Toenail speciation biomarkers in arsenic‐related disease: a feasibility study for investigating the association between arsenic exposure and chronic disease
Bibliographic record
Abstract
Long-term exposure to environmental arsenic has been associated with many chronic diseases, including several cancers, and diabetes. Urinary studies have implicated arsenic speciation as an important risk factor, however, such associations have not been replicated using toenail samples: a relatively new biosample for estimating long-term internal dose-exposure to arsenic. Despite having several advantages over conventional biosamples such as ease of collection and storage, standard methods for arsenic speciation analysis in toenails have not yet been established. The primary objectives of this study were to 1) establish an analytical method for arsenic speciation analysis in toenails, 2) describe preliminary arsenic speciation profiles of toenail samples from individuals with skin, lung, bladder, and kidney cancer, type II diabetes, and no known disease, and 3) determine if these speciation patterns differ between disease groups to inform the feasibility of subsequent research. A small cross-sectional feasibility study was carried out using 60 toenail samples and baseline questionnaire data from the Atlantic Partnership for Tomorrow's Health (Atlantic PATH) study. Arsenic speciation profiles were determined using high performance liquid chromatography (HPLC) paired with inductively coupled plasma-mass spectrometry (ICP-MS). While no differences in total arsenic were found, arsenic speciation profiles were significantly different between certain cancer groups and the reference group with no known disease. Specifically, the percentage of monomethylarsonic acid (%MMA) was found to be significantly higher in the toenails of individuals with lung cancer and kidney cancer, compared to healthy individuals with similar total arsenic exposure. To the best of our knowledge, this is the first study to describe arsenic speciation patterns in individuals with several arsenic-related diseases using toenails: a convenient, non-invasive, biobankable sample capable of longer-term exposure estimation than conventional biosamples. These preliminary data provide evidence that toenail arsenic speciation patterns differ between groups with arsenic-related disease, and those with no known disease. Toenail arsenic speciation analysis is feasible and could potentially have important implications for research on arsenic-related diseases. Further investigation is warranted and would benefit from including detailed arsenic exposure data to explore the observed heterogeneity in arsenic speciation profiles.
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 | 0.002 |
| 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 | 0.001 |
| 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".