Proteomic and direct analysis in real time mass spectrometry analysis of a Native American ceremonial hat

The Analyst ◽  
2019 ◽  
Vol 144 (24) ◽  
pp. 7437-7446 ◽  
Author(s):  
Timothy P. Cleland ◽  
G. Asher Newsome ◽  
R. Eric Hollinger
Keyword(s):  
Mass Spectrometry ◽  
Native American ◽  
Natural History ◽  
Real Time ◽  
Smithsonian Institution ◽  
Direct Analysis ◽  
Mass Spectrometry Analysis ◽  
National Museum ◽  
Spectrometry Analysis

Complementary mass spectrometry analyses were performed to study a broken ceremonial hat of the Tlingit in the collection of the Smithsonian Institution National Museum of Natural History.

scholarly journals Rapid Evaluation of Spermidine from 12 Bean Cultivars by Direct Real-Time Mass Spectrometry Analysis

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2138
Author(s):  
Tao Wu ◽  
Xiaoyu Wu ◽  
Xv Yuan ◽  
Yi Wang ◽  
Wenhua Zhou ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Real Time ◽  
Chromatographic Separation ◽  
Extraction Procedure ◽  
Direct Analysis ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Three Samples ◽  
Sample Extraction ◽  
Ionization Mode

The routine spermidine (SPD) detection method is time-consuming and laborious due to the lengthy chromatographic separation and/or tedious sample derivatization pretreatment. In this study, direct analysis in real-time ionization mode coupled with mass spectrometry (DART-MS) was developed to rapidly determine the SPD content of 12 bean cultivars. The results were compared in detail with those of the classical UHPLC-ESI-QTOF method. After conducting a series of optimizations, a simple sample extraction procedure employing 80% aqueous methanol, was followed by determination of sample extracts directly without any chromatographic separation or prior derivatization. The validated method showed excellent performance with low limits of detection (LOD of 0.025 mg·kg−1) and good recovery rates (102.79–148.44%). The investigation highlighted that the DART-MS method (~1.3 min per three samples) could be used as a high-throughput alternative to the classic UHPLC-ESI-QTOF method (~15 min per three samples).

scholarly journals Assessing the feasibility and acceptability of online measurements of exhaled volatile organic compounds (VOCs) in children with preschool wheeze: a pilot study

2021 ◽  
Vol 5 (1) ◽  
pp. e001003
Author(s):  
Karl Holden ◽  
Misty Makinde ◽  
Michael Wilde ◽  
Matthew Richardson ◽  
Tim Coats ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Preschool Children ◽  
Volatile Organic Compounds ◽  
Real Time ◽  
Organic Compounds ◽  
Mass Spectrometry Analysis ◽  
Breathing Patterns ◽  
Spectrometry Analysis ◽  
Non Invasive ◽  
Volatile Organic

BackgroundInvestigating airway inflammation and pathology in wheezy preschool children is both technically and ethically challenging. Identifying and validating non-invasive tests would be a huge clinical advance. Real-time analysis of exhaled volatile organic compounds (VOCs) in adults is established, however, the feasibility of this non-invasive method in young children remains undetermined.AimTo determine the feasibility and acceptability of obtaining breath samples from preschool children by means of real-time mass spectrometry analysis of exhaled VOCs.MethodsBreath samples from preschool children were collected and analysed in real time by proton transfer reaction–time of flight–mass spectrometry (PTR–TOF–MS) capturing unique breath profiles. Acetone (mass channel m/z 59) was used as a reference profile to investigate the breath cycle in more detail. Dynamic time warping (DTW) was used to compare VOC profiles from adult breath to those we obtained in preschool children.Results16 children were recruited in the study, of which eight had acute doctor-diagnosed wheeze (mean (range) age 3.2 (1.9–4.5) years) and eight had no history of wheezing (age 3.3 (2.2–4.1) years). Fully analysable samples were obtained in 11 (68%). DTW was used to ascertain the distance between the time series of mass channel m/z 59 (acetone) and the other 193 channels. Commonality of 12 channels (15, 31, 33, 41, 43, 51, 53, 55, 57, 60, 63 and 77) was established between adult and preschool child samples despite differences in the breathing patterns.ConclusionReal-time measurement of exhaled VOCs by means of PTR–MS is feasible and acceptable in preschool children. Commonality in VOC profiles was found between adult and preschool children.

scholarly journals Ancestral Caddo Ceramic Artifacts in the Jesse Martin Glasco Collection from Upshur County, Texas, at the National Museum of Natural History, Smithsonian Institution

2016 ◽  
Author(s):  
Timothy K. Perttula
Keyword(s):  
Native American ◽  
Natural History ◽  
Smithsonian Institution ◽  
National Museum

Jesse Martin Glasco, or J. M. Glasco, lived in Gilmer in Upshur County, Texas, between the mid- 1840s and 1886. During most of those years he served as Upshur County surveyor and deputy surveyor, as well as deputy county clerk, postmaster, and tax assessor, and he also represented Upshur County in the 11th Texas legislature. Between 1859-1861 and 1867-1873, he was a meteorological observer for Upshur County for the Smithsonian Institution, and also collected Native American pottery for the Smithsonian’s collections from the Gilmer area.

scholarly journals MealTime-MS: A Machine Learning-Guided Real-Time Mass Spectrometry Analysis for Protein Identification and Efficient Dynamic Exclusion

2020 ◽  
Author(s):  
Alexander R. Pelletier ◽  
Yun-En Chung ◽  
Zhibin Ning ◽  
Nora Wong ◽  
Daniel Figeys ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Real Time ◽  
Mass Spectra ◽  
Protein Identification ◽  
Learning Algorithm ◽  
Mass Spectrometry Data ◽  
Mass Spectrometry Analysis ◽  
Complex Samples ◽  
Spectrometry Analysis ◽  
Abundance Proteins

ABSTRACTMass spectrometry-based proteomics technologies are the prime methods for the high-throughput identification of proteins in complex biological samples. Nevertheless, there are still technical limitations that hinder the ability of mass spectrometry to identify low abundance proteins in complex samples. Characterizing such proteins is essential to provide a comprehensive understanding of the biological processes taking place in cells and tissues. Still today, most mass spectrometry-based proteomics approaches use a data-dependent acquisition strategy, which favors the collection of mass spectra from proteins of higher abundance. Since the computational identification of proteins from proteomics data is typically performed after mass spectrometry analysis, large numbers of mass spectra are typically redundantly acquired from the same abundant proteins, and little to no mass spectra are acquired for proteins of lower abundance. We therefore propose a novel supervised learning algorithm that identifies proteins in real-time as mass spectrometry data are acquired and prevents further data collection from confidently identified proteins to ultimately free mass spectrometry resources to improve the identification sensitivity of low abundance proteins. We use real-time simulations of a previously performed mass spectrometry analysis of a HEK293 cell lysate to show that our approach can identify 92.1% of the proteins detected in the experiment using 66.2% of the MS2 spectra. We also demonstrate that our approach outperforms a previously proposed method, is sufficiently fast for real-time mass spectrometry analysis, and is flexible. Finally, MealTime-MS’ efficient usage of mass spectrometry resources will provide a more comprehensive characterization of proteomes in complex samples.

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