Palmitic and Stearic Free Fatty Acids Are Consistently Found in Materials used for Dried Blood Spot Collection
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".