Multi-elemental determination of metals, metalloids and rare earth element concentrations in whole blood from the Canadian Health Measures Survey, 2009-2011
Bibliographic record
Abstract
BACKGROUND: As part of Government of Canada's Chemical Management Plan, substances containing aluminum (Al), bismuth (Bi), cerium (Ce), chromium (Cr), germanium (Ge), lanthanum (La), lithium (Li), neodymium (Nd), praseodymium (Pr), tellurium (Te), titanium (Ti) and yttrium (Y) were identified as priorities for risk assessment. Generating exposure estimates from all routes of exposure from multiple sources using a traditional approach for these elements can be challenging. The use of human biomonitoring (HBM) data would allow for direct and more precise assessment of the internal concentrations from all routes and all sources of exposure. There are no Canadian or North American population-level whole blood HBM data for the elements listed above. Therefore, this is the first biomonitoring project carried out to determine the concentrations of these elements from a nationally representative sample of Canadians. OBJECTIVES: The objective of this study was to generate whole blood concentrations for Al, Bi, Ce, Cr, Ge, La, Li. Nd, Pr, Te, Ti and Y in the Canadian population using biobank samples from the Canadian Health Measures Survey (CHMS) cycle 2 (2009-2011) for use in characterizing exposure in screening assessments and for establishing baseline concentrations to determine how exposures are changing over time. METHODS: The sample analysis was conducted by ICP-MS. A rigorous quality control and quality assurance process was implemented in order to generate data with high accuracy and precision while measuring low concentrations and minimizing possible inadvertent contamination. RESULTS: Of the elements analysed, the whole blood concentrations (μg/L) of Al, Ce, Cr, Ge, La, Nd, Pr, Te, Ti and Y in the Canadian population aged 3-79 years were below their respective method reporting limit (MRL). Two elements, Bi and Li were detected in 5 % and 66 % of the Canadian population. The median Li concentration was 0.47 μg/L. CONCLUSION: The results of this study provide information on concentrations of these elements in the Canadian population which can be utilized to characterize exposure in screening assessments and there by the potential for harm to human health. In addition, this study provides baseline HBM data which can be used as a comparative HBM dataset for other populations with similar exposure patterns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".