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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Robust production of monovalent bispecific IgG antibodies through novel electrostatic steering mutations at the C H 1-C λ interface

Bispecific antibodies represent an increasingly large fraction of biologics in therapeutic development due to their expanded scope in functional capabilities. Asymmetric monovalent bispecific IgGs (bsIgGs) have the additional advantage of maintaining a native antibody-like structure, which can provide favorable pharmacology and pharmacokinetic profiles. The production of correctly assembled asymmetric monovalent bsIgGs, however, is a complex engineering endeavor due to the propensity for non-cognate heavy and light chains to mis-pair. Previously, we introduced the DuetMab platform as a general solution for the production of bsIgGs, which utilizes an engineered interchain disulfide bond in one of the C H 1-C L domains to promote orthogonal chain pairing between heavy and light chains. While highly effective in promoting cognate heavy and light chain pairing, residual chain mispairing could be detected for specific combinations of Fv pairs. Here, we present enhancements to the DuetMab design that improve chain pairing and production through the introduction of novel electrostatic steering mutations at the C H 1-C L interface with lambda light chains (C H 1-C λ ). These mutations work together with previously established charge-pair mutations at the C H 1-C L interface with kappa light chains (C H 1-C κ ) and Fab disulfide engineering to promote cognate heavy and light chain pairing and enable the reliable production of bsIgGs. Importantly, these enhanced DuetMabs do not require engineering of the variable domains and are robust when applied to a panel of bsIgGs with diverse Fv sequences. We present a comprehensive biochemical, biophysical, and functional characterization of the resulting DuetMabs to demonstrate compatibility with industrial production benchmarks. Overall, this enhanced DuetMab platform substantially streamlines process development of these disruptive biotherapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network

Abstract Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein–protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision–recall curve of 0.63 and a Cohen’s Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network’s information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

Wang, Xiaowen↗
DOE OSTI2024

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗
DOE OSTI2020

Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing

ABSTRACT We test general relativity (GR) at the effective redshift $\bar{z} \sim 1.5$ by estimating the statistic EG, a probe of gravity, on cosmological scales $19 - 190\, h^{-1}{\rm Mpc}$. This is the highest redshift and largest scale estimation of EG so far. We use the quasar sample with redshifts 0.8 < z < 2.2 from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_\ell ^{qq}$ and the redshift-space distortion parameter β are estimated. By cross-correlating with the Planck 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_\ell ^{\kappa q}$ signal at $12\, \sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of EG at five bins covering different scales, with the later preferred for its better constraints on the covariances. We find EG estimates agree with the GR prediction at $1\, \sigma$ level over all these scales. With the CM estimated with 300 simulations, we report a best-fitting scale-averaged estimate of $E_G(\bar{z})=0.30\pm 0.05$, which is in line with the GR prediction $E_G^{\rm GR}(\bar{z})=0.33$ with Planck 2018 CMB + BAO matter density fraction Ωm = 0.31. The statistical errors of EG with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Cross-correlation of Planck CMB lensing with DESI-like LRGs

ABSTRACT Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy physics, and test theories of modified gravity. We detect a cross-correlation between Dark Energy Spectroscopic Instrument (DESI)-like luminous red galaxies (LRGs) selected from DECam Legacy Survey imaging and CMB lensing maps reconstructed with the Planck satellite at a significance of S/N = 27.2 over scales ℓmin = 30, ℓmax = 1000. To correct for magnification bias, we determine the slope of the LRG cumulative magnitude function at the faint limit as s = 0.999 ± 0.015, and find corresponding corrections of the order of a few per cent for $C^{\kappa g}_{\ell }, C^{gg}_{\ell }$ across the scales of interest. We fit the large-scale galaxy bias at the effective redshift of the cross-correlation zeff ≈ 0.68 using two different bias evolution agnostic models: a HaloFit times linear bias model where the bias evolution is folded into the clustering-based estimation of the redshift kernel, and a Lagrangian perturbation theory model of the clustering evaluated at zeff. We also determine the error on the bias from uncertainty in the redshift distribution; within this error, the two methods show excellent agreement with each other and with DESI survey expectations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spectroscopic diagnostics of high-temperature plasma in stellar coronae using Fe XXIV-XXIV K-shell lines with XRISM

The RS CVn type binary star GT Muscae was observed during its quiescence using the Resolve X-ray microcalorimeter spectrometer onboard XRISM. The main and satellite lines of the Fe XXIV-XXIV K-shell transitions were resolved for the first time from stellar sources. We conducted line ratio analysis to investigate any deviations from collisional ionization equilibrium and Maxwell electron energy distribution with a single temperature. By using five combinations of direct excitation lines and dielectronic recombination satellite lines in three line complexes (Fe He$\alpha$, Ly$\alpha$, and He$\beta$), we found that the plasma is well characterized by two-temperature thermal plasmas with temperatures of 1.7 and 4.3 keV, which is consistent with thermal broadening of Fe xxv, and the broad-band fitting results in the 1.7–10 keV band. Other forms of deviation from a single-temperature plasma, such as different ionization and electron temperatures or the $\kappa$ distribution for the electron energy distributions, are not favored, which is reasonable for stellar coronae at quiescence. This study demonstrates the utility of the Fe K-shell line ratio diagnostics to probe plasma conditions using X-ray microcalorimeters.

X-rays: stars↗
DOE OSTI2021

Probing the effect of magnetic field on charge order in the quasi-two-dimensional Mott insulator κ - (ET) 2 Hg(SCN) 2 Cl

Molecular-based quasi-two-dimensional charge-ordered Mott insulators can possess both spin S = 1/2 and an electric dipole degree of freedom residing on each (BEDT - TTF) 2 lattice site. There exists a theoretical proposal for a magnetoelectric effect in such a material, which can manifest itself as a sensitivity of charge distribution on (BEDT - TTF) 2 dimers to the magnetic field. Here in this work, we used Raman scattering spectroscopy in the magnetic field up to 31 T applied perpendicular to the two-dimensional triangular lattice planes to probe a magnetoelectric effect in $\kappa$ - (ET) 2 H g (SCN) 2 Cl. This is a model compound, which shows charge order and antiferromagnetic correlations at temperatures below 30 K. We discuss possible reasons for the absence of an observable magnetoelectric effect in the probed temperature and magnetic field ranges.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Superconducting-like response in driven systems near the Mott transition

Here we point out that fractionalized bosonic charge excitations can explain the recently discovered photoinduced superconducting-like response in $\kappa$-(ET) 2 Cu [N(CN) 2 ] Br, an organic metal close to the Mott transition. The pump laser exerts a periodic drive on the fractionalized field, creating a nonequilibrium condensate, which gives a Drude peak much narrower than the equilibrium scattering rate, hence a superconducting-like response. Our proposal illuminates alternative possibilities of detecting fractionalization and can be readily tested in spin liquid candidates and in cold atom systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Critical lensing and kurtosis near a critical point in the QCD phase diagram in and out of equilibrium

In this work, we study the lensing effect of the QCD critical point on hydrodynamic trajectories and its consequences on the net-proton kurtosis $\kappa$ 4 . Including critical behavior by means of the BEST Collaboration equation of state (EoS), we first consider a scenario in equilibrium, then compare with hydrodynamic 0+1⁢D simulations with Bjorken expansion, including both shear and bulk viscous terms. Here, we find that, both in and out of equilibrium, the size and shape of the critical region directly affect if the signal will survive through the dynamical evolution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Plasma proteomic biomarkers of physical frailty in heart failure: a propensity score matched discovery-based pilot study

Background: Physical frailty is highly prevalent in heart failure (HF), but we lack an understanding of the underlying pathophysiology. Proteomics evaluation of plasma samples may elucidate potential mechanisms and biomarkers of physical frailty in HF. We aimed to identify plasma proteomic biomarkers that are differentially expressed between physically frail and non physically frail adults with HF. Methods: This was a secondary analysis of a subset of data and plasma samples from a study of frailty among patients with New York Heart Association (NYHA) Functional Classification I-IV HF. Physical frailty was measured using the Frailty Phenotype Criteria. Propensity score matching was used to match pairs of physically frail (n = 20) vs. non-physically frail (n = 20) patients on clinical characteristics. Plasma samples were processed using a sensitive liquid chromatography mass spectrometry platform, utilizing a multiplexed tandem mass tag-labeled quantitative proteomics approach. Differentially expressed proteins were quantified individually using paired t tests with associated log fold change of 0.3 and Fisher’s combined p values. Results: The sample (n = 40) was 62.8±16.9 years old, 58% female, and 55% NYHA Class III/IV. Proteomics analysis revealed 7 proteins differentially expressed using full differential criteria: matrix metalloproteinase-14 was downregulated in frailty, and copine-1, low affinity immunoglobulin gamma Fc region receptor III-A and III-B, probable non-functional immunoglobulin kappa variable 2D-24, glutathione S-transferase Mu 1, and argininosuccinate lyase were upregulated in frailty. Conclusions: Proteomic biomarkers related to the immune system, stress response, and detoxification were differentially expressed between physically frail and non-physically frail adults with HF.

Biomarkers↗
DOE OSTI2022

A Generalizable Evaluated Approach, Applying Advanced Geospatial Statistical Methods, to Identify High Lead Exposure Locations at Census Tract Scale: Michigan Case Study

BACKGROUND: Despite great progress in reducing environmental lead (Pb) levels, many children in the United States are still being exposed. OBJECTIVE: Our aim was to develop a generalizable approach for systematically identifying, verifying, and analyzing locations with high prevalence of children’s elevated blood Pb levels (EBLLs) and to assess available Pb models/indices as surrogates, using a Michigan case study. METHODS: We obtained ~1:9 million BLL test results of children <6 years of age in Michigan from 2006–2016; we then evaluated them for data representativeness by comparing two percentage EBLL (%EBLL) rates (number of children tested with EBLL divided by both number of children tested and total population). We analyzed %EBLLs across census tracts over three time periods and between two EBLL reference values (≥5 vs. ≥10 μg/dL) to evaluate consistency. Locations with high %EBLLs were identified by a top 20 percentile method and a Getis-Ord Gi* geospatial cluster “hotspot” analysis. For the locations identified, we analyzed convergences with three available Pb exposure models/indices based on old housing and sociodemographics. RESULTS: Analyses of 2014–2016 %EBLL data identified 11 Michigan locations via cluster analysis and 80 additional locations via the top 20 percentile method and their associated census tracts. Data representativeness and consistency were supported by a 0.93 correlation coefficient between the two EBLL rates over 11 y, and a Kappa score of ~0:8 of %EBLL hotspots across the time periods (2014–2016) and reference values. Many EBLL hotspot locations converge with current Pb exposure models/indices; others diverge, suggesting additional Pb sources for targeted interventions. DISCUSSION: This analysis confirmed known Pb hotspot locations and revealed new ones at a finer geographic resolution than previously available, using advanced geospatial statistical methods and mapping/visualization. It also assessed the utility of surrogates in the absence of blood Pb data. This approach could be applied to other states to inform Pb mitigation and prevention efforts. https://doi.org/10.1289/EHP9705

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Design of Temperature Dependent Critical Experiments with SPRF/CX

This paper describes the investigation of temperature-dependent critical experiments using the Seven Percent Critical Experiments (7uPCX) and Burnup Credit Critical Experiments (BUCCX) fuel types within the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories (Sandia). The goal of these experiments is to test the effect of varying system temperature on the $\kappa$ eff bias of water-moderated systems. Temperatures of 5–95°C were considered in this work. Eighteen representative lattice configurations were analyzed that had variations in the number of fuel rods and water holes, as well as in the array configuration, to achieve a variety of moderation regimes. The configurations were based on those detailed in the LEU-COMP-THERM-078 and LEU- COMP-THERM-079 experiments, both of which were published in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Constraining Absolute Higgs Couplings using Vector Boson Fusion H to WW with FCC-hh

The absolute normalisation scale of Higgs couplings is difficult to determine in hadron colliders. An experimentally and theoretically clean way to establish the coupling scale is to measure the ratio of resonant Vector Boson Fusion $H \rightarrow WW^{*}$ production to non-resonant $qq \rightarrow qqWW$ because both the theoretical and detector response systematics all cancel to first order in the ratio. To set the scale of the sensitivity, a simple selection and fit is presented with gives a 1.8\% (1.9\%) statistical uncertainty on the ratio for a 100 (84) TeV FCC-hh at 30\,ab$^{-1}$, which would give a corresponding uncertainty on the $\kappa$ scale of 0.5-1\% depending on systematic effects and potential impacts of more sophisticated analysis.

Lipeles, Elliot [University of Pennsylvania] (ORCI↗
DOE OSTI2022

Sensitivity/Uncertainty Analysis for Nuclear Criticality Safety Validation [Slides]

Sensitivity coefficients predict the expected change in a response ($\kappa$) due to a change in some input parameter ($\Sigma$). These responses can be k eff (or ratios of reaction rates). These input parameters are typically nuclear data. The coefficients are dimensionless ratios. What would happen to the system k eff if some piece of data were changed by some amount? The coefficient is calculated without making the change.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Bayesian Monte-Carlo Framework: New Methods for Resonance Parameter Evaluation [Slides]

BMC evaluation is a tool to address imperfect data & models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allow for variance, covariance, skewness, etc. To better predict criticality, we could document non-normal parameter PDFs (i.e. asymmetric uncertainty), consider non-linear sensitivity of $\kappa$ eff to resonance parameters, and reduce uncertainty in key resonance parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Detection of Candida DNA in peritoneal fluids by PCR assay optimizing the diagnosis and treatment for intra-abdominal candidiasis in high-risk ICU patients: A prospective cohort study

Background Intra-abdominal candidiasis (IAC) is the predominant type of invasive candidiasis with high mortality in critically ill patients. This study aimed to investigate whether the polymerase chain reaction (PCR) assay for detecting Candida DNA in peritoneal fluids (PF) is useful in diagnosing and management of IAC in high-risk patients in intensive care unit (ICU). Methods A prospective single-center cohort study of surgical patients at high risk for IAC was conducted in the ICU. PF was collected from the abdominal drainage tubes (within 24 h) or by percutaneous puncture. Direct PF smear microscopy, PF culture, blood culture, and serum (1–3)-β-D-glucan were performed in all patients. For Candida PCR assay, the ITS1/ITS4 primers that targeted the ITS1-5.8 s-ITS2 regions were used for PCR, and sequencing analysis was used to identify the pathogen at the species level. IAC was defined according to the 2013 European consensus criteria. Results Among 83 patients at high risk for IAC, the IAC criteria were present in 17 (20.5%). The sensitivity and specificity of the Candida PCR assay were 64.7 and 89.4%, respectively, and the area under the receiver operating characteristic curve was 0.77 (95% CI: 0.63–0.91). In this cohort, the positive predictive value and negative predictive value were 90.8% (95% CI: 80.3–96.2%) and 61.1% (95% CI: 36.1–81.7%), respectively. Diagnostic consistency was moderate (kappa 0.529, p < 0.001) according to the 2013 European consensus criteria. Conclusion Detection of Candida DNA in PF using PCR can be considered an adjunct to existing routine diagnostic tools which may optimize the diagnosis and antifungal treatment of IAC in high-risk patients in the ICU.

Xie, Min↗
DOE OSTI2024

Enhancing Docking Accuracy with PECAN2, a 3D Atomic Neural Network Trained without Co-Complex Crystal Structures

Decades of drug development research have explored a vast chemical space for highly active compounds. The exponential growth of virtual libraries enables easy access to billions of synthesizable molecules. Computational modeling, particularly molecular docking, utilizes physics-based calculations to prioritize molecules for synthesis and testing. Nevertheless, the molecular docking process often yields docking poses with favorable scores that prove to be inaccurate with experimental testing. To address these issues, several approaches using machine learning (ML) have been proposed to filter incorrect poses based on the crystal structures. However, most of the methods are limited by the availability of structure data. Here, we propose a new pose classification approach, PECAN2 (Pose Classification with 3D Atomic Network 2), without the need for crystal structures, based on a 3D atomic neural network with Point Cloud Network (PCN). The new approach uses the correlation between docking scores and experimental data to assign labels, instead of relying on the crystal structures. We validate the proposed classifier on multiple datasets including human mu, delta, and kappa opioid receptors and SARS-CoV-2 Mpro. Our results demonstrate that leveraging the correlation between docking scores and experimental data alone enhances molecular docking performance by filtering out false positives and false negatives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Mapping Vegetation at Species Level with High-Resolution Multispectral and Lidar Data Over a Large Spatial Area: A Case Study with Kudzu

Mapping vegetation species is critical to facilitate related quantitative assessment, and mapping invasive plants is important to enhance monitoring and management activities. Integrating high-resolution multispectral remote-sensing (RS) images and lidar (light detection and ranging) point clouds can provide robust features for vegetation mapping. However, using multiple sources of high-resolution RS data for vegetation mapping on a large spatial scale can be both computationally and sampling intensive. Here, we designed a two-step classification workflow to potentially decrease computational cost and sampling effort and to increase classification accuracy by integrating multispectral and lidar data in order to derive spectral, textural, and structural features for mapping target vegetation species. We used this workflow to classify kudzu, an aggressive invasive vine, in the entire Knox County (1362 km2) of Tennessee (U.S.). Object-based image analysis was conducted in the workflow. The first-step classification used 320 kudzu samples and extensive, coarsely labeled samples (based on national land cover) to generate an overprediction map of kudzu using random forest (RF). For the second step, 350 samples were randomly extracted from the overpredicted kudzu and labeled manually for the final prediction using RF and support vector machine (SVM). Computationally intensive features were only used for the second-step classification. SVM had constantly better accuracy than RF, and the producer’s accuracy, user’s accuracy, and Kappa for the SVM model on kudzu were 0.94, 0.96, and 0.90, respectively. SVM predicted 1010 kudzu patches covering 1.29 km2 in Knox County. We found the sample size of kudzu used for algorithm training impacted the accuracy and number of kudzu predicted. The proposed workflow could also improve sampling efficiency and specificity. Our workflow had much higher accuracy than the traditional method conducted in this research, and could be easily implemented to map kudzu in other regions as well as map other vegetation species.

59 BASIC BIOLOGICAL SCIENCES↗