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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Mapping the Future: Towards Oncology Curriculum Reform in Undergraduate Medical Education at a Canadian Medical School

Purpose: To evaluate (1) the quantity and quality of current undergraduate oncology teaching at a major Canadian medical school; and (2) curricular changes over the past decade, to enhance local oncology education and provide insight for other educators. Methods and Materials: Relevant 2011-2012 undergraduate curricular sessions were extracted from the University of Toronto curriculum mapping database using keywords and database identifiers. Educational sessions were analyzed according to Medical Council of Canada objectives, discussion topics, instructor qualifications, teaching format, program year, and course subject. Course-related oncology research projects performed by students during 2000 to 2012 were extracted from another internal database. Elective choices of clerks during 2008-2014 were retrieved from the institution. The 2011-2012 and 2000-2001 curricula were compared using common criteria. Results: The 2011-2012 curriculum covers 5 major themes (public health, cancer biology, diagnosis, principles of care, and therapy), which highlight 286 oncology teaching topics within 80 sessions. Genitourinary (10, 12.5%), gynecologic (8, 10.0%), and gastrointestinal cancers (7.9, 9.8%) were the most commonly taught cancers. A minority of sessions were taught by surgical oncologists (6.5, 8.1%), medical oncologists (2.5, 3.1%), and radiation oncologists (1, 1.2%). During 2000-2012, 9.0% of students (233 of 2578) opted to complete an oncology research project. During 2008-2014, oncology electives constituted 2.2% of all clerkship elective choices (209 of 9596). Compared with pre-2001 curricula, the 2012 oncology curriculum shows notable expansion in the coverage of epidemiology (6:1 increase), prevention (4:1), screening (3:1), and molecular biology (6:1). Conclusions: The scope of the oncology curriculum has grown over the past decade. Nevertheless, further work is needed to improve medical student knowledge of cancers, particularly those relevant to public health needs. Defining minimum curricular content, emphasizing content based on population needs, and ensuring educational delivery with the support and expertise of oncologists and non-oncologists will be essential next steps.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Thermodynamic assessments and inter-relationships between systems involving Al, Am, Ga, Pu, and U

We present a newly developed self-consistent CALPHAD thermodynamic database involving Al, Am, Ga, Pu, and U. A first optimization of the slightly characterized Am-Al and completely unknown Am-Ga phase diagrams is proposed. To this end, phase diagram features as crystal structures, stoichiometric compounds, solubility limits, and melting temperatures have been studied along the U-Al → Pu-Al → Am-Al, and U-Ga → Pu-Ga → Am-Ga series, and the thermodynamic assessments involving Al and Ga alloying are compared. In addition, two distinct optimizations of the Pu-Al phase diagram are proposed to account for the low temperature and Pu-rich region controversy. We included the previously assessed thermodynamics of the other binary systems (Am-Pu, Am-U, Pu-U, and Al-Ga) in the database and is briefly described in the present work. In conclusion, predictions on phase stability of ternary and quaternary systems of interest are reported to check the consistency of the database.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A discrete integral transform for rapid spectral synthesis

Accurate synthetic spectra that rely on large Line-By-Line (LBL)-databases are used in a wide range of applications such as high temperature combustion, atmospheric re-entry, planetary surveillance and laboratory plasmas. Conventionally synthetic spectra are calculated by computing a lineshape for every spectral line in the database and adding those together, which may take multiple hours for large databases. In this paper we propose a new approach for spectral synthesis based on an integral transform: the synthetic spectrum is calculated as the integral over the product of a Voigt profile and a newly proposed three-dimensional “lineshape distribution function”, which is a function of spectral position and Gaussian- & Lorentzian width coordinates. A fast discrete version of this transform based on the Fast Fourier Transform (FFT) is proposed, which improves performance compared to the conventional approach by several orders of magnitude while maintaining accuracy. Strategies that minimize the discretization error are discussed. A Python implementation of the method is compared against state-of-the-art spectral code RADIS, and is since adopted as RADIS's default synthesis method. The synthesis of a benchmark CO2 spectrum consisting of 1.8 M spectral lines and 200k spectral points took only 3.1 s using the proposed method (1011 lines × spectral points/s), a factor ~300 improvement over the state-of-the-art, with the relative improvement generally increasing for higher number of lines and/or number of spectral points. Finally, an experimental GPU-implementation of the method was also benchmarked, which demonstrated another 2~3 orders performance increase, achieving up to 5 ∙ 10 14 lines × spectral points/s.

42 ENGINEERING↗
DOE OSTI2015

Atomic solid state energy scale: Universality and periodic trends in oxidation state

The atomic solid state energy (SSE) scale originates from a plot of the electron affinity (EA) and ionization potential (IP) versus band gap (E{sub G}). SSE is estimated for a given atom by assessing an average EA (for a cation) or an average IP (for an anion) for binary inorganic compounds having that specific atom as a constituent. Physically, SSE is an experimentally-derived average frontier orbital energy referenced to the vacuum level. In its original formulation, 69 binary closed-shell inorganic semiconductors and insulators were employed as a database, providing SSE estimates for 40 elements. In this contribution, EA and IP versus E{sub G} are plotted for an additional 92 compounds, thus yielding SSE estimates for a total of 64 elements from the s-, p-, d-, and f-blocks of the periodic table. Additionally, SSE is refined to account for its dependence on oxidation state. Although most cations within the SSE database are found to occur in a single oxidation state, data are available for nine d-block transition metals and one p-block main group metal in more than one oxidation state. SSE is deeper in energy for a higher cation oxidation state. Two p-block main group non-metals within the SSE database are found to exist in both positive and negative oxidation states so that they can function as a cation or anion. SSEs for most cations are positioned above −4.5 eV with respect to the vacuum level, and SSEs for all anions are positioned below. Hence, the energy −4.5 eV, equal to the hydrogen donor/acceptor ionization energy ε(+/−) or equivalently the standard hydrogen electrode energy, is considered to be an absolute energy reference for chemical bonding in the solid state. - Highlights: • Atomic solid-state energies are estimated for 64 elements from experimental data. • The relationship between atomic SSEs and oxidation state is assessed. • Cations are positioned above and absolute energy of −4.5 eV and anions below.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Atlas of Nuclear Isomers

We present an atlas of nuclear isomers containing the experimental data for the isomers with a half-life ≥ 10 ns together with their various properties such as excitation-energy, half-life, decay mode(s), spin-parity, energies and multipolarities of emitted gamma transitions, etc. The ENSDF database complemented by the XUNDL database has been extensively used in extracting the relevant data. Recent literature from primary nuclear physics journals, and the NSR bibliographic database have been searched to ensure that the compiled data Table is as complete and current as possible. The data from NUBASE-12 have also been checked for completeness, but as far as possible original references have been cited. Many interesting systematic features of nuclear isomers emerge, some of them new; these are discussed and presented in various graphs and figures. The cutoff date for the extraction of data from the literature is August 15, 2015.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

MiR-205–5p suppresses angiogenesis in gastric cancer by downregulating the expression of VEGFA and FGF1

Highlights: • MiR-205-5p was commonly downregulated in GC tissues from TCGA database and our hospital, and these events were associated with a worse TNM stagedistant metastasis and poor survival. • MiR-205-5p and CD31 expressions were negatively inter-related within GC tissues from TCGA database and our hospital. • GC cell lines expressed lower level of miR-205-5p significantly as compared with the normal gastric cell line. • MiR-205-5p upregulation significantly impaired proliferation and colony formation of GC cells and neovascularization induced by GC cells in vitro and in vivo. • The angiogenesis and ERK-signaling were depressed by VEGFA and FGF1 downregulation induced by miR-205-5p overexpression. The miR-205-5p inhibitor promoted malignant phenotypes by enhancing VEGFA and FGF1 expressions, as well as the activation of ERK-signaling. Anti-angiogenic therapy represents one of the most promising treatment modalities for human cancers. However, the response to antiangiogenic therapy in gastric cancer (GC) remains dismal. To help identify new strategies for antiangiogenic therapy in GC, we evaluated miR-205–5p expression in GC tissues from TCGA database and our hospital, and its functions in angiogenesis were explored in vitro and in vivo. We investigated miR-205–5p expression and microvessel densities (MVDs) in GC tissues and liver metastases from patients. The function and mechanisms of miR-205–5p were examined in human cell lines and in xenograft mouse models. Associations between miR-205–5p expression and clinical characteristics were analyzed using either Pearson's χ{sup 2} test or Fisher's exact test. Differences in overall survival (OS) distributions were evaluated using the log-rank test. Differences in measurement data were compared using Student's t-test and one-way ANOVA. We found that miR-205–5p expression was downregulated in GC tissues and was negatively correlated with CD31 expression in both TCGA and our clinical samples. GC cell lines expressed low levels of miR-205–5p, and miR-205–5p upregulation significantly impaired the proliferation and angiogenesis of GC cells. Moreover, vascular endothelial growth factor A (VEGFA) and fibroblast growth factor 1 (FGF1) expression and activation of extracellular-related kinase (ERK) signaling were suppressed by miR-205–5p. MiR-205–5p inhibition promoted malignant phenotypes by enhancing VEGFA and FGF1 expression, as well as the activation of ERK signaling. Angiogenesis and ERK signaling were decreased in response to VEGFA and FGF1 downregulation induced by miR-205–5p overexpression. The dual-luciferase reporter assay showed that VEGFA and FGF1 were direct targets of miR-205–5p. Xenograft mouse models revealed that miR-205–5p suppressed tumor growth by inhibiting neovascularization. Altogether, these results demonstrate that miR-205–5p suppresses angiogenesis in GC by attenuating the expression of VEGFA and FGF1, indicating that upregulation of miR-205–5p may represent as an antiangiogenic therapy for GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Thermochemical Data Fusion Using Graph Representation Learning

Large databases are required for “Big Data” applications in catalysis and materials science. Thermochemical databases can be created by combining data from various sources and by correcting low-fidelity datasets to higher accuracy with minimal computation. To achieve this “data fusion”, thermochemical quantities of interest, calculated at various levels of density functional theory (DFT), need to be mapped to the same, high levels of theory. In this work, a graph theoretical, statistical framework is proposed for such tasks. Subgraph frequencies are shown to provide a natural representation for learning these fusion maps. The maps are linear and are learnt with automated descriptor selection. Using a dataset of as few as ~1% from the QM9 database of 133,885 molecules, these models can predict multiple thermochemical quantities at a higher level of theory with an accuracy of 1 kcal/mol. Here, the method is explainable, generalizable, and provides a diagnostic tool for outlier identification

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Development of Porous Crystalline Materials for Selective Binding of O 2 from Air

Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.

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

Accurate Identification of Deamidation and Citrullination from Global Shotgun Proteomics Data Using a Dual-Search Delta Score Strategy

While proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data from a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched against database by MSGF+ twice with or without a +0.9840 Da mass shift on amino acids asparagine, glutamine, and arginine (NQR) as a dynamic modification. Consequently, for each spectrum the resulting two peptide-to-spectrum matches (PSM) with their respective MSGF+ scores were used for Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR), a “pseudo-decoy” approach was applied whether datasets were searched against a database with a “real modification” mass shift (+0.9840 Da) and a “mock modification” mass shift (+1.0227 Da). FDR was controlled to ~2% with a Delta Score filter greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score value contained deamidated/citrullinated fragments in their MS/MS spectra. Finally, the results demonstrated that in-situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data by the Dual-search Delta Score Strategy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

On the Morphodynamics of a Wide Class of Large‐Scale Meandering Rivers: Insights Gained by Coupling LES With Sediment‐Dynamics

Abstract In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting how these interactions affect the spatial patterns and magnitudes of bed deformation in meandering rivers is essential for various river engineering and geoscience problems. Computational fluid dynamics simulations can predict river morphodynamics at fine temporal and spatial scales but have traditionally been challenged by the large scale of natural rivers. We conducted coupled large‐eddy simulation and bed morphodynamics simulations to create a unique database of hydro‐morphodynamic data sets for 42 meandering rivers with a variety of planform shapes and large‐scale geometrical features that mimic natural meanders. For each simulated river, the database includes (a) bed morphology, (b) three‐dimensional mean velocity field, and (c) bed shear stress distribution under bankfull flow conditions. The calculated morphodynamics results at dynamic equilibrium revealed the formation of scour and deposition patterns near the outer and inner banks, respectively, while the location of point bars and scour regions around the apexes of the meander bends is found to vary as a function of the radius of curvature of the bends to the width ratio. A new mechanism is proposed that explains this seemingly paradoxical finding. The high‐fidelity simulation results generated in this work provide researchers and scientists with a rich numerical database for morphodynamics and bed shear stress distributions in large‐scale meandering rivers to enable systematic investigation of the underlying phenomena and support a range of river engineering applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Forest expansion dominates China’s land carbon sink since 1980

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China’s reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Automated generation and ensemble-learned matching of X-ray absorption spectra

X-ray absorption spectroscopy (XAS) is a widely used materials characterization technique to determine oxidation states, coordination environment, and other local atomic structure information. Analysis of XAS relies on comparison of measured spectra to reliable reference spectra. However, existing databases of XAS spectra are highly limited both in terms of the number of reference spectra available as well as the breadth of chemistry coverage. In this work, we report the development of XASdb, a large database of computed reference XAS, and an Ensemble-Learned Spectra IdEntification (ELSIE) algorithm for the matching of spectra. XASdb currently hosts more than 800,000 K-edge X-ray absorption near-edge spectra (XANES) for over 40,000 materials from the open-science Materials Project database. We discuss a high-throughput automation framework for FEFF calculations, built on robust, rigorously benchmarked parameters. FEFF is a computer program uses a real-space Green’s function approach to calculate X-ray absorption spectra. Here, we will demonstrate that the ELSIE algorithm, which combines 33 weak “learners” comprising a set of preprocessing steps and a similarity metric, can achieve up to 84.2% accuracy in identifying the correct oxidation state and coordination environment of a test set of 19 K-edge XANES spectra encompassing a diverse range of chemistries and crystal structures. The XASdb with the ELSIE algorithm has been integrated into a web application in the Materials Project, providing an important new public resource for the analysis of XAS to all materials researchers. Finally, the ELSIE algorithm itself has been made available as part of veidt, an open source machine-learning library for materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Tracking materials science data lineage to manage millions of materials experiments and analyses

Abstract In an era of rapid advancement of algorithms that extract knowledge from data, data and metadata management are increasingly critical to research success. In materials science, there are few examples of experimental databases that contain many different types of information, and compared with other disciplines, the database sizes are relatively small. Underlying these issues are the challenges in managing and linking data across disparate synthesis and characterization experiments, which we address with the development of a lightweight data management framework that is generally applicable for experimental science and beyond. Five years of managing experiments with this system has yielded the Materials Experiment and Analysis Database (MEAD) that contains raw data and metadata from millions of materials synthesis and characterization experiments, as well as the analysis and distillation of that data into property and performance metrics via software in an accompanying open source repository. The unprecedented quantity and diversity of experimental data are searchable by experiment and analysis attributes generated by both researchers and data processing software. The search web interface allows users to visualize their search results and download zipped packages of data with full annotations of their lineage. The enormity of the data provides substantial challenges and opportunities for incorporating data science in the physical sciences, and MEAD’s data and algorithm management framework will foster increased incorporation of automation and autonomous discovery in materials and chemistry research.

Soedarmadji, Edwin↗
DOE OSTI2022

Identification of high-dielectric constant compounds from statistical design

Abstract The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with very high dielectric constants (69 < ϵ < 101) and large band gaps (2.9 < E g (eV) < 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN). Two of these new dielectrics are mixed-anion compounds (Eu 5 SiCl 6 O 4 and HoClO) and are shown to be thermodynamically stable against common semiconductors via phase diagram analysis. We also uncovered four other materials with relatively large dielectric constants (20 < ϵ < 40) and band gaps (2.3 < E g (eV) < 2.7). While the ANN training-data are obtained from the Materials Project, the search-space consists of materials from the Open Quantum Materials Database (OQMD)—demonstrating a successful implementation of cross-database materials design. Overall, we report the dielectric properties of 17 materials calculated using ab initio calculations, that were selected in our design workflow. The dielectric materials with high-dielectric properties predicted in this work open up further experimental research opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine learning-based discovery of vibrationally stable materials

The identification of the ground state phases of a chemical space in the convex hull analysis is a key determinant of the synthesizability of materials. Online material databases have been instrumental in exploring one aspect of the synthesizability of many materials, namely thermodynamic stability. However, the vibrational stability, which is another aspect of synthesizability, of new materials is not known. Applying first principles approaches to calculate the vibrational spectra of materials in online material databases is computationally intractable. Here, a dataset of vibrational stability for ~3100 materials is used to train a machine learning classifier that can accurately distinguish between vibrationally stable and unstable materials. This classifier has the potential to be further developed as an essential filtering tool for online material databases that can inform the material science community of the vibrational stability or instability of the materials queried in convex hulls.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Candidate ferroelectrics via ab initio high-throughput screening of polar materials

Ferroelectrics are a class of polar and switchable functional materials with diverse applications, from microelectronics to energy conversion. Computational searches for new ferroelectric materials have been constrained by accurate prediction of the polarization and switchability with electric field, properties that, in principle, require a comparison with a nonpolar phase whose atomic-scale unit cell is continuously deformable from the polar ground state. For most polar materials, such a higher-symmetry nonpolar phase does not exist or is unknown. Here, we introduce a general high-throughput workflow that screens polar materials as potential ferroelectrics. We demonstrate our workflow on 1978 polar structures in the Materials Project database, for which we automatically generate a nonpolar reference structure using pseudosymmetries, and then compute the polarization difference and energy barrier between polar and nonpolar phases, comparing the predicted values to known ferroelectrics. Focusing on a subset of 182 potential ferroelectrics, we implement a systematic ranking strategy that prioritizes candidates with large polarization and small polar-nonpolar energy differences. To assess stability and synthesizability, we combine information including the computed formation energy above the convex hull, the Inorganic Crystal Structure Database id number, a previously reported machine learning-based synthesizability score, and ab initio phonon band structures. To distinguish between previously reported ferroelectrics, materials known for alternative applications, and lesser-known materials, we combine this ranking with a survey of the existing literature on these candidates through Google Scholar and Scopus databases, revealing ~130 promising materials uninvestigated as ferroelectric. Our workflow and large-scale high-throughput screening lays the groundwork for the discovery of novel ferroelectrics, revealing numerous candidates materials for future experimental and theoretical endeavors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Birth of protein folds and functions in the virome

The rapid evolution of viruses generates proteins that are essential for infectivity and replication but with unknown functions, due to extreme sequence divergence. Here, using a database of 67,715 newly predicted protein structures from 4,463 eukaryotic viral species, we found that 62% of viral proteins are structurally distinct and lack homologues in the AlphaFold database. Among the remaining 38% of viral proteins, many have non-viral structural analogues that revealed surprising similarities between human pathogens and their eukaryotic hosts. Structural comparisons suggested putative functions for up to 25% of unannotated viral proteins, including those with roles in the evasion of innate immunity. In particular, RNA ligase T-like phosphodiesterases were found to resemble phage-encoded proteins that hydrolyse the host immune-activating cyclic dinucleotides 3',3'- and 2',3'-cyclic GMP-AMP (cGAMP). Experimental analysis showed that RNA ligase T homologues encoded by avian poxviruses similarly hydrolyse cGAMP, showing that RNA ligase T-mediated targeting of cGAMP is an evolutionarily conserved mechanism of immune evasion that is present in both bacteriophage and eukaryotic viruses. Together, the viral protein structural database and analyses presented here afford new opportunities to identify mechanisms of virus–host interactions that are common across the virome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Author Correction: Informed-Proteomics: open-source software package for top-down proteomics

Correction to: Nature Methods 14, 909–914, https://doi.org/10.1038/nmeth.4388 (2017), published online 7 August 2017. In the version of this article initially published, the authors erroneously reported the search mode that was used for ProSightPC 3.0 in the Online Methods and in Supplementary Table 3. The results presented in Fig. 5 were obtained with ‘absolute mass’ search mode, not ‘biomarker discovery’ search mode. The ‘biomarker discovery’ search mode of ProSightPC 3.0 looks for subsequences of those contained in the annotated proteoform database (e.g., truncated forms from degradation and/or cleavage). This search mode is expected to generate similar numbers of identifications as Informed-Proteomics, but is also expected to take dramatically longer (~480 CPU hours). Unfortunately, because of these heavy computational requirements, the authors were unable to complete an analysis using this search mode. They chose to use ‘absolute mass’ mode to illustrate the effect of search mode and database choice on the results. ‘Absolute mass’ mode is the most restrictive of the search modes illustrated in Fig. 5, as it searches only for proteoforms explicitly listed in the proteoform database within a user-defined mass tolerance. In addition, in the supplementary information originally published online, Supplementary Table 3 incorrectly stated that ProSightPC v3.0 was used in ‘biomarker discovery’ mode. ‘Absolute mass’ mode was the mode actually used in this comparison. These errors have been corrected in the HTML and PDF versions of this article and in the associated supplementary information.

Park, Jungkap↗