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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

LC–MS Proteomics Analysis of the Insulin/IGF-1-Deficient Caenorhabditis elegans daf-2(e1370) Mutant Reveals Extensive Restructuring of Intermediary Metabolism

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including the expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass spectrometry (LC–MS)-based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the upregulation of many core intermediary metabolic pathways. These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid β-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complexes I, II, III, and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative of spatiotemporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. Finally, this restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves and possibly also shunting metabolites through alternative energy-generating pathways to sustain longevity.

Caenorhabditis elegans↗
DOE OSTI2017

Targeted Metabolomics of the Phenylpropanoid Pathway in Arabidopsis thaliana using Reversed Phase Liquid Chromatography Coupled with Tandem Mass Spectrometry: Measuring Lignin Precursors by LC-MS

The phenylpropanoid pathway is a source of a diverse group of compounds derived from phenylalanine, many of which are involved in lignin biosynthesis and serve as precursors for the production of valuable compounds, such as coumarins, flavonoids, and lignans. Consequently, recent efforts have been invested in mechanistically understanding monolignol biosynthesis, making the quantification of these metabolites vital. To develop an improved and comprehensive analytical method for (i) extensively profiling, and (ii) accurately quantifiying intermediates of the monolignol biosynthetic network, using Arabidopsis thaliana as a model system. A liquid chromatography-tandem mass spectrometry with electrospray ionization was developed to quantify phenylpropanoid metabolites in Arabidopsis wildtype and cinnamoyl CoA reductase1 (CCR1) deficient lines (ccr1). Vortexing at high temperatures (65°C) enhanced release of phenylpropanoids, specifically the more hydrophobic compounds. A pH of 5.3 and ammonium acetate buffer concentration of 2.5 mM resulted in an optimal analyte response across standards. Ion suppression was estimated using standard spike recovery studies for accurate quantitation. The optimized method was used to profile Arabidopsis wildtype and ccr1 stems. An increase in hydroxycinnamic acid derivatives and a decrease in the hydroxycinnamyl aldehydes and alcohols in ccr1 lines, supports a shift of flux from lignin synthesis to other secondary metabolites and phenylpropanoid derivatives. Compared to existing targeted profiling techniques, our method is capable of quantifying a wider range of intermediates (15 out of 22 in WT Arabidopsis stems) at low in vivo concentrations (~50 pmol/g-FW for certain compounds), while requiring minimal sample preparation.

09 BIOMASS FUELS↗
DOE OSTI2012

Label-Free Quantitative LC–MS Proteomics of Alzheimer’s Disease and Normally Aged Human Brains

uantitative proteomics analysis of cortical samples of 10 Alzheimer’s disease (AD) brains versus 10 normally aged brains was performed by following the accurate mass and time tag (AMT) approach with the high resolution LTQ Orbitrap mass spectrometer. More than 1400 proteins were identified and quantitated. A conservative approach of selecting only the consensus results of four normalization methods was suggested and used. A total of 197 proteins were shown to be significantly differentially abundant (p-values <0.05, corrected for multiplicity of testing) in AD versus control brain samples. Thirty-seven of these proteins were reported as differentially abundant or modified in AD in previous proteomics and transcriptomics publications. The rest to the best of our knowledge are new. Mapping of the discovered proteins with bioinformatic tools revealed significant enrichment with differentially abundant proteins of pathways and processes known to be important in AD, including signal transduction, regulation of protein phosphorylation, immune response, cytoskeleton organization, lipid metabolism, energy production, and cell death.

Alzheimer’s disease, brain, cortical samples, prot↗
DOE OSTI2020

Engineered Cementitious Composites (ECC) with limestone calcined clay cement (LC 3 )

Recent research have recognized that coupled use of calcined clay, limestone and cement clinker in concrete is viable to reduce environmental footprints at manufacture and to enhance material durability. In this study, a novel application of the limestone calcined clay cement (LC 3 ) is demonstrated by substituting the Ordinary Portland Cement (OPC) in Engineered Cementitious Composites (ECC). The composite mechanical properties including σ-δ and σ-ε relationships and residual crack widths were evaluated to 28 days under uniaxial tension. Matrix chemistry was characterized using thermogravimetric analysis and X-ray diffraction, while the pore structure of matrices and composites was analyzed using mercury intrusion porosimetry. The LC 3 -based ECC showed more rapid early strength development but lower 28-day strength (~32 MPa) due to a 20% higher water-to-solid ratio for attaining adequate workability and fiber dispersion. Nevertheless, the tensile strain capacity of LC 3 -based ECC achieved over 6% with an average residual crack width less than 50 μm. Additionally, the composite pore structure exhibited a decreasing volume fraction of large pores and voids (>100 nm) after substituting LC 3 for OPC. Here, the use of LC 3 marginally decreased the embodied material energy and cost, but led to about 32% and 28% reductions in CO 2 emissions compared to traditional OPC-based ECC and concrete, respectively. As a preliminary study, LC 3 -based ECC shows promise as a greener ductile concrete compared with OPC-based ECC.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Thorium, uranium and rare earth elements content in lanthanide concentrate (LC) and water leach purification (WLP) residue of Lynas advanced materials plant (LAMP)

Lynas Advanced Materials Plant (LAMP) has been licensed to produce the rare earths elements since early 2013 in Malaysia. LAMP processes lanthanide concentrate (LC) to extract rare earth elements and subsequently produce large volumes of water leach purification (WLP) residue containing naturally occurring radioactive material (NORM). This residue has been rising up the environmental issue because it was suspected to accumulate thorium with significant activity concentration and has been classified as radioactive residue. The aim of this study is to determine Th-232, U-238 and rare earth elements in lanthanide concentrate (LC) and water leach purification (WLP) residue collected from LAMP and to evaluate the potential radiological impacts of the WLP residue on the environment. Instrumental Neutron Activation Analysis and γ-spectrometry were used for determination of Th, U and rare earth elements concentrations. The results of this study found that the concentration of Th in LC was 1289.7 ± 129 ppm (5274.9 ± 527.6Bq/kg) whereas the Th and U concentrations in WLP were determined to be 1952.9±17.6 ppm (7987.4 ± 71.9 Bq/kg) and 17.2 ± 2.4 ppm respectively. The concentrations of Th and U in LC and WLP samples determined by γ- spectrometry were 1156 ppm (4728 ± 22 Bq/kg) and 18.8 ppm and 1763.2 ppm (7211.4 Bq/kg) and 29.97 ppm respectively. This study showed that thorium concentrations were higher in WLP compare to LC. This study also indicate that WLP residue has high radioactivity of {sup 232}Th compared to Malaysian soil natural background (63 - 110 Bq/kg) and come under preview of Act 304 and regulations. In LC, the Ce and Nd concentrations determined by INAA were 13.2 ± 0.6% and 4.7 ± 0.1% respectively whereas the concentrations of La, Ce, Nd and Sm in WLP were 0.36 ± 0.04%, 1.6%, 0.22% and 0.06% respectively. This result showed that some amount of rare earth had not been extracted and remained in the WLP and may be considered to be reextracted.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

metabCombiner 2.0: Disparate Multi-Dataset Feature Alignment for LC-MS Metabolomics

Liquid chromatography–high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a “primary” feature list is used as a template for matching compounds in “target” feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution’s in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Predicting the rheology of limestone calcined clay cements (LC 3 ): Linking composition and hydration kinetics to yield stress through Machine Learning

The physicochemical characteristics of calcined clay influence yield stress of limestone calcined clay cements (LC 3 ), but the independent influences the clay's physical and chemical characteristics as well as the effect of other variables on LC 3 rheology are less well-understood. Further, a relationship between LC 3 hydration kinetics and yield stress – important for informing mixture design – has not yet been established. Here, rheological properties were determined in pastes with varying water-to-solid ratio (w/s), constituent mass ratios (PC:metakaolin:limestone), limestone particle size and gypsum content. From these data, an ML model developed allowed the independent examination of the different mechanisms by which metakaolin fraction influences yield stress of LC 3 , identifying four predictors – packing index, Al 2 O 3 /SO 3 , total particle density and metakaolin fraction relative to limestone (MK/LS) – most significant for predicting LC 3 yield stress. A methodology based on kernel smoothing also identified hydration kinetics parameters best correlated with yield stress.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗
DOE OSTI2018

Increasing the Separation Capacity of Intact Histone Proteoforms Chromatography Coupling Online Weak Cation Exchange-HILIC to Reversed Phase LC UVPD-HRMS

Top-down proteomics is an emerging analytical strategy to characterize combinatorial protein post-translational modifications (PTMs). However, sample complexity and small mass differences between chemically closely related proteoforms often limit the resolution attainable by separations employing a single liquid chromatographic (LC) principle. In particular, for ultra-modified proteins like histones, extensive and time-consuming fractionation is needed to achieve deep proteoform coverage. Herein, we present the first online nano-flow comprehensive two-dimensional liquid chromatography (nLC×LC) platform top-down mass spectrometry analysis of histone proteoforms. The described two-dimensional LC system combines weak cation exchange chromatography under hydrophilic interaction LC conditions (i.e. charge- and hydrophilicity-based separation) with reversed phase liquid chromatography (i.e. hydrophobicity-based separation). The two independent chemical selectivities were run at nanoflows (300 nL/min) and coupled online with high-resolution mass spectrometry employing ultraviolet photodissociation (UVPD-HRMS). The nLC×LC workflow increased the number of intact protein masses observable relative to one-dimensional approaches and allowed characterization of hundreds of proteforms starting from limited sample quantities (~1.5 µg).

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

Analysis, identification and confirmation of synthetic opioids using chloroformate chemistry: Retrospective detection of fentanyl and acetylfentanyl in urine and plasma samples by EI-GC-MS and HR-LC-MS

Electron Impact Gas Chromatography-Mass Spectrometry (EI-GC-MS) and High Resolution Liquid Chromatography-Mass Spectrometry (HR-LC-MS) have been used in the analysis of products arising from the trichloroethoxycarbonylation of fentanyl and acetylfentanyl in urine and plasma matrices. The method involves the initial extraction of both synthetic opioids separately from the matrices followed by detection of the unique products that arise from their reaction with 2,2,2-trichloroethoxycarbonyl chloride (Troc-Cl), namely Troc-norfentanyl and Troc-noracetylfentanyl. The optimized protocol was successfully evaluated for its efficacy at detecting these species formed from fentanyl and acetylfentanyl when present at low and high levels in urine (fentanyl: 5 and 10 ng/mL and acetylfentanyl: 20 and 100 ng/mL) and plasma (fentanyl: 10 and 20 ng/mL and acetylfentanyl: 50 and 200 ng/mL), values that reflect levels reported in overdose victims. The HR-LC-MS method’s LOQ (limit of quantitation) for the Troc-norfentanyl and Troc-noracetylfentanyl products was determined to be ~10 ng/mL for both species. Even though the superiority in the detection of these species by HR-LC-MS over EI-GC-MS, the latter method proved to be important in the detection of the second product from the reaction, namely 2-phenylethyl chloride that is crucial in the determination of the original opioid. This observation highlights the importance of using complimentary analytical techniques in the analysis of a sample, whether biological or environmental in nature. The method herein serves as a complementary, qualitative confirmation for the presence of a fentanyl in collected urine, plasma and by extension other biological samples amenable to the common extraction procedures described for opioid analysis. More importantly, the method’s main strength comes from its ability to react with unknown fentanyls to yield products that can be not only detected by EI-GC-MS and HR-LC-MS but can then be used to retrospectively identify an unknown fentanyl.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If they are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Asymptotic geometric phase and purity for phase qubit dispersively coupled to lossy LC circuit

Analytical descriptions of the geometric phases (GPs) for the total system and subsystems are studied for a current biased Josephson phase qubit strongly coupled to a lossy LC circuit in the dispersive limit. It is found that, the GP and purity depend on the damping parameter which leads to the phenomenon of GP death. Coherence parameter delays the phenomenon of a regular sequence of deaths and births of the GP. The asymptotic behavior of the GP and the purity for the qubit-LC resonator state closely follow that for the qubit state, but however, for the LC circuit these asymptotic values are equal to zero. - Highlights: > The model of a current biased Josephson phase qubit, strongly coupled to loss LC circuit, is considered. > Analytical descriptions of the geometric phase (GP) of this model, in the dispersive limit, are studied. > The GP and purity depend on the dissipation which leads to the GP death phenomenon. > Coherence parameter delays the phenomenon of a regular sequence of deaths and births of the GP.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

ADMX SLIC: Results from a Superconducting $\textit{LC}$ Circuit Investigating Cold Axions

Axions are a promising cold dark matter candidate. Haloscopes, which use the conversion of axions to photons in the presence of a magnetic field to detect axions, are the basis of microwave cavity searches such as the Axion Dark Matter eXperiment (ADMX). To search for lighter, low frequency axions in the sub-2 × 10 –7 eV (50 MHz) range, a tunable lumped-element $\textit{LC}$ circuit has been proposed. For the first time, through ADMX SLIC (Superconducting $\textit{LC}$ Circuit Investigating Cold Axions), a resonant $\textit{LC}$ circuit was used to probe this region of axion mass-coupling space. The detector used a superconducting $\textit{LC}$ circuit with piezoelectric driven capacitive tuning. The axion mass and corresponding frequency ranges 1.7498–1.7519 × 10 –7 eV (42.31–42.36 MHz), 1.7734–1.7738 × 10 –7 eV (42.88–42.89 MHz), and 1.8007–1.8015 × 10 –7 eV (43.54–43.56 MHz) were covered at magnetic fields of 4.5 T, 5.0 T, and 7.0 T, respectively. Exclusion results from the search data, for coupling below 10 –12 GeV –1 , are presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Use of carbonyldiimidazole as a derivatization agent for the detection of pinacolyl alcohol, a forensic marker for Soman, by EI-GC–MS and LC-HRMS in official OPCW proficiency test matrices

Pinacolyl alcohol (PA), a key forensic marker for the nerve agent Soman (GD), is a particularly difficult analyte to detect by various analytical methods. In this work, we have explored the reaction between PA and 1,1'-carbonyldiimidazole (CDI) to yield pinacolyl 1H-imidazole-1-carboxylate (PIC), a product that can be conveniently detected by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Regarding its GC–MS profile, this new carbamate derivative of PA possesses favorable chromatographic features such as a sharp peak and a longer retention time (RT = 16.62 min) relative to PA (broad peak and short retention time, RT = 4.1 min). Additionally, the derivative can also be detected by LC-HRMS, providing an avenue for the analysis of this chemical using this technique where PA is virtually undetectable unless present in large concentrations. From a forensic science standpoint, detection of this low molecular weight alcohol signals the past or latent presence of the nerve agent Soman (GD) in a given matrix (i.e., environmental or biological). The efficiency of the protocol was tested separately in the analysis and detection of PA by EI-GC–MS and LC-HRMS when present at a 10 μg/mL in a soil matrix featured in the 44th PT and in a glycerol-rich liquid matrix featured in the 48th Official Organization for the Prohibition of Chemical Weapons (OPCW) Proficiency Test when present at a 5 μg/mL concentration. In both scenarios, PA was successfully transformed into PIC, establishing the protocol as an additional tool for the analysis of this unnatural and unique nerve agent marker by GC–MS and LC-HRMS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗
DOE OSTI2012

Simple Sodium Dodecyl Sulfate-Assisted Sample Preparation Method for LC-MS-based Proteomic Applications

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for highly efficient biological sample extraction; however, SDS presents a significant challenge to LC-MS-based proteomic analyses due to its severe interference with reversed-phase LC separations and electrospray ionization interfaces. This study reports a simple SDS-assisted proteomic sample preparation method facilitated by a novel peptide-level SDS removal protocol. After SDS-assisted protein extraction and digestion, SDS was effectively (>99.9%) removed from peptides through ion substitution-mediated DS- precipitation with potassium chloride (KCl) followed by {approx}10 min centrifugation. Excellent peptide recovery (>95%) was observed for less than 20 {mu}g of peptides. Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage from this SDS-assisted protocol was comparable to or better than those obtained from other standard proteomic preparation methods in both mammalian tissues and bacterial samples. These results suggest that this SDS-assisted protocol is a practical, simple, and broadly applicable proteomic sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.

59 BASIC BIOLOGICAL SCIENCES↗