A Review of Mercury Bioavailability in Humans and Fish
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To estimate human exposure to methylmercury (MeHg), risk assessors often assume 95%-100% bioavailability in their models. However, recent research suggests that assuming all, or most, of the ingested mercury (Hg) is absorbed into systemic circulation may be erroneous. The objective of this paper is to review and discuss the available state of knowledge concerning the assimilation or bioavailability of Hg in fish and humans. In fish, this meant reviewing studies on assimilation efficiency, that is the difference between ingested and excreted Hg over a given period of time. In humans, this meant reviewing studies that mostly investigated bioaccessibility (digestive processes) rather than bioavailability (cumulative digestive + absorptive processes), although studies incorporating absorption for a fuller picture of bioavailability were also included where possible. The outcome of this review shows that in a variety of organisms and experimental models that Hg bioavailability and assimilation is less than 100%. Specifically, 25 studies on fish were reviewed, and assimilation efficiencies ranged from 10% to 100% for MeHg and from 2% to 51% for Hg(II). For humans, 20 studies were reviewed with bioaccessibility estimates ranging from 2% to 100% for MeHg and 0.2% to 94% for Hg(II). The overall absorption estimates ranged from 12% to 79% for MeHg and 49% to 69% for Hg(II), and were consistently less than 100%. For both fish and humans, a number of cases are discussed in which factors (e.g., Hg source, cooking methods, nutrients) are shown to affect Hg bioavailability. The summaries presented here challenge a widely-held assumption in the Hg risk assessment field, and the paper discusses possible ways forward for the field.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it