Accumulation of Insensitive Munition Compounds in the Earthworm <i>Eisenia andrei</i> from Amended Soil: Methodological Considerations for Determination of Bioaccumulation Factors
Bibliographic record
Abstract
Abstract The present study investigates the bioaccumulation of the insensitive munition compounds 2,4-dinitroanisole (DNAN) and 3-nitro-1,2,4-triazol-5-one (NTO), developed for future weapons systems to replace current munitions containing sensitive explosives. The earthworm Eisenia andrei was exposed to sublethal concentrations of DNAN or NTO amended in Sassafras sandy loam. Chemical analysis indicated that 2- and 4-amino-nitroanisole (2-ANAN and 4-ANAN, respectively) were formed in DNAN-amended soils. The SumDNAN (sum of DNAN, 2-ANAN, and 4-ANAN concentrations) in soil decreased by 40% during the 14-d exposure period. The SumDNAN in the earthworm body residue increased until day 3 and decreased thereafter. Between days 3 and 14, there was a 73% decrease in tissue uptake that was greater than the 23% decrease in the soil concentration, suggesting that the bioavailable fraction may have decreased over time. By day 14, the DNAN concentration accounted for only 45% of the SumDNAN soil concentration, indicating substantial DNAN transformation in the presence of earthworms. The highest bioaccumulation factor (BAF; the tissue-to-soil concentration ratio) was 6.2 ± 1.0 kg/kg (dry wt) on day 3 and decreased to 3.8 ± 0.8 kg/kg by day 14. Kinetic studies indicated a BAF of 2.3 kg/kg, based on the earthworm DNAN uptake rate of 2.0 ± 0.24 kg/kg/d, compared with the SumDNAN elimination rate of 0.87 d–1 (half-life = 0.79 d). The compound DNAN has a similar potential to bioaccumulate from soil compared with trinitrotoluene. The NTO concentration in amended soil decreased by 57% from the initial concentration (837 mg NTO/kg dry soil) during 14 d, likely due to the formation of unknown transformation products. The bioaccumulation of NTO was negligible (BAF ≤ 0.018 kg/kg dry wt). Environ Toxicol Chem 2021;40:1713–1725. © 2021 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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".