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DOE OSTI2019

On the Road to Regeneration: “Tools” and “Routes” Towards Efficient Cardiac Cell Therapy for Ischemic Cardiomyopathy

Purpose of Review: Cardiac regenerative medicine is a field bridging together biotechnology and surgical science. In this review, we present the explored surgical roads to cell delivery and the known effects of each delivery method on cell therapy efficiency. We also list the more recent clinical trials, exploring the safety and efficacy of delivery routes used for cardiac cell therapy approaches. Recent Findings: There is no consensus in defining which way is the most suitable for the delivery of the different therapeutic cell types to the damaged heart tissue. In addition, it emerged that the “delivery issue” has not been systematically addressed in each clinical trial and for each and every cell type capable of cardiac repair. Summary: Cardiac damage occurring after an ischemic insult triggers a cascade of cellular events, eventually leading to heart failure through fibrosis and maladaptive remodelling. None of the pharmacological or medical interventions approved so far can rescue or reverse this phenomenon, and cardiovascular diseases are still the leading cause of death in the western world. Therefore, for nearly 20 years, regenerative medicine approaches have focused on cell therapy as a promising road to pursue, with numerous preclinical and clinical testing of cell-based therapies being studied and developed. Nonetheless, consistent clinical results are still missing to reach consensus on the most effective strategy for ischemic cardiomyopathy, based on patient selection, diagnosis and stage of the disease, therapeutic cell type, and delivery route.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

DeepClone: Lightweight State Replication of Deep Learning Models for Data Parallel Training

Training modern deep neural network (DNN) models involves complex workflows triggered by model exploration, sensitivity analysis, explainability, etc. A key primitive in this context is the ability to clone a model training instance, i.e. “fork” the training process in a potentially different direction, which enables comparisons of different evolution paths using variations of training data and model parameters. However, in a quest improve the training throughput, a mix of data parallel, model parallel, pipeline parallel and layer-wise parallel approaches are making the problem of cloning highly complex. In this paper, we explore the problem of efficient cloning under such circumstances. To this end, we leverage several properties of data-parallel training and layer-wise parallelism to design DeepClone, a cloning approach based on augmenting the execution graph to gain direct access to tensors, which are then sharded and reconstructed asynchronously in order to minimize runtime overhead, standby duration, readiness duration. Compared with state-of-art approaches, DeepClone shows orders of magnitude improvement for several classes of DNN models.

data-parallel training↗

NASA NTRSDate not supplied

Characterizing Electrical Arc Behavior in Ion Engines

Gridded ion engines represent a class of electric thrusters characterized by high propulsive efficiency and high total impulse capabilities. These engines operate by applying high voltage to multi-aperture electrodes, thereby electrostatically accelerating plasma to generate thrust. Within the course of normal operations, periodic occurrences of high voltage breakdowns manifest within the thruster. These breakdowns constitute an inherent aspect of operation, with observations indicating a diminishing frequency and total count over the thruster's operational lifespan. To safeguard the propulsion system during such occurrences, the power processing unit (PPU) employs an automated arc extinction sequence, termed "recycle," which is triggered upon detection of an over-current condition. The initial phase of this sequence involves momentarily deactivating the high voltage and reducing the discharge current to a predetermined level, minimizing plasma impingement as the ion beam is defocused. The high voltage is subsequently reapplied, and the discharge current is returned to its nominal value. The entire sequence typically spans approximately 800 milliseconds. Throughout a recycle event, the propulsion system experiences various current and voltage transients as the arc current traverses the system and different power supplies are toggled on and off.

electric propulsion↗

DOE OSTI2023

Devices and methods for increasing the speed or power efficiency of a computer when performing machine learning using spiking neural networks

A method for increasing a speed and efficiency of a computer when performing machine learning using spiking neural networks. The method includes computer-implemented operations; that is, operations that are solely executed on a computer. The method includes receiving, in a spiking neural network, a plurality of input values upon which a machine learning algorithm is based. The method also includes correlating, for each input value, a corresponding response speed of a corresponding neuron to a corresponding equivalence relationship between the input value to a corresponding latency of the corresponding neuron. Neurons that trigger faster than other neurons represent close relationships between input values and neuron latencies. Latencies of the neurons represent data points used in performing the machine learning. A plurality of equivalence relationships are formed as a result of correlating. The method includes performing the machine learning using the plurality of equivalence relationships.

Vineyard, Craig Michael↗

DOE OSTI2023

D-Egg: a dual PMT optical module for IceCube

The D-Egg, an acronym for "Dual optical sensors in an Ellipsoid Glass for Gen2," is one of the optical modules designed for future extensions of the IceCube experiment at the South Pole. The D-Egg has an elongated-sphere shape to maximize the photon-sensitive effective area while maintaining a narrow diameter to reduce the cost and the time needed for drilling of the deployment holes in the glacial ice for the optical modules at depths up to 2700 m. The D-Egg design is utilized for the IceCube Upgrade, the next stage of the IceCube project also known as IceCube-Gen2 Phase 1, where nearly half of the optical sensors to be deployed are D-Eggs. With two 8-inch high-quantum efficiency photomultiplier tubes (PMTs) per module, D-Eggs offer an increased effective area while retaining the successful design of the IceCube digital optical module (DOM). The convolution of the wavelength-dependent effective area and the Cherenkov emission spectrum provides an effective photodetection sensitivity that is 2.8 times larger than that of IceCube DOMs. The signal of each of the two PMTs is digitized using ultra-low-power 14-bit analog-to-digital converters with a sampling frequency of 240 MSPS, enabling a flexible event triggering, as well as seamless and lossless event recording of single-photon signals to multi-photons exceeding 200 photoelectrons within 10 ns. Mass production of D-Eggs has been completed, with 277 out of the 310 D-Eggs produced to be used in the IceCube Upgrade. In this paper, we report the design of the D-Eggs, as well as the sensitivity and the single to multi-photon detection performance of mass-produced D-Eggs measured in a laboratory using the built-in data acquisition system in each D-Egg optical sensor module.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

AEcroscopy: A Software–Hardware Framework Empowering Microscopy Toward Automated and Autonomous Experimentation

Microscopy has been pivotal in improving the understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most characterization labs. However, traditional microscopy operations are still limited largely by a human-centric click-and-go paradigm utilizing vendor-provided software, which limits the scope, utility, efficiency, effectiveness, and at times reproducibility of microscopy experiments. Here, in this work, a coupled software–hardware platform is developed that consists of a software package termed AEcroscopy (short for Automated Experiments in Microscopy), along with a field-programmable-gate-array device with LabView-built customized acquisition scripts, which overcome these limitations and provide the necessary abstractions toward full automation of microscopy platforms. The platform works across multiple vendor devices on scanning probe microscopes and electron microscopes. It enables customized scan trajectories, processing functions that can be triggered locally or remotely on processing servers, user-defined excitation waveforms, standardization of data models, and completely seamless operation through simple Python commands to enable a plethora of microscopy experiments to be performed in a reproducible, automated manner. This platform can be readily coupled with existing machine-learning libraries and simulations, to provide automated decision-making and active theory-experiment optimization to turn microscopes from characterization tools to instruments capable of autonomous model refinement and physics discovery.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Online Optimization of NSLS-II Dynamic Aperture and Injection Transient (Facility Improvement Project)

The Facility Improvement Project (FIP) “Methods of online optimization of NSLS-II storage ring concurrent with user operations” proposed and approved in 2018 is now complete. The first goal is the online optimization of nonlinear beam dynamics to increase the beam lifetime and injection efficiency. We have developed a model-independent optimization technique using advanced algorithms. Using this technique, we increased the NSLS-II dynamic aperture by 20% and reduced the amplitude-dependent tune shift by a factor of two. We applied sextupole optimization to the new high-chromaticity lattice, which has been developed to improve the beam stability and to increase the single-bunch beam intensity. We were able to double the injection efficiency and exceed 90%. The second goal of this project is to provide the top-off injection with minimized perturbations of the beamline user operations. To achieve the transparent injection, we optimize the matching of four storage ring injection kickers reducing the perturbation of the stored beam orbit. The first application of the online optimization resulted in a reduction of the amplitude of residual beam oscillation by a factor of six, from 1300 μm down to 200 μm. Further improvement was limited by the timing jitter of the trigger boards. Then, we replaced all trigger boards with a new design and reduced the timing jitter by a factor of five, from 5 ns down to 1 ns. This upgrade resulted in the injection transient reduction from 200 μm to 120 μm. To optimize the full set of kicker parameters, including the trigger timing, amplitude, and pulse width, we upgraded all kicker power supplies with the capability of tunable waveform width. As a result, we have reduced the injection transient to the limit of 60 μm.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Mechanistic assessment of tolerance to iron deficiency mediated by Trichoderma harzianum in soybean roots

Abstract Aims Iron (Fe) deficiency in soil is a continuing problem for soybean (Glycine max L.) production, partly as a result of continuing climate change. This study elucidates how Trichoderma harzianum strain T22 (TH) mitigates growth retardation associated with Fe-deficiency in a highly sensitive soybean cultivar. Methods and Results Soil TH supplementation led to mycelial colonization and the presence of UAOX1 gene in roots that caused substantial improvement in chlorophyll score, photosynthetic efficiency and morphological parameters, indicating a positive influence on soybean health. Although rhizosphere acidification was found to be a common feature of Fe-deficient soybean, the upregulation of Fe-reductase activity (GmFRO2) and total phenol secretion were two of the mechanisms that substantially increased the Fe availability by TH. Heat-killed TH applied to soil caused no improvement in photosynthetic attributes and Fe-reductase activity, confirming the active role of TH in mitigating Fe-deficiency. Consistent increases in tissue Fe content and increased Fe-transporter (GmIRT1, GmNRAMP2a, GmNRAMP2b and GmNRAMP7) mRNA levels in roots following TH supplementation were observed only under Fe-deprivation. Root cell death, electrolyte leakage, superoxide (O2•–) and hydrogen peroxide (H2O2) substantially declined due to TH in Fe-deprived plants. Further, the elevation of citrate and malate concentration along with the expression of citrate synthase (GmCs) and malate synthase (GmMs) caused by TH suggest improved chelation of Fe in Fe-deficient plants. Results also suggest that TH has a role in triggering antioxidant defence by increasing the activity of glutathione reductase (GR) along with elevated S-metabolites (glutathione and methionine) to stabilize redox status under Fe-deficiency. Conclusions TH increases the availability and mobilization of Fe by inducing Fe-uptake pathways, which appears to help provide resistance to oxidative stress associated with Fe-shortage in soybean. Significance and Impact of the Study These findings indicate that while Fe deficiency does not affect the rate or degree of TH hyphal association in soybean roots, the beneficial effects of TH alone may be Fe deficiency-dependent.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Valproate induced hepatic steatosis by enhanced fatty acid uptake and triglyceride synthesis

Steatosis is the characteristic type of VPA-induced hepatotoxicity and may result in life-threatening hepatic lesion. Approximately 61% of patients treated with VPA have been diagnosed with hepatic steatosis through ultrasound examination. However, the mechanisms underlying VPA-induced intracellular fat accumulation are not yet fully understood. Here we demonstrated the involvement of fatty acid uptake and lipogenesis in VPA-induced hepatic steatosis in vitro and in vivo by using quantitative real-time PCR (qRT-PCR) analysis, western blotting analysis, fatty acid uptake assays, Nile Red staining assays, and Oil Red O staining assays. Specifically, we found that the expression of cluster of differentiation 36 (CD36), an important fatty acid transport, and diacylglycerol acyltransferase 2 (DGAT2) were significantly up-regulated in HepG2 cells and livers of C57B/6J mice after treatment with VPA. Furthermore, VPA treatment remarkably enhanced the efficiency of fatty acid uptake mediated by CD36, while this effect was abolished by the interference with CD36-specific siRNA. Also, VPA treatment significantly increased DGAT2 expression as a result of the inhibition of mitogen-activated protein kinase kinase (MEK) – extracellular regulated kinase (ERK) pathway; however, DGAT2 knockdown significantly alleviated VPA-induced intracellular lipid accumulation. Additionally, we also found that sterol regulatory element binding protein-1c (SREBP-1c)-mediated fatty acid synthesis may be not involved in VPA-induced hepatic steatosis. Overall, VPA-triggered over-regulation of CD36 and DGAT2 could be helpful for a better understanding of the mechanisms underlying VPA-induced hepatic steatosis and may offer novel therapeutic strategies to combat VPA-induced hepatotoxicity. - Highlights: • VPA induced hepatic steatosis and modulated genes associated with lipid metabolism. • CD36-mediated fatty acid uptake contributed to VPA-induced lipid accumulation. • PA increased the hepatic level of DGAT2 through inhibiting MEK-ERK pathway and enhanced triglyceride synthesis. • SREBP-1c-mediated fatty acid synthesis was not involved in VPA-induced hepatic steatosis.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2003

Analysis Methods and Results for Weak Gamma-Ray Bursts in the BATSE Data

We report initial results on the statistical properties of the dimmest gamma-ray bursts (GRBs) observed with the Burst and Transient Source Experiment (BATSE), using new ground-based methods to obtain a sample of GRBs from 502 days of BATSE data. Using the most sensitive ground-based detection of GRBs, the sample extends to GRBs much fainter than those detected by the on-board trigger, but because of the temporal resolution of the data, the sample is limited to GRBs of duration of at least 2(approx.)s. For each detected event, Bayesian probabilities are calculated for the event to belong to each of seven classes of differing physical origins. The sample of GRB candidates is defined by the requirement that the Bayesian probability for belonging to the GRB class is higher than 0.5. The intensity distribution of the GRB sample is corrected using a Monte Carlo simulation of the post-flight detection efficiency. The dimmest BATSE bursts of the sample continue the hardness-intensity trend seen in brighter GREs and are consistent with isotropy.

Mitrofanov, I. G.↗

DOE OSTI2017

Bimetallic Cooperativity in Proton Reduction with an Amido-Bridged Cobalt Catalyst

The bimetallic catalyst [Co II 2 (L 1 )(bpy) 2 ]ClO 4 (1), in which L 1 is an [NN' 2 O 2 ] fused ligand, efficiently reduced H + to H 2 in CH 3 CN in the presence of 100 equiv of HOAc with a turnover number of 18 and a Faradaic efficiency of 94 % after 3 h of bulk electrolysis at -1.6 V (vs. Ag/AgCl). This observation allowed the proposal that this bimetallic cooperativity is associated with distance, angle, and orbital alignment of the two Co centers, as promoted by the unique Co-N amido -Co environment offered by L 1 . Experimental results revealed that the parent [Co II Co II ] complex undergoes two successive metal-based 1 e- reductions to generate the catalytically active species [CoICoI], and DFT calculations suggested that addition of a proton to one Co I triggers a cooperative 1 e - transfer by each of these Co I centers. This 2 e - transfer is an alternative route to generate a more reactive [Co II (Co II -H - )] hydride, thus avoiding the Co III -H - required in monometallic species. This [Co II (Co II -H - )] species then accepts another H + to release H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

A bacterial surface layer protein exploits multistep crystallization for rapid self-assembly

Surface layers (S-layers) are crystalline protein coats surrounding microbial cells. S-layer proteins (SLPs) regulate their extracellular self-assembly by crystallizing when exposed to an environmental trigger. However, molecular mechanisms governing rapid protein crystallization in vivo or in vitro are largely unknown. Here, we demonstrate that the Caulobacter crescentus SLP readily crystallizes into sheets in vitro via a calcium-triggered multistep assembly pathway. This pathway involves 2 domains serving distinct functions in assembly. The C-terminal crystallization domain forms the physiological 2-dimensional (2D) crystal lattice, but full-length protein crystallizes multiple orders of magnitude faster due to the N-terminal nucleation domain. Observing crystallization using a time course of electron cryo-microscopy (Cryo-EM) imaging reveals a crystalline intermediate wherein N-terminal nucleation domains exhibit motional dynamics with respect to rigid lattice-forming crystallization domains. Dynamic flexibility between the 2 domains rationalizes efficient S-layer crystal nucleation on the curved cellular surface. Rate enhancement of protein crystallization by a discrete nucleation domain may enable engineering of kinetically controllable self-assembling 2D macromolecular nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

GPU Usage in ATLAS Reconstruction and Analysis

With Graphical Processing Units (GPUs) and other kinds of accelerators becoming ever more accessible, High Performance Computing Centres all around the world using them ever more, ATLAS has to find the best way of making use of such accelerators in much of its computing. Tests with GPUs - mainly with CUDA - have been performed in the past in the experiment. At that time the conclusion was that it was not advantageous for the ATLAS offline and trigger software to invest time and money into GPUs. However as the usage of accelerators has become cheaper and simpler in recent years, their re-evaluation in ATLAS's offline software is warranted. We show new results of using GPU accelerated calculations in ATLAS's offline software environment using the ATLAS offline/analysis (xAOD) Event Data Model. We compare the performance and flexibility of a couple of the available GPU programming methods, and show how different memory management setups affect our ability to offload different types of calculations to a GPU efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

A programmable time alignment scheme for detector signals from the upgraded muon spectrometer at the ATLAS experiment

We present a programmable time alignment scheme used in an ASIC for the ATLAS forward muon trigger development. The scheme utilizes regenerated clocks with programmable phases to compensate for the timing offsets introduced by different detector trace lengths. Each ASIC used in the design has 104 input channels with delay compensation circuitry providing steps of ~ 3 ns and a full range of 25 ns for each channel. Detailed implementation of the scheme including majority logic to suppress single-event effects is presented. The scheme is flexible and fully synthesizable. Here, the approach is adaptable to other applications with similar phase shifting requirements. In addition, the design is resource efficient and is suitable for cost-effective digital implementation with a large number of channels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Charged Particle Tracking via Edge-Classifying Interaction Networks

Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high-energy particle physics. In particular, particle tracking data are naturally represented as a graph by identifying silicon tracker hits as nodes and particle trajectories as edges, given a set of hypothesized edges, edge-classifying GNNs identify those corresponding to real particle trajectories. In this work, we adapt the physics-motivated interaction network (IN) GNN toward the problem of particle tracking in pileup conditions similar to those expected at the high-luminosity Large Hadron Collider. Assuming idealized hit filtering at various particle momenta thresholds, we demonstrate the IN’s excellent edge-classification accuracy and tracking efficiency through a suite of measurements at each stage of GNN-based tracking: graph construction, edge classification, and track building. The proposed IN architecture is substantially smaller than previously studied GNN tracking architectures; this is particularly promising as a reduction in size is critical for enabling GNN-based tracking in constrained computing environments. Furthermore, the IN may be represented as either a set of explicit matrix operations or a message passing GNN. Efforts are underway to accelerate each representation via heterogeneous computing resources towards both high-level and low-latency triggering applications.

accelerator physics↗

DOE OSTI2017

Antibiotics-induced gut microbiota dysbiosis promotes tumor initiation via affecting APC-Th1 development in mice

Gut microbiota is critical for maintaining body immune homeostasis and thus affects tumor growth and therapeutic efficiency. Here, we investigated the link between microbiota and tumorgenesis in a mice model of subcutaneous melanoma cell transplantation, and explored the underlying mechanism. We found disruption of gut microbiota by pretreating mice with antibiotics promote tumor growth and remodeling the immune compartment within the primary tumor. Indeed, gut microbial dysbiosis reduced the infiltrated mature antigen-presenting cells of tumor, together with lower levels of co-stimulators, such as CD80, CD86 and MHCII, as well as defective Th1 cytokines, including IFNγ, TNFα, IL12p40, and IL12p35. Meantime, splenic APCs displayed blunted ability in triggering T cell proliferation and IFNγ secretion. However, oral administration of LPS restored the immune surveillance effects and thus inhibited tumor growth in the antibiotics induced gut microbiota dysbiosis group. Taken together, these data highly supported that antibiotics induced gut microbiota dysbiosis promotes tumor initiation, while LPS supplementation would restore the effective immune surveillance and repress tumor initiation. - Highlights: • Antibiotics induced gut microbiota dysbiosis promotes tumor initiation in mice. • Gut microbiota disruption compromise APC-Th1 development in tumor. • Orally LPS administration rescues tumor immune surveillance in gut microbiota disrupted mice. • None of the authors have any conflict of interest.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Final report for Collaborative Research on Ecophysiological Controls on Amazonian Precipitation Seasonality and Variability

The principal objective of our project is to address how vegetation influences climate variability and precipitation over Amazonian rainforests, with an emphasis on plant physiological controls on deep convection triggering along a geographical water stress gradient. Using a new tool of sun-induced chlorophyll fluorescence (SIF), our study integrates plant physiological observations and climate modeling and aims to decrease the gap between field ecology and climate modeling. We have installed sensors at Manaus site (K34) and at Rebio Jaru (Ji-Paraná, Rondonia). From field observations, we found a diversity of hydraulic functioning, indicating that within the same forest we will find different responses to the predicted climatic changes. The hydraulic strategies varied through a continuum of hydraulic security and water transport efficiency, which can be related to a long process of taxa evolution. The fact that taller trees are more hydraulically vulnerable indicates that if these forests go through higher drought conditions and temperature increase, they could experience a massive tree mortality that will promote changes on forest structure, changing the ecosystem functions, such as water fluxes and carbon storage. To investigate the role of water stress on the onset of the rainy season, we have developed high-resolution cloud resolving model (CRM) simulations using a new strategy coupling convective and large-scales. The first results show that the presence of early morning fog reduces the wet season transpiration and carbon uptake over the everwet regions of Amazonia. We have incorporated SIF into CLM to constrain energy, carbon and water flux of tropical forests. By using CloudSat-observed cloud vertical structure, we show an empirical relationship between atmospheric energetics and convective clouds in Amazonia, in comparison with the savanna/shrubland and tropical West Pacific, emphasizing predominant deep convection during the early wet season when Bowen ratio and convective available potential energy (CAPE) increase. Although on average the deep convections are prominent only during the short dry-to-wet transition while shallow/congestus clouds dominate the rest of the year in Amazonia, there is a clear cloud regime shift when CAPE grows beyond a threshold value. Our project helped initiate and maintain collaboration between US and Brazilian scientists. We have been collaborating through yearly field campaigns, weekly international research meetings, and ongoing other collaborative projects. Through these activities, we helped our students and postdocs fill their knowledge gaps and learn new research techniques.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Collaborative Research on Ecophysiological Controls on Amazonian Precipitation Seasonality and Variability (Final Technical Report)

54 ENVIRONMENTAL SCIENCES↗