Analysis of Mercury in Sequential Micrometer Segments of Single Hair Strands of Fish-Eaters
Bibliographic record
Abstract
Although it has been established that mercury (Hg) can be detected in single hair strands using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), calibration remains a challenge due to the lack of well-characterized matrix-matched standards. We concurrently evaluated two strategies for quantifying Hg signals in single hair strands using LA-ICP-MS. The main objective was to obtain time-resolved Hg concentrations in single hair strands of fish-eaters that would correspond to the changes of their body burden over time. Experiments were conducted using hair samples collected from 10 individuals. The first experiment involved the construction of a calibration curve with four powdered hair standard reference materials (SRMs) with a range of Hg concentrations (0.573-23.2 mg/kg). An internal standard, sulfur, as 34S, was applied to correct for ablation efficiency for both the hair strands and the SRMs. Results showed a linear relationship (R2 = 0.899) between the ratio of 202Hg to 34S obtained by LA-ICP-MS and the certified total Hg concentration in the SRMs. Using this calibration curve, average Hg concentrations of 10 shots within a 1-cm segment of a hair strand were calculated and then compared to the total Hg concentrations in the matched 1-cm segment as measured by cold vapor atomic absorption spectrometry (CV-AAS). A significant difference (p < 0.05) was observed. The difference could be attributed to the highly variable ablation/sampling process caused by the use of the laser on the hair powder SRM pellets and the difference in the physical properties of the SRMs. An alternative approach was adopted to quantify consecutive 202Hg to 34S ratios by calibrating the signals against the average Hg concentration of the matched hair segment as measured by CV-AAS. Consecutive daily Hg deposition in single hairs of fish eaters was determined. Results showed that apparent daily changes in Hg concentrations within a hair segment that corresponds to 1 month of hair growth. In addition, a significant decreasing or increasing time-trend was observed. The difference between the minimum and maximum Hg concentration within each individual corresponded to a change of 26-40%. Our results showed that LA-ICP-MS can be used to reconstruct time-resolved Hg exposure in micrometer segments of a single hair strand.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".