Analysis of major fatty acids from matched plasma and serum samples reveals highly comparable absolute and relative levels
Bibliographic record
Abstract
Measuring fatty acid (FA) levels in blood as a risk factor for chronic disease has been studied extensively. Previous research has used either plasma or serum samples to examine these associations. However, whether results from plasma and serum samples can be compared remains unclear, as differences in methodology related to the separation of plasma and serum from whole blood may impact FA levels. This study analyzed the individual FA content of matched plasma and serum samples in both absolute (μg/mL) and relative percent (%) composition. Analyses were performed using archived fasted morning samples from the Florey Adelaide Male Ageing Study (FAMAS). Matched plasma and serum samples were available from 98 male subjects aged 40-85. Total FA were analyzed by gas-liquid chromatography equipped with a flame ionization detector (GLC-FID). Analyses comprised of over 60 FA including major FA such as Palmitic Acid (PA), Palmitoleic acid (POA), Stearic Acid (SA), Oleic Acid (OA), Linoleic Acid (LNA), alpha-linolenic acid (ALA), Eicosapentaenoic acid (EPA), Arachidonic Acid (ARA), and Docosahexaenoic acid (DHA). Differences between groups was determined by t-test. Correlation and Bland-Altman analyses were also performed to examine the relationship between plasma and serum samples. There were no significant differences between major plasma and serum fatty acids expressed in μg/mL and relative % composition. Correlation analysis determined a strong and significantly positive association (r ≥ 0.65, p < 0.05) between major plasma and serum FA in absolute and relative terms. Bland-Altman analysis further supported the strong agreement between plasma and serum values in both absolute and relative terms. These findings demonstrate that studies reporting plasma or serum fatty acid analyzed by GLC-FID can be compared with one another.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".