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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-yield recombinant bacterial expression of 13 C-, 15 N-labeled, serine-16 phosphorylated, murine amelogenin using a modified third generation genetic code expansion protocol

Amelogenin constitutes ~ 90% of the enamel matrix in the secretory stage of amelogenesis, a still poorly understood process that results in the formation of the hardest and most mineralized tissue in vertebrates – enamel. Most biophysical research with amelogenin uses recombinant protein expressed in Escherichia coli. In addition to providing copious amounts of protein, recombinant expression allows 13 C- and 15 N-labelling for detailed structural studies using NMR spectroscopy. However, native amelogenin is phosphorylated at one position, Ser-16 in murine amelogenin, and a lingering question overshadowing decades of enamel research with recombinant amelogenin is the effect of phosphorylation on its biophysical properties. Using a modified genetic code expansion protocol we have expressed and purified uniformly 13 C-, 15 N-labeled murine amelogenin (pS16M179) with ~95% of the protein being correctly phosphorylated. Homogeneous phosphorylation was achieved using commercially available, enriched, 13 C-, 15 N-labeled media and protein expression was induced with isopropyl β-D-1-thiogalactopyranoside at 310 K. Phosphoserine incorporation was verified from one-dimensional 31P NMR spectra, comparison of 1 H- 15 N HSQC spectra, Phos-tag SDS PAGE, and mass spectrometry. Phosphorus-31 NMR spectra for pS16M179 under conditions known to trigger amelogenin self-assembly into nanospheres confirm nanosphere models with buried N-termini. Lambda phosphatase treatment of these nanospheres results in the dephosphorylation of pS16M179, confirming that smaller oligomers and monomers with exposed N-termini are in equilibrium with nanospheres. Such 13 C-, 15 N-labeling of amelogenin with accurately encoded phosphoserine incorporation will accelerate biomineralization research to understand amelogenesis and stimulate the expanded use of genetic code expansion protocols to introduce phosphorylated amino acids into proteins.

31P-NMR↗
DOE OSTI2023

High dimensional binary classification under label shift: phase transition and regularization

Label Shift has been widely believed to be harmful to the generalization performance of machine learning models. Researchers have proposed many approaches to mitigate the impact of the label shift, e.g., balancing the training data. However, these methods often consider the underparametrized regime, where the sample size is much larger than the data dimension. The research under the overparametrized regime is very limited. Here, to bridge this gap, we propose a new asymptotic analysis of the Fisher Linear Discriminant classifier for binary classification with label shift. Specifically, we prove that there exists a phase transition phenomenon: Under certain overparametrized regime, the classifier trained using imbalanced data outperforms the counterpart with reduced balanced data. Moreover, we investigate the impact of regularization to the label shift: The aforementioned phase transition vanishes as the regularization becomes strong.

binary classification↗
DOE OSTI2016

Selective disulfide reduction for labeling and enhancement of Fab antibody fragments

Many methods have been developed for chemical labeling and enhancement of the properties of antibodies and their common fragments, including the Fab and F(ab’){sub 2} fragments. Somewhat selective reduction of some antibody disulfide bonds has been previously achieved, yielding antibodies and antibody fragments that can be labeled at defined sites, enhancing their utility and properties. Selective reduction of the two hinge disulfide bonds present in F(ab’){sub 2} fragments using mild reduction has been useful. However, such reduction is often not quantitative and results in the reduction of multiple disulfide bonds, and therefore subsequent multiple labeling or conjugation sites are neither homogenous nor stoichiometric. Here, a simple and efficient selective reduction of the single disulfide bond linking the partial heavy chain and the intact light chain which compose the Fab fragment is accomplished utilizing tris(2-carboxyethyl)phosphine (TCEP) immobilized on agarose beads. The resultant reduced cysteine residues were labeled with several cysteine-selective fluorescent reagents, as well as by cysteine-directed PEGylation. These two cysteine residues can also be re-ligated by means of a bifunctional cysteine cross-linking agent, dibromobimane, thereby both restoring a covalent linkage between the heavy and light chains at this site, far removed from the antigen binding site, and also introducing a fluorescent probe. There are many other research and clinical uses for these selectively partially reduced Fab fragments, including biotinylation, toxin and drug conjugation, and incorporation of radioisotopes, and this technique enables simple generation of very useful Fab fragment derivatives with many potential applications. - Highlights: • TCEP agarose is effective for selective reduction of a single Fab disulfide bond. • This disulfide is solvent accessible and distant from the antigen binding site. • A variety of buffers of varying pHs can be used, simplifying subsequent steps. • The methods used are simple, easily verifiable, reproducible, and quantitative. • The selectively reduced Fab has many experimental and clinical applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The role of above-code labeling programs in reducing CO 2 e emissions in residential buildings

Residential buildings account for 15 % of total U.S. carbon dioxide (CO 2 ) emissions. Voluntary, above-code labeling programs, such as the ENERGY STAR and Zero Energy Ready Home programs, can play a crucial role in reducing the carbon footprint of the new construction residential building sector by encouraging adoption of more energy-efficient and lower emissions building practices and technologies. It's important for the industry to understand the carbon dioxide equivalent (CO 2 e) and energy cost savings potential of these programs. Here, to estimate the potential CO 2 e emissions savings for homes built to above-code labeling program levels, it is imperative to have reliable and accurate tools for estimating emissions from buildings. The open-source OpenStudio-ERI workflow employs detailed physics-based building energy modeling (BEM) to estimate energy usage and operational CO 2 e emissions. In this study we use the OpenStudio-ERI workflow and regional, time-varying emissions factors from the Cambium database to compare the CO 2 e emissions and energy costs of homes built to performance levels required by these above-code labeling programs relative to homes built to model energy codes. We present the results of our analysis and provide a range of emissions and annual energy cost savings for the above-code labeling programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Modeling framework for isotopic labeling of heteronuclear moieties

Background: Isotopic labeling is an analytic technique that is used to track the movement of isotopes through reaction networks. In general, the applicability of isotopic labeling techniques is limited to the investigation of reaction networks that consider homonuclear moieties, whose atoms are of one tracer element with two isotopes, distinguished by the presence of one additional neutron. Results: This article presents a reformulation of the modeling framework for isotopic labeling, generalized to arbitrarily large, heteronuclear moieties, arbitrary numbers of isotopic tracer elements, and arbitrary numbers of isotopes per element, distinguished by arbitrary numbers of additional neutrons. Conclusions: With this work, it is now possible to simulate the isotopic labeling states of metabolites in completely arbitrary biochemical reaction networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Coupling Metabolic Source Isotopic Pair Labeling and Genome Wide Association for Metabolite and Gene Annotation in Plants (Final Technical Report)

In this project, we applied our labeling pipeline to Arabidopsis and sorghum by feeding tissues with isotopically labeled versions of commercially available amino acids to identify all metabolite features that incorporate the label. In sorghum, we fed five accessions, sampled across the diversity of sorghum, to identify the precursor-of-origin for metabolites that vary between accessions as well as those that may be missing from a single reference genotype. This provided us with precursor-of-origin annotation for thousands of unknown metabolites. We then used GWA to map genes responsible for the synthesis of precursor-of-origin classified metabolites. For sorghum leaf and root ducible metabolites, we performed untargeted metabolomics on leaf and root tissues from 300 diverse genotyped sorghum inbred lines. The amino acid precursor-of-origin metabolite library were then used to identify the corresponding metabolites in the GWA data sets and to identify novel gene-metabolite associations. Finally, we utilized existing and newly generated sequenced EMS mutants of sorghum to validate the predicted gene-metabolite relationships that our labelling analysis identified. In parallel, we conducted similar feeding experiments in Arabidopsis to categorize metabolites based on precursor-of-origin, identify those that vary across our existing Arabidopsis metabolite GWA dataset, and identify genes required for the synthesis of each metabolite. To provide an independent test of gene annotation and pathway involvement, we tested the GWA gene-metabolite associations in Arabidopsis by analyzing the metabolic phenotypes of gene knockouts. Genes of particular interest from both sorghum and Arabidopsis were studied in detail by directly measuring the activity of the corresponding enzymes following heterologous expression. In summary, this work classified as-yet-unknown amino acid-derived metabolites and identified genes involved in their production generated through “omics” technologies. This information was used to validate gene function and identify new metabolism in Arabidopsis and sorghum.

09 BIOMASS FUELS↗
DOE OSTI2026

Cyber Labeling for Energy Industrial IoT

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security and Emergency Response (CESER), at the request of the Deputy National Security Advisor for Cyber and Emerging Technologies, Anne Neuberger, initiated research in 2023 to develop a cybersecurity labeling proof-of-concept for energy products to expand on the Federal Communications Commission’s (FCC) proposed U.S. Cyber Trust Mark program. DOE mobilized researchers from six National Laboratories to develop and gather feedback on a proof-of concept label for solar inverters and smart meters, which serve as representative products for market-facing energy sector Industrial Internet of Things (IIoT). This report details the research team’s process across two phases and the resulting findings, which include challenges facing cyber labeling programs and recommendations to implement an expanded IIoT cyber labeling program in the U.S.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2019

14 C-Cobalamin Absorption from Endogenously Labeled Chicken Eggs Assessed in Humans Using Accelerator Mass Spectrometry

Traditionally, the bioavailability of vitamin B-12 (B12) from in vivo labeled foods was determined by labeling the vitamin with radiocobalt ( 57 Co, 58 Co or 60 Co). This required use of penetrating radioactivity and sometimes used higher doses of B12 than the physiological limit of B12 absorption. The aim of this study was to determine the bioavailability and absorbed B12 from chicken eggs endogenously labeled with 14 C-B12 using accelerator mass spectrometry (AMS). 14C-B12 was injected intramuscularly into hens to produce eggs enriched in vivo with the 14 C labeled vitamin. The eggs, which provided 1.4 to 2.6 μg of B12 (~1.1 kBq) per serving, were scrambled, cooked and fed to 10 human volunteers. Baseline and post-ingestion blood, urine and stool samples were collected over a one-week period and assessed for 14 C-B12 content using AMS. Bioavailability ranged from 13.2 to 57.7% (mean 30.2 ± 16.4%). Difference among subjects was explained by dose of B12, with percent bioavailability from 2.6 μg only half that from 1.4 μg. The total amount of B12 absorbed was limited to 0.5–0.8 μg (mean 0.55 ± 0.19 μg B12) and was relatively unaffected by the amount consumed. The use of 14 C-B12 offers the only currently available method for quantifying B12 absorption in humans, including food cobalamin absorption. An egg is confirmed as a good source of B12, supplying approximately 20% of the average adult daily requirement (RDA for adults = 2.4 μg/day).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effective Labeling of Primary Somatic Stem Cells with BaTiO 3 Nanocrystals for Second Harmonic Generation Imaging

Abstract While nanoparticles are an increasingly popular choice for labeling and tracking stem cells in biomedical applications such as cell therapy, their intracellular fate and subsequent effect on stem cell differentiation remain elusive. To establish an effective stem cell labeling strategy, the intracellular nanocrystal concentration should be minimized to avoid adverse effects, without compromising the intensity and persistence of the signal necessary for long‐term tracking. Here, the use of second‐harmonic generating barium titanate nanocrystals is reported, whose achievable brightness allows for high contrast stem cell labeling with at least one order of magnitude lower intracellular nanocrystals than previously reported. Their long‐term photostability enables to investigate quantitatively at the single cell level their cellular fate in hematopoietic stem cells (HSCs) using both multiphoton and electron microscopy. It is found that the concentration of nanocrystals in proliferative multipotent progenitors is over 2.5‐fold greater compared to quiescent stem cells; this difference vanishes when HSCs enter a nonquiescent, proliferative state, while their potency remains unaffected. Understanding the nanoparticle stem cell interaction allows to establish an effective and safe nanoparticle labeling strategy into somatic stem cells that can critically contribute to an understanding of their in vivo therapeutic potential.

Sugiyama, Nami↗
DOE OSTI2017

Classification without labels: learning from mixed samples in high energy physics

Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In this paper, we introduce the paradigm of classification without labels (CWoLa) in which a classifier is trained to distinguish statistical mixtures of classes, which are common in collider physics. Crucially, neither individual labels nor class proportions are required, yet we prove that the optimal classifier in the CWoLa paradigm is also the optimal classifier in the traditional fully-supervised case where all label information is available. After demonstrating the power of this method in an analytical toy example, we consider a realistic benchmark for collider physics: distinguishing quark- versus gluon-initiated jets using mixed quark/gluon training samples. More generally, CWoLa can be applied to any classification problem where labels or class proportions are unknown or simulations are unreliable, but statistical mixtures of the classes are available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Development of 52Mn Labeled Trastuzumab for Extended Time Point PET Imaging of HER2

Abstract Purpose Due to their long circulation time in the blood, monoclonal antibodies (mAbs) such as trastuzumab, are usually radiolabeled with long-lived positron emitters for the development of agents for Positron Emission Tomography (PET) imaging. Manganese-52 ( 52 Mn, t 1/2 = 5.6 d, β + = 29.6%, E(β ave ) = 242 keV) is suitable for imaging at longer time points providing a complementary technique to Zirconium-89 ( 89 Zr, t 1/2 = 3.3 d, β + = 22.7%, E(β ave ) = 396 keV)) because of its long half-life and low positron energy. To exploit these properties, we aimed to investigate suitable bifunctional chelators that could be readily conjugated to antibodies and labeled with 52 Mn under mild conditions using trastuzumab as a proof-of-concept. Procedures Trastuzumab was incubated with S-2-(4-isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-SCN-Bn-DOTA), 1-Oxa-4,7,10-tetraazacyclododecane-5-S-(4-isothiocyantobenzyl)-4,7,10-triacetic acid (p-SCN-Bn-Oxo-DO3A), and 3,6,9,15-tetraazabicyclo[9.3.1] pentadeca-1(15),11,13-triene-4-S-(4-isothiocyanatobenzyl)-3,6,9-triacetic acid (p-SCN-Bn-PCTA) at a tenfold molar excess. The immunoconjugates were purified, combined with [ 52 Mn]MnCl 2 at different ratios, and the labeling efficiency was assessed by iTLC. The immunoreactive fraction of the radiocomplex was determined through a Lindmo assay. Cell studies were conducted in HER2 + (BT474) and HER2- (MDA-MB-468) cell lines followed by in vivo studies. Results Trastuzumab-Oxo-DO3A was labeled within 30 min at 37 °C with a radiochemical yield (RCY) of 90 ± 1.5% and with the highest specific activity of the chelators investigated of 16.64 MBq/nmol. The labeled compound was purified with a resulting radiochemical purity of > 98% and retained a 67 ± 1.2% immunoreactivity. DOTA and PCTA immunoconjugates resulted in < 50 ± 2.5% (RCY) with similar specific activity. Mouse serum stability studies of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab showed 95% intact complex for over 5 days. Cell uptake studies showed higher uptake in HER2 + (12.51 ± 0.83% /mg) cells compared to HER2- (0.85 ± 0.10%/mg) cells. PET images of mice bearing BT474 tumors showed high tumor uptake that was consistent with the biodistribution (42.02 ± 2.16%ID/g, 14 d) compared to MDA-MB-468 tumors (2.20 ± 0.80%ID/g, 14 d). Additionally, both models exhibited low bone uptake of < 1% ID/g. Conclusion The bifunctional chelator p-SCN-Bn-Oxo-DO3A is promising for the development of 52 Mn radiopharmaceuticals as it was easily conjugated, radiolabeled at mild conditions, and illustrated stability for a prolonged duration both in vitro and in vivo . High-quality PET/CT images of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab were obtained 14 d post-injection. This study illustrates the potential of [ 52 Mn]Mn-Oxo-DO3A for the evaluation of antibodies using PET imaging.

Omweri, James M.↗
DOE OSTI2017

Intracellular in situ labeling of TiO 2 nanoparticles for fluorescence microscopy detection

Titanium dioxide (TiO 2 ) nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic nanoparticles for cancer detection and treatment, drug delivery, induction of DNA double-strand breaks, and imaging of specific cells and subcellular structures. Currently, the use of optical microscopy, an imaging technique most accessible to biology and medical pathology, to detect TiO 2 nanoparticles in cells and tissues ex vivo is limited with low detection limits, while more sensitive imaging methods (transmission electron microscopy, X-ray fluorescence microscopy, etc.) have low throughput and technical and operational complications. In this paper, we describe two in situ posttreatment labeling approaches to stain TiO 2 nanoparticles taken up by the cells. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called Click chemistry, for labeling and detection of azide-conjugated TiO 2 nanoparticles with alkyneconjugated fluorescent dyes such as Alexa Fluor 488. To confirm that optical fluorescence signals of these nanoparticles match the distribution of the Ti element, we used synchrotron X-ray fluorescence microscopy (XFM) at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific XFM showed excellent overlap with the location of optical fluorescence detected by confocal microscopy. Finally and therefore, future experiments with TiO 2 nanoparticles may safely rely on confocal microscopy after in situ nanoparticle labeling using approaches described here.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Stable Isotope Labeling for Improved Comparative Analysis of RNA Digests by Mass Spectrometry

Even with the advent of high throughput methods to detect modified ribonucleic acids (RNAs), mass spectrometry remains a reliable method to detect, characterize, and place post-transcriptional modifications within an RNA sequence. Here we have developed a stable isotope labeling comparative analysis of RNA digests (SIL-CARD) approach, which improves upon the original {sup 18}O/{sup 16}O labeling CARD method. Like the original, SIL-CARD allows sequence or modification information from a previously uncharacterized in vivo RNA sample to be obtained by direct comparison with a reference RNA, the sequence of which is known. This reference is in vitro transcribed using a {sup 13}C/{sup 15}N isotopically enriched nucleoside triphosphate (NTP). The two RNAs are digested with an endonuclease, the specificity of which matches the labeled NTP used for transcription. As proof of concept, several transfer RNAs (tRNAs) were characterized by SIL-CARD, where labeled guanosine triphosphate was used for the reference in vitro transcription. RNase T1 digestion products from the in vitro transcript will be 15 Da higher in mass than the same digestion products from the in vivo tRNA that are unmodified, leading to a doublet in the mass spectrum. Singlets, rather than doublets, arise if a sequence variation or a post-transcriptional modification is present that results in a relative mass shift different from 15 Da. Moreover, the use of the in vitro synthesized tRNA transcript allows for quantitative measurement of RNA abundance. Overall, SIL-CARD simplifies data analysis and enhances quantitative RNA modification mapping by mass spectrometry. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Fluorescence-labeled liposome accumulation in injured colon of a mouse model of T-cell transfer-mediated inflammatory bowel disease

Drug delivery systems maximize the efficacy of drugs by improving their pharmacokinetic profiles, pharmacodynamic effects, or both and reducing their adverse effects. One of the most advanced, clinically available formulations are liposome-encapsulated drugs. In this study, we aimed to determine if liposomes can selectively deliver compounds in gastrointestinal diseases. Initially, we evaluated the correlation between the diarrhea score and accumulation of fluorescence (FL)-labeled liposome using in vivo imaging systems in various disease states of an inflammatory bowel disease mouse model. The result showed that FL-labeled liposome accumulation and colon tissue weight, which reflect the disease state were highly and positively correlated. Then, to confirm the accumulation of liposomes at injured sites of the colon, we administered both FL-labeled liposomes and luminescence probes for detecting reactive oxygen species (ROS) to the mouse model. The imaging data showed that liposome accumulation tended to coincide with ROS detected sites and the correlation coefficient indicated a significantly positive correlation between liposome accumulation and ROS detection levels. Finally, we evaluated the involvement of macrophages in the uptake mechanism of the liposomes by analyzing the relationship between FL-labeled liposome accumulation and macrophage marker gene expression levels. The result showed that the expression of each macrophage marker gene and liposome accumulation showed a significant positive correlation. Therefore, the macrophages considerably contributed to the uptake mechanism of the liposomes. These data suggest that liposomes could be an attractive delivery tool for enhancing the accumulation of drug candidates through macrophages in injured colonic tissues. This approach is expected to provide new treatment options for patients with colitis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Crystal structure of a thermophilic O 6-alkylguanine-DNA alkyltransferase-derived self-labeling protein-tag in covalent complex with a fluorescent probe

Highlights: • The labeling of proteins is a valid approach for studying their function. • SNAP-tag{sup ®} is a self-labeling protein tag that binds different probes (e.g. SVG). • SsOGT-H{sup 5} is a thermostable alternative to the SNAP-tag{sup ®} technology. • The SsOGT-H{sup 5}-SVG structure reveals new details of protein-probe interaction. • The SsOGT-H{sup 5}-SVG structure highlights new OGTs structure-function relationships. The self-labeling protein tags are robust and versatile tools for studying different molecular aspects of cell biology. In order to be suitable for a wide spectrum of experimental conditions, it is mandatory that these systems are stable after the fluorescent labeling reaction and do not alter the properties of the fusion partner. SsOGT-H{sup 5} is an engineered variant alkylguanine-DNA-alkyl-transferase (OGT) of the hyperthermophilic archaeon Sulfolobus solfataricus, and it represents an alternative solution to the SNAP-tag{sup ®} technology under harsh reaction conditions. Here we present the crystal structure of SsOGT-H{sup 5} in complex with the fluorescent probe SNAP-Vista Green{sup ®} (SsOGT-H{sup 5}-SVG) that reveals the conformation adopted by the protein upon the trans-alkylation reaction with the substrate, which is observed covalently bound to the catalytic cysteine residue. Moreover, we identify the amino acids that contribute to both the overall protein stability in the post-reaction state and the coordination of the fluorescent moiety stretching-out from the protein active site. We gained new insights in the conformational changes possibly occurring to the OGT proteins upon reaction with modified guanine base bearing bulky adducts; indeed, our structural analysis reveals an unprecedented conformation of the active site loop that is likely to trigger protein destabilization and consequent degradation. Interestingly, the SVG moiety plays a key role in restoring the interaction between the N- and C-terminal domains of the protein that is lost following the new conformation adopted by the active site loop in the SsOGT-H{sup 5}-SVG structure. Molecular dynamics simulations provide further information into the dynamics of SsOGT-H{sup 5}-SVG structure, highlighting the role of the fluorescent ligand in keeping the protein stable after the trans-alkylation reaction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Machine learning for reactor power monitoring with limited labeled data

Real-time reactor power monitoring is critical for a variety of nuclear applications, spanning safety, security, operations, and maintenance. While machine learning methods have shown promise in monitoring reactor power levels, there is limited research on their efficacy in label-starved environments. The goal of this work is to assess the feasibility of classifying nuclear reactor power level using multisource data in scenarios with limited labels. Data were collected using low-resolution multisensors at four nuclear reactor facilities: two large research reactors and two TRIGA reactors. Within each pair, one reactor dataset served as the source and the other as the target in a transfer learning paradigm. Twenty-three supervised models were trained on labeled sequences of magnetic field and acceleration data from each of the target sites. Self-learning and transfer learning methods were applied to the top performing models to assess their classification performance with increasing amounts of labeled data. While reactor power level classification was achieved with a Matthews Correlation Coefficient of up to 0.739 ± 0.003 and 0.622 ± 0.009 with only 400 sequences per power state for the large research reactor and TRIGA target sites, respectively, self-learning and transfer learning leveraging source site data did not improve target classification performance. These findings suggest that alternative methods, such as higher sensitivity sensors, digital twins, or the use of physics-informed models, are required to enable high-performance classification in machine learning approaches to reactor monitoring with a dearth of target ground truth.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites

Mass spectrometry analyses have identified tens of thousands of unknown small molecule-associated peaks in different biological specimens. Notably, even the simplest and best studied organisms like Escherichia coli and Saccharomyces cerevisiae yield thousands of unknown peaks. A key question is how many of these reflect actual novel endogenous metabolites. To explore this, Mahieu and Patti used complete 13 C -labeling in E. coli to credential peaks as biological. This reduced the number of unknowns by more than 90%. Here, we carry out similar uniform 13 C-labeling in the Baker’s yeast S. cerevisiae and two less-studied bioenergy-relevant yeasts Rhodotorula toruloides (lipid producer) and Issatchenkia orientalis (organic acid producer). Identification of unknown metabolite peaks and their molecular formulas is facilitated through software tailored for 13 C labeling data and resulting knowledge of carbon atom count. A classification model evaluates the plausibility of each candidate formula, with peaks lacking plausible candidate formulas unlikely to reflect metabolite molecular ions. This approach prioritizes about one hundred candidate abundant unknown metabolites with logical molecular formulas. Most of these are species-specific rather than conserved across yeasts, and more are found in the nonmodel yeasts than S. cerevisiae. Thus, 13 C-labeling data on unknown metabolites highlights the potential for discovering new metabolites and pathways in nonmodel yeasts.

Carbon↗
DOE OSTI2025

Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues

Abstract Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Science & Technology - Other Topics↗