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At least 1,711 records · Page 95

Radiobiology, Omics and Microdosimetry of Systemic and Targeted Radiotherapeutics Workshop

The Radiobiology, Omics and Microdosimetry of Systemic and Targeted Radiotherapeutics Workshop fostered engagement across disciplines on critical topics that impact the development of targeted radionuclide therapies, bringing together scientific and medical professionals actively involved in radiotherapeutic design, optimization testing, patient treatment, and clinical trials along with basic science researchers, whose novel techniques have the potential to further our understanding of targeted radionuclide therapy. Discussion of the applications of radiotherapeutics to pediatric and adult, brain, prostate and blood cancers, and metastatic disease allowed scientific research to be presented in the context of real-world medical applications and provided an important backdrop to the basic research performed in computers, laboratories, and animal facilities. The workshop format, presentations, and panel discussions were designed to consider a holistic approach to the development of systemic and targeted radiotherapies, integrating radiobiology and microdosimetry, biological assessments on the microscale, and physiologically relevant models of tumor and tissue microenvironments. Important needs highlighted in the workshop include better models to assess the biological effects of radionuclide therapy, novel strategies to target radiotherapeutics to disease sites with high specificity, and new dosimetry techniques that address the importance of tumor microenvironments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

225 Ac/ 213 Bi Generator Based on Millifluidics Controlled Electrodeposition

Radioisotopes provide both diagnostic tools and therapeutic treatments for cancer and other diseases. In the US, millions of radioisotope doses are given to patients per year. Radiopharmaceutical generators are widely used to provide such short-lived medical radioisotopes in a clinical setting. These generators work by exploiting chemical differences in a parent/daughter isotope relationship. Actinium-225 (half-life 10 d) is used to provide clinically useful amounts of daughter isotopes 213 Bi (46 m). An integrated millifluidic 225 Ac/ 213 Bi radiopharmaceutical generator device was engineered to produce 213 Bi labeled biomolecules. Using recent LANL successes in additive manufacturing of small-scale fluidic devices, a disposable device was developed that integrates three steps for the production of 213 Bi labeled antibodies: 1) 213 Bi separation from 225 Ac parent, 2) 213 Bi antibody labeling, and 3) purification of the labelled antibody.

213Bi↗

Non-Equilibrium Plasma Interactions with Biomaterials, Biological Solutions and Tissues

Cold atmospheric pressure plasma discharges offer an abundant source of reactive oxygen and nitrogen species (RONS) at room temperature enabling unique interactions with biomaterials, biological solutions and tissues. These interactions particularly with living matter are presently an important intellectual frontier in plasma science with promising potential applications ranging from human health care to advanced biomaterial processing. Exciting case studies have been reported that illustrate the huge potential of cold atmospheric plasma technology in wound healing and cancer treatment. The interaction of plasma with conducting and dielectric biomaterials such as tissue strongly influences the plasma properties. In turn this changes the impact of the plasma on the biomaterial. Particularly in the case of living matter, liquid based solutions are ubiquitous which complicates interfacial processes. The lack of insight into the underlying mechanisms of the interaction of plasma with wounds and tumors is currently a bottleneck for the further development of the technology and gives rise to many interesting scientific questions. This project was focused on plasma properties and kinetics during plasma-biomaterial interactions. Both DC pulsed and RF driven atmospheric pressure plasma jets, extensively used by the plasma community were studied. The bio-interfaces included hydrogel as a tissue model, (saline) solutions, bacteria and virus. Plasma diagnostics used include Thomson scattering, Rayleigh scattering, Raman scattering, (two-photon absorption) laser induced fluorescence, optical emission spectroscopy, absorption spectroscopy, molecular beam mass spectrometry and fast imaging allowing to determine electron densities and temperatures, ionic species, reactive species including radicals, gas temperatures, gas composition, electric fields and solution components transferred to the gas phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Prototyping a self-learning digital twin platform for personalized treatment in melanoma patients (Final Report)

We completed all the Milestones and disseminated results at the 2021 Computational Approaches for Cancer Workshop (CAFCW21) at the SuperComputing21 conference. As part of Milestone 1, we developed and implemented a prototype digital twin of metastatic melanoma patients, performed quality checks on the code and released it as open source. The work has directly driven major grant proposals by the team on computational digital twins and supporting software infrastructure, including a successful fellowship application by the PI. Work was lead by Paul Macklin (Contact PI, Indiana University), in collaboration with Ilya Shmulevich (PI, Institute for Systems Biology), Tina Hernandez-Boussard (PI, Stanford Univ.), Jeffrey Bryan (Co-I, University of Missouri), Snigdhansu Chatterjee (Co-I, University of Minnesota), and Mohammad Fallahi-Sichani (Co-I, U. of Virginia). Postdoctoral student Heber L. Rocha (Macklin lab, IU) performed intensive computational work, in collaboration with Senior Research Scientist Boris Aguilar (Shmulevich lab, ISB).

59 BASIC BIOLOGICAL SCIENCES↗

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Enhancing Radionuclide Production Capabilities at the Duke University Medical Center Cyclotron with a Focus on Astatine-211

Radionuclides play an important role in a diverse array of fields including physics, chemistry, agriculture, materials science, national security, medical research and patient care. Establishing a reliable domestic supply of key radionuclides is critical to our national competitiveness in these areas. Regarding medical applications, targeted alpha-particle therapy (TAT) has become of great interest to basic researchers and clinicians alike and is emerging as a valuable and cost-effective approach for cancer treatment. Unfortunately, progress in TAT, particularly with regard to its clinical translation, has been severely hampered by the limited availability of the most promising radionuclides at a reasonable cost, and with appropriate chemical and radiochemical purity. In this project, we have attempted to address this problem by focusing on production of the 7.2-h half-life α-particle emitter, 211 At, which has long been considered to be one of the most promising radionuclides for TAT. We note that he critical importance of improving the supply of 211 At in the United States was noted in the Funding Opportunity Announcement related to this project. At Duke University, we have a CS-30 cyclotron that is one of the few accelerators in the United States that has an alpha-particle beam that has enough energy to make useful quantities of 211 At. With this cyclotron, we have been able to produce more 211 At than anywhere else in the world because of our unique internal cyclotron target system. However, the CS-30 cyclotron is nearly 40 years old and was no longer reliable. In addition, its operation required considerable skill, largely because it had analog control systems, and vital parts including old-fashioned power supplies, were becoming unavailable. For these reasons, the current project was undertaken to evaluate all the subsystems of the CS-30 cyclotron and replace, repair, and update them. With help from our consultant, Ionetix, this has now been accomplished. We believe that because of this work, the CS-30 can reliably supply 211 At for basic research and clinical trials both at Duke and beyond.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Cleaner Cooking: Exploring Tools to Measure and Understand the Long-term Adoption and Environmental Significance of Cookstoves in India

About 40% of the world’s population, or roughly 3 billion people, rely on solid biomass fuels like coal, wood, dung, and crop residues to cook and meet their household energy needs. This outdated energy system has severe social, health, and environmental implications. Women are disproportionately affected as they predominantly bear the burden of cooking and collecting fuelwood, which exacerbates the “time poverty” trap that restricts them from participating in economic and educational activities. Exposure to indoor solid fuel combustion, also known as household air pollution, is responsible for 3-4 million premature deaths per year and is a leading risk factor for chronic obstructive pulmonary disease, childhood pneumonia, stroke, ischemic heart disease, and lung cancer. Solid-fuel cooking contributes to 16% of global ambient air pollution, emitting CO 2 and other climate-forcing pollutants like carbon monoxide, black carbon, and methane.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Defining Lipidomic Responses to Coronavirus Infection

Highly pathogenic human coronavirus infection can cause a severe atypical, rapid onset pneumonia with a mortality rate of up to 10% for severe acute respiratory syndrome coronavirus 1 (SARS-CoV 1), 35% for Middle East respiratory syndrome coronavirus (MERS-CoV), or 1% for severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2 causative agent of COVID 19). While medical countermeasures successfully controlled the worldwide SARS-CoV epidemic, the MERS-CoV epidemic is still ongoing and continues to be a concern for travelers in the Middle East and the multi-year SARS-CoV 2 pandemic underscore the importance of defining biomarkers that are diagnostic and/or predictive of severe disease outcomes for respiratory viruses. Systems biology approaches provide global snapshots of infection induced changes in host cells/tissues and provide extremely rich datasets for understanding host pathogen interactions. Metabolites, especially lipids, are critical for viral replication but less is understood about infection induced changes to lipids due to limits in lipid species detection and identification. To characterize how individual lipid species and proteins with lipid associated functions contribute to highly pathogenic human coronavirus replication and disease severity, existing datasets were probed to determine cell type specific lipid responses to MERS-CoV infection and verification studies were performed to determine if modification of the host lipid signature (by inhibiting enzymatic functions that produce specific lipid species) can perturb CoV replication in human lung cells. MERS-CoV infects human lung epithelial, endothelial and fibroblast cells. All three cell types were infected with MERS-CoV and samples collected to analyze lipids, proteins, metabolites, and transcripts from 12 to 48 hours post infection. Time matched mock-infected cells were collected in parallel for each cell type. Following sample and statistical analysis, functional enrichment and bioinformatic analysis was performed to identify differentially expressed lipids and proteins. Two lipid species were found to be significantly upregulated following MERS-CoV infection, ceramides, and triacylglycerol both of which are indicative of cells undergoing apoptotic cell death. In contrast, sphingomyelins (lipid molecules that can serve as a precursor for one pathway for ceramide synthesis) had significantly decreased expression in MERS-CoV infected cells. An inhibitor of acid sphingomyelinase (that converts sphingomyelin to ceramides and phosphorylcholine) reduced MERS-CoV replication suggesting that production of ceramides is key for successful viral replication and transmission. Acyl-CoA-synthetase 3 (ACSL3), the only protein whose function is lipid associated and had increased differential expression in our dataset, regulates the synthesis of triacylglycerol (increased expression). Inhibitors that directly block ACSL3 (Triacsin C) but not steps later in the triacylglycerol synthesis pathway (Etomoxir) inhibit MERS-CoV replication suggesting that triacylglycerol production and/or ACSL3 activity is also key for viral replication. ACSL3 expression is also upregulated in lung cancer cells and is predicted to promote continued cell viability which would also enhance viral replication. The differentially expressed lipid and lipid-associated protein species identified in our studies suggest that MERS-CoV infection is activating cellular death pathways to limit the number of cells that become infected but also stimulating the production of lipid-associated enzymes that can prolong host cell viability and the amount of time progeny virions can be produced and released. As the inhibitors that worked against MERS-CoV infection were also efficacious against SARS-CoV 2 infection, countermeasures that target these host pathways may provide novel ways to block highly pathogenic human coronavirus infection and/or prevent severe disease outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

In Situ Infrared Spectroscopy of a Plasma Jet and Data-Driven Solution of Multi-Scale Plasma Chemistry Problems

Multi-scale problems are commonly known in many scientific and engineering fields where microscopic behaviors are coupled with macroscopic processes. This is also an unsolved problem in low-temperature plasma chemistry where hundreds of chemical species are involved in thousands of chemical reactions. To address this problem, a physics-informed data-driven modeling is developed to solve such a multi-scale problem using the experimental Fourier-transform infrared spectroscopy (FTIR) measurements of several species’ concentrations. The modeling based on modern machine learning techniques provides concentrations of other relevant species along with the electron temperature and gas temperature at the location of FTIR measurements. For example, the concentrations O, OH, and H 2 O 2 play key roles in plasma-based cancer therapy. This approach overcomes the multi-scale difficulties of microscopic low-temperature plasma chemistry coupling with macroscopic gas flow and allows the acquisition of a full picture of output species concentrations. Presented here for the helium-air jet at atmospheric pressure, the ML-based modeling can be used to describe and possibly control multiscale systems using partial experimental data sets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Review: PFAS Adsorption, Sensing, and Remediation with Engineered Nanoporous Materials

Per- and polyfluoroalkyl substances (PFAS) are among the most abundant environmental contaminant species. They are widespread due to uncontrolled industrial and commercial use and have been linked to health risks such as cancer. With rising global concerns about the public health effects of PFAS, there is an incentive to develop strategies for reliable monitoring and effective PFAS removal, particularly in drinking water. Traditional PFAS sensing techniques are inefficient due to long measurement times, high labor input, high costs, and limitations to ex situ analysis. Current commercially available sorbents for PFAS removal generally lack the ability to capture PFAS components rapidly and quantitatively. Furthermore, existing sorbents are notably inefficient in removing the more toxic, smaller PFAS chemical chains. Large-scale applications of these methods tend to be costly and resource-intensive. Pacific Northwest National Laboratory has developed unique strategies for PFAS sensing and removal with capture probe technology that has an affinity for fluorocarbons, including PFAS. For both sensing and removal, the customizable capture probes can target specific PFAS compounds since they used a metal-organic framework (MOF)-based technology that can be fine-tuned and molecularly tailored. This tailoring of the materials enables high PFAS sensitivity, selectivity, and faster uptake. PNNL’s capture probe materials have been developed into a sensing technique based on the interactions of the capture probes with PFAS at the molecular level and further transduced that to a quantifiable electrochemical response. The materials have been integrated into a sensor platform developed by New Jersey Institute of Technology (NJIT). Tunable capture probes with a range of detection sensitivities allow for faster and more sensitive PFAS detection limits as low as what appears to be 0.5 ng/L (compared to the U.S. Environmental Protection Agency health advisory level of 70 ng/L). Customization of the capture probe results in improved sorption capacities (fast kinetics and high capacities) compared to commercial granular activated carbons. This research applied various experimental and modeling tools to improve understanding the molecular level interactions between the sorbents towards PFAS adsorption properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Impact of Excluding the Submersion Exposure Route for Existing Superfund Radionuclide Screening Level Calculator Soil and Tap Water Models

The U.S. Environmental Protection Agency (EPA) provides initial data screening guidelines for radionuclide-contaminated Superfund sites using preliminary remediation goals (PRGs) and dose compliance concentrations (DCCs). PRGs and DCCs are target concentration values based on acceptable excess lifetime cancer risk and annual dose limits, respectively. They are calculated for various environmental media that may be encountered by residential and worker land uses. PRGs and DCCs typically consist of multiple exposure routes. One of these routes is submersion, which is exposure to a gaseous or particulate radionuclide that is suspended in air. Currently, submersion is only included in air calculations. This study focused on determining whether factoring submersion into total PRG/DCC calculations for soil and tap water created a significant difference in the target concentrations. New equations for individual submersion PRGs/DCCs for each land use of interest for soil and tap water were developed. A wind-driven particulate emission factor and Andelman’s constant were used to model the amount of soil and vapor in the air from soil and household use of tap water, respectively. The submersion PRG/DCC was then included in the total PRG/DCC for each radionuclide, followed by a percent difference comparison of the old and new totals to quantify the impact of the change. For total soil PRGs/DCCs, with and without submersion, the difference was less than 1 percent; however, many of the tap water radionuclides analyzed – including multiple radon and polonium isotopes – showed as high as a 200 percent difference.This technical memorandum (TM) presents recommendations for updates to current EPA guidelines for initial data screens of radionuclide contaminated tap water.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection (Final Report)

The COVID-19 pandemic demonstrated how a novel, elusive, and diffuse biological threat can engender uncertainty and misinformation, and it underscored the need for flexible analytical modalities agnostic to the identity of biological material. Yet even before the pandemic, recognition of the limitations of the current, list-based approach, which focuses on known pathogens and biotoxins, and of the importance of agent-agnostic biodetection was growing within the biosecurity community. In a 2018 report on “Biodefense in the Age of Synthetic Biology,” for example, the National Academy of Sciences stated that “an overreliance on the Select Agent List is a systematic weakness affecting many aspects of the United States’ current biodefense mitigation capability”. More recently, a group of biodefense researchers proposed the identification and adoption of “bioagent-agnostic signatures (BASs)” as a way of detecting and characterizing not only existing agents but also novel ones, an approach they believe will “enable a more flexible and resilient biodefense posture”. Indeed, the future of biodetection requires us to begin developing novel analytics that can identify anomalies and/or characteristics that indicate a potential threat, whether known or unknown, without looking for a specific signature that has been identified previously. To assess potential threats more rapidly, it is critical to develop agnostic artificial intelligence (AI)/machine learning (ML) systems that can be employed for real-time assessment of the nature and source of a perturbation. Such systems should be multi scale and multi-dimensional, integrating sensor data from a range of biological, chemical, and physical application spaces. Emerging deep learning (DL) models demonstrate exceptional promise for identification of discriminatory features within multi-dimensional datasets. DL models have the capacity to recognize and encode highly complex patterns in a wide range of input data modalities, including images, text, and biological/chemical/physical spectra. As such, they can execute a wide range of assessments and determinations that have traditionally required a human operator. The promise of advances in DL is apparent in the realm of human health and medicine. DL models have been validated for evaluating a variety of clinical threats to human health in a range of contexts, including infection and cancer, and they demonstrated improved performance in predicting stroke relative to human neurologists in some categories of data. Continuously evolving advances in AI/ML are expected to support more efficient evaluation of raw sequence, spectroscopy, and spectrometry data. For instance, recent advances and deployment of large language models (LLM) such as Generative Pre training Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) have already motivated application of these models for biological function prediction. As frameworks such as LLMs become larger and more complex in their representations, their capacity to serve as pre-trained models that can be fine-tuned for biological/biodetection purposes will similarly be amplified. While existing and emerging AI/ML have found broad applicability and use cases in the clinical sciences, development for environmental evaluation and biodetection has been limited. Functionalizing such capabilities for this purpose requires an understanding of the existing technical landscape and how the respective tools and algorithms are currently being employed. This landscape awareness then allows an assessment of the current practical capabilities of existing models and the anticipated requirements and development efforts that will be needed to adapt available algorithms for biodetection applications relevant to DHS. Leveraging expertise in biodetection, ML, and operational biodetection, the effort described in this report is comprised of a systematic landscape assessment (Subtask 2.1), comparative evaluation (Subtask 2.2), and formulation of a value proposition (Subtask 2.3) for the prospect of ML-enabled, agnostic biodetection from raw, or minimally-processed, datasets.

59 BASIC BIOLOGICAL SCIENCES↗

Reference Gastrointestinal Absorption Fractions for Radionuclides Ingested in Soil

Oak Ridge National Laboratory is conducting a project for the Environmental Protection Agency (EPA) Office of Superfund Remediation and Technology Innovation involving derivation of cancer risk coefficients for ingestion of radionuclides in soil. EPA provides guidance on quantifying gastrointestinal (GI) absorption of a chemical in a given medium for use in risk evaluations including assessments for Superfund sites. Essentially, a medium-specific GI absorption fraction may be applied if and only if there is sound information to support that value. Otherwise, the applied GI absorption fraction should be the best estimate of fractional absorption of the chemical when ingested in highly soluble form. Based on our review of the literature on GI absorption of elements in soil, we have concluded that for many elements there is convincing evidence of substantially reduced absorption in ingested soil compared with ingestion in readily dissolved form. This report summarizes the reviewed information and proposes a comprehensive set of GI absorption fractions for ingestion of elements in soil. For most elements, the proposed GI absorption fractions are lower than the default absorption fractions recommended by the International Commission on Radiological Protection for radionuclides ingested in highly soluble form, even though considerable conservatism has been incorporated into the proposed soil-specific GI absorption fractions.

59 BASIC BIOLOGICAL SCIENCES↗

Foundations of Molecular 'Isotomics'

The naturally occurring rare isotopes are versions of common elements, such as hydrogen, carbon and oxygen, that contain a larger than usual number of neutrons in their atomic nuclei and therefore are higher in mass than the common atoms of that element. Isotopes exist for most elements and are found in most natural and synthetic materials, but are uneven in their distribution because chemical and physical processes are isotope-selective (e.g., a chemical reaction may proceed more rapidly for one isotope than for another). For this reason, abundances of isotopes in a material of interest can provide a record, or ‘signature’ of various features of that material’s origin and history. These signatures have been used in the geo, life, chemical and physical sciences in a wide variety of ways over close to 8 decades. However, many such applications struggle to reach unique interpretations of isotopic data because multiple factors combine to control a given sample’s overall isotopic content. That is, the factors controlling isotopic content are too numerous and complex to fully constrain from a simple measurement of a material’s isotope abundances. However, the distribution of isotopes within materials, at molecular scales potentially provides a vastly larger number and diversity of constraints on the chemical and physical processes that comprise a material’s history. The rare isotopes may be concentrated into one atomic position in a molecule relative to another, some proportion of molecules in a sample may contain two or more rare isotopes, and those multiply-isotope-substituted forms of molecules may also have uneven distributions of those isotopes across individual atomic sites. For these reasons, even small, seemingly simple molecules, such as sugars, amino acids or drug compounds, actually exist in a vast number of isotopically unique forms (often millions or more), and each one of those forms is in some sense an independent ‘vote’ on that sample’s history. This project has focused on opening this rich archive of information by enabling the creation of routinely and widely applicable ways of measuring and interpreting isotopic structures of molecules. This work has included the development of core technologies and analytical methods, advancing fundamental understanding of the physical and chemical properties of isotopic versions of molecules, and conducting proof of concept studies of illustrative geochemical, cosmochemical and forensic problems in order to show how these technologies, methods and principles come together to solve problems in new ways. A key to the success of this project was the adaptation of ‘Fourier transform mass spectrometry’ (FTMS) to the task of precisely measuring proportions of the rare, naturally occurring isotopic forms of molecules. FTMS is a highly specialized form of mass spectrometry that traps ions within magnetic or electrostatic cavities and, effectively, ‘listens’ (through registering of subtle electrical signals) to the harmonic signals they make while rapidly orbiting within those cavities. These signals have periods that are a function of their mass and strength (or ‘loudness’) that is proportional to their abundances. Thus, these signals constrain relative amounts of molecules that differ in their mass due to various isotopic substitutions. This technology has been essential to the identification of organic molecules in the life, chemical and environmental sciences for over 4 decades, but generally has lacked the control, stability and precision to meaningfully measure rare isotope forms of molecules. This project’s most fundamental contribution has been to modify FTMS, both in terms of hardware and methods, to enable such measurements. The raw data of molecular isotopic structure is tremendously voluminous and complex, so another important activity of this project has been developing the theoretical and data-science tools needed to interpret the data generated by this new form of isotopic measurement. A particularly challenging part of this task has been predicting molecular isotopic structure, as only through the comparison of measurements with predictions can we make progress on hypothesis driven research questions. We have attacked this this prediction task through a combination of first-principles chemical-physics models of the effects of isotope substitution on molecule properties and data-science models that permit us to generalize that chemical physics to cases that have not yet been studied by detailed chemical physics theory. The proof of concept applications we have pursued over the course of this study include biological reactions of amino acids and other biomolecules, non-biological synthesis of organic molecules in extra-terrestrial settings such as meteorites, petroleum geoscience questions concerning the origin and evolution of natural gas, oil and kerogen compounds, and forensic questions such as the sourcing of chemical weapons. The successes of these applications have laid the groundwork for the next phase of this field’s development, which will include larger scale and more ambitious studies of molecular isotopic structure as a means of diagnosing human diseases, such as cancer, and reconstructing detailed interpretations of the origin and evolution of organic molecules in modern and geological environments.

Cesar, Jaime↗

Production of Astatine-211 for Translational Science in Radiotherapy (Research Performance Progress Report)

In this proposal we outline the methods to improve the isotope production of astatine-211 at the University of Pennsylvania Cyclotron Facility. Astatine-211 is an isotope that emits alpha- radiation and has high potential for treating otherwise untreatable cancers. The goal of this proposal is two fold, 1) Optimize current production of astatine-211 and maintain routine production and 2) develop new isotope production target systems and chemical isolation systems. By completing this proposal we will ensure that the University of Pennsylvania Cyclotron Facility continues to build it’s isotope program in an effort that unites under DOE isotope network supply initiatives with the overall goal of increasing the national supply of isotopes. The University of Pennsylvania is uniquely located in the northeast corridor of the United States of America and has access to dozens of institutions that could use astatine-211 in their research. With the support of the DOE we have the opportunity to provide additional momentum to this growing field of research and will be able to provide the foundation for economical development of astatine-211 research and application in medicine.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Spread Out Carbon Bragg Peak at NSRL

Charged particles lose energy continuously while traversing non-vacuum medium but have a sharp peak of dE/dx near the end of the path length. This can be very beneficial for cancer radiotherapy where healthy tissues surrounding a tumor are left with little dose compared to traditional therapy methods. However, since the region of high dose is localized to such a small area, it can present challenges when attempting to treat tumors of larger volume. By utilizing a variable thickness degrader system, the treatment area can be expanded during clinical treatment applications. To accommodate these types of radiobiology experiments, NSRL has produced a spread-out Bragg peak degrader wheel which aims to widen the Bragg peak of a 108 MeV/n Carbon beam to deliver a constant linear energy transfer, in water, of 97.7 keV/µm over a range of 36.7 mm.

43 PARTICLE ACCELERATORS↗

Optical Microsystems for Molecular Sensing (CRADA Final Report)

As part of the Cyclotron Road program, NuSight Photonics sought to implement and investigate an optical Raman spectroscopy instrument for material and molecular analysis. Raman spectroscopy is widely used for quick and non-invasive material measurement when accurate results are needed – e.g., for monitoring manufacturing process in pharmaceutical plants, or identifying illicit substances and explosives by Law Enforcement. This technique is also growing rapidly in popularity as it is applied successfully to a broad range of applications, from pathology and non-invasive early cancer detection, to food and drug safety. The biggest challenge for Raman spectroscopy to achieve its full potential is the hardware cost, ranging from $\$ $25k to $\$ $250k, with the lower cost solutions significantly limited in sensitivity—or detection limit. NuSight Photonics aimed to tackle this obstacle through a novel hardware approach: Swept-Source Raman Spectroscopy.

36 MATERIALS SCIENCE↗

WarpX: Delivering Unprecedented Particle-in-Cell Simulation Capability

Since 1939, more than 30 percent of all Nobel prizes in physics and four of the past 14 prizes in chemistry have been awarded for work with particle accelerators. These tools are now used to treat cancer and produce medical supplies, support research in applied fields such as pharmaceuticals, create microcircuits, and sterilize food—and the applications list continues to grow. However, the size of the facilities needed to house these machines—which are often dozens of kilometers long—has limited their future potential. Thus, researchers are motivated to create novel particle accelerator designs that provide new imaging capability but have a much smaller footprint. The Exascale Computing Project’s WarpX application captures the full complexity of the acceleration processes within plasma-based design, supporting the rapid and cost-efficient development of tens of thousands of new particle accelerators for various applications from improving human health to nuclear fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗