Effects of silver nanoparticles on bacterial activity in natural waters
Bibliographic record
Abstract
Silver nanoparticles (AgNPs) may be introduced into aquatic ecosystems because of their widespread use as antimicrobial agents. However, few studies have investigated the impacts of AgNPs on natural aquatic microbial activity in an environmentally relevant context. In this study, bacterioplankton were collected from nine aquatic habitats and exposed to six concentrations of carboxy-functionalized AgNP (ViveNano, 10-nm particle size, 20% Ag w/w) over 48 h. After 1 h of exposure, bacterial production and extracellular alkaline phosphatase affinity were significantly reduced in all AgNP-exposed samples. However, across a 48-h exposure, extracellular aminopeptidase affinity was not consistently impacted by AgNPs. After 48 h, bacterial production recovered by 40 to 250% at low AgNP nominal concentrations (0.05 and 0.1 mg/L) but remained inhibited at the two highest AgNP nominal concentrations (1 and 10 mg/L). In contrast, AgNO(3) additions between 0.01 to 2 mg Ag/L fully inhibited bacterial production over the 48-h exposure. At 48-h exposure, the lowest observed effective concentrations and average median effective concentration for bacterial production ranged from 8 to 66 and 15 to 276 µg Ag/L, respectively. Thus, in natural aquatic systems, AgNP concentrations in the nanogram per liter range are unlikely to negatively impact aquatic biogeochemical cycles. Instead, exposures in the low microgram per liter range would likely be required to negatively impact natural aquatic bacterioplankton processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".