Earthworm Sublethal Responses to Titanium Dioxide Nanomaterial in Soil Detected by <sup>1</sup>H NMR Metabolomics
Bibliographic record
Abstract
¹H NMR-based metabolomics was used to examine the response of Eisenia fetida earthworms raised from juveniles for 20-23 weeks in soil spiked with either 20 or 200 mg/kg of a commercially available uncoated titanium dioxide (TiO(2)) nanomaterial (nominal diameter of 5 nm). To distinguish responses specific to particle size, soil treatments spiked with a micrometer-sized TiO(2) material (nominal diameter, <45 μm) at the same concentrations (20 and 200 mg/kg) were also included in addition to an unspiked control soil. Multivariate statistical analysis of the (1)H NMR spectra for aqueous extracts of E. fetida tissue suggested that earthworms exhibited significant changes in their metabolic profile following TiO(2) exposure for both particle sizes. The observed earthworm metabolic changes appeared to be consistent with oxidative stress, a proposed mechanism of toxicity for nanosized TiO(2). In contrast, a prior study had observed no impairment of E. fetida survival, reproduction, or growth following exposure to the same TiO(2) spiked soils. This suggests that (1)H NMR-based metabolomics provides a more sensitive measure of earthworm response to TiO(2) materials in soil and that further targeted assays to detect specific cellular or molecular level damage to earthworms caused by chronic exposure to TiO(2) are warranted.
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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 | 0.000 | 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) | 0.000 | 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".