A New<i>In Vitro</i>Test to Simulate Gastric Absorption of Copper, Lead, Tin and Zinc from Polluted Soils Mise au Point d'un Test<i>In Vitro</i>Simulant le Suc Gastrique pour Dépister les Sols Contaminés par le Cuivre, le Plomb, l'Étain et le Zinc
Bibliographic record
Abstract
Metals in polluted soils can be ingested by young children and cause toxicity through gastro-intestinal absorption. Very few tests are used to evaluate the gastric absorption of metals from polluted soils. The Toxicity Characteristics Leaching Procedure (TCLP) of the Environmental Protection Agency of the United States is indirectly used as usually no action is taken on a polluted soil if lead is less than 5 mg l(-1) in the test. This paper presents a new In vitro simple screening test to detect soils polluted by metals which can cause gastric absorption. The gastric juice simulation test (GJST) is based on the chemistry of the stomach. The TCLP and the GJST has been applied to six different size fractions of 5 soils. Lead carbonate was the main form of lead pollution. Lead oxide, lead silicate, lead phosphate and PbaSnbOc(CO3)d, PbaTibOc(CO3)d and PbaCrbOc were also present. Copper is mainly found as elemental copper partly carbonated while zinc is as zinc oxide or carbonate. Tin is usually associated with iron alloy or oxide or in PbaSnbOc(CO3)d. The percentage of the surface occupied by a polluting phase is higher in small particles. The proportion of particles for which pollution is located near the surface of the particle is more important for small particles. The GJST leaches more copper, lead and zinc than the TCLP, particularly on small size fractions. Inorganic tin is not solubilised by the TCLP or the GJST. The percentage of metal leached from small particles is very important with the GJST, but not with the TCLP. The pH 5 of the TCLP is too high to solubilise much metals and is not a good test to evaluate polluted soils if gastric absorption is to be considered. For two soils out of five, the TCLP didn't detect problematic soils as detected with the Integrated Exposure Uptake Biokinetic model of the USEPA. The GJST detected all the problematic soils and is better to evaluate the chemical solubility of metals in the gastric environment. The GJST better represents the stomach environment (Cl-, pH 2, T = 37 degrees C). The GJST appears to be a good test to detect metal contaminated soils.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".