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Palmitic and Stearic Free Fatty Acids Are Consistently Found in Materials used for Dried Blood Spot Collection

2017· article· en· W4389020697 on OpenAlexaffabout
Jan Gunash, Juan J. Aristizabal Henao, Ken D. Stark

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChromatographyChemistryFormic acidFatty acidStearic acidDried blood spotPalmitic acidBiochemistryOrganic chemistry

Abstract

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Background Dried blood spotting has been used to collect samples for fatty acid analysis, particularly when access to analytical laboratories or ultra‐cold storage is limited. However, the materials used to collect dried blood spots are often contaminated with lipids and/or fatty acids. Objective To measure background/containment fatty acid and lipids on materials used to collect dried blood spots. Methods Three materials used for dried blood spot collection that included 903 protein saver cards (Fischer Scientific, St. Louis, USA), chromatography paper cut into strips (Analtech Inc., Newark, DE), and novel Mitra Microsamplers (Neoteryx, California, USA). Blank collection materials as purchased were handled with nitrile gloves and preexisting lipids were extracted using 2:1 chloroform:methanol (v/v) solution. Lipid extracts were divided into two, with one portion for gas chromatography (GC) analysis of fatty acids and the other portion for lipidomic analyses using ultra‐high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC‐MS/MS) in a quadrupole‐orbitrap system (Q‐Exactive, Thermo Scientific, New York, USA). Fatty acid methyl esters were prepared for GC analysis by direct transesterification of the lipid extracts using boron trifluoride. Lipid extracts were dried and re‐suspended in 65:35:5 acetonitrile:isopropanol:water + 0.1% formic acid and analyzed using a 47‐minute reversed‐phase UHPLC multi‐step binary protocol with top‐5 data dependent MS/MS acquisition. Samples were run twice, once under positive ESI‐MS/MS and once under negative ESI‐MS/MS to enable the identification of compounds that preferentially ionize with different polarities. Results GC analysis identified 0.64±0.05 μg of palmitic acid (C16:0) and 0.88±0.04 μg stearic acid (C18:0) per 6mm punch from 903 protein saver cards, 0.97±0.08 μg 16:0 and 1.43±0.16 μg 18:0 per 6mm punch of Whatman chromatography paper and 0.64±0.08 μg 16:0 and 0.88±0.10 μg 18:0 per Mitra tip. In the positive ESI‐MS/MS analyses, scanning for fragment losses of phospholipids (choline, ethanolamine, serine head groups) did not result in extracted ion chromatograms that would indicate that these compounds were present. Neutral‐loss scanning of fatty acids like palmitate and stearate in positive ESI also showed no evidence of other complex lipids such as triacylglycerols or cholesteryl esters in the blank samples. However, negative ESI‐MS/MS experiments confirmed that the palmitate and stearate that were identified using GC are found as free fatty acids and not as part of complex lipids. Conclusions Materials used to collect dried blood spots appear consistently contaminated with palmitic and stearic free fatty acids. GC determinations of fatty acids from dried blood spots samples need to consider this contamination and/or take steps to prewash sample collecting materials. For lipidomic analysis, these contaminants can be ignored if complex lipids and not free fatty acids are being examined. Support or Funding Information This work was supported by a Natural Sciences and Engineering Research Council (NSERC) Discovery grant (327149, to K.D.S), and an NSERC doctoral scholarship to J.J.A.H. K.D.S. is also supported by a Canada Research Chair in Nutritional Lipidomics.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.296
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2017
Admission routes2
Has abstractyes

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