Selenium-mediated arsenic excretion in mammals: a synchrotron-based study of whole-body distribution and tissue-specific chemistry
Bibliographic record
Abstract
Arsenicosis, a syndrome caused by ingestion of arsenic contaminated drinking water, currently affects millions of people in South-East Asia and elsewhere. Previous animal studies revealed that the toxicity of arsenite essentially can be abolished if selenium is co-administered as selenite. Although subsequent studies have provided some insight into the biomolecular basis of this striking antagonism, many details of the biochemical pathways that ultimately result in the detoxification and excretion of arsenic using selenium supplements have yet to be thoroughly studied. To this end and in conjunction with the recent Phase III clinical trial "Selenium in the Treatment of Arsenic Toxicity and Cancers", we have applied synchrotron X-ray techniques to elucidate the mechanisms of this arsenic-selenium antagonism at the tissue and organ levels using an animal model. X-ray fluorescence imaging (XFI) of cryo-dried whole-body sections of laboratory hamsters that had been injected with arsenite, selenite, or both chemical species, provided insight into the distribution of both metalloids 30 minutes after treatment. Co-treated animals showed strong co-localization of arsenic and selenium in the liver, gall bladder and small intestine. X-ray absorption spectroscopy (XAS) of freshly frozen organs of co-treated animals revealed the presence in liver tissues of the seleno bis-(S-glutathionyl) arsinium ion, which was rapidly excreted via bile into the intestinal tract. These results firmly support the previously postulated hepatobiliary excretion of the seleno bis-(S-glutathionyl) arsinium ion by providing the first data pertaining to organs of whole animals.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".