Determination of essential and toxic metals in blood by ICP-MS with calibration in synthetic matrix
Bibliographic record
Abstract
A high throughput method has been developed and validated for the analysis of heavy metals in blood using inductively coupled plasma mass spectrometry (ICP-MS) with an integrated sample introduction system with discrete sampling (ISIS-DS). Blood analyses are performed using an Agilent 7700x ICP-MS in helium collision mode. For this study, we selected a metal panel that included As, Cd, Hg, Mn, Pb, and U. Blood specimens, reference material and intermediate calibration standards were diluted 50 times with a diluent composed of n-butanol, NH4OH, H4EDTA, Triton X-100 and five internal standards (ISTDs). A 50 times dilution alone however does not dissipate the blood matrix effect. We found that the addition of NaCl and CaCl2 to calibration standards created a synthetic matrix (SM) environment leading to excellent analytical accuracy for all metals in the study, with results for lead nearly identical to isotopic dilution technique results. In addition, our study demonstrated that under matrix-match conditions for blood samples and calibration standards, any ISTD can be selected for any analyte regardless of first ionization potential or atomic mass (i.e., 55Ge is an acceptable ISTD for 238U or 205Tl for 55Mn, etc.). This method was initially validated using the following external reference materials: four levels of NIST standard reference material (SRM) 955c samples supplied by the National Institute of Standards and Technology (NIST), Wisconsin State Laboratory of Hygiene (WSLH) blood sample pools that were used to prepare Filter Paper Blood Lead proficiency testing (PT) samples (June 2011 event), and multi-element blood samples supplied by the Institute National de Santé Publique Quebec (INSPQ). When calibration standards were prepared without the matrix-match components, notable differences between present study results and respective reference or mean values were observed. This approach may offer a universal technique to improve the accuracy of ICP-MS results for metal analyses in any complex matrix. This method is currently being used to analyze human blood specimens as part of the California Environmental Contaminant Biomonitoring Program (CECBP).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".