic to small cross-sections (e.g., small mass, small magnetic moments or neutron absorbing materials). This instrument is optimized to enable unprecedented characterization of quantum materials, spin liquids, thermoelectric and battery materials, liquids, and soft matter. The ability to simultaneously measure dynamic processes over a wide energy range for very small samples will make CHESS the spectrometer of choice for the initial exploration of new materials. The broad dynamic range will also be well matched to measurements of relaxation processes and excitations in soft and biological matter. The 15 Hz repetition rate of STS enables use of multiple incident energies within a single source pulse, greatly expanding the information gained in a single experiment. An essential feature of CHESS is the capability for polarization analysis to separate nuclear from magnetic scattering or coherent from incoherent scattering in hydrogenous materials, and better understanding spin-anisotropic correlations. This instrument will employ advanced sample environments such as high-pressure cells, dilution refrigerators, high field cryo-magnets and polarization devices, as well as combinations of these, to solve problems at the forefront of materials research. CHESS will be one of the flagship spectrometers of the Second Target Station (STS), providing world leading capabilities.
Dunaliella salina and Dunaliella tertiolecta are extremophile, marine algae that can survive in very low Fe conditions. In this study, we used TMT-proteomics to compare the Fe starvation responses to the Fe replete responses. Samples were digested with trypsin, labeled with TMT 10-Plex, then analyzed by LC-MS/MS. Data was searched with MS-GF+ using PNNL's DMS Processing pipeline.