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Introduction: Core-Collapse Supernovae; CCSN Explosion Mechanism; The CCSN “Problem” and possible solutions; conclusions & summary: 3D CCSN Progenitors; 3D Simulations of a 15 M⊙ star; Landscape of 3D Progenitors; 3D Rotating 16 M⊙ star; Multi-messenger Signals from CCSNe.
Medical countermeasures (MCMs) based on messenger ribonucleic acid (mRNA) are promising due to their programmability, targeting precision and specificity, predictable physicochemical properties, and amenability to scalable manufacture. However, safe and effective delivery vehicles are needed, especially for targeting the lung. We developed a generalized approach to nanoparticle-mediated mRNA delivery to lung, and used it to evaluate candidate therapies. In initial studies, reporter mRNA was delivered using lipid-coated mesoporous silica nanoparticles (LC-MSNs) and lipid nanoparticles (LNPs), the latter with greater consistency. Then, mRNA encoding known protein therapies were delivered using LNPs. These formulations showed some toxicity in mice with lung damage, but those with IL-1RA, sACE2-Ig, and ANGPT1 mRNA were modestly therapeutic on balance. Our work advances the state of the art for mRNA delivery to lung, and provides a foundation for evaluating and characterizing mRNA-based lung therapies, including three that appear to be exceptionally promising.
Free neutrons decay via the weak interaction with a mean lifetime of around 15 minutes. Knowledge of this lifetime is important as it provides constraints on the unitarity of the CKM matrix and is a key parameter for studies of Big-Bang nucleosynthesis. However, current laboratory measurements differ by as much as 5σ. We are investigating a new technique to measure neutron lifetime: space-based neutron spectroscopy. We will complete a proof-of-principle demonstration using data from NASA’s MESSENGER mission to Mercury.
The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.
The nuclear equation of state (EOS) is at the center of numerous theoretical and experimental efforts in nuclear physics, motivated by its crucial role in our understanding of the properties of nuclear matter found on Earth, in neutron stars, and in neutron-star mergers. With advances in microscopic theories for nuclear interactions, the availability of experiments probing nuclear matter under conditions not reached before, and the advent of multi-messenger astronomy, the next decade will bring new opportunities for determining the nuclear matter EOS.
The Interplanetary Network (IPN) is a detection, localization and alert system that utilizes the arrival time of transient signals in gamma-ray detectors on spacecraft separated by planetary baselines to geometrically locate the origin of these transients. Due to the changing astrophysical landscape and the new emphasis on time domain and multi messenger astrophysics (TDAMM) from the Pathways to Discovery in Astronomy and Astrophysics for the 2020s , this Gamma-ray Transient Network Science Analysis Group was tasked to understand the role of the IPN and high-energy monitors in this new era. The charge includes describing the science made possible with these facilities, tracing the corresponding requirements and capabilities, and highlighting where improved operations of existing instruments and the IPN would enhance TDAMM science. While this study considers the full multiwavelength and multimessenger context, the findings are specific to space-based high-energy monitors. These facilities are important both for full characterization of these transients as well as facilitating follow-up observations through discovery and localization. The full document reports the history of this field in Section 1, followed by our detailed analyses and findings in some 68 pages, providing a holistic overview of the role of the IPN and high-energy monitors in the coming decades.
Fermilab’s fagship Deep Underground Neutrino Experiment (DUNE) seeks to better understand the nature of neutrinos within the context of Leptogenesis, neutrino oscillations, multi-messenger Astronomy, and other scientifc phenomena. The experiment will send a beam of neutrinos from the Fermilab site in Illinois to the Sanford Underground Neutrino Facility (SURF) in South Dakota, generating petabytes of scientifc data. Given the high volume of data expected when measurements begin at the end of the decade, DUNE computing and the data management group must carefully monitor data transfers across the 15 remote storage sites and, more generally, the 36 global DUNE computing sites. This report will describe both the frontend and backend data monitoring software designed to analyze and visualize these data transfers. Specifc emphasis will be placed on the software’s setup, usage, and methods for future implementations. The full software code can be found under the DUNE/data-mgmt-testing GitHub repository.
Most of our universe is dark. It is dark literally—visible matter makes up only 5% of the energy density—and conceptually, as many outstanding questions remain unsolved. The discovery of particle dark matter would shed light on our dark universe and throw open a window on the highest energy scales. This research made progress toward dark matter and new particle searches in three ways. Extreme compact objects, such as black holes, neutron stars, and stellar cores, can parametrically increase the production rates of feebly interacting particles and yield observable signatures. Specifically, a process known as superradiance leads to exponential growth of the number of ultralight particles gravitationally bound to rotating black holes, and turns astrophysical black holes into particle detectors. This research broadened the scope of applicability of superradiance studies to particles with a wide range of interactions and masses, predicting multi messenger signals. When ultralight particles are produced as dark matter in the early universe, they can be detected directly in laboratory experiments. However, these feebly interacting particles lead to small signals that are inevitably difficult to tease out from backgrounds; their detection requires the theoretical development of unique signatures that can be searched for in low-noise experiments. Some dark matter particles could be detectable with thin film metamaterials combined with low noise single-photon detectors. This research develop the theoretical framework and supported experimental efforts for ambitious searches for a wider class of ultralight particles. Overall, the outcome of this theoretical particle physics program developed novel signatures of new dark matter particles, and thereby expanded the particle parameter space which can be explored with astrophysical observations and precision experiments.
The development of protein-based pharmaceuticals has taken place for years, often finding roadblocks relevant to in vitro biomanufacturing, drug delivery, and drug half-life. Industrial and national laboratory focus has now shifted to messenger RNA (mRNA)-based pharmaceuticals, as mRNA can be manufactured and delivered more easily, and can lead to direct intracellular protein production. Artificial stabilization of the naturally transient mRNA is needed to prolong protein production by recipient cells. Incorporation of viral genome elements known as exoribonuclease-resistant RNA (xrRNA) should allow for this stabilization. To evaluate the effects of xrRNA on mRNA stability, fluorescent proteins are encoded within the mRNA of interest for easier detection through immunocytochemistry, microplate reader screening, and high-content confocal microscopy. As seen with the Pfizer and Moderna COVID 19 vaccines, mRNA-based medical countermeasures can be powerful tools in service of public health and biodefense, and our work to improve mRNA stability should further enhance this promising new approach to medicine.
Modern high energy physics experiments are faced not only with the challenge of having to deal with extremely high data rates but with the need to process data quickly to meet real time constraints. At Fermilab, we explore the use of novel computing technologies and techniques to address these challenges. I will discuss my R&D efforts in applying such computing solutions to enhance the multi-messenger astronomy capabilities and improve the overall physics performance of large-scale LArTPC based neutrino experiments. These efforts offer excellent opportunities for fruitful collaboration.
The TeV gamma-ray source MGRO J1908+06 is one of the highest-energy sources known, with observed emission by the High Altitude Water Cherenkov (HAWC) Observatory extending well past 100 TeV. The source exhibits both energy-dependent morphology and a spatially-dependent spectral index. The emission is likely to be dominantly leptonic, and associated with the radio-quiet PSR J1907+0602. However, one-population models do not describe the data well; a second particle population is needed to explain the shape of the spectral energy distribution at the highest energies. This component can be well-described by either leptonic or hadronic hypotheses. We discuss this feature and implications for detection by multi-wavelength and multi-messenger experiments.
Two highly segmented NOvA scintillation detectors, separated by 810 km and located in the pathof the NuMI neutrino beam produced at Fermilab, are optimized to study the neutrino oscillationphenomenon. At the same time, the larger Far Detector with 4,000 m2 surface area is capable to search for the low-mass magnetic monopoles, and to monitor the flux of the high-multiplicitycosmic ray showers. The smaller Near Detector, located 100 m underground at Fermilab, is ableto search for the presence of possible elusive Dark Matter particles in the high-intensity NuMIneutrino beam, and to study the seasonal variations of multi-muon cosmic flux component. BothNOvA detectors serve in combination as a powerful supernova neutrino detector, and allow forthe multi-messenger signal searches in coincidence with LIGO/Virgo gravitational wave events.A survey of the most recent NOvA results on these topics is presented.
Considering graviton as the only messenger that exists between the inflaton, the dark sector and the Standard Model (SM), we show, it is possible to simultaneously generate the observed relic density of dark matter (DM), the baryon asymmetry via leptogenesis, as well as successful reheating after inflation. Assuming the inflaton Φ oscillates in a monomial potential V(Φ) ∝ Φ k at the end of inflation, reheating via minimal gravitational interaction turns out to be excluded due to excessive production of gravitational wave (GW) energy density from inflation. We thus (a) extend the minimal model by considering a non-minimal gravitational contribution to radiation and (b)) propose an explanation for the PeV excess observed by IceCube, when the DM has an explicit Yukawa coupling to the SM leptong and Higgs. We also propose a novel scenario, where the gravitational production is a two-step process, through the production of a pair of scalars, that eventually decay into fermionic final states. Our framework gives rise to detectable primordial GW signal, that falls within the sensitivity of several proposed GW detectors.
The Facility for Rare Isotope Beams is a world-leading center for experimental nuclear physics research, and relies on a first-in-kind superconducting RF driver linac to supply 400 kW beams of a uniquely large range of particles, from protons through the heaviest uranium ions. The FRIB400 project proposes to double the end energy of the current superconducting FRIB linac for the heaviest uranium ions from 200 MeV per nucleon (MeV/u) to 400 MeV/u, which equates to approximately 1 GeV for protons. The increased rare isotope production from higher-energy drive beams would deliver new and exciting capabilities to FRIB users, which include extending the facility's reach along the neutron drip-line, greatly increasing the facility's rare isotope yield, and significantly improving the precision of parameter measurements for the nuclear matter equation of state, which is a particularly timely complement to the recent advent of multi-messenger astronomy, and the study of neutron star mergers. The unique set of design parameters defined by the 400 MeV/u (uranium) energy goal, the physical size, continuous-wave operation, and cryogenic capacity of the extant facilities at FRIB, requires development of a first-in-kind beta = v/c = 0.65, 644 MHz 5-cell elliptical superconducting RF (SRF) cavity, with field-leading efficiency, measured by the cavity's intrinsic quality factor, Q_0. The field of SRF has recently experienced a very active period of development, which demonstrated the potential to raise the Q_0 of 1.3 GHz cavities by factors of two to three or more. In addition to uncovering fascinating new properties of the fundamental physics of superconducting RF phenomena, these improvements suggest substantial improvements could be made over the minimum Q_0 of the proposed FRIB400 upgrade SRF cavities, if these new techniques can be adapted to the beta = 0.65, 644 MHz regime. This work presents the first validation of the the novel beta = 0.65, 644 MHz 5-cell elliptical superconducting RF cavity design, and the first results of both conventional and advanced RF surface preparation techniques. In particular, this work focuses on two recently-developed high-Q_0 recipes: N-doping, and furnace baking, setting the current world-record Q_0 for this type of resonant cavity at 3.8 x 10^10 at the FRIB400 operating gradient of 17.5 MV/m. We also find evidence that these results may be further improved upon, and make the case for further RF surface preparation recipe optimization. We then pair these high-power RF investigations with techniques borrowed from material science to try to better understand the ways in which specific properties of the niobium material, such as grain structure and superconducting flux pinning force, can be related to its superconducting RF performance. These experiments better elucidate the effects of high-temperature annealing on niobium samples, which suggest methods of further optimizing cavity flux expulsion and thus SRF performance.Read
mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.
During spaceflight, astronauts are exposed to various physiological and psychological stressors that have been associated with adverse health effects. Therefore, there is an unmet need to develop novel diagnostic tools to predict early alterations in astronauts’ health. Small nucleolar RNA (snoRNA) is a type of short non-coding RNA (60–300 nucleotides) known to guide 2'-O-methylation (Nm) or pseudouridine (ψ) of ribosomal RNA (rRNA), small nuclear RNA (snRNA), or messenger RNA (mRNA). Emerging evidence suggests that dysregulated snoRNAs may be key players in regulating fundamental cellular mechanisms and in the pathogenesis of cancer, heart, and neurological disease. Therefore, we sought to determine whether the spaceflight-induced snoRNA changes in astronaut’s peripheral blood (PB) plasma extracellular vesicles (PB-EV) and peripheral blood mononuclear cells (PBMCs). Using unbiased small RNA sequencing (sRNAseq), we evaluated changes in PB-EV snoRNA content isolated from astronauts (n = 5/group) who underwent median 12-day long Shuttle missions between 1998 and 2001. Using stringent cutoff (fold change > 2 or log 2 -fold change >1, FDR < 0.05), we detected 21 down-and 9—up-regulated snoRNAs in PB-EVs 3 days after return (R + 3) compared to 10 days before launch (L-10). qPCR validation revealed that SNORA74A was significantly down-regulated at R + 3 compared to L-10. We next determined snoRNA expression levels in astronauts’ PBMCs at R + 3 and L-10 (n = 6/group). qPCR analysis further confirmed a significant increase in SNORA19 and SNORA47 in astronauts’ PBMCs at R + 3 compared to L-10. Notably, many downregulated snoRNA-guided rRNA modifications, including four Nms and five ψs. Our findings revealed that spaceflight induced changes in PB-EV and PBMCs snoRNA expression, thus suggesting snoRNAs may serve as potential novel biomarkers for monitoring astronauts’ health.
Post-translational modification of host and viral proteins by ubiquitin and ubiquitin-like proteins plays a key role in a host’s ability to mount an effective immune response. Avian species lack a ubiquitin-like protein found in mammals and other non-avian reptiles; interferon stimulated gene product 15 (ISG15). ISG15 serves as a messenger molecule and can be conjugated to both host and viral proteins leading them to be stabilized, degraded, or sequestered. Structurally, ISG15 is comprised of a tandem ubiquitin-like domain (Ubl), which serves as the motif for post-translational modification. The 2’-5’ oligoadenylate synthetase-like proteins (OASL) also encode two Ubl domains in series near its C-terminus which binds OASL to retinoic acid inducible gene-I (RIG-I). This protein-protein interaction increases the sensitivity of RIG-I and results in an enhanced production of type 1 interferons and a robust immune response. Unlike human and other mammalian OASL homologues, avian OASLs terminate their tandem Ubl domains with the same LRLRGG motif found in ubiquitin and ISG15, a motif required for their conjugation to proteins. Chickens, however, lack RIG-I, raising the question of structural and functional characteristics of chicken OASL (chOASL). By investigating chOASL, the evolutionary history of viruses with deubiquitinases can be explored and drivers of species specificity for these viruses may be uncovered. Here we show that the chOASL tandem Ubl domains shares structural characteristics with mammalian ISG15, and that chOASL can oligomerize and conjugate to itself. In addition, the ISG15-like features of avian OASLs and how they impact interactions with viral deubiquitinases and deISGylases are explored.
Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.