Exposure–Response Relationship of Toxic Metal(loid)s in Mammals: Their Bioinorganic Chemistry in Blood Is an Intrinsic Component of the Selectivity Filters That Mediate Organ Availability
Bibliographic record
Abstract
The gastrointestinal tract mediates the absorption of nutrients from the diet, which is increasingly contaminated with toxic metal(loid) species (TMs) and thus threatens food safety. Evidence in support of the influx of TMs into the bloodstream of the general and vulnerable populations (babies, children, pregnant women, and industrial workers) has been obtained by accurately quantifying their blood concentrations. The interpretation of these TM blood concentrations, however, is problematic, as we cannot distinguish between those that are tolerable from those that may cause the onset of environmental diseases. Since TMs that have invaded the bloodstream may perturb biochemical processes therein that will eventually cause organ damage it is crucial to better understand their bioinorganic chemistry as these processes collectively determine their organ availability. Thus, bioinorganic processes of TMs in the bloodstream represent selectivity filters which protect organs from their influx and ultimately determine the corresponding exposure-response relationships. The need to better understand selectivity filters prompted us to mechanistically disentangle them into the major bioinorganic chemistry processes. It is argued that the detoxification of TMs in the bloodstream and the biomolecular mechanisms, which mediate their uptake into target organs, represent critical knowledge gaps to revise regulatory frameworks to reduce the disease burden.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".