Comparison of Proteins in Whole Blood and Dried Blood Spot Samples by LC/MS/MS
Why this work is in the frame
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Bibliographic record
Abstract
Dried blood spot (DBS) sampling methods are desirable for population-wide biomarker screening programs because of their ease of collection, transportation, and storage. Immunoassays are traditionally used to quantify endogenous proteins in these samples but require a separate assay for each protein. Recently, targeted mass spectrometry (MS) has been proposed for generating highly-multiplexed assays for biomarker proteins in DBS samples. In this work, we report the first comparison of proteins in whole blood and DBS samples using an untargeted MS approach. The average number of proteins identified in undepleted whole blood and DBS samples by liquid chromatography (LC)/MS/MS was 223 and 253, respectively. Protein identification repeatability was between 77%-92% within replicates and the majority of these repeated proteins (70%) were observed in both sample formats. Proteins exclusively identified in the liquid or dried fluid spot format were unbiased based on their molecular weight, isoelectric point, aliphatic index, and grand average hydrophobicity. In addition, we extended this comparison to include proteins in matching plasma and serum samples with their dried fluid spot equivalents, dried plasma spot (DPS), and dried serum spot (DSS). This work begins to define the accessibility of endogenous proteins in dried fluid spot samples for analysis by MS and is useful in evaluating the scope of this new approach.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it