Longitudinal changes in bone lead concentration: implications for modelling of human bone lead metabolism
Bibliographic record
Abstract
In this study, 539 occupationally exposed subjects received in vivo bone lead measurements using 109Cd excited K X-ray fluorescence (109Cd K XRF). Of these subjects, 327 had previously been measured five years earlier. Measurements were made from both tibia and calcaneus samples, taken to reflect cortical and trabecular bone, respectively. Changes in tibia lead concentration related negatively to initial tibia lead concentration and positively to both lead exposure between the measurement dates and initial calcaneus lead concentration. This finding confirmed and strengthened the interpretation of an earlier study involving fewer subjects. With the larger data set it was possible to examine subgroups of subjects. This showed that people aged less than 40 years had a shorter half-life for the release of lead from the tibia (4.9, 95% CI 3.6-7.8 years) than did those older than 40 (13.8, 95% CI 9.7-23.8 years). Similarly, less intensely exposed subjects (lifetime average blood lead < or = 25 micrograms dL-1) had a shorter tibia lead half-life (6.2, 95% CI 4.7-9.0 years) than those with a lifetime average blood lead > 25 micrograms dL-1 (14.7, 95% CI 9.7-29.9 years). Age and measures of lead exposure were strongly correlated; nevertheless, age matched subgroups with high and low intensity exposures showed clearance rates that were significantly different at the 10% level, with the lower exposure intensity again being associated with the faster clearance. These findings imply that current models of human lead metabolism should be examined with a view to adjusting them to account for kinetic rates varying with age and probably also with exposure level.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".