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DOE OSTI2019

Online supercritical fluid extraction mass spectrometry (SFE-LC-FTMS) for sensitive characterization of soil organic matter

We report a novel technical approach for subcritical fluid extraction (SFE) for organic matter characterization in complex matrices such as soil. The custom platform combines on-line SFE with micro-solid phase extraction, nano liquid chromatography (LC), electrospray ionization and Fourier transform mass spectrometry (SFE-LC-FTMS). We demonstrated the utility of SFE-LC-FTMS, including results from both Orbitrap and FTICR MS, for analysis of complex mixtures of organic compounds in a solid matrix by characterizing soil organic matter in peat, a high-carbon soil. For example, in a single experiment, >6000 molecular formulas can be assigned based upon FTICR MS data from 1–50 μL of soil samples (roughly 1–50 mg of soil, dependent on soil density), nearly twice that typically obtained from direct infusion liquid solvent extraction (LSE) from an order of magnitude larger volume of the same soil. The detected species consisted predominately of lipid-like, lignin-like and protein-like compounds, based on their O/C and H/C ratios, with predominantly CHO and CHONP molecular compositions. These results clearly demonstrate that SFE has the potential to effectively extract a variety of molecular species and could become an important member of a suite of extraction methods for studying SOM and other natural organic matter. This is especially true when comprehensive coverage, minimal sample volumes, and high sensitivity are required, or when the presence of organic solvent residue in residual soil is problematic. Lastly, the SFE based extraction protocol could potentially enable spatially resolved characterization of organic matter in soil with a resolution of ~1 mm3 to facilitate studies probing the spatial heterogeneity of soil.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Improved Quality Control Processing of Peptide-centric LC-MS Proteomics Data

In the analysis of differential peptide peak intensities (i.e., abundance measures), LC-MS analyses with poor quality peptide abundance data can bias downstream statistical analyses and hence the biological interpretation for an otherwise high quality data set. Although considerable effort has been placed on assuring the quality of the peptide identification with respect to spectral processing, to date quality assessment of the subsequent peptide abundance data matrix has been limited to a subjective visual inspection of run-by-run correlation or individual peptide components. Identifying statistical outliers is a critical step in the processing of proteomics data as many of the downstream statistical analyses (e.g., ANOVA) rely upon accurate estimates of sample variance, and their results are influenced by extreme values. Results: We describe a multivariate statistical strategy for the identification of LC-MS runs with extreme peptide abundance distributions. Comparison with current method (run-by-run correlation) demonstrates the significantly better rate of identification of outlier runs by the multivariate strategy. Simulation studies also suggest this strategy significantly outperforms correlation alone in the identification of statistically extreme LC-MS runs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

A Comparative Analysis of Computational Approaches to Relative Protein Quantification Using Peptide Peak Intensities in Label-free LC-MS Proteomics Experiments

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred from one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2016

Large-Scale and Deep Quantitative Proteome Profiling Using Isobaric Labeling Coupled with Two-Dimensional LC-MS/MS

Comprehensive, quantitative information on abundances of proteins and their post-translational modifications (PTMs) can potentially provide novel biological insights into diseases pathogenesis and therapeutic intervention. Herein, we introduce a quantitative strategy utilizing isobaric stable isotope-labelling techniques combined with two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) for large-scale, deep quantitative proteome profiling of biological samples or clinical specimens such as tumor tissues. The workflow includes isobaric labeling of tryptic peptides for multiplexed and accurate quantitative analysis, basic reversed-phase LC fractionation and concatenation for reduced sample complexity, and nano-LC coupled to high resolution and high mass accuracy MS analysis for high confidence identification and quantification of proteins. This proteomic analysis strategy has been successfully applied for in-depth quantitative proteomic analysis of tumor samples, and can also be used for integrated proteome and PTM characterization, as well as comprehensive quantitative proteomic analysis across samples from large clinical cohorts.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2022

Tag you're it: Application of stable isotope labeling and LC-MS to identify the precursors of specialized metabolites in plants

Untargeted liquid chromatography/mass spectrometry (LC-MS) can contribute a comprehensive and unbiased picture of the metabolic space of plants. These data can be used to quantify natural metabolite variation for genome wide association studies, to compare global metabolic responses from environmental or genetic perturbations, and to identify previously undescribed metabolites in Nature. A major limitation with untargeted metabolomics is the classification and identification of the thousands of metabolite features that can be detected in a single analytical run. Isotopic labeling improves the informational value of these datasets by categorizing metabolites as being derived from specific upstream precursors and/or to known metabolic pathways. When a 13 C-labeled precursor is fed to either a plant or tissue, the downstream metabolites produced from it have a higher m/z value than the molecules in the pre-existing pool, generating an m/z peak pair that can be specifically identified within the MS data. In this paper, we outline methods and principles to consider when supplementing untargeted MS data with isotopic labeling, including how to choose the appropriate isotopic label, grow and feed plant tissues to maximize label uptake and incorporation into derivatives, optimize LC-MS methods, and interpret the resulting labeling data. Although the focus here is on annotation of amino acid-derived metabolites using LC-MS, we anticipate that the methods are generally adaptable to other precursors, plant species, and chromatographic approaches.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Metabolic profiling associated with autophagy of human placenta-derived mesenchymal stem cells by chemical isotope labeling LC−MS

Autophagy has been reported to have a pivotal role in maintaining stemness, regulating immunomodulation and enhancing the survival of mesenchymal stem cells (MSCs). However, the effect of autophagy on MSC metabolism is largely unknown. Here, we report a workflow for examining the impact of autophagy on human placenta-derived MSC (hPMSC) metabolome profiling with chemical isotope labeling (CIL) LC−MS. Rapamycin or 3-methyladenine was successfully used to induce or inhibit autophagy, respectively. Then, {sup 12}C- and {sup 13}C-dansylation labeling LC−MS were used to profile the amine/phenol submetabolome. A total of 935 peak pairs were detected and 50 metabolites were positively identified using the dansylation metabolite standards library, and 669 metabolites were putatively identified based on an accurate mass match in metabolome databases. {sup 12}C/{sup 13}C-p-dimethylaminophenacyl bromide labeling LC−MS was used to analyze the carboxylic acid submetabolome; 4736 peak pairs were detected, among which 33 metabolites were positively identified in the dimethylaminophenacyl metabolite standards library, and 3007 metabolites were putatively identified. PCA/OPLS-DA analysis combined with volcano plots and Venn diagrams was used to determine the significant metabolites. Metabolites pathway analysis demonstrated that hPMSCs appeared to generate more ornithine with the arginine and proline metabolism pathway and utilized more pantothenic acid to synthesize acetyl-CoA in the beta-alanine metabolism pathway when autophagy was activated. Meanwhile, acetyl-CoA conversion to fatty acids led to accumulation in the fatty acid biosynthesis pathway. In contrast, when autophagy was suppressed, a reduction in metabolites demonstrated weakened metabolic activity in these metabolic pathways. Our research provides a more comprehensive understanding of hPMSC metabolism associated with autophagy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Separation of thorium (IV) from lanthanide concentrate (LC) and water leach purification (WLP) residue

Thorium (IV) content in industrial residue produced from rare earth elements production industry is one of the challenges to Malaysian environment. Separation of thorium from the lanthanide concentrate (LC) and Water Leach Purification (WLP) residue from rare earth elements production plant is described. Both materials have been tested by sulphuric acid and alkaline digestions. Th concentrations in LC and WLP were determined to be 1289.7 ± 129 and 1952.9±17.6 ppm respectively. The results of separation show that the recovery of Th separation from rare earth in LC after concentrated sulphuric acid dissolution and reduction of acidity to precipitate Th was found 1.76-1.20% whereas Th recovery from WLP was less than 4% after concentrated acids and alkali digestion processes. Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) was used to determine Th concentrations in aqueous phase during separation stages. This study indicated that thorium maybe exists in refractory and insoluble form which is difficult to separate by these processes and stays in WLP residue as naturally occurring radioactive material (NORM)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2013

LC-IMS-MS Feature Finder. Detecting Multidimensional Liquid Chromatography, Ion Mobility, and Mass Spectrometry Features in Complex Datasets

We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time, and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Carbon dioxide (CO2) flux, amplicon sequencing and liquid chromatography–mass spectrometry (LC-MS) data for pyrogenic organic matter (PYOM) amended soil incubations in lab, Madison, WI, 2021-22

This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

Environmental Molecular Sciences Laboratory↗

NASA NTRS2008

Assessment of the LC-2 Prelaunch Fatigue Spectra of the CM-to-SM Flange Weld

The pad stay and rollout components of the Ares I-X life cycle can generate cyclic stress oscillations to the vehicle that could initiate and grow fatigue cracks from weld defects. The Ares I-X Project requested that a study be performed to determine if stabilization of the vehicle is required to reduce the stresses that could initiate and grow fatigue cracks at the flange-to-skin weld of the Command Module (CM) and Service Module (SM) interface. A fatigue crack growth analysis was conducted that used loads (LC-2) and stress analyses developed by the Ares I-X Project and utilized material data and analysis methods developed by a critical initial flaw size (CIFS) analysis conducted by NASA Engineering and Safety Center (NESC) for the Upper Stage Simulator (USS) of the Ares I-X vehicle. A full CIFS analysis for the CM-to-SM flange-to-skin weld was not performed because the full flight spectrum was not provided and was not necessary to answer the question posed by the Ares I-X Project. Instead, an approach was developed to determine if the crack growth due to the pad stay and rollout components of the flight spectrum would adversely influence the CIFS. The approach taken used a number of conservative assumptions that eliminated the need for high-fidelity analyses and additional material testing, but still provided a bounding solution for the uncertainties of the problem. The results from this analysis indicate that the LC-2 pad stay and rollout spectrum components would not produce significant fatigue crack growth on the CM-to-SM flange-to-skin weld. Thus, from a fatigue crack growth standpoint, no stabilization is required to reduce the LC-2 pad stay and rollout cyclic stresses on the CM-to-SM flange-to-skin weld.

Dawicke, David S.↗

NASA NTRS2016

A Simple and Sensitive LC-MS/MS Method for the Determination of Free 8-Hydroxy-2'-Deoxyguanosine in Human Urine

Urinary free 8-hydroxy-2'-deoxyguanosine (8OHdG), an oxidized product of DNA, and is frequently chosen as a biomarker of oxidative stress in humans, including studies of oxidative DNA damage during space flight. It is challenging to accurately and efficiently quantify urinary free 8OHdG in large scale human studies. LC-MS/MS is emerging as a preferable analytical technique owing its high sensitivity, selectivity and efficiency, compared to some traditional methods such as ELISA and HPLC. A simple and sensitive LC-MS/MS method has been developed for the determination of free 8OHdG in human urine. Sample preparation was done by solid phase extraction with a Waters Oasis HLB 96 well plate. A Waters Alliance 2795 HT Separation Module combined with a Quattro Micro tandem mass spectrometer was used as the LC-MS/MS system. The runtime of one injection can be less than 5 minutes using a reversed phase C18 column and an isocratic flow of methanol/water. ESI positive ions were quantified in the multiple reaction modes (MRM) using m/z 284 yields 168 for 8OHdG and m/z 289 yields173 for stable isotope labeled internal standard [(15)N5] 8OHdG. With this method for 8OHdG, a lower limit of quantitation of 1.0 nM (0.28 ng/mL) has been achieved using 100 microliter urine sample. The analytical range is between 1.0 and 100 nM with a correlation coefficient greater than or equal to 0.99. Good reproducibility can be obtained with intra-assay and inter-assay CVs less than or equal to 10% for 8OHdG spiked urine QC samples. This method can be used in high-throughput routine analysis of free 8OHdG in human urine.

Wang, Zuwei↗

DOE OSTI2014

Untargeted metabolomics studies employing NMR and LC–MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

Interactions between species are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC–MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. Lastly, this finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC–MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

LC-MEMENTO: A Memory Model for Accelerated Architectures

With the advent of heterogeneous architectures, in particular, with the ubiquity of multi-GPU systems, it is becoming increasingly important to manage device memory efficiently in order to reap the benefits of the additional core count. To date, such responsibility mainly falls on the programmer where device-to-host data communication (and vice versa), if not done properly, may incur costly memory transfer operations and synchronization. The problem may be compounded by additional requirement to maintain system-wide memory consistency that may involve expensive synchronization overhead. In this paper, we present Location Consistency Memory Model for Enhanced Transfer Operations (LC-MEMENTO). This framework considers incorporating runtime techniques for multi-GPU memory management to support relaxed synchronization semantics and memory transfer operations automatically. Specifically, we implement a relaxed form of a memory consistency model based on the Location Consistency (LC) in an Asynchronous Many-Task Runtime (ARTS) and demonstrate that, this memory model enables additional optimization opportunities for the three representative applications encompassing different computational patterns (scientific computation, graphs, data streaming, etc.).

Memory Models, Accelerators, Adaptive Optimization↗

DOE OSTI2012

Evaluation of the sensitizing potential of antibiotics in vitro using the human cell lines THP-1 and MUTZ-LC and primary monocyte‐derived dendritic cells

Since the 7th amendment to the EU cosmetics directive foresees a complete ban on animal testing, alternative in vitro methods have been established to evaluate the sensitizing potential of small molecular weight compounds. To find out whether these novel in vitro assays are also capable to predict the sensitizing potential of small molecular weight drugs, model compounds such as beta-lactams and sulfonamides – which are the most frequent cause of adverse drug reactions – were co-incubated with THP-1, MUTZ-LC, or primary monocyte‐derived dendritic cells for 48 h and subsequent expression of selected marker genes (IL-8, IL-1β, CES1, NQO1, GCLM, PIR and TRIM16) was studied by real time PCR. Benzylpenicillin and phenoxymethylpenicillin were recognized as sensitizing compounds because they are capable to induce the mRNA expression of these genes in moDCs and, except for IL-8, in THP-1 cells but not in MUTZ-LC. Ampicillin stimulated the expression of some marker genes in moDCs and THP-1 cells. SMX did not affect the expression of these genes in THP-1, however, in moDCs, at least PIR was enhanced and there was an increase of the release of IL-8. These data reveal that novel in vitro DC based assays might play a role in the evaluation of the allergenic potential of novel drug compounds, but these systems seem to lack the ability to detect the sensitizing potential of prohaptens that require metabolic activation prior to sensitization and moDCs seem to be superior with regard to the sensitivity compared with THP-1 and MUTZ-3 cell lines. -- Highlights: ► We tested the sensitizing potential of small molecular weight drugs in vitro. ► In vitro assays were performed with moDCs and THP-1 cells. ► Beta-lactam antibiotics can be recognized as sensitizing compounds. ► They affect the expression of metabolic enzymes, cytokines and transcription factors. ► Sulfamethoxazole has no measurable effect on THP-1 cells and moDCs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Part 3: Solid phase extraction of Russian VX and its chemical attribution signatures in food matrices and their detection by GC-MS and LC-MS [Extraction and Detection of Russian VX and its Chemical Attribution Signatures in Food and Environmental Matrices at LLNL]

Chemical attribution signatures indicative of O-isobutyl S-(2-diethylaminoethyl) methylphosphonothioate (Russian VX) synthetic routes were investigated in spiked food samples. Attribution signatures were identified using a multifaceted approach: Russian VX was synthesized using six synthetic routes and the chemical attribution signatures identified by GC-MS and LC-MS. Three synthetic routes were then down selected and spiked into complex matrices: bottled water, baby food, milk, liquid eggs, and hot dogs. Sampling and extraction methodologies were developed for these materials and used to isolate the attribution signatures and Russian VX from each matrix. Recoveries greater than 60% were achieved for most signatures in all matrices; some signatures provided recoveries greater than 100%, indicating some degradation during sample preparation. A chemometric model was then developed and validated with the concatenated data from GC-MS and LC-MS analyses of the signatures; the classification results of the model were > 75% for all samples. Finally, this work is part three of a three-part series in this issue of the United States-Sweden collaborative efforts towards the understanding of the chemical attribution signatures of Russian VX in crude materials and in food matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Development of a Universal Second-Tier Newborn Screening LC–MS/MS Method for Amino Acids, Lysophosphatidylcholines, and Organic Acids

First-tier MS-based newborn screening by flow injection analysis can have high presumptive positive rates, often due to isomeric/isobaric compounds or poor biomarker specificity. These presumptive positive samples can be analyzed by second-tier screening assays employing separations such as liquid chromatography–mass spectrometry (LC–MS/MS), which increases test specificity and drastically reduces false positive referrals. The ability to screen for multiple disorders in a single multiplexed test simplifies workflows and maximizes public health laboratories’ resources. In this study, we developed and validated a highly multiplexed second-tier method for dried blood spots using a hydrophilic interaction liquid chromatography (HILIC) column coupled to an MS/MS system. The LC–MS/MS method was capable of simultaneously detecting second-tier biomarkers for maple syrup urine disease, homocystinuria, methylmalonic acidemia, propionic acidemia, glutaric acidemia type 1, glutaric acidemia type 2, guanidinoacetate methyltransferase deficiency, short-chain acyl-CoA dehydrogenase deficiency, adrenoleukodystrophy, and Pompe disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-Peptide

Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here, in this study, we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: (i) quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteoforms typically introduced when using a single antibody; (ii) Lys-C digestion producing unique signature peptides for each proteoform, and (iii) trapping-nano-LC coupled with FAIMS/dCV-MS for an ultrasensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing S/N. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive (n = 20) and new-onset type 1 diabetes (T1D, n = 19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the β-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.

Shen, Qingqing [University at Buffalo, NY (United ↗